MTF Ichimoku Conversion Line SMA with H/L mirrored levelsWelcome to MTF Ichimoku Conversion Line with SMA Highs/Lows Extended Lines!
1. Overview
It is designed to provide a multi-timeframe view of market trends and potential support/resistance levels by obtaining a Simple Moving Average (SMA) of the Conversion Line of Ichimoku Equibilium (Ichimoku Kinko-Hyo), which acts as a substantial trend line on the candlestick chart. The SMA of the conversion line smooths out price fluctuations and indicates the overall trend direction—if the candles are above it, the trend can be read as an uptrend, while below it, the trend can be read as a downtrend.
2. Calculation
The indicator first calculates the Conversion Line (see the description of Ichimoku theory anywhere, e.g., Wikipedia), as the average of the highest high and lowest low over a user-defined period (Conversion Line Length, default is 9, also recommended is 9).
It then retrieves this Conversion Line from a higher timeframe (MTF Timeframe) to add a broader perspective. Using a specified period (SMA Length)., an SMA is computed on this multi-timeframe conversion line. This SMA serves as a trend line that visually represents the prevailing price trend, making it easier to assess market direction.
3. Pivot Highs/low detection and drawing their extensions
In addition, the indicator identifies pivot highs and lows from the SMA data using a defined pivot length. When these pivots occur, horizontal lines are drawn and extended across the chart. These extended lines (drawn in a yellowish color by default) include a full extension, a half extension, and a middle extension line representing the midpoint between the high and low pivot.
4. Mirror lines
The indicator also offers optional mirror line features. When the Mirror Upside option is enabled, five additional lines are drawn above the highest extended yellow line at equal intervals. Similarly, when the Mirror Downside option is enabled, five lines are drawn below the lowest extended yellow line. These light gray mirror lines serve as extra reference levels, which can help identify potential support or resistance zones.
5. Parameters
User parameters include:
- Conversion Line Length: The period used to calculate the conversion line.
- MTF Timeframe: The higher timeframe from which the conversion line is obtained.
- SMA Length: The period over which the SMA is calculated on the conversion line.
- SMA Mode: A toggle to display either the SMA or the raw conversion line (SMA recommended).
- SMA Line Width: The thickness of the SMA line.
- Pivot Length for SMA Highs/Lows: The period used to detect pivot highs and lows in the SMA.
- Horizontal Extension: Number of bars by which the pivot and extended lines are drawn across the chart
- Colors for High and Low Pivot Lines and Extended Lines: Customizable colors are used to draw the lines.
Mirror Upside and Mirror Downside: These options enable drawing additional mirror lines above and below the extended lines.
- Hide Old Lines: An option to hide previous pivot lines once new ones are drawn for a cleaner chart. Turned on by default.
6. Conclusion
Overall, the Conversion Line SMA in this indicator smooths out the conversion line data and effectively functions as a trend line for the candlestick chart, helping traders visually interpret the underlying market trend. The extended and mirror lines provide further context for potential price reversal or continuation areas, making this a powerful tool for multi-timeframe technical analysis.
In den Scripts nach "horizontal line" suchen
Grid Bot Parabolic [xxattaxx]🟩 The Grid Bot Parabolic, a continuation of the Grid Bot Simulator Series , enhances traditional gridbot theory by employing a dynamic parabolic curve to visualize potential support and resistance levels. This adaptability is particularly useful in volatile or trending markets, enabling traders to explore grid-based strategies and gain deeper market insights. The grids are divided into customizable trade zones that trigger signals as prices move into new zones, empowering traders to gain deeper insights into market dynamics and potential turning points.
While traditional grid bots excel in ranging markets, the Grid Bot Parabolic’s introduction of acceleration and curvature adds new dimensions, enabling its use in trending markets as well. It can function as a traditional grid bot with horizontal lines, a tilted grid bot with linear slopes, or a fully parabolic grid with curves. This dynamic nature allows the indicator to adapt to various market conditions, providing traders with a versatile tool for visualizing dynamic support and resistance levels.
🔑 KEY FEATURES 🔑
Adaptable Grid Structures (Horizontal, Linear, Curved)
Buy and Sell Signals with Multiple Trigger/Confirmation Conditions
Secondary Buy and Secondary Sell Signals
Projected Grid Lines
Customizable Grid Spacing and Zones
Acceleration and Curvature Control
Sensitivity Adjustments
📐 GRID STRUCTURES 📐
Beyond its core parabolic functionality, the Parabolic Grid Bot offers a range of grid configurations to suit different market conditions and trading preferences. By adjusting the "Acceleration" and "Curvature" parameters, you can transform the grid's structure:
Parabolic Grids
Setting both acceleration and curvature to non-zero values results in a parabolic grid.This configuration can be particularly useful for visualizing potential turning points and trend reversals. Example: Accel = 10, Curve = -10)
Linear Grids
With a non-zero acceleration and zero curvature, the grid tilts to represent a linear trend, aiding in identifying potential support and resistance levels during trending phases. Example: Accel =1.75, Curve = 0
Horizontal Grids
When both acceleration and curvature are set to zero, the indicator reverts to a traditional grid bot with horizontal lines, suitable for ranging markets. Example: Accel=0, Curve=0
⚙️ INITIAL SETUP ⚙️
1.Adding the Indicator to Your Chart
Locate a Starting Point: To begin, visually identify a price point on your chart where you want the grid to start.This point will anchor your grid.
2. Setting Up the Grid
Add the Grid Bot Parabolic Indicator to your chart. A “Start Time/Price” dialog will appear
CLICK on the chart at your chosen start point. This will anchor the start point and open a "Confirm Inputs" dialog box.
3. Configure Settings. In the dialog box, you can set the following:
Acceleration: Adjust how quickly the grid reacts to price changes.
Curve: Define the shape of the parabola.
Intervals: Determine the distance between grid levels.
If you choose to keep the default settings, with acceleration set to 0 and curve set to 0, the grid will display as traditional horizontal lines. The grid will align with your selected price point, and you can adjust the settings at any time through the indicator’s settings panel.
⚙️ CONFIGURATION AND SETTINGS ⚙️
Grid Settings
Accel (Acceleration): Controls how quickly the price reacts to changes over time.
Curve (Curvature): Defines the overall shape of the parabola.
Intervals (Grid Spacing): Determines the vertical spacing between the grid lines.
Sensitivity: Fine tunes the magnitude of Acceleration and Curve.
Buy Zones & Sell Zones: Define the number of grid levels used for potential buy and sell signals.
* Each zone is represented on the chart with different colors:
* Green: Buy Zones
* Red: Sell Zones
* Yellow: Overlap (Buy and Sell Zones intersect)
* Gray: Neutral areas
Trigger: Chooses which part of the candlestick is used to trigger a signal.
* `Wick`: Uses the high or low of the candlestick
* `Close`: Uses the closing price of the candlestick
* `Midpoint`: Uses the middle point between the high and low of the candlestick
* `SWMA`: Uses the Symmetrical Weighted Moving Average
Confirm: Specifies how a signal is confirmed.
* `Reverse`: The signal is confirmed if the price moves in the opposite direction of the initial trigger
* `Touch`: The signal is confirmed when the price touches the specified level or zone
Sentiment: Determines the market sentiment, which can influence signal generation.
* `Slope`: Sentiment is based on the direction of the curve, reflecting the current trend
* `Long`: Sentiment is bullish, favoring buy signals
* `Short`: Sentiment is bearish, favoring sell signals
* `Neutral`: Sentiment is neutral. No secondary signals will be generated
Show Signals: Toggles the display of buy and sell signals on the chart
Chart Settings
Grid Colors: These colors define the visual appearance of the grid lines
Projected: These colors define the visual appearance of the projected lines
Parabola/SWMA: Adjust colors as needed. These are disabled by default.
Time/Price
Start Time & Start Price: These set the starting point for the parabolic curve.
* These fields are automatically populated when you add the indicator to the chart and click on an initial location
* These can be adjusted manually in the settings panel, but he easiest way to change these is by directly interacting with the start point on the chart
Please note: Time and Price must be adjusted for each chart when switching assets. For example, a Start Price on BTCUSD of $60,000 will not work on an ETHUSD chart.
🤖 ALGORITHM AND CALCULATION 🤖
The Parabolic Function
At the core of the Parabolic Grid Bot lies the parabolic function, which calculates a dynamic curve that adapts to price action over time. This curve serves as the foundation for visualizing potential support and resistance levels.
The shape and behavior of the parabola are influenced by three key user-defined parameters:
Acceleration: This parameter controls the rate of change of the curve's slope, influencing its tilt or steepness. A higher acceleration value results in a more pronounced tilt, while a lower value leads to a gentler slope. This applies to both curved and linear grid configurations.
Curvature: This parameter introduces and controls the curvature or bend of the grid. A higher curvature value results in a more pronounced parabolic shape, while a lower value leads to a flatter curve or even a straight line (when set to zero).
Sensitivity: This setting fine-tunes the overall responsiveness of the grid, influencing how strongly the Acceleration and Curvature parameters affect its shape. Increasing sensitivity amplifies the impact of these parameters, making the grid more adaptable to price changes but potentially leading to more frequent adjustments. Decreasing sensitivity reduces their impact, resulting in a more stable grid structure with fewer adjustments. It may be necessary to adjust Sensitivity when switching between different assets or timeframes to ensure optimal scaling and responsiveness.
The parabolic function combines these parameters to generate a curve that visually represents the potential path of price movement. By understanding how these inputs influence the parabola's shape and behavior, traders can gain valuable insights into potential support and resistance areas, aiding in their decision-making process.
Sentiment
The Parabolic Grid Bot incorporates sentiment to enhance signal generation. The "Sentiment" input allows you to either:
Manually specify the market sentiment: Choose between 'Long' (bullish), 'Short' (bearish), or 'Neutral'.
Let the script determine sentiment based on the slope of the parabolic curve: If 'Slope' is selected, the sentiment will be considered 'Long' when the curve is sloping upwards, 'Short' when it's sloping downwards, and 'Neutral' when it's flat.
Buy and Sell Signals
The Parabolic Grid Bot generates buy and sell signals based on the interaction between the price and the grid levels.
Trigger: The "Trigger" input determines which part of the candlestick is used to trigger a signal (wick, close, midpoint, or SWMA).
Confirmation: The "Confirm" input specifies how a signal is confirmed ('Reverse' or 'Touch').
Zones: The number of "Buy Zones" and "Sell Zones" determines the areas on the grid where buy and sell signals can be generated.
When the trigger condition is met within a buy zone and the confirmation criteria are satisfied, a buy signal is generated. Similarly, a sell signal is generated when the trigger and confirmation occur within a sell zone.
Secondary Signals
Secondary signals are generated when a regular buy or sell signal contradicts the prevailing sentiment. For example:
A buy signal in a bearish market (Sentiment = 'Short') would be considered a "secondary buy" signal.
A sell signal in a bullish market (Sentiment = 'Long') would be considered a "secondary sell" signal.
These secondary signals are visually represented on the chart using hollow triangles, differentiating them from regular signals (filled triangles).
While they can be interpreted as potential contrarian trade opportunities, secondary signals can also serve other purposes within a grid trading strategy:
Exit Signals: A secondary signal can suggest a potential shift in market sentiment or a weakening trend. This could be a cue to consider exiting an existing position, even if it's currently profitable, to lock in gains before a potential reversal
Risk Management: In a strong trend, secondary signals might offer opportunities for cautious counter-trend trades with controlled risk. These trades could utilize smaller position sizes or tighter stop-losses to manage potential downside if the main trend continues
Dollar-Cost Averaging (DCA): During a prolonged trend, the parabolic curve might generate multiple secondary signals in the opposite direction. These signals could be used to implement a DCA strategy, gradually accumulating a position at potentially favorable prices as the market retraces or consolidates within the larger trend
Secondary signals should be interpreted with caution and considered in conjunction with other technical indicators and market context. They provide additional insights into potential market reversals or consolidation phases within a broader trend, aiding in adapting your grid trading strategy to the evolving market dynamics.
Examples
Trigger=Wick, Confirm=Touch. Signals are generated when the wick touches the next gridline.
Trigger=Close, Confirm=Touch. Signals require the close to touch the next gridline.
Trigger=SWMA, Confirm=Reverse. Signals are triggered when the Symmetrically Weighted Moving Average reverse crosses the next gridline.
🧠THEORY AND RATIONALE 🧠
The innovative approach of the Parabolic Grid Bot can be better understood by first examining the limitations of traditional grid trading strategies and exploring how this indicator addresses them by incorporating principles of market cycles and dynamic price behavior
Traditional Grid Bots: One-Dimensional and Static
Traditional grid bots operate on a simple premise: they divide the price chart into a series of equally spaced horizontal lines, creating a grid of trading zones. These bots excel in ranging markets where prices oscillate within a defined range. Buy and sell orders are placed at these grid levels, aiming to profit from mean reversion as prices bounce between the support and resistance zones.
However, traditional grid bots face challenges in trending markets. As the market moves in one direction, the bot continues to place orders in that direction, leading to a stacking of positions. If the market eventually reverses, these stacked trades can be profitable, amplifying gains. But the risk lies in the potential for the market to continue trending, leaving the trader with a series of losing trades on the wrong side of the market
The Parabolic Grid Bot: Adding Dimensions
The Parabolic Grid Bot addresses the limitations of traditional grid bots by introducing two additional dimensions:
Acceleration (Second Dimension): This parameter introduces a second dimension to the grid, allowing it to tilt upwards or downwards to align with the prevailing market trend. A positive acceleration creates an upward-sloping grid, suitable for uptrends, while a negative acceleration results in a downward-sloping grid, ideal for downtrends. The magnitude of acceleration controls the steepness of the tilt, enabling you to fine-tune the grid's responsiveness to the trend's strength
Curvature (Third Dimension): This parameter adds a third dimension to the grid by introducing a parabolic curve. The curve's shape, ranging from gentle bends to sharp turns, is controlled by the curvature value. This flexibility allows the grid to closely mirror the market's evolving structure, potentially identifying turning points and trend reversals.
Mean Reversion in Trending Markets
Even in trending markets, the Parabolic Grid Bot can help identify opportunities for mean reversion strategies. While the grid may be tilted to reflect the trend, the buy and sell zones can capture short-term price oscillations or consolidations within the broader trend. This allows traders to potentially pinpoint entry and exit points based on temporary pullbacks or reversals.
Visualize and Adapt
The Parabolic Grid Bot acts as a visual aid, enhancing your understanding of market dynamics. It allows you to "see the curve" by adapting the grid to the market's patterns. If the market shows a parabolic shape, like an upward curve followed by a peak and a downward turn (similar to a head and shoulders pattern), adjust the Accel and Curve to match. This highlights potential areas of interest for further analysis.
Beyond Straight Lines: Visualizing Market Cycle
Traditional technical analysis often employs straight lines, such as trend lines and support/resistance levels, to interpret market movements. However, many analysts, including Brian Millard, contend that these lines can be misleading. They propose that what might appear as a straight line could represent just a small part of a larger curve or cycle that's not fully visible on the chart.
Markets are inherently cyclical, marked by phases of expansion, contraction, and reversal. The Parabolic Grid Bot acknowledges this cyclical behavior by offering a dynamic, curved grid that adapts to these shifts. This approach helps traders move beyond the limitations of straight lines and visualize potential support and resistance levels in a way that better reflects the market's true nature
By capturing these cyclical patterns, whether subtle or pronounced, the Parabolic Grid Bot offers a nuanced understanding of market dynamics, potentially leading to more accurate interpretations of price action and informed trading decisions.
⚠️ DISCLAIMER⚠️
This indicator utilizes a parabolic curve fitting approach to visualize potential support and resistance levels. The mathematical formulas employed have been designed with adaptability and scalability in mind, aiming to accommodate various assets and price ranges. While the resulting curves may visually resemble parabolas, it's important to note that they might not strictly adhere to the precise mathematical definition of a parabola.
The indicator's calculations have been tested and generally produce reliable results. However, no guarantees are made regarding their absolute mathematical accuracy. Traders are encouraged to use this tool as part of their broader analysis and decision-making process, combining it with other technical indicators and market context.
Please remember that trading involves inherent risks, and past performance is not indicative of future results. It is always advisable to conduct your own research and exercise prudent risk management before making any trading decisions.
🧠 BEYOND THE CODE 🧠
The Parabolic Grid Bot, like the other grid bots in this series, is designed with education and community collaboration in mind. Its open-source nature encourages exploration, experimentation, and the development of new grid trading strategies. We hope this indicator serves as a framework and a starting point for future innovations in the field of grid trading.
Your comments, suggestions, and discussions are invaluable in shaping the future of this project. We welcome your feedback and look forward to seeing how you utilize and enhance the Parabolic Grid Bot.
Uptrick: DPO Signal & Zone Indicator
## **Uptrick: DPO Signal & Zone Indicator**
### **Introduction:**
The **Uptrick: DPO Signal & Zone Indicator** is a sophisticated technical analysis tool tailored to provide insights into market momentum, identify potential trading signals, and recognize extreme market conditions. It leverages the Detrended Price Oscillator (DPO) to strip out long-term trends from price movements, allowing traders to focus on short-term fluctuations and cyclical behavior. The indicator integrates multiple components, including a Detrended Price Oscillator, a Signal Line, a Histogram, and customizable alert levels, to deliver a robust framework for market analysis and trading decision-making.
### **Detailed Breakdown:**
#### **1. Detrended Price Oscillator (DPO):**
- **Purpose and Functionality:**
- The DPO is designed to filter out long-term trends from the price data, isolating short-term price movements. This helps in understanding the cyclical patterns and momentum of an asset, allowing traders to detect periods of acceleration or deceleration that might be overlooked when focusing solely on long-term trends.
- **Calculation:**
- **Formula:** `dpo = close - ta.sma(close, smaLength)`
- **`close`:** The asset’s closing price for each period in the dataset.
- **`ta.sma(close, smaLength)`:** The Simple Moving Average (SMA) of the closing prices over a period defined by `smaLength`.
- The DPO is derived by subtracting the SMA value from the current closing price. This calculation reveals how much the current price deviates from the moving average, effectively detrending the price data.
- **Interpretation:**
- **Positive DPO Values:** Indicate that the current price is higher than the moving average, suggesting bullish market conditions and a potential upward trend.
- **Negative DPO Values:** Indicate that the current price is lower than the moving average, suggesting bearish market conditions and a potential downward trend.
- **Magnitude of DPO:** Reflects the strength of momentum. Larger positive or negative values suggest stronger momentum in the respective direction.
#### **2. Signal Line:**
- **Purpose and Functionality:**
- The Signal Line is a smoothed average of the DPO, intended to act as a reference point for generating trading signals. It helps to filter out short-term fluctuations and provides a clearer perspective on the prevailing trend.
- **Calculation:**
- **Formula:** `signalLine = ta.sma(dpo, signalLength)`
- **`ta.sma(dpo, signalLength)`:** The SMA of the DPO values over a period defined by `signalLength`.
- The Signal Line is calculated by applying a moving average to the DPO values. This smoothing process reduces noise and highlights the underlying trend direction.
- **Interpretation:**
- **DPO Crossing Above Signal Line:** Generates a buy signal, suggesting that short-term momentum is turning bullish relative to the longer-term trend.
- **DPO Crossing Below Signal Line:** Generates a sell signal, suggesting that short-term momentum is turning bearish relative to the longer-term trend.
- **Signal Line’s Role:** Provides a benchmark for assessing the strength of the DPO. The interaction between the DPO and the Signal Line offers actionable insights into potential entry or exit points.
#### **3. Histogram:**
- **Purpose and Functionality:**
- The Histogram visualizes the difference between the DPO and the Signal Line. It provides a graphical representation of momentum strength and direction, allowing traders to quickly gauge market conditions.
- **Calculation:**
- **Formula:** `histogram = dpo - signalLine`
- The Histogram is computed by subtracting the Signal Line value from the DPO value. Positive values indicate that the DPO is above the Signal Line, while negative values indicate that the DPO is below the Signal Line.
- **Interpretation:**
- **Color Coding:**
- **Green Bars:** Represent positive values, indicating bullish momentum.
- **Red Bars:** Represent negative values, indicating bearish momentum.
- **Width of Bars:** Indicates the strength of momentum. Wider bars signify stronger momentum, while narrower bars suggest weaker momentum.
- **Zero Line:** A horizontal gray line that separates positive and negative histogram values. Crosses of the histogram through this zero line can signal shifts in momentum direction.
#### **4. Alert Levels:**
- **Purpose and Functionality:**
- Alert levels define specific thresholds to identify extreme market conditions, such as overbought and oversold states. These levels help traders recognize potential reversal points and extreme market conditions.
- **Inputs:**
- **`alertLevel1`:** Defines the upper threshold for identifying overbought conditions.
- **Default Value:** 0.5
- **`alertLevel2`:** Defines the lower threshold for identifying oversold conditions.
- **Default Value:** -0.5
- **Interpretation:**
- **Overbought Condition:** When the DPO exceeds `alertLevel1`, indicating that the market may be overbought. This condition suggests that the asset could be due for a correction or reversal.
- **Oversold Condition:** When the DPO falls below `alertLevel2`, indicating that the market may be oversold. This condition suggests that the asset could be poised for a rebound or reversal.
#### **5. Visual Elements:**
- **DPO and Signal Line Plots:**
- **DPO Plot:**
- **Color:** Blue
- **Width:** 2 pixels
- **Purpose:** To visually represent the deviation of the current price from the moving average.
- **Signal Line Plot:**
- **Color:** Red
- **Width:** 1 pixel
- **Purpose:** To provide a smoothed reference for the DPO and generate trading signals.
- **Histogram Plot:**
- **Color Coding:**
- **Green:** For positive values, signaling bullish momentum.
- **Red:** For negative values, signaling bearish momentum.
- **Style:** Histogram bars are displayed with varying width to represent the strength of momentum.
- **Zero Line:** A gray horizontal line separating positive and negative histogram values.
- **Overbought/Oversold Zones:**
- **Background Colors:**
- **Green Shading:** Applied when the DPO exceeds `alertLevel1`, indicating an overbought condition.
- **Red Shading:** Applied when the DPO falls below `alertLevel2`, indicating an oversold condition.
- **Horizontal Lines:**
- **Dotted Green Line:** At `alertLevel1`, marking the upper alert threshold.
- **Dotted Red Line:** At `alertLevel2`, marking the lower alert threshold.
- **Purpose:** To provide clear visual cues for extreme market conditions, aiding in the identification of potential reversal points.
#### **6. Trading Signals and Alerts:**
- **Buy Signal:**
- **Trigger:** When the DPO crosses above the Signal Line.
- **Visual Representation:** A "BUY" label appears below the price bar in the specified buy color.
- **Purpose:** Indicates a potential buying opportunity as short-term momentum turns bullish.
- **Sell Signal:**
- **Trigger:** When the DPO crosses below the Signal Line.
- **Visual Representation:** A "SELL" label appears above the price bar in the specified sell color.
- **Purpose:** Indicates a potential selling opportunity as short-term momentum turns bearish.
- **Overbought/Oversold Alerts:**
- **Overbought Alert:** Triggered when the DPO crosses below `alertLevel1`.
- **Oversold Alert:** Triggered when the DPO crosses above `alertLevel2`.
- **Visual Representation:** Labels "OVERBOUGHT" and "OVERSOLD" appear with distinctive colors and sizes to highlight extreme conditions.
- **Purpose:** To signal potential reversal points and extreme market conditions that may lead to price corrections or trend reversals.
- **Alert Conditions:**
- **DPO Cross Above Signal Line:** Alerts traders when the DPO crosses above the Signal Line, generating a buy signal.
- **DPO Cross Below Signal Line:** Alerts traders when the DPO crosses below the Signal Line, generating a sell signal.
- **DPO Above Upper Alert Level:** Alerts when the DPO is above `alertLevel1`, indicating an overbought condition.
- **DPO Below Lower Alert Level:** Alerts when the DPO is below `alertLevel2`, indicating an oversold condition.
- **Purpose:** To provide real-time notifications of significant market events, enabling traders to make informed decisions promptly.
### **Practical Applications:**
#### **1. Trend Following Strategies:**
- **Objective:**
- To capture and ride the prevailing market trends by entering trades that align with the direction of the momentum.
- **How to Use:**
- Monitor buy and sell signals generated by the DPO crossing the Signal Line. A buy signal suggests a bullish trend and a potential long trade, while a sell signal suggests a bearish trend and a potential short trade.
- Use the Histogram to confirm the strength of the trend. Expanding green bars indicate strong bullish momentum, while expanding red bars indicate strong bearish momentum.
- **Advantages:**
- Helps traders stay aligned with the market trend, increasing the likelihood of capturing substantial price moves.
#### **2. Reversal Trading:**
- **Objective:**
- To identify potential market reversals
by detecting overbought and oversold conditions.
- **How to Use:**
- Look for overbought and oversold signals based on the DPO crossing `alertLevel1` and `alertLevel2`. These conditions suggest that the market may be due for a reversal.
- Confirm reversal signals with the Histogram. A decrease in histogram bars (from green to red or vice versa) may support the reversal hypothesis.
- **Advantages:**
- Provides early warnings of potential market reversals, allowing traders to position themselves before significant price changes occur.
#### **3. Momentum Analysis:**
- **Objective:**
- To gauge the strength and direction of market momentum for making informed trading decisions.
- **How to Use:**
- Analyze the Histogram to assess momentum strength. Positive and expanding histogram bars indicate increasing bullish momentum, while negative and expanding bars suggest increasing bearish momentum.
- Use momentum insights to validate or question existing trading positions and strategies.
- **Advantages:**
- Offers valuable information about the market's momentum, helping traders confirm the validity of trends and trading signals.
### **Customization and Flexibility:**
The **Uptrick: DPO Signal & Zone Indicator** offers extensive customization options to accommodate diverse trading preferences and market conditions:
- **SMA Length and Signal Line Length:**
- Adjust the `smaLength` and `signalLength` parameters to control the sensitivity and responsiveness of the DPO and Signal Line. Shorter lengths make the indicator more responsive to price changes, while longer lengths provide smoother, less volatile signals.
- **Alert Levels:**
- Modify `alertLevel1` and `alertLevel2` to fit varying market conditions and volatility. Setting these levels appropriately helps tailor the indicator to different asset classes and trading strategies.
- **Color and Shape Customization:**
- Customize the colors and sizes of buy/sell signals, histogram bars, and alert levels to enhance visual clarity and align with personal preferences. This customization helps ensure that the indicator integrates seamlessly with a trader's charting setup.
### **Conclusion:**
The **Uptrick: DPO Signal & Zone Indicator** is a multifaceted analytical tool that combines the power of the Detrended Price Oscillator with customizable visual elements and alert levels to deliver a comprehensive approach to market analysis. By offering insights into momentum strength, trend direction, and potential reversal points, this indicator equips traders with valuable information to make informed decisions and enhance their trading strategies. Its flexibility and customization options ensure that it can be adapted to various trading styles and market conditions, making it a versatile addition to any trader's toolkit.
Supertrend Advance Pullback StrategyHandbook for the Supertrend Advance Strategy
1. Introduction
Purpose of the Handbook:
The main purpose of this handbook is to serve as a comprehensive guide for traders and investors who are looking to explore and harness the potential of the Supertrend Advance Strategy. In the rapidly changing financial market, having the right tools and strategies at one's disposal is crucial. Whether you're a beginner hoping to dive into the world of trading or a seasoned investor aiming to optimize and diversify your portfolio, this handbook offers the insights and methodologies you need. By the end of this guide, readers should have a clear understanding of how the Supertrend Advance Strategy works, its benefits, potential pitfalls, and practical application in various trading scenarios.
Overview of the Supertrend Advance Pullback Strategy:
At its core, the Supertrend Advance Strategy is an evolution of the popular Supertrend Indicator. Designed to generate buy and sell signals in trending markets, the Supertrend Indicator has been a favorite tool for many traders around the world. The Advance Strategy, however, builds upon this foundation by introducing enhanced mechanisms, filters, and methodologies to increase precision and reduce false signals.
1. Basic Concept:
The Supertrend Advance Strategy relies on a combination of price action and volatility to determine the potential trend direction. By assessing the average true range (ATR) in conjunction with specific price points, this strategy aims to highlight the potential starting and ending points of market trends.
2. Methodology:
Unlike the traditional Supertrend Indicator, which primarily focuses on closing prices and ATR, the Advance Strategy integrates other critical market variables, such as volume, momentum oscillators, and perhaps even fundamental data, to validate its signals. This multidimensional approach ensures that the generated signals are more reliable and are less prone to market noise.
3. Benefits:
One of the main benefits of the Supertrend Advance Strategy is its ability to filter out false breakouts and minor price fluctuations, which can often lead to premature exits or entries in the market. By waiting for a confluence of factors to align, traders using this advanced strategy can increase their chances of entering or exiting trades at optimal points.
4. Practical Applications:
The Supertrend Advance Strategy can be applied across various timeframes, from intraday trading to swing trading and even long-term investment scenarios. Furthermore, its flexible nature allows it to be tailored to different asset classes, be it stocks, commodities, forex, or cryptocurrencies.
In the subsequent sections of this handbook, we will delve deeper into the intricacies of this strategy, offering step-by-step guidelines on its application, case studies, and tips for maximizing its efficacy in the volatile world of trading.
As you journey through this handbook, we encourage you to approach the Supertrend Advance Strategy with an open mind, testing and tweaking it as per your personal trading style and risk appetite. The ultimate goal is not just to provide you with a new tool but to empower you with a holistic strategy that can enhance your trading endeavors.
2. Getting Started
Navigating the financial markets can be a daunting task without the right tools. This section is dedicated to helping you set up the Supertrend Advance Strategy on one of the most popular charting platforms, TradingView. By following the steps below, you'll be able to integrate this strategy into your charts and start leveraging its insights in no time.
Setting up on TradingView:
TradingView is a web-based platform that offers a wide range of charting tools, social networking, and market data. Before you can apply the Supertrend Advance Strategy, you'll first need a TradingView account. If you haven't set one up yet, here's how:
1. Account Creation:
• Visit TradingView's official website.
• Click on the "Join for free" or "Sign up" button.
• Follow the registration process, providing the necessary details and setting up your login credentials.
2. Navigating the Dashboard:
• Once logged in, you'll be taken to your dashboard. Here, you'll see a variety of tools, including watchlists, alerts, and the main charting window.
• To begin charting, type in the name or ticker of the asset you're interested in the search bar at the top.
3. Configuring Chart Settings:
• Before integrating the Supertrend Advance Strategy, familiarize yourself with the chart settings. This can be accessed by clicking the 'gear' icon on the top right of the chart window.
• Adjust the chart type, time intervals, and other display settings to your preference.
Integrating the Strategy into a Chart:
Now that you're set up on TradingView, it's time to integrate the Supertrend Advance Strategy.
1. Accessing the Pine Script Editor:
• Located at the top-center of your screen, you'll find the "Pine Editor" tab. Click on it.
• This is where custom strategies and indicators are scripted or imported.
2. Loading the Supertrend Advance Strategy Script:
• Depending on whether you have the script or need to find it, there are two paths:
• If you have the script: Copy the Supertrend Advance Strategy script, and then paste it into the Pine Editor.
• If searching for the script: Click on the “Indicators” icon (looks like a flame) at the top of your screen, and then type “Supertrend Advance Strategy” in the search bar. If available, it will show up in the list. Simply click to add it to your chart.
3. Applying the Strategy:
• After pasting or selecting the Supertrend Advance Strategy in the Pine Editor, click on the “Add to Chart” button located at the top of the editor. This will overlay the strategy onto your main chart window.
4. Configuring Strategy Settings:
• Once the strategy is on your chart, you'll notice a small settings ('gear') icon next to its name in the top-left of the chart window. Click on this to access settings.
• Here, you can adjust various parameters of the Supertrend Advance Strategy to better fit your trading style or the specific asset you're analyzing.
5. Interpreting Signals:
• With the strategy applied, you'll now see buy/sell signals represented on your chart. Take time to familiarize yourself with how these look and behave over various timeframes and market conditions.
3. Strategy Overview
What is the Supertrend Advance Strategy?
The Supertrend Advance Strategy is a refined version of the classic Supertrend Indicator, which was developed to aid traders in spotting market trends. The strategy utilizes a combination of data points, including average true range (ATR) and price momentum, to generate buy and sell signals.
In essence, the Supertrend Advance Strategy can be visualized as a line that moves with the price. When the price is above the Supertrend line, it indicates an uptrend and suggests a potential buy position. Conversely, when the price is below the Supertrend line, it hints at a downtrend, suggesting a potential selling point.
Strategy Goals and Objectives:
1. Trend Identification: At the core of the Supertrend Advance Strategy is the goal to efficiently and consistently identify prevailing market trends. By recognizing these trends, traders can position themselves to capitalize on price movements in their favor.
2. Reducing Noise: Financial markets are often inundated with 'noise' - short-term price fluctuations that can mislead traders. The Supertrend Advance Strategy aims to filter out this noise, allowing for clearer decision-making.
3. Enhancing Risk Management: With clear buy and sell signals, traders can set more precise stop-loss and take-profit points. This leads to better risk management and potentially improved profitability.
4. Versatility: While primarily used for trend identification, the strategy can be integrated with other technical tools and indicators to create a comprehensive trading system.
Type of Assets/Markets to Apply the Strategy:
1. Equities: The Supertrend Advance Strategy is highly popular among stock traders. Its ability to capture long-term trends makes it particularly useful for those trading individual stocks or equity indices.
2. Forex: Given the 24-hour nature of the Forex market and its propensity for trends, the Supertrend Advance Strategy is a valuable tool for currency traders.
3. Commodities: Whether it's gold, oil, or agricultural products, commodities often move in extended trends. The strategy can help in identifying and capitalizing on these movements.
4. Cryptocurrencies: The volatile nature of cryptocurrencies means they can have pronounced trends. The Supertrend Advance Strategy can aid crypto traders in navigating these often tumultuous waters.
5. Futures & Options: Traders and investors in derivative markets can utilize the strategy to make more informed decisions about contract entries and exits.
It's important to note that while the Supertrend Advance Strategy can be applied across various assets and markets, its effectiveness might vary based on market conditions, timeframe, and the specific characteristics of the asset in question. As always, it's recommended to use the strategy in conjunction with other analytical tools and to backtest its effectiveness in specific scenarios before committing to trades.
4. Input Settings
Understanding and correctly configuring input settings is crucial for optimizing the Supertrend Advance Strategy for any specific market or asset. These settings, when tweaked correctly, can drastically impact the strategy's performance.
Grouping Inputs:
Before diving into individual input settings, it's important to group similar inputs. Grouping can simplify the user interface, making it easier to adjust settings related to a specific function or indicator.
Strategy Choice:
This input allows traders to select from various strategies that incorporate the Supertrend indicator. Options might include "Supertrend with RSI," "Supertrend with MACD," etc. By choosing a strategy, the associated input settings for that strategy become available.
Supertrend Settings:
1. Multiplier: Typically, a default value of 3 is used. This multiplier is used in the ATR calculation. Increasing it makes the Supertrend line further from prices, while decreasing it brings the line closer.
2. Period: The number of bars used in the ATR calculation. A common default is 7.
EMA Settings (Exponential Moving Average):
1. Period: Defines the number of previous bars used to calculate the EMA. Common periods are 9, 21, 50, and 200.
2. Source: Allows traders to choose which price (Open, Close, High, Low) to use in the EMA calculation.
RSI Settings (Relative Strength Index):
1. Length: Determines how many periods are used for RSI calculation. The standard setting is 14.
2. Overbought Level: The threshold at which the asset is considered overbought, typically set at 70.
3. Oversold Level: The threshold at which the asset is considered oversold, often at 30.
MACD Settings (Moving Average Convergence Divergence):
1. Short Period: The shorter EMA, usually set to 12.
2. Long Period: The longer EMA, commonly set to 26.
3. Signal Period: Defines the EMA of the MACD line, typically set at 9.
CCI Settings (Commodity Channel Index):
1. Period: The number of bars used in the CCI calculation, often set to 20.
2. Overbought Level: Typically set at +100, denoting overbought conditions.
3. Oversold Level: Usually set at -100, indicating oversold conditions.
SL/TP Settings (Stop Loss/Take Profit):
1. SL Multiplier: Defines the multiplier for the average true range (ATR) to set the stop loss.
2. TP Multiplier: Defines the multiplier for the average true range (ATR) to set the take profit.
Filtering Conditions:
This section allows traders to set conditions to filter out certain signals. For example, one might only want to take buy signals when the RSI is below 30, ensuring they buy during oversold conditions.
Trade Direction and Backtest Period:
1. Trade Direction: Allows traders to specify whether they want to take long trades, short trades, or both.
2. Backtest Period: Specifies the time range for backtesting the strategy. Traders can choose from options like 'Last 6 months,' 'Last 1 year,' etc.
It's essential to remember that while default settings are provided for many of these tools, optimal settings can vary based on the market, timeframe, and trading style. Always backtest new settings on historical data to gauge their potential efficacy.
5. Understanding Strategy Conditions
Developing an understanding of the conditions set within a trading strategy is essential for traders to maximize its potential. Here, we delve deep into the logic behind these conditions, using the Supertrend Advance Strategy as our focal point.
Basic Logic Behind Conditions:
Every strategy is built around a set of conditions that provide buy or sell signals. The conditions are based on mathematical or statistical methods and are rooted in the study of historical price data. The fundamental idea is to recognize patterns or behaviors that have been profitable in the past and might be profitable in the future.
Buy and Sell Conditions:
1. Buy Conditions: Usually formulated around bullish signals or indicators suggesting upward price momentum.
2. Sell Conditions: Centered on bearish signals or indicators indicating downward price momentum.
Simple Strategy:
The simple strategy could involve using just the Supertrend indicator. Here:
• Buy: When price closes above the Supertrend line.
• Sell: When price closes below the Supertrend line.
Pullback Strategy:
This strategy capitalizes on price retracements:
• Buy: When the price retraces to the Supertrend line after a bullish signal and is supported by another bullish indicator.
• Sell: When the price retraces to the Supertrend line after a bearish signal and is confirmed by another bearish indicator.
Indicators Used:
EMA (Exponential Moving Average):
• Logic: EMA gives more weight to recent prices, making it more responsive to current price movements. A shorter-period EMA crossing above a longer-period EMA can be a bullish sign, while the opposite is bearish.
RSI (Relative Strength Index):
• Logic: RSI measures the magnitude of recent price changes to analyze overbought or oversold conditions. Values above 70 are typically considered overbought, and values below 30 are considered oversold.
MACD (Moving Average Convergence Divergence):
• Logic: MACD assesses the relationship between two EMAs of a security’s price. The MACD line crossing above the signal line can be a bullish signal, while crossing below can be bearish.
CCI (Commodity Channel Index):
• Logic: CCI compares a security's average price change with its average price variation. A CCI value above +100 may mean the price is overbought, while below -100 might signify an oversold condition.
And others...
As the strategy expands or contracts, more indicators might be added or removed. The crucial point is to understand the core logic behind each, ensuring they align with the strategy's objectives.
Logic Behind Each Indicator:
1. EMA: Emphasizes recent price movements; provides dynamic support and resistance levels.
2. RSI: Indicates overbought and oversold conditions based on recent price changes.
3. MACD: Showcases momentum and direction of a trend by comparing two EMAs.
4. CCI: Measures the difference between a security's price change and its average price change.
Understanding strategy conditions is not just about knowing when to buy or sell but also about comprehending the underlying market dynamics that those conditions represent. As you familiarize yourself with each condition and indicator, you'll be better prepared to adapt and evolve with the ever-changing financial markets.
6. Trade Execution and Management
Trade execution and management are crucial aspects of any trading strategy. Efficient execution can significantly impact profitability, while effective management can preserve capital during adverse market conditions. In this section, we'll explore the nuances of position entry, exit strategies, and various Stop Loss (SL) and Take Profit (TP) methodologies within the Supertrend Advance Strategy.
Position Entry:
Effective trade entry revolves around:
1. Timing: Enter at a point where the risk-reward ratio is favorable. This often corresponds to confirmatory signals from multiple indicators.
2. Volume Analysis: Ensure there's adequate volume to support the movement. Volume can validate the strength of a signal.
3. Confirmation: Use multiple indicators or chart patterns to confirm the entry point. For instance, a buy signal from the Supertrend indicator can be confirmed with a bullish MACD crossover.
Position Exit Strategies:
A successful exit strategy will lock in profits and minimize losses. Here are some strategies:
1. Fixed Time Exit: Exiting after a predetermined period.
2. Percentage-based Profit Target: Exiting after a certain percentage gain.
3. Indicator-based Exit: Exiting when an indicator gives an opposing signal.
Percentage-based SL/TP:
• Stop Loss (SL): Set a fixed percentage below the entry price to limit potential losses.
• Example: A 2% SL on an entry at $100 would trigger a sell at $98.
• Take Profit (TP): Set a fixed percentage above the entry price to lock in gains.
• Example: A 5% TP on an entry at $100 would trigger a sell at $105.
Supertrend-based SL/TP:
• Stop Loss (SL): Position the SL at the Supertrend line. If the price breaches this line, it could indicate a trend reversal.
• Take Profit (TP): One could set the TP at a point where the Supertrend line flattens or turns, indicating a possible slowdown in momentum.
Swing high/low-based SL/TP:
• Stop Loss (SL): For a long position, set the SL just below the recent swing low. For a short position, set it just above the recent swing high.
• Take Profit (TP): For a long position, set the TP near a recent swing high or resistance. For a short position, near a swing low or support.
And other methods...
1. Trailing Stop Loss: This dynamic SL adjusts with the price movement, locking in profits as the trade moves in your favor.
2. Multiple Take Profits: Divide the position into segments and set multiple TP levels, securing profits in stages.
3. Opposite Signal Exit: Exit when another reliable indicator gives an opposite signal.
Trade execution and management are as much an art as they are a science. They require a blend of analytical skill, discipline, and intuition. Regularly reviewing and refining your strategies, especially in light of changing market conditions, is crucial to maintaining consistent trading performance.
7. Visual Representations
Visual tools are essential for traders, as they simplify complex data into an easily interpretable format. Properly analyzing and understanding the plots on a chart can provide actionable insights and a more intuitive grasp of market conditions. In this section, we’ll delve into various visual representations used in the Supertrend Advance Strategy and their significance.
Understanding Plots on the Chart:
Charts are the primary visual aids for traders. The arrangement of data points, lines, and colors on them tell a story about the market's past, present, and potential future moves.
1. Data Points: These represent individual price actions over a specific timeframe. For instance, a daily chart will have data points showing the opening, closing, high, and low prices for each day.
2. Colors: Used to indicate the nature of price movement. Commonly, green is used for bullish (upward) moves and red for bearish (downward) moves.
Trend Lines:
Trend lines are straight lines drawn on a chart that connect a series of price points. Their significance:
1. Uptrend Line: Drawn along the lows, representing support. A break below might indicate a trend reversal.
2. Downtrend Line: Drawn along the highs, indicating resistance. A break above might suggest the start of a bullish trend.
Filled Areas:
These represent a range between two values on a chart, usually shaded or colored. For instance:
1. Bollinger Bands: The area between the upper and lower band is filled, giving a visual representation of volatility.
2. Volume Profile: Can show a filled area representing the amount of trading activity at different price levels.
Stop Loss and Take Profit Lines:
These are horizontal lines representing pre-determined exit points for trades.
1. Stop Loss Line: Indicates the level at which a trade will be automatically closed to limit losses. Positioned according to the trader's risk tolerance.
2. Take Profit Line: Denotes the target level to lock in profits. Set according to potential resistance (for long trades) or support (for short trades) or other technical factors.
Trailing Stop Lines:
A trailing stop is a dynamic form of stop loss that moves with the price. On a chart:
1. For Long Trades: Starts below the entry price and moves up with the price but remains static if the price falls, ensuring profits are locked in.
2. For Short Trades: Starts above the entry price and moves down with the price but remains static if the price rises.
Visual representations offer traders a clear, organized view of market dynamics. Familiarity with these tools ensures that traders can quickly and accurately interpret chart data, leading to more informed decision-making. Always ensure that the visual aids used resonate with your trading style and strategy for the best results.
8. Backtesting
Backtesting is a fundamental process in strategy development, enabling traders to evaluate the efficacy of their strategy using historical data. It provides a snapshot of how the strategy would have performed in past market conditions, offering insights into its potential strengths and vulnerabilities. In this section, we'll explore the intricacies of setting up and analyzing backtest results and the caveats one must be aware of.
Setting Up Backtest Period:
1. Duration: Determine the timeframe for the backtest. It should be long enough to capture various market conditions (bullish, bearish, sideways). For instance, if you're testing a daily strategy, consider a period of several years.
2. Data Quality: Ensure the data source is reliable, offering high-resolution and clean data. This is vital to get accurate backtest results.
3. Segmentation: Instead of a continuous period, sometimes it's helpful to backtest over distinct market phases, like a particular bear or bull market, to see how the strategy holds up in different environments.
Analyzing Backtest Results:
1. Performance Metrics: Examine metrics like the total return, annualized return, maximum drawdown, Sharpe ratio, and others to gauge the strategy's efficiency.
2. Win Rate: It's the ratio of winning trades to total trades. A high win rate doesn't always signify a good strategy; it should be evaluated in conjunction with other metrics.
3. Risk/Reward: Understand the average profit versus the average loss per trade. A strategy might have a low win rate but still be profitable if the average gain far exceeds the average loss.
4. Drawdown Analysis: Review the periods of losses the strategy could incur and how long it takes, on average, to recover.
9. Tips and Best Practices
Successful trading requires more than just knowing how a strategy works. It necessitates an understanding of when to apply it, how to adjust it to varying market conditions, and the wisdom to recognize and avoid common pitfalls. This section offers insightful tips and best practices to enhance the application of the Supertrend Advance Strategy.
When to Use the Strategy:
1. Market Conditions: Ideally, employ the Supertrend Advance Strategy during trending market conditions. This strategy thrives when there are clear upward or downward trends. It might be less effective during consolidative or sideways markets.
2. News Events: Be cautious around significant news events, as they can cause extreme volatility. It might be wise to avoid trading immediately before and after high-impact news.
3. Liquidity: Ensure you are trading in assets/markets with sufficient liquidity. High liquidity ensures that the price movements are more reflective of genuine market sentiment and not due to thin volume.
Adjusting Settings for Different Markets/Timeframes:
1. Markets: Each market (stocks, forex, commodities) has its own characteristics. It's essential to adjust the strategy's parameters to align with the market's volatility and liquidity.
2. Timeframes: Shorter timeframes (like 1-minute or 5-minute charts) tend to have more noise. You might need to adjust the settings to filter out false signals. Conversely, for longer timeframes (like daily or weekly charts), you might need to be more responsive to genuine trend changes.
3. Customization: Regularly review and tweak the strategy's settings. Periodic adjustments can ensure the strategy remains optimized for the current market conditions.
10. Frequently Asked Questions (FAQs)
Given the complexities and nuances of the Supertrend Advance Strategy, it's only natural for traders, both new and seasoned, to have questions. This section addresses some of the most commonly asked questions regarding the strategy.
1. What exactly is the Supertrend Advance Strategy?
The Supertrend Advance Strategy is an evolved version of the traditional Supertrend indicator. It's designed to provide clearer buy and sell signals by incorporating additional indicators like EMA, RSI, MACD, CCI, etc. The strategy aims to capitalize on market trends while minimizing false signals.
2. Can I use the Supertrend Advance Strategy for all asset types?
Yes, the strategy can be applied to various asset types like stocks, forex, commodities, and cryptocurrencies. However, it's crucial to adjust the settings accordingly to suit the specific characteristics and volatility of each asset type.
3. Is this strategy suitable for day trading?
Absolutely! The Supertrend Advance Strategy can be adjusted to suit various timeframes, making it versatile for both day trading and long-term trading. Remember to fine-tune the settings to align with the timeframe you're trading on.
4. How do I deal with false signals?
No strategy is immune to false signals. However, by combining the Supertrend with other indicators and adhering to strict risk management protocols, you can minimize the impact of false signals. Always use stop-loss orders and consider filtering trades with additional confirmation signals.
5. Do I need any prior trading experience to use this strategy?
While the Supertrend Advance Strategy is designed to be user-friendly, having a foundational understanding of trading and market analysis can greatly enhance your ability to employ the strategy effectively. If you're a beginner, consider pairing the strategy with further education and practice on demo accounts.
6. How often should I review and adjust the strategy settings?
There's no one-size-fits-all answer. Some traders adjust settings weekly, while others might do it monthly. The key is to remain responsive to changing market conditions. Regular backtesting can give insights into potential required adjustments.
7. Can the Supertrend Advance Strategy be automated?
Yes, many traders use algorithmic trading platforms to automate their strategies, including the Supertrend Advance Strategy. However, always monitor automated systems regularly to ensure they're operating as intended.
8. Are there any markets or conditions where the strategy shouldn't be used?
The strategy might generate more false signals in markets that are consolidative or range-bound. During significant news events or times of unexpected high volatility, it's advisable to tread with caution or stay out of the market.
9. How important is backtesting with this strategy?
Backtesting is crucial as it allows traders to understand how the strategy would have performed in the past, offering insights into potential profitability and areas of improvement. Always backtest any new setting or tweak before applying it to live trades.
10. What if the strategy isn't working for me?
No strategy guarantees consistent profits. If it's not working for you, consider reviewing your settings, seeking expert advice, or complementing the Supertrend Advance Strategy with other analysis methods. Remember, continuous learning and adaptation are the keys to trading success.
Other comments
Value of combining several indicators in this script and how they work together
Diversification of Signals: Just as diversifying an investment portfolio can reduce risk, using multiple indicators can offer varied perspectives on potential price movements. Each indicator can capture a different facet of the market, ensuring that traders are not overly reliant on a single data point.
Confirmation & Reduced False Signals: A common challenge with many indicators is the potential for false signals. By requiring confirmation from multiple indicators before acting, the chances of acting on a false signal can be significantly reduced.
Flexibility Across Market Conditions: Different indicators might perform better under different market conditions. For example, while moving averages might excel in trending markets, oscillators like RSI might be more useful during sideways or range-bound conditions. A mashup strategy can potentially adapt better to varying market scenarios.
Comprehensive Analysis: With multiple indicators, traders can gauge trend strength, momentum, volatility, and potential market reversals all at once, providing a holistic view of the market.
How do the different indicators in the Supertrend Advance Strategy work together?
Supertrend: This is primarily a trend-following indicator. It provides traders with buy and sell signals based on the volatility of the price. When combined with other indicators, it can filter out noise and give more weight to strong, confirmed trends.
EMA (Exponential Moving Average): EMA gives more weight to recent price data. It can be used to identify the direction and strength of a trend. When the price is above the EMA, it's generally considered bullish, and vice versa.
RSI (Relative Strength Index): An oscillator that measures the magnitude of recent price changes to evaluate overbought or oversold conditions. By cross-referencing with other indicators like EMA or MACD, traders can spot potential reversals or confirmations of a trend.
MACD (Moving Average Convergence Divergence): This indicator identifies changes in the strength, direction, momentum, and duration of a trend in a stock's price. When the MACD line crosses above the signal line, it can be a bullish sign, and when it crosses below, it can be bearish. Pairing MACD with Supertrend can provide dual confirmation of a trend.
CCI (Commodity Channel Index): Initially developed for commodities, CCI can indicate overbought or oversold conditions. It can be used in conjunction with other indicators to determine entry and exit points.
In essence, the synergy of these indicators provides a balanced, comprehensive approach to trading. Each indicator offers its unique lens into market conditions, and when they align, it can be a powerful indication of a trading opportunity. This combination not only reduces the potential drawbacks of each individual indicator but leverages their strengths, aiming for more consistent and informed trading decisions.
Backtesting and Default Settings
• This indicator has been optimized to be applied for 1 hour-charts. However, the underlying principles of this strategy are supply and demand in the financial markets and the strategy can be applied to all timeframes. Daytraders can use the 1min- or 5min charts, swing-traders can use the daily charts.
• This strategy has been designed to identify the most promising, highest probability entries and trades for each stock or other financial security.
• The combination of the qualifiers results in a highly selective strategy which only considers the most promising swing-trading entries. As a result, you will normally only find a low number of trades for each stock or other financial security per year in case you apply this strategy for the daily charts. Shorter timeframes will result in a higher number of trades / year.
• Consequently, traders need to apply this strategy for a full watchlist rather than just one financial security.
• Default properties: RSI on (length 14, RSI buy level 50, sell level 50), EMA, RSI, MACD on, type of strategy pullback, SL/TP type: ATR (length 10, factor 3), trade direction both, quantity 5, take profit swing hl 5.1, highest / lowest lookback 2, enable ATR trail (ATR length 10, SL ATR multiplier 1.4, TP multiplier 2.1, lookback = 4, trade direction = both).
LA - MACD EMA BandsOverview of the "LA - MACD EMA Bands" Indicator
For Better view, use this indicator along with "LA - EMA Bands with MTF Dashboard"
The "LA - MACD EMA Bands" is a custom technical indicator written in Pine Script v6 for TradingView. It builds on the traditional Moving Average Convergence Divergence (MACD) oscillator by incorporating additional smoothing via Exponential Moving Averages (EMAs) and Bollinger Bands (BB) applied directly to the MACD line. This creates a multi-layered momentum and volatility tool displayed in a separate pane below the price chart (not overlaid on the price itself).
The indicator allows for customization, such as selecting a different timeframe (for multi-timeframe analysis) and adjusting period lengths. It fetches data from the specified timeframe using request.security with lookahead enabled to avoid repainting issues. The core idea is to provide insights into momentum trends, crossovers, and volatility expansions/contractions in the MACD's behavior, making it suitable for identifying potential trend reversals, continuations, or ranging markets.
Unlike a standard MACD, which focuses primarily on momentum via a single line, signal line, and histogram, this version emphasizes longer-term smoothing and volatility boundaries. It uses visual fills between lines to highlight bullish/bearish conditions, aiding quick interpretation. Below, I'll break down each component, its calculation, visual representation, and practical uses.
Detailed Breakdown of Each Component and Its Uses
MACD Line (Blue Line, Labeled 'MACD Line')
Calculation: This is the core MACD value, computed as the difference between a fast EMA (default length 12) and a slow EMA (default length 144) of the input source (default: close price). The EMAs are calculated on data from the selected timeframe.
Visuals: Plotted as a solid blue line.
Uses:
Measures momentum: When above zero, it indicates bullish momentum (prices rising faster in the short term); below zero, bearish momentum.
Trend identification: Rising MACD suggests strengthening uptrends; falling suggests downtrends.
Divergence spotting: Compare with price action—e.g., if price makes higher highs but MACD makes lower highs, it signals potential bearish reversal (and vice versa for bullish divergence).
In trading: Often used for entry/exit signals when crossing the zero line or other lines in the indicator.
MACD EMA (Red Line, Labeled 'MACD EMA')
Calculation: A 12-period EMA applied to the MACD Line itself.
Visuals: Plotted as a solid red line.
Uses:
Acts as a signal line for the MACD, smoothing out short-term noise.
Crossover signals: When the MACD Line crosses above the MACD EMA, it can signal a bullish buy opportunity; crossing below suggests a bearish sell.
Trend confirmation: Helps filter false signals in choppy markets by requiring confirmation from this slower-moving average.
In trading: Useful for momentum-based strategies, like entering trades on crossovers in alignment with the overall trend.
Fill Between MACD Line and MACD EMA (Green/Red Shaded Area, Titled 'MACD Fill')
Calculation: The area between the MACD Line and MACD EMA is filled with color based on their relative positions.
Color Logic: Green (with 57% transparency) if MACD Line > MACD EMA (bullish); red if MACD Line < MACD EMA (bearish).
Visuals: Semi-transparent fill for easy visibility without overwhelming the lines.
Uses:
Quick visual cue for momentum shifts: Green areas highlight bullish phases; red for bearish.
Enhances readability: Makes crossovers more apparent at a glance, especially in fast-moving markets.
In trading: Can be used to time entries/exits or as a filter (e.g., only take long trades in green zones).
Bollinger Bands on MACD (BB Upper: Black Dotted, BB Basis: Maroon Dotted, BB Lower: Black Dotted)
Calculation: Bollinger Bands applied to the MACD Line.
BB Basis: 144-period EMA of the MACD Line.
BB Standard Deviation: 144-period stdev of the MACD Line.
BB Upper: BB Basis + (2.0 * BB Stdev)
BB Lower: BB Basis - (2.0 * BB Stdev)
Visuals: Upper and lower bands as black dotted lines; basis as maroon dotted
Uses:
Volatility measurement: Bands expand during high momentum volatility (strong trends) and contract during low volatility (ranging or consolidation).
Mean reversion: When MACD Line touches or exceeds the upper band, it may signal overbought conditions (potential sell); lower band for oversold (potential buy).
Squeeze detection: Narrow bands (squeeze) often precede big moves—watch for breakouts.
In trading: Combines momentum with volatility; e.g., a MACD Line breakout above the upper band could confirm a strong uptrend.
BB Basis EMA (Green Line, Labeled 'BB Basis EMA')
Calculation: A 72-period EMA applied to the BB Basis (which is already a 144-period EMA of the MACD Line).
Visuals: Solid green line.
Uses:
Further smoothing: Provides a longer-term view of the MACD's average behavior, reducing noise from the BB Basis.
Trend direction: Acts as a baseline for the BB system—above it suggests bullish bias in momentum volatility; below, bearish.
Crossover with BB Basis: Can signal shifts in volatility trends (e.g., BB Basis crossing above BB Basis EMA indicates increasing bullish volatility).
In trading: Useful for confirming longer-term trends or as a filter for BB-based signals.
Fill Between BB Basis and BB Basis EMA (Gray Shaded Area, Titled 'BB Basis Fill')
Calculation: The area between BB Basis and BB Basis EMA is filled.
Color Logic: Currently set to a constant semi-transparent gray regardless of position.
Visuals: Semi-transparent gray fill.
Uses:
Highlights divergence: Shows when the shorter-term BB Basis deviates from its longer-term EMA, indicating potential volatility shifts.
Visual aid for crossovers: Makes it easier to spot when BB Basis crosses its EMA.
In trading: Could be used to identify overextensions in volatility (e.g., wide gray areas might signal impending mean reversion).
Zero Line (Black Horizontal Line)
Calculation: A simple horizontal line at y=0.
Visuals: Solid black line.
Uses:
Reference point: Divides bullish (above) from bearish (below) territory for all MACD-related lines.
In trading: Crossovers of the zero line by the MACD Line or BB Basis can signal major trend changes.
How It Differs from a Normal MACD
A standard MACD (e.g., the built-in TradingView MACD with defaults 12/26/9) consists of:
MACD Line: EMA(12) - EMA(26).
Signal Line: EMA(MACD Line, 9).
Histogram: MACD Line - Signal Line (bars showing convergence/divergence).
Key differences in "LA - MACD EMA Bands":
Periods: Uses a much longer slow EMA (144 vs. 26), making it more sensitive to long-term trends but less reactive to short-term price action. The MACD EMA is 12 periods (vs. 9), further emphasizing smoothing.
No Histogram: Replaces the histogram with fills and bands for visual emphasis on crossovers and volatility.
Added Bollinger Bands: Applies BB directly to the MACD Line (with a long 144-period basis), introducing volatility analysis absent in standard MACD. This helps detect "squeezes" or expansions in momentum.
Additional EMA Layer: The BB Basis EMA (72-period) adds a secondary smoothing level to the BB system, providing a hierarchical view of momentum (short-term MACD → mid-term BB → long-term EMA).
Multi-Timeframe Support: Built-in option for higher timeframes, unlike basic MACD.
Focus: Standard MACD is purely momentum-focused; this version integrates volatility (via BB) and multi-layer smoothing, making it better for trend-following in volatile markets but potentially overwhelming for beginners.
Overall, this indicator transforms the MACD from a simple oscillator into a comprehensive momentum-volatility hybrid, reducing false signals in trending markets but introducing lag.
Overall Pros and Cons
Pros:
Enhanced Visualization: Fills and bands make trends, crossovers, and volatility easier to spot without needing multiple indicators.
Reduced Noise: Longer periods (144, 72) smooth out whipsaws, ideal for swing or position trading in trending assets like stocks or forex.
Volatility Integration: BB adds a dimension not in standard MACD, helping identify breakouts or consolidations.
Customizable: Inputs for timeframes and lengths allow adaptation to different assets/timeframes.
Multi-Layered Insights: Combines short-term signals (MACD crossovers) with long-term confirmation (BB EMA), improving signal reliability.
Cons:
Lagging Nature: Long periods (e.g., 144) delay signals, missing early entries in fast markets or leading to late exits.
Complexity: Multiple lines and fills can clutter the pane, requiring experience to interpret; beginners might misread it.
Potential Overfitting: Custom periods (12/144/12/144/72) may work well on historical data but underperform in live trading without backtesting.
No Built-in Alerts/Signals: Relies on visual interpretation; users must manually set alerts for crossovers.
Resource Intensive: On lower timeframes or with lookahead, it might slow chart loading on Trading View.
This indicator shines in strategies combining momentum and volatility, like trend-following with BB squeezes, but test it on your assets (e.g., via backtesting) to ensure it fits your style.
For Better view, use this indicator along with "LA - EMA Bands with MTF Dashboard"
Cnagda Pure Price ActionCnagda Pure Price Action (CPPA) indicator is a pure price action-based system designed to provide traders with real-time, dynamic analysis of the market. It automatically identifies key candles, support and resistance zones, and potential buy/sell signals by combining price, volume, and multiple popular trend indicators.
How Price Action & Volume Analysis Works
Silver Zone – Logic, Reason, and Trade Planning
Logic & Visualization:
The Silver Zone is created when the closing price is the lowest in the chosen window and volume is the highest in that window.
Visually, a large silver-colored box/rectangle appears on the chart.
Thick horizontal lines (top and bottom) are drawn at the high and low of that candle/bar, extending to the right.
Reasoning:
This combination typically occurs at strong “accumulation” or support areas:
Sellers push the price down to the lowest point, but aggressive buyers step in with high volume, absorbing supply.
Indicates potential exhaustion of selling and likely shift in market control to buyers.
How to Plan Trades Using Silver Zone:
Watch if price returns to the Silver Zone in the future: It often acts as powerful support.
Bullish entries (buys) can be planned when price tests or slightly pierces this zone, especially if new buy signals occur (like yellow/green candle labels).
Place your stop-loss below the bottom line of the Silver Zone.
Target: Look for the nearest resistance or opposing zone, or use indicator’s bullish label as confirmation.
Extra Tip:
Multiple touches of the Silver Zone reinforce its importance, but if price closes deeply below it with high volume, that’s a caution signal—support may be breaking.
Black Zone – Logic, Reason, and Trade Planning (as CPPA):
Logic & Visualization:
The Black Zone is created when the closing price is the highest in the chosen window and volume is the lowest in that window.
Visually, a large black-colored box/rectangle appears on the chart, along with thick horizontal lines at the top (high) and bottom (low) of the candle, extending to the right.
Reasoning:
This combination signals a strong “distribution” or resistance area:
Buyers push the price up to a local high, but low volume means there is not much follow-through or conviction in the move.
Often marks exhaustion where uptrend may pause or reverse, as sellers can soon step in.
How to Plan Trades Using Black Zone:
If price revisits the Black Zone in the future, it often acts as major resistance.
Bearish entries (sells) are considered when price is near, testing, or slightly above the Black Zone—especially if new sell signals appear (like blue/red candle labels).
Place your stop-loss just above the top line of the Black Zone.
Target: Nearest support zone (such as a Silver Zone) or next indicator’s bearish label.
Extra Tip:
Multiple touches of the Black Zone make it stronger, but if price closes far above with rising volume, be cautious—resistance might be breaking.
Support Line – Logic, Reason, and Trade Planning (as Cppa):
Logic & Visualization:
The Support Line is a dynamically drawn dashed line (usually blue) that marks key price levels where the market has previously shown significant buying interest.
The line is generated whenever a candle forms a high price with high volume (orange logic).
The script checks for historical pivot lows, past support zones, and even higher timeframe (HTF) supports, and then extends a blue dashed line from that price level to the right, labeling it (sometimes as “Prev Support Orange, HTF”).
Reasoning:
This line helps you visually identify where demand has been strong enough to hold price from falling further—essentially a floor in the market used by professional traders.
If price approaches or re-tests this line, there’s a good chance buyers will defend it again.
How to Plan Trades Using Support Line:
Watch for price to approach the Support Line during down moves. If you see a bullish candlestick pattern, buy labels (yellow/green), or other indicators aligning, this can be a high-probability entry zone.
Great for planning stop-loss for long trades: place stops just below this line.
Target: Next resistance zone, Black Zone, or the top of the last swing.
Extra Tip:
Multiple confirmations (support line + Silver Zone + bullish label) provide powerful entry signals.
If price closes strongly below the Support Line with volume, be cautious—support may be breaking, and a trend reversal or deeper correction could follow.
Resistance Line – Logic, Reason, and Trade Planning (from CPPA):
Logic & Visualization:
The Resistance Line is a dynamically drawn dashed line (usually purple or red) that identifies price levels where the market has previously faced significant selling pressure.
This line is created when a candle reaches a high price combined with high volume (orange logic), or from a historical pivot high/resistance,
The script also tracks higher timeframe (HTF) resistance lines, labeled as “Prev Resistance Orange, HTF,” and extends these dashed lines to the right across the chart.
Reasoning:
Resistance Lines are visual markers of “supply zones,” where buyers previously failed, and sellers took control.
If the price returns to this line later, sellers may get active again to defend this level, halting the uptrend.
How to Plan Trades Using Resistance Line:
Watch for price to approach the Resistance Line during up moves. If you see bearish candlestick patterns, sell labels (blue/red), or bearish indicator confirmation, this becomes a strong shorting opportunity.
Perfect for placing stop-loss in short trades—put your stop just above the Resistance Line.
Target: Next support zone (Silver Zone) or bottom of the last swing.
If the price breaks above with high volume, avoid shorting—resistance may be failing.
Extra Tip:
Multiple resistances (Resistance Line + Black Zone + bearish label) make short signals stronger.
Choppy movement around this line often signals indecision; wait for a clear rejection before entering trades.
Bullish / Bearish Label – Logic, Reason, and Trade Planning:
Logic & Visualization:
The indicator constantly calculates a "Bull Score" and a "Bear Score" based on several factors:
Trend direction from price slope
Confirmation by popular indicators (RSI, ADX, SAR, CMF, OBV, CCI, Bollinger Bands, TWAP)
Adaptive scoring (higher score for each bullish/bearish condition met)
If Bull Score > Bear Score, the chart displays a green "BULLISH" label (usually below the bar).
If Bear Score > Bull Score, the chart displays a red "BEARISH" label (usually above the bar).
If neither dominates, a "NEUTRAL" label appears.
Reasoning:
The labels summarize complex price action and indicator analysis into a simple, actionable sentiment cue:
Bullish: Majority of conditions indicate buying strength; trend is up.
Bearish: Majority signals show selling pressure; trend is down.
How to Use in Trade Planning:
Use the Bullish label as confirmation to enter or hold long (buy) positions, especially if near support/Silver Zone.
Use the Bearish label to enter/hold short (sell) positions, especially if near resistance/Black Zone.
For best results, combine with candle color, volume analysis, or other labels (yellow/green for buys, blue/red for sells).
Avoid trading against these labels unless you have strong confluence from zones/support levels.
Yellow Label (Buy Signal) – Logic, Reason & Trade Planning:
Logic & Visualization:
The yellow label appears below a candle (label.style_label_up, yloc.belowbar) and marks a potential buy signal.
Script conditions:
The candle must be a “yellow candle” (which means it’s at the local lowest close, not a high, with normal volume).
Volume is decreasing for 2 consecutive candles (current volume < previous volume, previous volume < second previous).
When these conditions are met, a yellow label is plotted below the candle.
Reasoning:
This scenario often marks the end of selling pressure and start of possible accumulation—buyers may be stepping in as sellers exhaust.
Decreasing volume during a local price low means selling is slowing, possibly hinting at a reversal.
How to Trade Using Yellow Label:
Entry: Consider buying at/just above the yellow-labeled candle’s close.
Stop-loss: A bit below the candle’s low (or Silver Zone line, if present).
Target: Next resistance level, Black Zone, or chart’s bullish label.
Extra Tip:
If the yellow label is found at/near a Silver Zone or Support Line, and trend is “Bullish,” the setup gets even stronger.
Avoid trading if overall indicator shows “Bearish.”
Green Label (Buy with Increasing Volume) – Logic, Reason & Trade Planning:
Logic & Visualization:
The green label is plotted below a candle (label.style_label_up, yloc.belowbar) and marks a strong buy signal.
Script conditions:
The candle must be a “yellow candle” (at the local lowest close, normal volume).
Volume is increasing for 2 consecutive candles (current volume > previous volume, previous volume > second previous).
When these conditions are met, a green label is plotted below the candle.
Reasoning:
This scenario signals that buyers are stepping in aggressively at a local price low—the end of a downtrend with strong, rising activity.
Increasing volume at a price low is a classic sign of accumulation, where institutions or large players may be buying.
How to Trade Using Green Label:
Entry: Consider buying at/just above the green-labeled candle’s close for a momentum-based reversal.
Stop-loss: Slightly below the candle’s low, or the Silver Zone/support line if present.
Target: Nearest resistance zone/Black Zone, indicator’s bullish label, or next swing high.
Extra Tip:
If the green label is near other supports (Silver Zone, Support Line), the setup is extra strong.
Use confirmation from Bullish labels or trend signals for best results.
Green label setups are suitable for quick, high momentum trades due to increasing volume
Blue Label (Sell Signal on Decreasing Volume) – Logic, Reason & Trade Planning:
Logic & Visualization:
The blue label is plotted above a candle (label.style_label_down, yloc.abovebar) as a potential sell signal.
Script conditions:
The candle is a “blue candle” (local highest close, but not also lowest, and volume is neither highest nor lowest).
Volume is decreasing over 2 consecutive candles (current volume < previous, previous < two ago).
When these match, a blue label appears above the candle.
Reasoning:
This typically signals buyer exhaustion at a local high: price has gone up, but volume is dropping, suggesting big players may not be buying any more at these levels.
The trend is losing strength, and a reversal or pullback is likely.
How to Trade Using Blue Label:
Entry: Look to sell at/just below the candle with the blue label.
Stop-loss: Just above the candle’s high (or above the Black Zone/resistance if present).
Target: Nearest support, Silver Zone, or a swing low.
Extra Tip:
Blue label signals are stronger if they appear near Black Zones or Resistance Lines, or when the general market label is "Bearish."
As with buy setups, always check for confirmation from trend or volume before trading aggressively.
Blue Label (Sell Signal on Decreasing Volume) – Logic, Reason & Trade Planning:
Logic & Visualization:
The blue label is plotted above a candle (label.style_label_down, yloc.abovebar) as a potential sell signal.
Script conditions:
The candle is a “blue candle” (local highest close, but not also lowest, and volume is neither highest nor lowest).
Volume is decreasing over 2 consecutive candles (current volume < previous, previous < two ago).
When these match, a blue label appears above the candle.
Reasoning:
This typically signals buyer exhaustion at a local high: price has gone up, but volume is dropping, suggesting big players may not be buying any more at these levels.
The trend is losing strength, and a reversal or pullback is likely.
How to Trade Using Blue Label:
Entry: Look to sell at/just below the candle with the blue label.
Stop-loss: Just above the candle’s high (or above the Black Zone/resistance if present).
Target: Nearest support, Silver Zone, or a swing low.
Extra Tip:
Blue label signals are stronger if they appear near Black Zones or Resistance Lines, or when the general market label is "Bearish."
As with buy setups, always check for confirmation from trend or volume before trading aggressively.
Here’s a summary of all key chart labels, zones, and trading logic of your Price Action script:
Silver Zone: Powerful support zone. Created at lowest close + highest volume. Best for buy entries near its lines.
Black Zone: Strong resistance zone. Created at highest close + lowest volume. Ideal for short trades near its levels.
Support Line: Blue dashed line at historical demand; buyers defend here. Look for bullish setups when price approaches.
Resistance Line: Purple/red dashed line at supply; sellers defend here. Great for bearish setups when price nears.
Bullish/Bearish Labels: Summarize trend direction using price action + multiple indicator confirmations. Plan buys, holds on bullish; sells, shorts on bearish.
Yellow Label: Buy signal on decreasing volume and local price low. Entry above candle, stop below, target next resistance.
Green Label: Strong buy on increasing volume at a price low. Entry for momentum trade, stop below, target next zone.
Blue Label: Sell signal on dropping volume and local price high. Entry below candle, stop above, target next support.
Best Practices:
Always combine zone/label signals for higher probability trades.
Use stop-loss near zones/lines for risk management.
Prefer trading in the trend direction (bullish/bearish label agrees with your entry).
if Any Question, Suggestion Feel free to ask
Disclaimer:
All information provided by this indicator is for educational and analysis purposes only, and should not be considered financial advice.
MERV: Market Entropy & Rhythm Visualizer [BullByte]The MERV (Market Entropy & Rhythm Visualizer) indicator analyzes market conditions by measuring entropy (randomness vs. trend), tradeability (volatility/momentum), and cyclical rhythm. It provides traders with an easy-to-read dashboard and oscillator to understand when markets are structured or choppy, and when trading conditions are optimal.
Purpose of the Indicator
MERV’s goal is to help traders identify different market regimes. It quantifies how structured or random recent price action is (entropy), how strong and volatile the movement is (tradeability), and whether a repeating cycle exists. By visualizing these together, MERV highlights trending vs. choppy environments and flags when conditions are favorable for entering trades. For example, a low entropy value means prices are following a clear trend line, whereas high entropy indicates a lot of noise or sideways action. The indicator’s combination of measures is original: it fuses statistical trend-fit (entropy), volatility trends (ATR and slope), and cycle analysis to give a comprehensive view of market behavior.
Why a Trader Should Use It
Traders often need to know when a market trend is reliable vs. when it is just noise. MERV helps in several ways: it shows when the market has a strong direction (low entropy, high tradeability) and when it’s ranging (high entropy). This can prevent entering trend-following strategies during choppy periods, or help catch breakouts early. The “Optimal Regime” marker (a star) highlights moments when entropy is very low and tradeability is very high, typically the best conditions for trend trades. By using MERV, a trader gains an empirical “go/no-go” signal based on price history, rather than guessing from price alone. It’s also adaptable: you can apply it to stocks, forex, crypto, etc., on any timeframe. For example, during a bullish phase of a stock, MERV will turn green (Trending Mode) and often show a star, signaling good follow-through. If the market later grinds sideways, MERV will shift to magenta (Choppy Mode), warning you that trend-following is now risky.
Why These Components Were Chosen
Market Entropy (via R²) : This measures how well recent prices fit a straight line. We compute a linear regression on the last len_entropy bars and calculate R². Entropy = 1 - R², so entropy is low when prices follow a trend (R² near 1) and high when price action is erratic (R² near 0). This single number captures trend strength vs noise.
Tradeability (ATR + Slope) : We combine two familiar measures: the Average True Range (ATR) (normalized by price) and the absolute slope of the regression line (scaled by ATR). Together they reflect how active and directional the market is. A high ATR or strong slope means big moves, making a trend more “tradeable.” We take a simple average of the normalized ATR and slope to get tradeability_raw. Then we convert it to a percentile rank over the lookback window so it’s stable between 0 and 1.
Percentile Ranks : To make entropy and tradeability values easy to interpret, we convert each to a 0–100 rank based on the past len_entropy periods. This turns raw metrics into a consistent scale. (For example, an entropy rank of 90 means current entropy is higher than 90% of recent values.) We then divide by 100 to plot them on a 0–1 scale.
Market Mode (Regime) : Based on those ranks, MERV classifies the market:
Trending (Green) : Low entropy rank (<40%) and high tradeability rank (>60%). This means the market is structurally trending with high activity.
Choppy (Magenta) : High entropy rank (>60%) and low tradeability rank (<40%). This is a mostly random, low-momentum market.
Neutral (Cyan) : All other cases. This covers mixed regimes not strongly trending or choppy.
The mode is shown as a colored bar at the bottom: green for trending, magenta for choppy, cyan for neutral.
Optimal Regime Signal : Separately, we mark an “optimal” condition when entropy_norm < 0.3 and tradeability > 0.7 (both normalized 0–1). When this is true, a ★ star appears on the bottom line. This star is colored white when truly optimal, gold when only tradeability is high (but entropy not quite low enough), and black when neither condition holds. This gives a quick visual cue for very favorable conditions.
What Makes MERV Stand Out
Holistic View : Unlike a single-oscillator, MERV combines trend, volatility, and cycle analysis in one tool. This multi-faceted approach is unique.
Visual Dashboard : The fixed on-chart dashboard (shown at your chosen corner) summarizes all metrics in bar/gauge form. Even a non-technical user can glance at it: more “█” blocks = a higher value, colors match the plots. This is more intuitive than raw numbers.
Adaptive Thresholds : Using percentile ranks means MERV auto-adjusts to each market’s character, rather than requiring fixed thresholds.
Cycle Insight : The rhythm plot adds information rarely found in indicators – it shows if there’s a repeating cycle (and its period in bars) and how strong it is. This can hint at natural bounce or reversal intervals.
Modern Look : The neon color scheme and glow effects make the lines easy to distinguish (blue/pink for entropy, green/orange for tradeability, etc.) and the filled area between them highlights when one dominates the other.
Recommended Timeframes
MERV can be applied to any timeframe, but it will be more reliable on higher timeframes. The default len_entropy = 50 and len_rhythm = 30 mean we use 30–50 bars of history, so on a daily chart that’s ~2–3 months of data; on a 1-hour chart it’s about 2–3 days. In practice:
Swing/Position traders might prefer Daily or 4H charts, where the calculations smooth out small noise. Entropy and cycles are more meaningful on longer trends.
Day trader s could use 15m or 1H charts if they adjust the inputs (e.g. shorter windows). This provides more sensitivity to intraday cycles.
Scalpers might find MERV too “slow” unless input lengths are set very low.
In summary, the indicator works anywhere, but the defaults are tuned for capturing medium-term trends. Users can adjust len_entropy and len_rhythm to match their chart’s volatility. The dashboard position can also be moved (top-left, bottom-right, etc.) so it doesn’t cover important chart areas.
How the Scoring/Logic Works (Step-by-Step)
Compute Entropy : A linear regression line is fit to the last len_entropy closes. We compute R² (goodness of fit). Entropy = 1 – R². So a strong straight-line trend gives low entropy; a flat/noisy set of points gives high entropy.
Compute Tradeability : We get ATR over len_entropy bars, normalize it by price (so it’s a fraction of price). We also calculate the regression slope (difference between the predicted close and last close). We scale |slope| by ATR to get a dimensionless measure. We average these (ATR% and slope%) to get tradeability_raw. This represents how big and directional price moves are.
Convert to Percentiles : Each new entropy and tradeability value is inserted into a rolling array of the last 50 values. We then compute the percentile rank of the current value in that array (0–100%) using a simple loop. This tells us where the current bar stands relative to history. We then divide by 100 to plot on .
Determine Modes and Signal : Based on these normalized metrics: if entropy < 0.4 and tradeability > 0.6 (40% and 60% thresholds), we set mode = Trending (1). If entropy > 0.6 and tradeability < 0.4, mode = Choppy (-1). Otherwise mode = Neutral (0). Separately, if entropy_norm < 0.3 and tradeability > 0.7, we set an optimal flag. These conditions trigger the colored mode bars and the star line.
Rhythm Detection : Every bar, if we have enough data, we take the last len_rhythm closes and compute the mean and standard deviation. Then for lags from 5 up to len_rhythm, we calculate a normalized autocorrelation coefficient. We track the lag that gives the maximum correlation (best match). This “best lag” divided by len_rhythm is plotted (a value between 0 and 1). Its color changes with the correlation strength. We also smooth the best correlation value over 5 bars to plot as “Cycle Strength” (also 0 to 1). This shows if there is a consistent cycle length in recent price action.
Heatmap (Optional) : The background color behind the oscillator panel can change with entropy. If “Neon Rainbow” style is on, low entropy is blue and high entropy is pink (via a custom color function), otherwise a classic green-to-red gradient can be used. This visually reinforces the entropy value.
Volume Regime (Dashboard Only) : We compute vol_norm = volume / sma(volume, len_entropy). If this is above 1.5, it’s considered high volume (neon orange); below 0.7 is low (blue); otherwise normal (green). The dashboard shows this as a bar gauge and percentage. This is for context only.
Oscillator Plot – How to Read It
The main panel (oscillator) has multiple colored lines on a 0–1 vertical scale, with horizontal markers at 0.2 (Low), 0.5 (Mid), and 0.8 (High). Here’s each element:
Entropy Line (Blue→Pink) : This line (and its glow) shows normalized entropy (0 = very low, 1 = very high). It is blue/green when entropy is low (strong trend) and pink/purple when entropy is high (choppy). A value near 0.0 (below 0.2 line) indicates a very well-defined trend. A value near 1.0 (above 0.8 line) means the market is very random. Watch for it dipping near 0: that suggests a strong trend has formed.
Tradeability Line (Green→Yellow) : This represents normalized tradeability. It is colored bright green when tradeability is low, transitioning to yellow as tradeability increases. Higher values (approaching 1) mean big moves and strong slopes. Typically in a market rally or crash, this line will rise. A crossing above ~0.7 often coincides with good trend strength.
Filled Area (Orange Shade) : The orange-ish fill between the entropy and tradeability lines highlights when one dominates the other. If the area is large, the two metrics diverge; if small, they are similar. This is mostly aesthetic but can catch the eye when the lines cross over or remain close.
Rhythm (Cycle) Line : This is plotted as (best_lag / len_rhythm). It indicates the relative period of the strongest cycle. For example, a value of 0.5 means the strongest cycle was about half the window length. The line’s color (green, orange, or pink) reflects how strong that cycle is (green = strong). If no clear cycle is found, this line may be flat or near zero.
Cycle Strength Line : Plotted on the same scale, this shows the autocorrelation strength (0–1). A high value (e.g. above 0.7, shown in green) means the cycle is very pronounced. Low values (pink) mean any cycle is weak and unreliable.
Mode Bars (Bottom) : Below the main oscillator, thick colored bars appear: a green bar means Trending Mode, magenta means Choppy Mode, and cyan means Neutral. These bars all have a fixed height (–0.1) and make it very easy to see the current regime.
Optimal Regime Line (Bottom) : Just below the mode bars is a thick horizontal line at –0.18. Its color indicates regime quality: White (★) means “Optimal Regime” (very low entropy and high tradeability). Gold (★) means not quite optimal (high tradeability but entropy not low enough). Black means neither condition. This star line quickly tells you when conditions are ideal (white star) or simply good (gold star).
Horizontal Guides : The dotted lines at 0.2 (Low), 0.5 (Mid), and 0.8 (High) serve as reference lines. For example, an entropy or tradeability reading above 0.8 is “High,” and below 0.2 is “Low,” as labeled on the chart. These help you gauge values at a glance.
Dashboard (Fixed Corner Panel)
MERV also includes a compact table (dashboard) that can be positioned in any corner. It summarizes key values each bar. Here is how to read its rows:
Entropy : Shows a bar of blocks (█ and ░). More █ blocks = higher entropy. It also gives a percentage (rounded). A full bar (10 blocks) with a high % means very chaotic market. The text is colored similarly (blue-green for low, pink for high).
Rhythm : Shows the best cycle period in bars (e.g. “15 bars”). If no calculation yet, it shows “n/a.” The text color matches the rhythm line.
Cycle Strength : Gives the cycle correlation as a percentage (smoothed, as shown on chart). Higher % (green) means a strong cycle.
Tradeability : Displays a 10-block gauge for tradeability. More blocks = more tradeable market. It also shows “gauge” text colored green→yellow accordingly.
Market Mode : Simply shows “Trending”, “Choppy”, or “Neutral” (cyan text) to match the mode bar color.
Volume Regime : Similar to tradeability, shows blocks for current volume vs. average. Above-average volume gives orange blocks, below-average gives blue blocks. A % value indicates current volume relative to average. This row helps see if volume is abnormally high or low.
Optimal Status (Large Row) : In bold, either “★ Optimal Regime” (white text) if the star condition is met, “★ High Tradeability” (gold text) if tradeability alone is high, or “— Not Optimal” (gray text) otherwise. This large row catches your eye when conditions are ripe.
In short, the dashboard turns the numeric state into an easy read: filled bars, colors, and text let you see current conditions without reading the plot. For instance, five blue blocks under Entropy and “25%” tells you entropy is low (good), and a row showing “Trending” in green confirms a trend state.
Real-Life Example
Example : Consider a daily chart of a trending stock (e.g. “AAPL, 1D”). During a strong uptrend, recent prices fit a clear upward line, so Entropy would be low (blue line near bottom, perhaps below the 0.2 line). Volatility and slope are high, so Tradeability is high (green-yellow line near top). In the dashboard, Entropy might show only 1–2 blocks (e.g. 10%) and Tradeability nearly full (e.g. 90%). The Market Mode bar turns green (Trending), and you might see a white ★ on the optimal line if conditions are very good. The Volume row might light orange if volume is above average during the rally. In contrast, imagine the same stock later in a tight range: Entropy will rise (pink line up, more blocks in dashboard), Tradeability falls (fewer blocks), and the Mode bar turns magenta (Choppy). No star appears in that case.
Consolidated Use Case : Suppose on XYZ stock the dashboard reads “Entropy: █░░░░░░░░ 20%”, “Tradeability: ██████████ 80%”, Mode = Trending (green), and “★ Optimal Regime.” This tells the trader that the market is in a strong, low-noise trend, and it might be a good time to follow the trend (with appropriate risk controls). If instead it reads “Entropy: ████████░░ 80%”, “Tradeability: ███▒▒▒▒▒▒ 30%”, Mode = Choppy (magenta), the trader knows the market is random and low-momentum—likely best to sit out until conditions improve.
Example: How It Looks in Action
Screenshot 1: Trending Market with High Tradeability (SOLUSD, 30m)
What it means:
The market is in a clear, strong trend with excellent conditions for trading. Both trend-following and active strategies are favored, supported by high tradeability and strong volume.
Screenshot 2: Optimal Regime, Strong Trend (ETHUSD, 1h)
What it means:
This is an ideal environment for trend trading. The market is highly organized, tradeability is excellent, and volume supports the move. This is when the indicator signals the highest probability for success.
Screenshot 3: Choppy Market with High Volume (BTC Perpetual, 5m)
What it means:
The market is highly random and choppy, despite a surge in volume. This is a high-risk, low-reward environment, avoid trend strategies, and be cautious even with mean-reversion or scalping.
Settings and Inputs
The script is fully open-source; here are key inputs the user can adjust:
Entropy Window (len_entropy) : Number of bars used for entropy and tradeability (default 50). Larger = smoother, more lag; smaller = more sensitivity.
Rhythm Window (len_rhythm ): Bars used for cycle detection (default 30). This limits the longest cycle we detect.
Dashboard Position : Choose any corner (Top Right default) so it doesn’t cover chart action.
Show Heatmap : Toggles the entropy background coloring on/off.
Heatmap Style : “Neon Rainbow” (colorful) or “Classic” (green→red).
Show Mode Bar : Turn the bottom mode bar on/off.
Show Dashboard : Turn the fixed table panel on/off.
Each setting has a tooltip explaining its effect. In the description we will mention typical settings (e.g. default window sizes) and that the user can move the dashboard corner as desired.
Oscillator Interpretation (Recap)
Lines : Blue/Pink = Entropy (low=trend, high=chop); Green/Yellow = Tradeability (low=quiet, high=volatile).
Fill : Orange tinted area between them (for visual emphasis).
Bars : Green=Trending, Magenta=Choppy, Cyan=Neutral (at bottom).
Star Line : White star = ideal conditions, Gold = good but not ideal.
Horizontal Guides : 0.2 and 0.8 lines mark low/high thresholds for each metric.
Using the chart, a coder or trader can see exactly what each output represents and make decisions accordingly.
Disclaimer
This indicator is provided as-is for educational and analytical purposes only. It does not guarantee any particular trading outcome. Past market patterns may not repeat in the future. Users should apply their own judgment and risk management; do not rely solely on this tool for trading decisions. Remember, TradingView scripts are tools for market analysis, not personalized financial advice. We encourage users to test and combine MERV with other analysis and to trade responsibly.
-BullByte
Emotion Line with Volume Confirmation by langshenHow to Use It?
Add the Indicator:
Copy the code into TradingView's Pine Script editor.
Save and add the indicator to your chart.
Understand the Lines:
Emotion Line (Green): Represents the current market sentiment.
MA Emotion Line (Red): A smoothed version of the Emotion Line.
Horizontal Lines:
20% (Gray): Indicates potential positive sentiment (Attention Zone).
40% (Orange): Suggests strong market sentiment (Entry Zone).
80% (Red): Signals overly optimistic sentiment (Reduce Position Zone).
Interpret the Signals:
When the Emotion Line crosses above 20%, it may indicate a positive shift in sentiment.
When the Emotion Line crosses above 40%, it suggests a strong market sentiment, which could be a potential entry point.
When the Emotion Line crosses above 80%, it may indicate an overbought market, signaling a potential reduction in positions.
When the Emotion Line crosses below the MA Emotion Line, it may indicate a weakening sentiment, signaling an exit.
Customize the Inputs:
N Period: Adjust the period for calculating the Emotion Line (default is 7).
MA Period: Adjust the period for the moving average of the Emotion Line (default is 6).
Logic Explanation
Ray Calculation:
The Ray is a smoothed price value calculated as the simple moving average (SMA) of (2 * close + high + low) / 4.
Close Line (CL):
The CL is derived from the Ray and represents the core price trend.
Directional Change (DlR1):
Measures the absolute difference between the current CL and its value two bars ago (CL ).
Volume in Range (VlR1):
Sums the absolute differences between the current CL and its previous value (CL ) over a specified period.
Efficiency Ratio (ER1):
Calculates the ratio of directional change (DlR1) to volume in range (VlR1), representing the efficiency of price movement.
Cumulative Strength (CS1):
Simplified as the efficiency ratio (ER1).
Cumulative Quotient (CQ1):
Squares the cumulative strength (CS1) to amplify its effect.
Adjusted Moving Average (AMA5):
A dynamic moving average that adjusts based on the CQ1 value, simulating a responsive trend line.
Cost (7-day SMA of AMA5):
The 7-period SMA of the AMA5.
Composite Line (CLX):
The average of AMA5 and Cost.
Emotion Line:
Calculated as the percentage of days where the CLX is higher than its previous value over the last N periods.
MA Emotion Line:
The moving average of the Emotion Line, smoothing out its fluctuations.
Key Features
Trend Identification: Helps identify shifts in market sentiment.
Customizable Periods: Adjust N and M to fit your trading style.
Visual Cues: Horizontal lines provide clear levels for attention, entry, and reduce position signals.
Best Practices
Use this indicator in conjunction with other tools (e.g., RSI, MACD) for confirmation.
Adjust the N and M periods based on your trading timeframe (e.g., shorter periods for scalping, longer periods for swing trading).
Combine the indicator with volume analysis to confirm signals.
This indicator is designed to be simple yet powerful, providing clear insights into market sentiment while adhering to TradingView's coding standards.
Fixed Range LevelsThis indicator draws horizontal price levels on your chart based on a starting price and a range size that you define. It can also draw midpoint lines between the main levels if enabled.
Here's a breakdown of its functionality:
Key Features:
Starting Price:
You define a starting price (e.g., 21630).
The indicator calculates a corrected base price by rounding the starting price to the nearest multiple of the range size.
Range Size:
You define a range size (e.g., 71).
The indicator draws horizontal lines at intervals of the range size above and below the corrected base price.
Dual Ranges:
You can define two range sizes (e.g., 71 and 29).
The indicator can draw levels for both ranges simultaneously or individually, depending on your settings.
Midpoint Lines:
If enabled, the indicator draws midpoint lines between the main levels.
For example, if the main levels are at 21584 and 21655, the midpoint line will be at 21619.5.
Customizable Styles:
You can customize the line style (solid, dotted, dashed) and color for both the main levels and midpoint lines.
Dynamic Levels:
The levels are recalculated and redrawn dynamically based on the starting price and range size.
How It Works:
Corrected Base Price Calculation:
The indicator calculates the corrected base price using the formula:
pinescript
Copy
correctedBasePrice = math.floor(startingPrice / rangeSize) * rangeSize
For example, if startingPrice = 21630 and rangeSize = 71:
Copy
correctedBasePrice = math.floor(21630 / 71) * 71 = 304 * 71 = 21584
Drawing Levels:
The indicator draws horizontal lines at intervals of the range size above and below the corrected base price.
For example, if rangeSize = 71 and maxLevels = 5, the levels will be drawn at:
Copy
21584 - (5 * 71) = 21249
21584 - (4 * 71) = 21320
...
21584 + (5 * 71) = 21939
Midpoint Lines:
If enabled, the indicator draws midpoint lines between the main levels.
For example, if the main levels are at 21584 and 21655, the midpoint line will be at:
Copy
(21584 + 21655) / 2 = 21619.5
Dual Ranges:
If you enable both ranges, the indicator will draw levels for both range sizes simultaneously.
For example, if rangeSize1 = 71 and rangeSize2 = 29, the indicator will draw two sets of levels:
Levels at intervals of 71 (e.g., 21584, 21655, 21726, ...).
Levels at intervals of 29 (e.g., 21634, 21663, 21692, ...).
Example Use Case:
Imagine you're trading a stock or cryptocurrency, and you want to identify key support and resistance levels based on a specific price range. Here's how you can use this indicator:
Set the Starting Price:
For example, if the current price is 21630, you can set this as the starting price.
Define the Range Size:
If you believe the price moves in increments of 71, set rangeSize1 = 71.
If you also want to track smaller increments of 29, set rangeSize2 = 29.
Enable Midpoint Lines:
If you want to see the midpoint between the main levels, enable Show Midpoint Line.
Customize Line Styles:
Choose different colors and styles for the main levels and midpoint lines to make them visually distinct.
Analyze the Chart:
The indicator will draw horizontal lines at the specified intervals, helping you identify potential support, resistance, and midpoint levels.
Why Is This Useful?
Support and Resistance Levels:
The horizontal lines act as dynamic support and resistance levels based on the range size you define.
Price Targets:
You can use the levels to identify potential price targets or areas where the price might reverse.
Midpoint Analysis:
The midpoint lines can help you identify areas of consolidation or potential breakout points.
Flexibility:
You can customize the range sizes, colors, and styles to suit your trading strategy.
Summary:
This indicator is a powerful tool for traders who want to visualize price levels and midpoints based on a specific range size. It helps you identify key levels for support, resistance, and potential price targets, making it easier to plan your trades.
Linear Regression Trend ChannelThe "Linear Regression Trend Channel" is a technical indicator designed to illustrate price trends and their volatility using linear regression. This indicator calculates the main linear regression line based on the user-defined period length and computes the standard deviation to form a trend channel.
Key Features:
- Linear Regression Calculation: Computes the linear regression line based on the selected price data source and the defined period length.
- Slope and Intercept Calculation: Calculates the slope and intercept of the linear regression line using the calcSlopeIntercept function.
- Deviation Channels: Adds standard deviation channels to the linear regression line to highlight potential support and resistance areas.
Settings
- Linear Regression Length: Specifies the length of the period for the linear regression calculation (default: 100).
- Linear Regression Source: Defines the data source for the linear regression calculation, such as close price, open price, etc. (default: close).
- Linear Regression Color: Sets the color of the linear regression line (default: gray).
- Show Price Labels: Option to display price labels on the horizontal lines (default: true).
How to Use
- Set the Linear Regression Length to define the period for regression calculation.
- Choose the Linear Regression Source to specify the price data (e.g., close, open).
- Enable or disable Show Price Labels based on whether you want to see price labels on the horizontal lines.
This Indicator helps identify dynamic support and resistance levels and potential market turning points.
Ichimoku Theories [LuxAlgo]The Ichimoku Theories indicator is the most complete Ichimoku tool you will ever need. Four tools combined into one to harness all the power of Ichimoku Kinkō Hyō.
This tool features the following concepts based on the work of Goichi Hosoda:
Ichimoku Kinkō Hyō: Original Ichimoku indicator with its five main lines and kumo.
Time Theory: automatic time cycle identification and forecasting to understand market timing.
Wave Theory: automatic wave identification to understand market structure.
Price Theory: automatic identification of developing N waves and possible price targets to understand future price behavior.
🔶 ICHIMOKU KINKŌ HYŌ
Ichimoku with lines only, Kumo only and both together
Let us start with the basics: the Ichimoku original indicator is a tool to understand the market, not to predict it, it is a trend-following tool, so it is best used in trending markets.
Ichimoku tells us what is happening in the market and what may happen next, the aim of the tool is to provide market understanding, not trading signals.
The tool is based on calculating the mid-point between the high and low of three pre-defined ranges as the equilibrium price for short (9 periods), medium (26 periods), and long (52 periods) time horizons:
Tenkan sen: middle point of the range of the last 9 candles
Kinjun sen: middle point of the range of the last 26 candles
Senkou span A: middle point between Tankan Sen and Kijun Sen, plotted 26 candles into the future
Senkou span B: midpoint of the range of the last 52 candles, plotted 26 candles into the future
Chikou span: closing price plotted 26 candles into the past
Kumo: area between Senkou pans A and B (kumo means cloud in Japanese)
The most basic use of the tool is to use the Kumo as an area of possible support or resistance.
🔶 TIME THEORY
Current cycles and forecast
Time theory is a critical concept used to identify historical and current market cycles, and use these to forecast the next ones. This concept is based on the Kihon Suchi (translating to "Basic Numbers" in Japanese), these are 9 and 26, and from their combinations we obtain the following sequence:
9, 17, 26, 33, 42, 51, 65, 76, 129, 172, 200, 257
The main idea is that the market moves in cycles with periods set by the Kihon Suchi sequence.
When the cycle has the same exact periods, we obtain the Taito Suchi (translating to "Same Number" in Japanese).
This tool allows traders to identify historical and current market cycles and forecast the next one.
🔹 Time Cycle Identification
Presentation of 4 different modes: SWINGS, HIGHS, KINJUN, and WAVES .
The tool draws a horizontal line at the bottom of the chart showing the cycles detected and their size.
The following settings are used:
Time Cycle Mode: up to 7 different modes
Wave Cycle: Which wave to use when WAVE mode is selected, only active waves in the Wave Theory settings will be used.
Show Time Cycles: keep a cleaner chart by disabling cycles visualisation
Show last X time cycles: how many cycles to display
🔹 Time Cycle Forecast
Showcasing the two forecasting patterns: Kihon Suchi and Taito Suchi
The tool plots horizontal lines, a solid anchor line, and several dotted forecast lines.
The following settings are used:
Show time cycle forecast: to keep things clean
Forecast Pattern: comes in two flavors
Kihon Suchi plots a line from the anchor at each number in the Kihon Suchi sequence.
Taito Suchi plot lines from the anchor with the same size detected in the anchored cycle
Anchor forecast on last X time cycle: traders can place the anchor in any detected cycle
🔶 WAVE THEORY
All waves activated with overlapping
The main idea behind this theory is that markets move like waves in the sea, back and forth (making swing lows and highs). Understanding the current market structure is key to having realistic expectations of what the market may do next. The waves are divided into Simple and Complex.
The following settings are used:
Basic Waves: allows traders to activate waves I, V and N
Complex Waves: allows traders to activate waves P, Y and W
Overlapping waves: to avoid missing out on any of the waves activated
Show last X waves: how many waves will be displayed
🔹 Basic Waves
The three basic waves
The basic waves from which all waves are made are I, V, and N
I wave: one leg moves
V wave: two legs move, one against the other
N wave: Three legs move, push, pull back, and another push
🔹 Complex Waves
Three complex waves
There are other waves like
P wave: contracting market
Y wave: expanding market
W wave: double top or double bottom
🔶 PRICE THEORY
All targets for the current N wave with their calculations
This theory is based on identifying developing N waves and predicting potential price targets based on that developing wave.
The tool displays 4 basic targets (V, E, N, and NT) and 3 extended targets (2E and 3E) according to the calculations shown in the chart above. Traders can enable or disable each target in the settings panel.
🔶 USING EVERYTHING TOGETHER
Please DON'T do this. This is not how you use it
Now the real example:
Daily chart of Nasdaq 100 futures (NQ1!) with our Ichimoku analysis
Time, waves, and price theories go together as one:
First, we identify the current time cycles and wave structure.
Then we forecast the next cycle and possible key price levels.
We identify a Taito Suchi with both legs of exactly 41 candles on each I wave, both together forming a V wave, the last two I waves are part of a developing N wave, and the time cycle of the first one is 191 candles. We forecast this cycle into the future and get 22nd April as a key date, so in 6 trading days (as of this writing) the market would have completed another Taito Suchi pattern if a new wave and time cycle starts. As we have a developing N wave we can see the potential price targets, the price is actually between the NT and V targets. We have a bullish Kumo and the price is touching it, if this Kumo provides enough support for the price to go further, the market could reach N or E targets.
So we have identified the cycle and wave, our expectations are that the current cycle is another Taito Suchi and the current wave is an N wave, the first I wave went for 191 candles, and we expect the second and third I waves together to amount to 191 candles, so in theory the N wave would complete in the next 6 trading days making a swing high. If this is indeed the case, the price could reach the V target (it is almost there) or even the N target if the bulls have the necessary strength.
We do not predict the future, we can only aim to understand the current market conditions and have future expectations of when (time), how (wave), and where (price) the market will make the next turning point where one side of the market overcomes the other (bulls vs bears).
To generate this chart, we change the following settings from the default ones:
Swing length: 64
Show lines: disabled
Forecast pattern: TAITO SUCHI
Anchor forecast: 2
Show last time cycles: 5
I WAVE: enabled
N WAVE: disabled
Show last waves: 5
🔶 SETTINGS
Show Swing Highs & Lows: Enable/Disable points on swing highs and swing lows.
Swing Length: Number of candles to confirm a swing high or swing low. A higher number detects larger swings.
🔹 Ichimoku Kinkō Hyō
Show Lines: Enable/Disable the 5 Ichimoku lines: Kijun sen, Tenkan sen, Senkou span A & B and Chikou Span.
Show Kumo: Enable/Disable the Kumo (cloud). The Kumo is formed by 2 lines: Senkou Span A and Senkou Span B.
Tenkan Sen Length: Number of candles for Tenkan Sen calculation.
Kinjun Sen Length: Number of candles for the Kijun Sen calculation.
Senkou Span B Length: Number of candles for Senkou Span B calculation.
Chikou & Senkou Offset: Number of candles for Chikou and Senkou Span calculation. Chikou Span is plotted in the past, and Senkou Span A & B in the future.
🔹 Time Theory
Show Time Cycle Forecast: Enable/Disable time cycle forecast vertical lines. Disable for better performance.
Forecast Pattern: Choose between two patterns: Kihon Suchi (basic numbers) or Taito Suchi (equal numbers).
Anchor forecast on last X time cycle: Number of time cycles in the past to anchor the time cycle forecast. The larger the number, the deeper in the past the anchor will be.
Time Cycle Mode: Choose from 7 time cycle detection modes: Tenkan Sen cross, Kijun Sen cross, Kumo change between bullish & bearish, swing highs only, swing lows only, both swing highs & lows and wave detection.
Wave Cycle: Choose which type of wave to detect from 6 different wave types when the time cycle mode is set to WAVES.
Show Time Cycles: Enable/Disable time cycle horizontal lines. Disable for better performance.
how last X time cycles: Maximum number of time cycles to display.
🔹 Wave Theory
Basic Waves: Enable/Disable the display of basic waves, all at once or one at a time. Disable for better performance.
Complex Waves: Enable/Disable complex wave display, all at once or one by one. Disable for better performance.
Overlapping Waves: Enable/Disable the display of waves ending on the same swing point.
Show last X waves: 'Maximum number of waves to display.
🔹 Price Theory
Basic Targets: Enable/Disable horizontal price target lines. Disable for better performance.
Extended Targets: Enable/Disable extended price target horizontal lines. Disable for better performance.
@tk · fractal rsi levels█ OVERVIEW
This script is an indicator that helps traders to identify the RSI Levels for multiple fractals wherever the current timeframe is. This script was based on RSI Levels, 20-30 & 70-80 by abdomi indicator, that calculates the Relative Strenght Index levels based on the asset's price and plots it into the chart, creating a "wave" style indicator. The core feature of this indicator is the fractal rays, so trader can visualize each of the oversold and overbought levels of multiple timeframe on the current timeframe that he is on. The indicator will plots multiple rays after the chart bars. indicating where is the oversold and overbought levels for others fractals.
█ MOTIVATION
Since the RSI Levels, 20-30 & 70-80 by abdomi indicator helps a lot to identify the possible price levels when the asset is oversold or overbought, I saw myself drawing multiple horizontal lines on these levels in lower timeframes so, in an uptrend or downtrend, I can try to get a pullback of these trends when the asset reaches oversold or overboght levels. So, I get the idea to make those lines visible in multiple timeframes so I don't need to draw it myself manually anymore.
█ CONCEPT
The trading concept to use this indicator is the concept to make entries on uptrend or downtrend pullbacks when the asset price reaches oversold or overbought levels. But this strategy don't works alone. It needs to be aligned together with others indicators like Exponential Moving Averages, Chart Patterns, Support and Resistance, and so on... Even more confluences that you have, bigger are your chances to increase the probability for a successful trade. So, don't use this indicator alone. Compose a trading strategy and use it to improve your analysis.
█ CUSTOMIZATION
This indicator allows the trader to customize the following settings:
GENERAL
Text size
Changes the font size of the labels to improve accessibility.
Type: string
Options: `tiny`, `small`, `normal`, `large`.
Default: `small`
RSI LEVELS · SETTINGS
Pre-oversold Level
Changes the RSI Level to calculate the "pre-oversold" price level on the chart.
Type: int
Min: 1
Max: 49
Default: 33
Pre-overbought Level
Changes the RSI Level to calculate the "pre-overbought" price level on the chart.
Type: int
Min: 51
Max: 100
Default: 67
Show "Pre-over" Levels
Enables / Disables the pre-oversold and pre-overbought levels on the chart.
Type: bool
Default: true
FRACTAL RAYS · SETTINGS
Length
Changes the base length for the RSI calculation.
Type: int
Min: 1
Default: 14
Source
Changes the base source for the RSI calculation.
Type: float
Default: close
FRACTAL RAYS · STYLE
Ray Color
Changes the color of all fractal rays and its label.
Type: color
Default: color.rgb(187, 74, 207)
Ray Style
Changes the style of all fractal rays.
Type: string
Options: `line.style_solid`, `line.style_dashed`, `line.style_dotted`
Default: line.style_dotted
Ray Length
Changes the length of all fractal rays.
Type: int
Default: 15
FRACTAL RAYS · OVERSOLD
Oversold Level
Changes the base RSI Level for fractal rays calculation.
Type: int
Min: 1
Default: 30
Oversold Prefix
Customizes the fractal ray label with a prefix text.
Type: string
Default: 🚀
Oversold Suffix
Customizes the fractal ray label with a suffix text.
Type: string
Default: (empty)
FRACTAL RAYS · OVERBOUGHT
Overbought Level
Changes the base RSI Level for fractal rays calculation.
Type: int
Min: 1
Default: 70
Overbought Prefix
Customizes the fractal ray label with a prefix text.
Type: string
Default: 🐻
Overbought Suffix
Customizes the fractal ray label with a suffix text.
Type: string
Default: (empty)
FRACTAL RAYS · VISIBILITY RULES
These rules are applied for each of fractal rays so, the traders can choose what timeframes they wants to show the fractal rays for each of it. The rule will be applied as the following condition: `if timeframe != CURRENT_TIMEFRAME and timeframe <= CHOSEN_OPTION`. Actually, the fractal rays are on the chart but, isn't visible because it was applied a transparent color, so it is visually not on the chart to prevent chart's over polution.
LABELS
Show Labels on Price Scale
Shows labels on price scale.
Type: bool
Default: false
Show Price on Fractal Rays
Shows the RSI Level price on each of fractal rays respectively.
Type: bool
Default: false
█ EXTERNAL LIBRARIES
This script uses the `tk` library to calculate RSI Levels. It is a library that contains various functions that helps pine script developers to calculate RSI Levels.
█ FUNCTIONS
The library contains the following functions:
fn_fractalVisibilityRule(string visibilityRule)
Converts the fractal rays timeframe visibility rule label to timestamp int.
Parameters:
visibilityRule: (string) Fractal ray visibility rule label.
Returns: (int) Fractal ray visibility rule timestamp.
fn_requestFractal(string period, expression)
Converts the fractal rays timeframe visibility rule label to timestamp int.
Parameters:
period: (string) Timeframe period for the desired fractal.
expression: (mixed) Security expression that will be applied for calculation.
Returns: (mixed) A result determined by expression.
fn_plotRay(float y, string label, color color, int length)
Plots ray after chart bars for the current time.
Parameters:
period: (string) Timeframe period for the desired fractal.
expression: (mixed) Security expression that will be applied for calculation.
Returns: (void) This function only plots the elements into the chart
fn_plotRsiLevelRay(simple string period, simple int level, color color)
Plots RSI Levels ray after chart bars for the current time.
Parameters:
period: (simple string) Timeframe period.
level: (simple int) Relative Strength Index level.
color: (color) The color of both, ray and label text.
Returns: (void) This function only plots the elements into the chart
Dynamic Linear Regression Oscillator | AdulariDescription:
This dynamic linear regression oscillator visualizes the general price trend of specific ranges in the chart based on the linear regression calculation, it automatically determines these ranges with pivot detection. The central line of the indicator is the baseline of the linear regression itself. This is a good tool to use to determine when a price is unusually far away from its baseline. The lines above or below it are overbought and oversold zones. These zones are based on the high or low of the range, in combination with the set multipliers.
The overbought and oversold lines indicate support and resistance; when the prices stay outside these levels for a significant period of time, a reversal can be expected soon. When the oscillator's value crosses above the signal or smoothed line the trend may become bullish. When it crosses below, the trend may become bearish.
This indicator is quite special, as it first determines price ranges using pivot detection. It then uses the middle of the range to determine how far the current price is from the baseline. This value is then rescaled compared to a set amount of bars back, putting it into relevant proportions with the current price action.
How do I use it?
Never use this indicator as standalone trading signal, it should be used as confluence.
When the value crosses above the signal this indicates the current bearish trend is getting weak and may reverse upwards.
When the value crosses below the signal this indicates the current bullish trend is getting weak and may reverse downwards.
When the value is above the middle line this shows the bullish trend is strong.
When the value is below the middle line this shows the bearish trend is strong.
When the value crosses above the upper line this indicates the trend may reverse downwards.
When the value crosses below the lower line this indicates the trend may reverse upwards.
Features:
Oscillator value indicating how far the price has currently deviated from the middle of the range. Proportioned to data from a set amount of bars ago.
Signal value to indicate whether or not the price is abnormally far from the middle of the range.
Horizontal lines such as oversold, overbought and middle lines, indicating possible reversal zones.
Automatic range detection using pivots.
Built-in rescaling functionality to ensure values are proportionate with the latest data.
How does it work? (simplified)
1 — Calculate the middle of the range.
2 — Define whether the current price is above the middle of the range or below.
3 — If above the middle of the range, calculate the difference of the current high and the middle line. If below, calculate the difference of the current low and the middle line.
4 — Smooth the value using a set moving average type.
5 — Rescale the value to proportionate it with the latest data.
TPCLines_PublicLibrary "TPCLines_Public"
Helpers for lines
lineVA(start, lines, labels, lineColor, labelBgColor, labelTextColor, highPrice, lowPrice, extend, style, width, labelText, labelSize, labelStyle, labelTextAlign, bi) Draws a vertical line and optional label on the chart.
Parameters:
start : The start bar index or time.
lines : Line array to which the created line will be pushed.
labels : Label array to which the created label will be pushed.
lineColor : The color for the line and label.
labelBgColor : The background color for the label.
labelTextColor : The text color for the label.
highPrice : The upper price for the line.
lowPrice : The lower price for the line.
extend : Options for toggline line extend (extend.right, extend.left, extend.both, or extend.none). If none is provided, provides a best guess.
style : The line's style. Defaults to line.style_dotted.
width : The line's width. Defaults to 1.
labelText : Optional text to display next to the line.
labelSize : The label's size. Defaults to size.tiny.
labelStyle : The label's style. Defaults to label.style_label_left.
labelTextAlign : The label's text alignment. Defaults to text.align_center.
bi : Set true to use bar indices, set false to use time. Defaults to true (use bar indices).
Returns: Nothing. Draws a line and optional label on the chart.
lineHA(price, lines, labels, lineColor, labelBgColor, extend, labelTextColor, labelText, end, start, bi, showPrice, pips, style, width, labelAlign, labelSize, labelStyle, labelTextAlign) Draws a horizontal line and optional label on the chart.
Parameters:
price : The price at which to draw the lie.
lines : Line array to which the created line will be pushed.
labels : Label array to which the created label will be pushed.
lineColor : The color for the line and label.
labelBgColor : The background color for the label.
extend : Options for toggline line extend (extend.right, extend.left, extend.both, or extend.none). Defaults to extend.none.
labelTextColor : The text color for the label.
labelText : Optional text to display next to the line.
end : The time or bar index to end the line at.
start : The time or bar index to start the line at.
bi : Set true to use bar indices, set false to use time. Defaults to true (use bar indices).
showPrice : Option to show the price on the label.
pips : If a value is provided, will be displayed on the label.
style : The line's style. Defaults to line.style_solid.
width : The line's width. Defaults to 1.
labelAlign : Which side of the line to align the label on. Can be r for right, l for left, c for center, or t for the current time.
labelSize : The label's size. Defaults to size.tiny.
labelStyle : The label's style. Defaults to label.style_none.
labelTextAlign : The label's text alignment. Defaults to text.align_center.
Returns: Nothing. Draws a line and optional label on the chart.
lineH()
lineV()
Parallel Pivot Lines [LuxAlgo]Displays lines connecting past pivot high/low points with each line having the slope of a linear regression. This slope can also be controlled by the user with the 'Slope' setting. Each line can be used as a support or resistance by the user.
Settings
Length : Pivot length. Use higher values for having lines connected to more significant pivots points.
Lookback : Number of lines connecting a pivot high/low to display, with a total of lines equal to Lookback*2
Slope : Allows the user to multiply the linear regression slope by a number within -1 and 1
Limitations
The script has currently several real time behavior limitations. Lines are displayed retrospectively and will not update with the arrival of new bars. Readjusting the indicator to newer pivots will require the user to either hide/unhide the indicator or change its settings.
High Length or Lookback values might not return any lines if the location of a pivot point is outside the defined buffer size of the indicator (set as 5000 bars).
How To Use
The indicator can be used to get supports and resistances and is more so closer to a drawing tool due to its limitations. The lines not updating with the arrival of new bars have the advantage of providing fixed supports/resistances.
The Slope setting allows the user to control the angle and direction of the lines. Using a Slope of 1 will return lines with the same slope as the one of a linear regression fit from the farthest pivot point displayed by the indicator to the most recent bar.
The chart above shows the indicators and a linear regression in orange.
If you want to have horizontal lines, use a Slope equal to 0.
Finally using a negative slope value will allow the user to have lines in opposite directions to the main trend.
Conclusion
We hope you like this indicator (drawing tool) and find it useful for drawing your support & resistances in a unique way!
Inside SwingsOverview
The Inside Swings indicator identifies and visualizes "inside swing" patterns in price action. These patterns occur when price creates a series of pivots that form overlapping ranges, indicating potential consolidation or reversal zones.
What are Inside Swings?
Inside swings are specific pivot patterns where:
- HLHL Pattern: High-Low-High-Low sequence where the first high is higher than the second high, and the first low is lower than the second low
- LHLH Pattern: Low-High-Low-High sequence where the first low is lower than the second low, and the first high is higher than the second high
Here an Example
These patterns create overlapping price ranges that often act as:
- Support/Resistance zones
- Consolidation areas
- Potential reversal points
- Breakout levels
Levels From the Created Range
Input Parameters
Core Settings
- Pivot Lookback Length (default: 5): Number of bars on each side to confirm a pivot high/low
- Max Boxes (default: 100): Maximum number of patterns to display on chart
Extension Settings
- Extend Lines: Enable/disable line extensions - this extends the Extremes of the Swings to where a new Swing Started or Extended Right for the Latest Inside Swings
- Show High 1 Line: Display first high/low extension line
- Show High 2 Line: Display second high/low extension line
- Show Low 1 Line: Display first low/high extension line
- Show Low 2 Line: Display second low/high extension line
Visual Customization
Box Colors
- HLHL Box Color: Color for HLHL pattern boxes (default: green)
- HLHL Border Color: Border color for HLHL boxes
- LHLH Box Color: Color for LHLH pattern boxes (default: red)
- LHLH Border Color: Border color for LHLH boxes
Line Colors
- HLHL Line Color: Extension line color for HLHL patterns
- LHLH Line Color: Extension line color for LHLH patterns
- Line Width: Thickness of extension lines (1-5)
Pattern Detection Logic
HLHL Pattern (Bullish Inside Swing)
Condition: High1 > High2 AND Low1 < Low2
Sequence: High → Low → High → Low
Visual: Two overlapping boxes with first range encompassing second
Detection Criteria:
1. Last 4 pivots form High-Low-High-Low sequence
2. Fourth pivot (first high) > Second pivot (second high)
3. Third pivot (first low) < Last pivot (second low)
LHLH Pattern (Bearish Inside Swing)
Condition: Low1 < Low2 AND High1 > High2
Sequence: Low → High → Low → High
Visual: Two overlapping boxes with first range encompassing second
Detection Criteria:
1. Last 4 pivots form Low-High-Low-High sequence
2. Fourth pivot (first low) < Second pivot (second low)
3. Third pivot (first high) > Last pivot (second high)
Visual Elements
Boxes
- Box 1: Spans from first pivot to last pivot (larger range)
- Box 2: Spans from third pivot to last pivot (smaller range)
- Overlap: The intersection of both boxes represents the inside swing zone
Extension Lines
- High 1 Line: Horizontal line at first high/low level
- High 2 Line: Horizontal line at second high/low level
- Low 1 Line: Horizontal line at first low/high level
- Low 2 Line: Horizontal line at second low/high level
Line Extension Behavior
- Historical Patterns: Lines extend until the next pattern starts
- Latest Pattern: Lines extend to the right edge of chart
- Dynamic Updates: All lines are redrawn on each bar for accuracy
Trading Applications
Support/Resistance Levels
Inside swing levels often act as:
- Dynamic support/resistance
- Breakout confirmation levels
- Reversal entry points
Pattern Interpretation
- HLHL Patterns: Potential bullish continuation or reversal
- LHLH Patterns: Potential bearish continuation or reversal
- Overlap Zone: Key area for price interaction
Entry Strategies
1. Breakout Strategy: Enter on break above/below inside swing levels
2. Reversal Strategy: Enter on bounce from inside swing levels
3. Range Trading: Trade between inside swing levels
Technical Implementation
Data Structures
type InsideSwing
int startBar // First pivot bar
int endBar // Last pivot bar
string patternType // "HLHL" or "LHLH"
float high1 // First high/low
float low1 // First low/high
float high2 // Second high/low
float low2 // Second low/high
box box1 // First box
box box2 // Second box
line high1Line // High 1 extension line
line high2Line // High 2 extension line
line low1Line // Low 1 extension line
line low2Line // Low 2 extension line
bool isLatest // Latest pattern flag
Memory Management
- Pattern Storage: Array-based storage with automatic cleanup
- Pivot Tracking: Maintains last 4 pivots for pattern detection
- Resource Cleanup: Automatically removes oldest patterns when limit exceeded
Performance Optimization
- Duplicate Prevention: Checks for existing patterns before creation
- Efficient Redraw: Only redraws lines when necessary
- Memory Limits: Configurable maximum pattern count
Usage Tips
Best Practices
1. Combine with Volume: Use volume confirmation for breakouts
2. Multiple Timeframes: Check higher timeframes for context
3. Risk Management: Set stops beyond inside swing levels
4. Pattern Validation: Wait for confirmation before entering
Common Scenarios
- Consolidation Breakouts: Inside swings often precede significant moves
- Reversal Zones: Failed breakouts at inside swing levels
- Trend Continuation: Inside swings in trending markets
Limitations
- Lagging Indicator: Patterns form after completion
- False Signals: Not all inside swings lead to significant moves
- Market Dependent: Effectiveness varies by market conditions
Customization Options
Visual Adjustments
- Modify colors for different market conditions
- Adjust line widths for visibility
- Enable/disable specific elements
Detection Sensitivity
- Increase pivot length for smoother patterns
- Decrease for more sensitive detection
- Balance between noise and signal
Display Management
- Control maximum pattern count
- Adjust cleanup frequency
- Manage memory usage
Conclusion
The Inside Swings indicator provides a systematic approach to identifying consolidation and potential reversal zones in price action. By visualizing overlapping pivot ranges
The indicator's strength lies in its ability to:
- Identify key price levels automatically
- Provide visual context for market structure
- Offer flexible customization options
- Maintain performance through efficient memory management
ATAI Volume analysis with price action V 1.00ATAI Volume Analysis with Price Action
1. Introduction
1.1 Overview
ATAI Volume Analysis with Price Action is a composite indicator designed for TradingView. It combines per‑side volume data —that is, how much buying and selling occurs during each bar—with standard price‑structure elements such as swings, trend lines and support/resistance. By blending these elements the script aims to help a trader understand which side is in control, whether a breakout is genuine, when markets are potentially exhausted and where liquidity providers might be active.
The indicator is built around TradingView’s up/down volume feed accessed via the TradingView/ta/10 library. The following excerpt from the script illustrates how this feed is configured:
import TradingView/ta/10 as tvta
// Determine lower timeframe string based on user choice and chart resolution
string lower_tf_breakout = use_custom_tf_input ? custom_tf_input :
timeframe.isseconds ? "1S" :
timeframe.isintraday ? "1" :
timeframe.isdaily ? "5" : "60"
// Request up/down volume (both positive)
= tvta.requestUpAndDownVolume(lower_tf_breakout)
Lower‑timeframe selection. If you do not specify a custom lower timeframe, the script chooses a default based on your chart resolution: 1 second for second charts, 1 minute for intraday charts, 5 minutes for daily charts and 60 minutes for anything longer. Smaller intervals provide a more precise view of buyer and seller flow but cover fewer bars. Larger intervals cover more history at the cost of granularity.
Tick vs. time bars. Many trading platforms offer a tick / intrabar calculation mode that updates an indicator on every trade rather than only on bar close. Turning on one‑tick calculation will give the most accurate split between buy and sell volume on the current bar, but it typically reduces the amount of historical data available. For the highest fidelity in live trading you can enable this mode; for studying longer histories you might prefer to disable it. When volume data is completely unavailable (some instruments and crypto pairs), all modules that rely on it will remain silent and only the price‑structure backbone will operate.
Figure caption, Each panel shows the indicator’s info table for a different volume sampling interval. In the left chart, the parentheses “(5)” beside the buy‑volume figure denote that the script is aggregating volume over five‑minute bars; the center chart uses “(1)” for one‑minute bars; and the right chart uses “(1T)” for a one‑tick interval. These notations tell you which lower timeframe is driving the volume calculations. Shorter intervals such as 1 minute or 1 tick provide finer detail on buyer and seller flow, but they cover fewer bars; longer intervals like five‑minute bars smooth the data and give more history.
Figure caption, The values in parentheses inside the info table come directly from the Breakout — Settings. The first row shows the custom lower-timeframe used for volume calculations (e.g., “(1)”, “(5)”, or “(1T)”)
2. Price‑Structure Backbone
Even without volume, the indicator draws structural features that underpin all other modules. These features are always on and serve as the reference levels for subsequent calculations.
2.1 What it draws
• Pivots: Swing highs and lows are detected using the pivot_left_input and pivot_right_input settings. A pivot high is identified when the high recorded pivot_right_input bars ago exceeds the highs of the preceding pivot_left_input bars and is also higher than (or equal to) the highs of the subsequent pivot_right_input bars; pivot lows follow the inverse logic. The indicator retains only a fixed number of such pivot points per side, as defined by point_count_input, discarding the oldest ones when the limit is exceeded.
• Trend lines: For each side, the indicator connects the earliest stored pivot and the most recent pivot (oldest high to newest high, and oldest low to newest low). When a new pivot is added or an old one drops out of the lookback window, the line’s endpoints—and therefore its slope—are recalculated accordingly.
• Horizontal support/resistance: The highest high and lowest low within the lookback window defined by length_input are plotted as horizontal dashed lines. These serve as short‑term support and resistance levels.
• Ranked labels: If showPivotLabels is enabled the indicator prints labels such as “HH1”, “HH2”, “LL1” and “LL2” near each pivot. The ranking is determined by comparing the price of each stored pivot: HH1 is the highest high, HH2 is the second highest, and so on; LL1 is the lowest low, LL2 is the second lowest. In the case of equal prices the newer pivot gets the better rank. Labels are offset from price using ½ × ATR × label_atr_multiplier, with the ATR length defined by label_atr_len_input. A dotted connector links each label to the candle’s wick.
2.2 Key settings
• length_input: Window length for finding the highest and lowest values and for determining trend line endpoints. A larger value considers more history and will generate longer trend lines and S/R levels.
• pivot_left_input, pivot_right_input: Strictness of swing confirmation. Higher values require more bars on either side to form a pivot; lower values create more pivots but may include minor swings.
• point_count_input: How many pivots are kept in memory on each side. When new pivots exceed this number the oldest ones are discarded.
• label_atr_len_input and label_atr_multiplier: Determine how far pivot labels are offset from the bar using ATR. Increasing the multiplier moves labels further away from price.
• Styling inputs for trend lines, horizontal lines and labels (color, width and line style).
Figure caption, The chart illustrates how the indicator’s price‑structure backbone operates. In this daily example, the script scans for bars where the high (or low) pivot_right_input bars back is higher (or lower) than the preceding pivot_left_input bars and higher or lower than the subsequent pivot_right_input bars; only those bars are marked as pivots.
These pivot points are stored and ranked: the highest high is labelled “HH1”, the second‑highest “HH2”, and so on, while lows are marked “LL1”, “LL2”, etc. Each label is offset from the price by half of an ATR‑based distance to keep the chart clear, and a dotted connector links the label to the actual candle.
The red diagonal line connects the earliest and latest stored high pivots, and the green line does the same for low pivots; when a new pivot is added or an old one drops out of the lookback window, the end‑points and slopes adjust accordingly. Dashed horizontal lines mark the highest high and lowest low within the current lookback window, providing visual support and resistance levels. Together, these elements form the structural backbone that other modules reference, even when volume data is unavailable.
3. Breakout Module
3.1 Concept
This module confirms that a price break beyond a recent high or low is supported by a genuine shift in buying or selling pressure. It requires price to clear the highest high (“HH1”) or lowest low (“LL1”) and, simultaneously, that the winning side shows a significant volume spike, dominance and ranking. Only when all volume and price conditions pass is a breakout labelled.
3.2 Inputs
• lookback_break_input : This controls the number of bars used to compute moving averages and percentiles for volume. A larger value smooths the averages and percentiles but makes the indicator respond more slowly.
• vol_mult_input : The “spike” multiplier; the current buy or sell volume must be at least this multiple of its moving average over the lookback window to qualify as a breakout.
• rank_threshold_input (0–100) : Defines a volume percentile cutoff: the current buyer/seller volume must be in the top (100−threshold)%(100−threshold)% of all volumes within the lookback window. For example, if set to 80, the current volume must be in the top 20 % of the lookback distribution.
• ratio_threshold_input (0–1) : Specifies the minimum share of total volume that the buyer (for a bullish breakout) or seller (for bearish) must hold on the current bar; the code also requires that the cumulative buyer volume over the lookback window exceeds the seller volume (and vice versa for bearish cases).
• use_custom_tf_input / custom_tf_input : When enabled, these inputs override the automatic choice of lower timeframe for up/down volume; otherwise the script selects a sensible default based on the chart’s timeframe.
• Label appearance settings : Separate options control the ATR-based offset length, offset multiplier, label size and colors for bullish and bearish breakout labels, as well as the connector style and width.
3.3 Detection logic
1. Data preparation : Retrieve per‑side volume from the lower timeframe and take absolute values. Build rolling arrays of the last lookback_break_input values to compute simple moving averages (SMAs), cumulative sums and percentile ranks for buy and sell volume.
2. Volume spike: A spike is flagged when the current buy (or, in the bearish case, sell) volume is at least vol_mult_input times its SMA over the lookback window.
3. Dominance test: The buyer’s (or seller’s) share of total volume on the current bar must meet or exceed ratio_threshold_input. In addition, the cumulative sum of buyer volume over the window must exceed the cumulative sum of seller volume for a bullish breakout (and vice versa for bearish). A separate requirement checks the sign of delta: for bullish breakouts delta_breakout must be non‑negative; for bearish breakouts it must be non‑positive.
4. Percentile rank: The current volume must fall within the top (100 – rank_threshold_input) percent of the lookback distribution—ensuring that the spike is unusually large relative to recent history.
5. Price test: For a bullish signal, the closing price must close above the highest pivot (HH1); for a bearish signal, the close must be below the lowest pivot (LL1).
6. Labeling: When all conditions above are satisfied, the indicator prints “Breakout ↑” above the bar (bullish) or “Breakout ↓” below the bar (bearish). Labels are offset using half of an ATR‑based distance and linked to the candle with a dotted connector.
Figure caption, (Breakout ↑ example) , On this daily chart, price pushes above the red trendline and the highest prior pivot (HH1). The indicator recognizes this as a valid breakout because the buyer‑side volume on the lower timeframe spikes above its recent moving average and buyers dominate the volume statistics over the lookback period; when combined with a close above HH1, this satisfies the breakout conditions. The “Breakout ↑” label appears above the candle, and the info table highlights that up‑volume is elevated relative to its 11‑bar average, buyer share exceeds the dominance threshold and money‑flow metrics support the move.
Figure caption, In this daily example, price breaks below the lowest pivot (LL1) and the lower green trendline. The indicator identifies this as a bearish breakout because sell‑side volume is sharply elevated—about twice its 11‑bar average—and sellers dominate both the bar and the lookback window. With the close falling below LL1, the script triggers a Breakout ↓ label and marks the corresponding row in the info table, which shows strong down volume, negative delta and a seller share comfortably above the dominance threshold.
4. Market Phase Module (Volume Only)
4.1 Concept
Not all markets trend; many cycle between periods of accumulation (buying pressure building up), distribution (selling pressure dominating) and neutral behavior. This module classifies the current bar into one of these phases without using ATR , relying solely on buyer and seller volume statistics. It looks at net flows, ratio changes and an OBV‑like cumulative line with dual‑reference (1‑ and 2‑bar) trends. The result is displayed both as on‑chart labels and in a dedicated row of the info table.
4.2 Inputs
• phase_period_len: Number of bars over which to compute sums and ratios for phase detection.
• phase_ratio_thresh : Minimum buyer share (for accumulation) or minimum seller share (for distribution, derived as 1 − phase_ratio_thresh) of the total volume.
• strict_mode: When enabled, both the 1‑bar and 2‑bar changes in each statistic must agree on the direction (strict confirmation); when disabled, only one of the two references needs to agree (looser confirmation).
• Color customisation for info table cells and label styling for accumulation and distribution phases, including ATR length, multiplier, label size, colors and connector styles.
• show_phase_module: Toggles the entire phase detection subsystem.
• show_phase_labels: Controls whether on‑chart labels are drawn when accumulation or distribution is detected.
4.3 Detection logic
The module computes three families of statistics over the volume window defined by phase_period_len:
1. Net sum (buyers minus sellers): net_sum_phase = Σ(buy) − Σ(sell). A positive value indicates a predominance of buyers. The code also computes the differences between the current value and the values 1 and 2 bars ago (d_net_1, d_net_2) to derive up/down trends.
2. Buyer ratio: The instantaneous ratio TF_buy_breakout / TF_tot_breakout and the window ratio Σ(buy) / Σ(total). The current ratio must exceed phase_ratio_thresh for accumulation or fall below 1 − phase_ratio_thresh for distribution. The first and second differences of the window ratio (d_ratio_1, d_ratio_2) determine trend direction.
3. OBV‑like cumulative net flow: An on‑balance volume analogue obv_net_phase increments by TF_buy_breakout − TF_sell_breakout each bar. Its differences over the last 1 and 2 bars (d_obv_1, d_obv_2) provide trend clues.
The algorithm then combines these signals:
• For strict mode , accumulation requires: (a) current ratio ≥ threshold, (b) cumulative ratio ≥ threshold, (c) both ratio differences ≥ 0, (d) net sum differences ≥ 0, and (e) OBV differences ≥ 0. Distribution is the mirror case.
• For loose mode , it relaxes the directional tests: either the 1‑ or the 2‑bar difference needs to agree in each category.
If all conditions for accumulation are satisfied, the phase is labelled “Accumulation” ; if all conditions for distribution are satisfied, it’s labelled “Distribution” ; otherwise the phase is “Neutral” .
4.4 Outputs
• Info table row : Row 8 displays “Market Phase (Vol)” on the left and the detected phase (Accumulation, Distribution or Neutral) on the right. The text colour of both cells matches a user‑selectable palette (typically green for accumulation, red for distribution and grey for neutral).
• On‑chart labels : When show_phase_labels is enabled and a phase persists for at least one bar, the module prints a label above the bar ( “Accum” ) or below the bar ( “Dist” ) with a dashed or dotted connector. The label is offset using ATR based on phase_label_atr_len_input and phase_label_multiplier and is styled according to user preferences.
Figure caption, The chart displays a red “Dist” label above a particular bar, indicating that the accumulation/distribution module identified a distribution phase at that point. The detection is based on seller dominance: during that bar, the net buyer-minus-seller flow and the OBV‑style cumulative flow were trending down, and the buyer ratio had dropped below the preset threshold. These conditions satisfy the distribution criteria in strict mode. The label is placed above the bar using an ATR‑based offset and a dashed connector. By the time of the current bar in the screenshot, the phase indicator shows “Neutral” in the info table—signaling that neither accumulation nor distribution conditions are currently met—yet the historical “Dist” label remains to mark where the prior distribution phase began.
Figure caption, In this example the market phase module has signaled an Accumulation phase. Three bars before the current candle, the algorithm detected a shift toward buyers: up‑volume exceeded its moving average, down‑volume was below average, and the buyer share of total volume climbed above the threshold while the on‑balance net flow and cumulative ratios were trending upwards. The blue “Accum” label anchored below that bar marks the start of the phase; it remains on the chart because successive bars continue to satisfy the accumulation conditions. The info table confirms this: the “Market Phase (Vol)” row still reads Accumulation, and the ratio and sum rows show buyers dominating both on the current bar and across the lookback window.
5. OB/OS Spike Module
5.1 What overbought/oversold means here
In many markets, a rapid extension up or down is often followed by a period of consolidation or reversal. The indicator interprets overbought (OB) conditions as abnormally strong selling risk at or after a price rally and oversold (OS) conditions as unusually strong buying risk after a decline. Importantly, these are not direct trade signals; rather they flag areas where caution or contrarian setups may be appropriate.
5.2 Inputs
• minHits_obos (1–7): Minimum number of oscillators that must agree on an overbought or oversold condition for a label to print.
• syncWin_obos: Length of a small sliding window over which oscillator votes are smoothed by taking the maximum count observed. This helps filter out choppy signals.
• Volume spike criteria: kVolRatio_obos (ratio of current volume to its SMA) and zVolThr_obos (Z‑score threshold) across volLen_obos. Either threshold can trigger a spike.
• Oscillator toggles and periods: Each of RSI, Stochastic (K and D), Williams %R, CCI, MFI, DeMarker and Stochastic RSI can be independently enabled; their periods are adjustable.
• Label appearance: ATR‑based offset, size, colors for OB and OS labels, plus connector style and width.
5.3 Detection logic
1. Directional volume spikes: Volume spikes are computed separately for buyer and seller volumes. A sell volume spike (sellVolSpike) flags a potential OverBought bar, while a buy volume spike (buyVolSpike) flags a potential OverSold bar. A spike occurs when the respective volume exceeds kVolRatio_obos times its simple moving average over the window or when its Z‑score exceeds zVolThr_obos.
2. Oscillator votes: For each enabled oscillator, calculate its overbought and oversold state using standard thresholds (e.g., RSI ≥ 70 for OB and ≤ 30 for OS; Stochastic %K/%D ≥ 80 for OB and ≤ 20 for OS; etc.). Count how many oscillators vote for OB and how many vote for OS.
3. Minimum hits: Apply the smoothing window syncWin_obos to the vote counts using a maximum‑of‑last‑N approach. A candidate bar is only considered if the smoothed OB hit count ≥ minHits_obos (for OverBought) or the smoothed OS hit count ≥ minHits_obos (for OverSold).
4. Tie‑breaking: If both OverBought and OverSold spike conditions are present on the same bar, compare the smoothed hit counts: the side with the higher count is selected; ties default to OverBought.
5. Label printing: When conditions are met, the bar is labelled as “OverBought X/7” above the candle or “OverSold X/7” below it. “X” is the number of oscillators confirming, and the bracket lists the abbreviations of contributing oscillators. Labels are offset from price using half of an ATR‑scaled distance and can optionally include a dotted or dashed connector line.
Figure caption, In this chart the overbought/oversold module has flagged an OverSold signal. A sell‑off from the prior highs brought price down to the lower trend‑line, where the bar marked “OverSold 3/7 DeM” appears. This label indicates that on that bar the module detected a buy‑side volume spike and that at least three of the seven enabled oscillators—in this case including the DeMarker—were in oversold territory. The label is printed below the candle with a dotted connector, signaling that the market may be temporarily exhausted on the downside. After this oversold print, price begins to rebound towards the upper red trend‑line and higher pivot levels.
Figure caption, This example shows the overbought/oversold module in action. In the left‑hand panel you can see the OB/OS settings where each oscillator (RSI, Stochastic, Williams %R, CCI, MFI, DeMarker and Stochastic RSI) can be enabled or disabled, and the ATR length and label offset multiplier adjusted. On the chart itself, price has pushed up to the descending red trendline and triggered an “OverBought 3/7” label. That means the sell‑side volume spiked relative to its average and three out of the seven enabled oscillators were in overbought territory. The label is offset above the candle by half of an ATR and connected with a dashed line, signaling that upside momentum may be overextended and a pause or pullback could follow.
6. Buyer/Seller Trap Module
6.1 Concept
A bull trap occurs when price appears to break above resistance, attracting buyers, but fails to sustain the move and quickly reverses, leaving a long upper wick and trapping late entrants. A bear trap is the opposite: price breaks below support, lures in sellers, then snaps back, leaving a long lower wick and trapping shorts. This module detects such traps by looking for price structure sweeps, order‑flow mismatches and dominance reversals. It uses a scoring system to differentiate risk from confirmed traps.
6.2 Inputs
• trap_lookback_len: Window length used to rank extremes and detect sweeps.
• trap_wick_threshold: Minimum proportion of a bar’s range that must be wick (upper for bull traps, lower for bear traps) to qualify as a sweep.
• trap_score_risk: Minimum aggregated score required to flag a trap risk. (The code defines a trap_score_confirm input, but confirmation is actually based on price reversal rather than a separate score threshold.)
• trap_confirm_bars: Maximum number of bars allowed for price to reverse and confirm the trap. If price does not reverse in this window, the risk label will expire or remain unconfirmed.
• Label settings: ATR length and multiplier for offsetting, size, colours for risk and confirmed labels, and connector style and width. Separate settings exist for bull and bear traps.
• Toggle inputs: show_trap_module and show_trap_labels enable the module and control whether labels are drawn on the chart.
6.3 Scoring logic
The module assigns points to several conditions and sums them to determine whether a trap risk is present. For bull traps, the score is built from the following (bear traps mirror the logic with highs and lows swapped):
1. Sweep (2 points): Price trades above the high pivot (HH1) but fails to close above it and leaves a long upper wick at least trap_wick_threshold × range. For bear traps, price dips below the low pivot (LL1), fails to close below and leaves a long lower wick.
2. Close break (1 point): Price closes beyond HH1 or LL1 without leaving a long wick.
3. Candle/delta mismatch (2 points): The candle closes bullish yet the order flow delta is negative or the seller ratio exceeds 50%, indicating hidden supply. Conversely, a bearish close with positive delta or buyer dominance suggests hidden demand.
4. Dominance inversion (2 points): The current bar’s buyer volume has the highest rank in the lookback window while cumulative sums favor sellers, or vice versa.
5. Low‑volume break (1 point): Price crosses the pivot but total volume is below its moving average.
The total score for each side is compared to trap_score_risk. If the score is high enough, a “Bull Trap Risk” or “Bear Trap Risk” label is drawn, offset from the candle by half of an ATR‑scaled distance using a dashed outline. If, within trap_confirm_bars, price reverses beyond the opposite level—drops back below the high pivot for bull traps or rises above the low pivot for bear traps—the label is upgraded to a solid “Bull Trap” or “Bear Trap” . In this version of the code, there is no separate score threshold for confirmation: the variable trap_score_confirm is unused; confirmation depends solely on a successful price reversal within the specified number of bars.
Figure caption, In this example the trap module has flagged a Bear Trap Risk. Price initially breaks below the most recent low pivot (LL1), but the bar closes back above that level and leaves a long lower wick, suggesting a failed push lower. Combined with a mismatch between the candle direction and the order flow (buyers regain control) and a reversal in volume dominance, the aggregate score exceeds the risk threshold, so a dashed “Bear Trap Risk” label prints beneath the bar. The green and red trend lines mark the current low and high pivot trajectories, while the horizontal dashed lines show the highest and lowest values in the lookback window. If, within the next few bars, price closes decisively above the support, the risk label would upgrade to a solid “Bear Trap” label.
Figure caption, In this example the trap module has identified both ends of a price range. Near the highs, price briefly pushes above the descending red trendline and the recent pivot high, but fails to close there and leaves a noticeable upper wick. That combination of a sweep above resistance and order‑flow mismatch generates a Bull Trap Risk label with a dashed outline, warning that the upside break may not hold. At the opposite extreme, price later dips below the green trendline and the labelled low pivot, then quickly snaps back and closes higher. The long lower wick and subsequent price reversal upgrade the previous bear‑trap risk into a confirmed Bear Trap (solid label), indicating that sellers were caught on a false breakdown. Horizontal dashed lines mark the highest high and lowest low of the lookback window, while the red and green diagonals connect the earliest and latest pivot highs and lows to visualize the range.
7. Sharp Move Module
7.1 Concept
Markets sometimes display absorption or climax behavior—periods when one side steadily gains the upper hand before price breaks out with a sharp move. This module evaluates several order‑flow and volume conditions to anticipate such moves. Users can choose how many conditions must be met to flag a risk and how many (plus a price break) are required for confirmation.
7.2 Inputs
• sharp Lookback: Number of bars in the window used to compute moving averages, sums, percentile ranks and reference levels.
• sharpPercentile: Minimum percentile rank for the current side’s volume; the current buy (or sell) volume must be greater than or equal to this percentile of historical volumes over the lookback window.
• sharpVolMult: Multiplier used in the volume climax check. The current side’s volume must exceed this multiple of its average to count as a climax.
• sharpRatioThr: Minimum dominance ratio (current side’s volume relative to the opposite side) used in both the instant and cumulative dominance checks.
• sharpChurnThr: Maximum ratio of a bar’s range to its ATR for absorption/churn detection; lower values indicate more absorption (large volume in a small range).
• sharpScoreRisk: Minimum number of conditions that must be true to print a risk label.
• sharpScoreConfirm: Minimum number of conditions plus a price break required for confirmation.
• sharpCvdThr: Threshold for cumulative delta divergence versus price change (positive for bullish accumulation, negative for bearish distribution).
• Label settings: ATR length (sharpATRlen) and multiplier (sharpLabelMult) for positioning labels, label size, colors and connector styles for bullish and bearish sharp moves.
• Toggles: enableSharp activates the module; show_sharp_labels controls whether labels are drawn.
7.3 Conditions (six per side)
For each side, the indicator computes six boolean conditions and sums them to form a score:
1. Dominance (instant and cumulative):
– Instant dominance: current buy volume ≥ sharpRatioThr × current sell volume.
– Cumulative dominance: sum of buy volumes over the window ≥ sharpRatioThr × sum of sell volumes (and vice versa for bearish checks).
2. Accumulation/Distribution divergence: Over the lookback window, cumulative delta rises by at least sharpCvdThr while price fails to rise (bullish), or cumulative delta falls by at least sharpCvdThr while price fails to fall (bearish).
3. Volume climax: The current side’s volume is ≥ sharpVolMult × its average and the product of volume and bar range is the highest in the lookback window.
4. Absorption/Churn: The current side’s volume divided by the bar’s range equals the highest value in the window and the bar’s range divided by ATR ≤ sharpChurnThr (indicating large volume within a small range).
5. Percentile rank: The current side’s volume percentile rank is ≥ sharp Percentile.
6. Mirror logic for sellers: The above checks are repeated with buyer and seller roles swapped and the price break levels reversed.
Each condition that passes contributes one point to the corresponding side’s score (0 or 1). Risk and confirmation thresholds are then applied to these scores.
7.4 Scoring and labels
• Risk: If scoreBull ≥ sharpScoreRisk, a “Sharp ↑ Risk” label is drawn above the bar. If scoreBear ≥ sharpScoreRisk, a “Sharp ↓ Risk” label is drawn below the bar.
• Confirmation: A risk label is upgraded to “Sharp ↑” when scoreBull ≥ sharpScoreConfirm and the bar closes above the highest recent pivot (HH1); for bearish cases, confirmation requires scoreBear ≥ sharpScoreConfirm and a close below the lowest pivot (LL1).
• Label positioning: Labels are offset from the candle by ATR × sharpLabelMult (full ATR times multiplier), not half, and may include a dashed or dotted connector line if enabled.
Figure caption, In this chart both bullish and bearish sharp‑move setups have been flagged. Earlier in the range, a “Sharp ↓ Risk” label appears beneath a candle: the sell‑side score met the risk threshold, signaling that the combination of strong sell volume, dominance and absorption within a narrow range suggested a potential sharp decline. The price did not close below the lower pivot, so this label remains a “risk” and no confirmation occurred. Later, as the market recovered and volume shifted back to the buy side, a “Sharp ↑ Risk” label prints above a candle near the top of the channel. Here, buy‑side dominance, cumulative delta divergence and a volume climax aligned, but price has not yet closed above the upper pivot (HH1), so the alert is still a risk rather than a confirmed sharp‑up move.
Figure caption, In this chart a Sharp ↑ label is displayed above a candle, indicating that the sharp move module has confirmed a bullish breakout. Prior bars satisfied the risk threshold — showing buy‑side dominance, positive cumulative delta divergence, a volume climax and strong absorption in a narrow range — and this candle closes above the highest recent pivot, upgrading the earlier “Sharp ↑ Risk” alert to a full Sharp ↑ signal. The green label is offset from the candle with a dashed connector, while the red and green trend lines trace the high and low pivot trajectories and the dashed horizontals mark the highest and lowest values of the lookback window.
8. Market‑Maker / Spread‑Capture Module
8.1 Concept
Liquidity providers often “capture the spread” by buying and selling in almost equal amounts within a very narrow price range. These bars can signal temporary congestion before a move or reflect algorithmic activity. This module flags bars where both buyer and seller volumes are high, the price range is only a few ticks and the buy/sell split remains close to 50%. It helps traders spot potential liquidity pockets.
8.2 Inputs
• scalpLookback: Window length used to compute volume averages.
• scalpVolMult: Multiplier applied to each side’s average volume; both buy and sell volumes must exceed this multiple.
• scalpTickCount: Maximum allowed number of ticks in a bar’s range (calculated as (high − low) / minTick). A value of 1 or 2 captures ultra‑small bars; increasing it relaxes the range requirement.
• scalpDeltaRatio: Maximum deviation from a perfect 50/50 split. For example, 0.05 means the buyer share must be between 45% and 55%.
• Label settings: ATR length, multiplier, size, colors, connector style and width.
• Toggles : show_scalp_module and show_scalp_labels to enable the module and its labels.
8.3 Signal
When, on the current bar, both TF_buy_breakout and TF_sell_breakout exceed scalpVolMult times their respective averages and (high − low)/minTick ≤ scalpTickCount and the buyer share is within scalpDeltaRatio of 50%, the module prints a “Spread ↔” label above the bar. The label uses the same ATR offset logic as other modules and draws a connector if enabled.
Figure caption, In this chart the spread‑capture module has identified a potential liquidity pocket. Buyer and seller volumes both spiked above their recent averages, yet the candle’s range measured only a couple of ticks and the buy/sell split stayed close to 50 %. This combination met the module’s criteria, so it printed a grey “Spread ↔” label above the bar. The red and green trend lines link the earliest and latest high and low pivots, and the dashed horizontals mark the highest high and lowest low within the current lookback window.
9. Money Flow Module
9.1 Concept
To translate volume into a monetary measure, this module multiplies each side’s volume by the closing price. It tracks buying and selling system money default currency on a per-bar basis and sums them over a chosen period. The difference between buy and sell currencies (Δ$) shows net inflow or outflow.
9.2 Inputs
• mf_period_len_mf: Number of bars used for summing buy and sell dollars.
• Label appearance settings: ATR length, multiplier, size, colors for up/down labels, and connector style and width.
• Toggles: Use enableMoneyFlowLabel_mf and showMFLabels to control whether the module and its labels are displayed.
9.3 Calculations
• Per-bar money: Buy $ = TF_buy_breakout × close; Sell $ = TF_sell_breakout × close. Their difference is Δ$ = Buy $ − Sell $.
• Summations: Over mf_period_len_mf bars, compute Σ Buy $, Σ Sell $ and ΣΔ$ using math.sum().
• Info table entries: Rows 9–13 display these values as texts like “↑ USD 1234 (1M)” or “ΣΔ USD −5678 (14)”, with colors reflecting whether buyers or sellers dominate.
• Money flow status: If Δ$ is positive the bar is marked “Money flow in” ; if negative, “Money flow out” ; if zero, “Neutral”. The cumulative status is similarly derived from ΣΔ.Labels print at the bar that changes the sign of ΣΔ, offset using ATR × label multiplier and styled per user preferences.
Figure caption, The chart illustrates a steady rise toward the highest recent pivot (HH1) with price riding between a rising green trend‑line and a red trend‑line drawn through earlier pivot highs. A green Money flow in label appears above the bar near the top of the channel, signaling that net dollar flow turned positive on this bar: buy‑side dollar volume exceeded sell‑side dollar volume, pushing the cumulative sum ΣΔ$ above zero. In the info table, the “Money flow (bar)” and “Money flow Σ” rows both read In, confirming that the indicator’s money‑flow module has detected an inflow at both bar and aggregate levels, while other modules (pivots, trend lines and support/resistance) remain active to provide structural context.
In this example the Money Flow module signals a net outflow. Price has been trending downward: successive high pivots form a falling red trend‑line and the low pivots form a descending green support line. When the latest bar broke below the previous low pivot (LL1), both the bar‑level and cumulative net dollar flow turned negative—selling volume at the close exceeded buying volume and pushed the cumulative Δ$ below zero. The module reacts by printing a red “Money flow out” label beneath the candle; the info table confirms that the “Money flow (bar)” and “Money flow Σ” rows both show Out, indicating sustained dominance of sellers in this period.
10. Info Table
10.1 Purpose
When enabled, the Info Table appears in the lower right of your chart. It summarises key values computed by the indicator—such as buy and sell volume, delta, total volume, breakout status, market phase, and money flow—so you can see at a glance which side is dominant and which signals are active.
10.2 Symbols
• ↑ / ↓ — Up (↑) denotes buy volume or money; down (↓) denotes sell volume or money.
• MA — Moving average. In the table it shows the average value of a series over the lookback period.
• Σ (Sigma) — Cumulative sum over the chosen lookback period.
• Δ (Delta) — Difference between buy and sell values.
• B / S — Buyer and seller share of total volume, expressed as percentages.
• Ref. Price — Reference price for breakout calculations, based on the latest pivot.
• Status — Indicates whether a breakout condition is currently active (True) or has failed.
10.3 Row definitions
1. Up volume / MA up volume – Displays current buy volume on the lower timeframe and its moving average over the lookback period.
2. Down volume / MA down volume – Shows current sell volume and its moving average; sell values are formatted in red for clarity.
3. Δ / ΣΔ – Lists the difference between buy and sell volume for the current bar and the cumulative delta volume over the lookback period.
4. Σ / MA Σ (Vol/MA) – Total volume (buy + sell) for the bar, with the ratio of this volume to its moving average; the right cell shows the average total volume.
5. B/S ratio – Buy and sell share of the total volume: current bar percentages and the average percentages across the lookback period.
6. Buyer Rank / Seller Rank – Ranks the bar’s buy and sell volumes among the last (n) bars; lower rank numbers indicate higher relative volume.
7. Σ Buy / Σ Sell – Sum of buy and sell volumes over the lookback window, indicating which side has traded more.
8. Breakout UP / DOWN – Shows the breakout thresholds (Ref. Price) and whether the breakout condition is active (True) or has failed.
9. Market Phase (Vol) – Reports the current volume‑only phase: Accumulation, Distribution or Neutral.
10. Money Flow – The final rows display dollar amounts and status:
– ↑ USD / Σ↑ USD – Buy dollars for the current bar and the cumulative sum over the money‑flow period.
– ↓ USD / Σ↓ USD – Sell dollars and their cumulative sum.
– Δ USD / ΣΔ USD – Net dollar difference (buy minus sell) for the bar and cumulatively.
– Money flow (bar) – Indicates whether the bar’s net dollar flow is positive (In), negative (Out) or neutral.
– Money flow Σ – Shows whether the cumulative net dollar flow across the chosen period is positive, negative or neutral.
The chart above shows a sequence of different signals from the indicator. A Bull Trap Risk appears after price briefly pushes above resistance but fails to hold, then a green Accum label identifies an accumulation phase. An upward breakout follows, confirmed by a Money flow in print. Later, a Sharp ↓ Risk warns of a possible sharp downturn; after price dips below support but quickly recovers, a Bear Trap label marks a false breakdown. The highlighted info table in the center summarizes key metrics at that moment, including current and average buy/sell volumes, net delta, total volume versus its moving average, breakout status (up and down), market phase (volume), and bar‑level and cumulative money flow (In/Out).
11. Conclusion & Final Remarks
This indicator was developed as a holistic study of market structure and order flow. It brings together several well‑known concepts from technical analysis—breakouts, accumulation and distribution phases, overbought and oversold extremes, bull and bear traps, sharp directional moves, market‑maker spread bars and money flow—into a single Pine Script tool. Each module is based on widely recognized trading ideas and was implemented after consulting reference materials and example strategies, so you can see in real time how these concepts interact on your chart.
A distinctive feature of this indicator is its reliance on per‑side volume: instead of tallying only total volume, it separately measures buy and sell transactions on a lower time frame. This approach gives a clearer view of who is in control—buyers or sellers—and helps filter breakouts, detect phases of accumulation or distribution, recognize potential traps, anticipate sharp moves and gauge whether liquidity providers are active. The money‑flow module extends this analysis by converting volume into currency values and tracking net inflow or outflow across a chosen window.
Although comprehensive, this indicator is intended solely as a guide. It highlights conditions and statistics that many traders find useful, but it does not generate trading signals or guarantee results. Ultimately, you remain responsible for your positions. Use the information presented here to inform your analysis, combine it with other tools and risk‑management techniques, and always make your own decisions when trading.
Differential-Isaac-Newton
Description of the Differential-Isaac-Newton Indicator (DF-Newton)
This indicator plots custom Fibonacci levels on the chart using configurable multiples and offers various display options to assist with technical analysis.
What does it do?
Calculates and plots Fibonacci levels based on user-defined multiples (default multiple is 20).
Allows switching between long mode (buy) and short mode (sell) to adjust the levels accordingly.
Displays horizontal lines at Fibonacci levels with customizable colors and styles.
Shows labels with different information such as level price, Fibonacci percentage, and difference between levels.
Includes controls to show/hide different elements and customize the appearance.
How to use it?
Main Settings
Multiple of 2 for Fibonacci: Defines the percentage interval used to calculate Fibonacci levels (e.g., 20 creates levels at 0%, 20%, 40%, etc.).
Line Horizontal Offset: Defines the horizontal distance (in bars) of the Fibonacci line to improve visibility.
Short Mode: Enable to calculate levels based on a downward movement (from low to high).
Classic Mode: Changes the line colors to a classic Fibonacci color scheme (blue, green, yellow, orange, red).
Toggle Solid Line: Switches between solid and dotted lines for Fibonacci levels.
Labels
Choose which information to display on the labels next to the lines:
Show Only Level Prices: Displays only the Fibonacci level price.
Show Only Level Percentages: Displays only the Fibonacci percentage level.
Show Difference Values (Δ): Shows the difference between the current and previous level, along with the percentage (which can be hidden).
Hide Percentage in Difference Mode: Hides the percentage when difference mode is enabled.
Hide All Labels: Hides all labels from the chart.
Visual Customization
Label Size: Size of the label text (XS, S, M, L).
Label Horizontal Offset: Horizontal distance of labels relative to the lines.
Background Offset: Adjusts background color offset for better visibility.
Fibonacci Line Color: Color of the Fibonacci lines (when classic mode is off).
Label Text Color: Color of the label text.
Level Interpretation
Fibonacci levels are calculated between the highest high and lowest low of the last 100 candles.
The indicator plots horizontal lines at Fibonacci levels according to the selected multiple.
Line colors help identify important levels (configurable in classic mode).
Labels show the exact level price and Fibonacci percentage, helping with entry, exit, support, and resistance decisions.
Recommendations
Use Short Mode to analyze Fibonacci levels for sell trades.
Use Classic Mode for a traditional color scheme and easier identification.
Adjust Line Horizontal Offset to avoid overlapping current candles.
Combine price and percentage display for easier analysis.
Explore Difference Mode (Δ) to understand gaps between consecutive Fibonacci levels.
Practical Example
If you set the multiple to 20, the indicator will show levels at 0%, 20%, 40%, 60%, 80%, and 100%. Each level will have a horizontal line and a label showing the corresponding price and percentage, or the difference from the previous level, depending on your settings.
Composite Scaled EMA LevelsComposite Scaled EMA Levels Indicator
This TradingView Pine Script indicator calculates a “composite EMA” that compares the closing price of the current asset with that of the XU100 index and scales the EMA values to the XU100 level. It then visualizes these computed levels as horizontal lines on the chart with corresponding labels.
Key Components:
Inputs and Data Retrieval:
Length Input: The user defines a parameter length (default is 10) which determines over how many bars the horizontal line is drawn.
Data Collection:
The daily closing price of the current symbol (current_close) is retrieved using request.security().
The daily closing price of the XU100 index (xu100) is also retrieved.
A ratio is computed as current_close / xu100. This ratio serves as the basis for calculating the composite EMAs.
EMA Calculations:
The indicator computes Exponential Moving Averages (EMAs) on the ratio for specific periods.
In the provided version, the script calculates EMAs for three periods (34, 55, and 233), though you can easily expand this to other periods if needed.
Each computed EMA (for instance, EMA34, EMA55, EMA233) is then scaled by multiplying it with the XU100 index’s close, converting it to a price level that is meaningful on the chart.
Drawing Horizontal Lines:
Instead of using the standard plot() function, the script uses line.new() to draw horizontal lines representing the scaled EMA values over the last “length” bars.
Before drawing new lines, any existing lines and labels are deleted to ensure that only the most current values are shown.
Adding Labels to Lines:
The script creates a label for each EMA using label.new(), placing the label at the current bar (i.e., the rightmost position on the chart) using label.style_label_left so that the text appears to the right of the line.
The label displays the name of the composite EMA (e.g., "Composite EMA 34") along with its current scaled value.
Visualization:
The horizontal lines and labels provide a visual reference for the composite EMA levels. These lines help traders see critical support/resistance levels derived from the relationship between the current asset and the XU100 index.
Colors are assigned for clarity (for example, the EMA lines in this version use green).
Summary:
The Composite Scaled EMA Levels indicator is designed to help traders analyze the relationship between an asset’s price and the broader market index (XU100) by calculating a ratio and then applying EMAs on that ratio. By scaling these EMAs back to price levels and displaying them as horizontal lines with clear labels on the chart, the indicator offers a visual tool to assess trend direction and potential support or resistance levels. This can assist in making informed trading decisions based on composite trend analysis.
Stop Loss & TargetHow to Use the SL/TP Indicator
The SL/TP indicator is a versatile tool designed for traders to easily visualize entry, stop-loss (SL), and take-profit (TP) levels on their charts. This guide will walk you through the steps to configure and use the indicator effectively.
Features:
Configure Long Trades and Short Trades independently.
Define Entry Price, Stop Loss, and up to three Take Profit levels for each trade.
Customize line colors for better visualization.
Works for both risk-reward and target-based trading.
Adding the Indicator:
Open the TradingView platform.
Search for the indicator name: SL/TP.
Click the Add to Chart button to apply it.
Configuration:
1. Long Trade Settings
Enable Long Trade: Check this option to activate long trade lines on the chart.
Long Entry Price: Input the price at which you plan to enter the long trade.
Long Stop Loss: Input your stop-loss level for the long trade.
Line Colors: You can customize the colors for the Entry, SL, and TP lines in the Long Trade settings group.
Take Profit Levels (Calculated Automatically):
TP1: 1:1 Risk-Reward ratio (difference between Entry and SL added to Entry).
TP2: 1:2 Risk-Reward ratio.
TP3: 1:3 Risk-Reward ratio.
2. Short Trade Settings
Enable Short Trade: Check this option to activate short trade lines on the chart.
Short Entry Price: Input the price at which you plan to enter the short trade.
Short Stop Loss: Input your stop-loss level for the short trade.
Line Colors: You can customize the colors for the Entry, SL, and TP lines in the Short Trade settings group.
Take Profit Levels (Calculated Automatically):
TP1: 1:1 Risk-Reward ratio (difference between Entry and SL subtracted from Entry).
TP2: 1:2 Risk-Reward ratio.
TP3: 1:3 Risk-Reward ratio.
Visualizing on the Chart:
Once you configure the settings and enable the trade, the indicator will draw horizontal lines on the chart for:
Entry Price
Stop Loss
Take Profit Levels (TP1, TP2, TP3)
Each line will extend to three bars ahead of the current bar index.
Customization:
Adjust colors for better visibility depending on your chart theme.
The width and style of lines can also be modified in the source code if needed.
Example Usage:
Long Trade Example:
Enable Long Trade: Check the box.
Set Entry Price: 100.
Set Stop Loss: 95.
The indicator will draw the following lines:
Entry Line: At 100 (customizable color).
Stop Loss Line: At 95 (customizable color).
TP1 Line: At 105 (1:1 Risk-Reward).
TP2 Line: At 110 (1:2 Risk-Reward).
TP3 Line: At 115 (1:3 Risk-Reward).
Short Trade Example:
Enable Short Trade: Check the box.
Set Entry Price: 200.
Set Stop Loss: 205.
The indicator will draw the following lines:
Entry Line: At 200 (customizable color).
Stop Loss Line: At 205 (customizable color).
TP1 Line: At 195 (1:1 Risk-Reward).
TP2 Line: At 190 (1:2 Risk-Reward).
TP3 Line: At 185 (1:3 Risk-Reward).
Notes:
Ensure that you input valid and realistic price levels for Entry and Stop Loss.
The indicator will only display lines if both the Entry Price and Stop Loss are non-zero.
Use this indicator for planning trades visually but always confirm levels with your trading strategy.
Disclaimer: This indicator is a tool to assist in trading. Use it with proper risk management and your own due diligence.
2x ATR Horizontal Rays2x ATR Horizontal Rays Indicator
This script plots horizontal rays based on the 2x ATR (Average True Range) of the previous candle. It helps traders visualize key support and resistance levels by extending lines from the last candle's price, calculated with a 2x ATR multiplier. The indicator draws two lines:
Upper ATR Line: Positioned above the previous candle’s close by 2x the ATR value.
Lower ATR Line: Positioned below the previous candle’s close by 2x the ATR value.
Key Features:
Customizable ATR Length: Allows users to input their preferred ATR period to suit different market conditions.
Dynamic Horizontal Lines: The lines update with each new candle, giving traders a clear visual of volatility levels.
Extended Right Lines: The horizontal rays extend to the right, serving as potential zones for price reversals or breakouts.
This indicator is useful for traders looking to gauge market volatility and set target levels or stops based on historical price movements.
How to Use:
Add the indicator to your chart and adjust the ATR length in the settings.
Watch how the price interacts with the upper and lower ATR lines as potential zones for support, resistance, or trend continuation.
Happy trading!
What RSI? Weighted Heiken Ashi Triple RSIWhat You're Looking At:
The indicator presents a few key elements on its pane which is separate from the price chart:
Smoothed RSI Average Line: This line represents an average of three different RSI calculations, each weighted differently. It's been smoothed out to reduce noise and help you see the trend more clearly.
Moving Average Line: This is a line that smooths out the average RSI line even further and helps you identify the overall trend.
Bollinger Bands: These are two lines that create a channel around the RSI average line. The upper band typically represents an overbought condition, and the lower band represents an oversold condition.
Background Color: The background of the indicator pane will change colors to indicate buy (green) or sell (red) signals.
Horizontal Lines: There are horizontal lines drawn at levels 70, 50, and 30. These represent overbought, midpoint, and oversold levels, respectively.
How to Operate and Interpret:
Trend Identification: Look at the moving average line. If it's trending upwards, the overall momentum may be considered bullish. If it's trending downwards, the momentum may be bearish.
Buy Signals: You may consider a buy signal when:
The smoothed RSI average crosses above the moving average line.
The smoothed RSI average is below 30 and starts to rise, crossing the oversold line.
The background color turns green, signifying favorable conditions to buy according to the indicator's logic.
Sell Signals: You may consider a sell signal when:
The smoothed RSI average crosses below the moving average line.
The smoothed RSI average is above 70 and starts to fall, crossing the overbought line.
The background color turns red, signifying favorable conditions to sell according to the indicator's logic.
Overbought/Oversold Conditions: When the smoothed RSI line touches or crosses the Bollinger Bands, it could be indicating that the asset is overbought (upper band) or oversold (lower band). Some traders use these conditions to look for potential reversals.
Cautions for Trading:
If the smoothed RSI average is between the bands and near the middle line (50), the market might be considered neutral, and some traders may choose to wait for clearer signals.
Just because the indicator gives a buy or sell signal, it doesn't mean the price will immediately move in that direction. It's important to consider other factors in your trading strategy.
Final Notes:
Always use this indicator in conjunction with other analysis methods. No indicator is perfect, and they should be used to supplement your trading strategy, not replace it.
It's important to set stop losses according to your risk tolerance when entering any trades based on these signals.
Practice with the indicator in a demo account to become familiar with its behavior before using it with real money.
By following the movements and signals of this indicator, you can get a sense of the momentum and potential entry or exit points in the markets you are trading.
VoVix DEVMA🌌 VoVix DEVMA: A Deep Dive into Second-Order Volatility Dynamics
Welcome to VoVix+, a sophisticated trading framework that transcends traditional price analysis. This is not merely another indicator; it is a complete system designed to dissect and interpret the very fabric of market volatility. VoVix+ operates on the principle that the most powerful signals are not found in price alone, but in the behavior of volatility itself. It analyzes the rate of change, the momentum, and the structure of market volatility to identify periods of expansion and contraction, providing a unique edge in anticipating major market moves.
This document will serve as your comprehensive guide, breaking down every mathematical component, every user input, and every visual element to empower you with a profound understanding of how to harness its capabilities.
🔬 THEORETICAL FOUNDATION: THE MATHEMATICS OF MARKET DYNAMICS
VoVix+ is built upon a multi-layered mathematical engine designed to measure what we call "second-order volatility." While standard indicators analyze price, and first-order volatility indicators (like ATR) analyze the range of price, VoVix+ analyzes the dynamics of the volatility itself. This provides insight into the market's underlying state of stability or chaos.
1. The VoVix Score: Measuring Volatility Thrust
The core of the system begins with the VoVix Score. This is a normalized measure of volatility acceleration or deceleration.
Mathematical Formula:
VoVix Score = (ATR(fast) - ATR(slow)) / (StDev(ATR(fast)) + ε)
Where:
ATR(fast) is the Average True Range over a short period, representing current, immediate volatility.
ATR(slow) is the Average True Range over a longer period, representing the baseline or established volatility.
StDev(ATR(fast)) is the Standard Deviation of the fast ATR, which measures the "noisiness" or consistency of recent volatility.
ε (epsilon) is a very small number to prevent division by zero.
Market Implementation:
Positive Score (Expansion): When the fast ATR is significantly higher than the slow ATR, it indicates a rapid increase in volatility. The market is "stretching" or expanding.
Negative Score (Contraction): When the fast ATR falls below the slow ATR, it indicates a decrease in volatility. The market is "coiling" or contracting.
Normalization: By dividing by the standard deviation, we normalize the score. This turns it into a standardized measure, allowing us to compare volatility thrust across different market conditions and timeframes. A score of 2.0 in a quiet market means the same, relatively, as a score of 2.0 in a volatile market.
2. Deviation Analysis (DEV): Gauging Volatility's Own Volatility
The script then takes the analysis a step further. It calculates the standard deviation of the VoVix Score itself.
Mathematical Formula:
DEV = StDev(VoVix Score, lookback_period)
Market Implementation:
This DEV value represents the magnitude of chaos or stability in the market's volatility dynamics. A high DEV value means the volatility thrust is erratic and unpredictable. A low DEV value suggests the change in volatility is smooth and directional.
3. The DEVMA Crossover: Identifying Regime Shifts
This is the primary signal generator. We take two moving averages of the DEV value.
Mathematical Formula:
fastDEVMA = SMA(DEV, fast_period)
slowDEVMA = SMA(DEV, slow_period)
The Core Signal:
The strategy triggers on the crossover and crossunder of these two DEVMA lines. This is a profound concept: we are not looking at a moving average of price or even of volatility, but a moving average of the standard deviation of the normalized rate of change of volatility.
Bullish Crossover (fastDEVMA > slowDEVMA): This signals that the short-term measure of volatility's chaos is increasing relative to the long-term measure. This often precedes a significant market expansion and is interpreted as a bullish volatility regime.
Bearish Crossunder (fastDEVMA < slowDEVMA): This signals that the short-term measure of volatility's chaos is decreasing. The market is settling down or contracting, often leading to trending moves or range consolidation.
⚙️ INPUTS MENU: CONFIGURING YOUR ANALYSIS ENGINE
Every input has been meticulously designed to give you full control over the strategy's behavior. Understanding these settings is key to adapting VoVix+ to your specific instrument, timeframe, and trading style.
🌀 VoVix DEVMA Configuration
🧬 Deviation Lookback: This sets the lookback period for calculating the DEV value. It defines the window for measuring the stability of the VoVix Score. A shorter value makes the system highly reactive to recent changes in volatility's character, ideal for scalping. A longer value provides a smoother, more stable reading, better for identifying major, long-term regime shifts.
⚡ Fast VoVix Length: This is the lookback period for the fastDEVMA. It represents the short-term trend of volatility's chaos. A smaller number will result in a faster, more sensitive signal line that reacts quickly to market shifts.
🐌 Slow VoVix Length: This is the lookback period for the slowDEVMA. It represents the long-term, baseline trend of volatility's chaos. A larger number creates a more stable, slower-moving anchor against which the fast line is compared.
How to Optimize: The relationship between the Fast and Slow lengths is crucial. A wider gap (e.g., 20 and 60) will result in fewer, but potentially more significant, signals. A narrower gap (e.g., 25 and 40) will generate more frequent signals, suitable for more active trading styles.
🧠 Adaptive Intelligence
🧠 Enable Adaptive Features: When enabled, this activates the strategy's performance tracking module. The script will analyze the outcome of its last 50 trades to calculate a dynamic win rate.
⏰ Adaptive Time-Based Exit: If Enable Adaptive Features is on, this allows the strategy to adjust its Maximum Bars in Trade setting based on performance. It learns from the average duration of winning trades. If winning trades tend to be short, it may shorten the time exit to lock in profits. If winners tend to run, it will extend the time exit, allowing trades more room to develop. This helps prevent the strategy from cutting winning trades short or holding losing trades for too long.
⚡ Intelligent Execution
📊 Trade Quantity: A straightforward input that defines the number of contracts or shares for each trade. This is a fixed value for consistent position sizing.
🛡️ Smart Stop Loss: Enables the dynamic stop-loss mechanism.
🎯 Stop Loss ATR Multiplier: Determines the distance of the stop loss from the entry price, calculated as a multiple of the current 14-period ATR. A higher multiplier gives the trade more room to breathe but increases risk per trade. A lower multiplier creates a tighter stop, reducing risk but increasing the chance of being stopped out by normal market noise.
💰 Take Profit ATR Multiplier: Sets the take profit target, also as a multiple of the ATR. A common practice is to set this higher than the Stop Loss multiplier (e.g., a 2:1 or 3:1 reward-to-risk ratio).
🏃 Use Trailing Stop: This is a powerful feature for trend-following. When enabled, instead of a fixed stop loss, the stop will trail behind the price as the trade moves into profit, helping to lock in gains while letting winners run.
🎯 Trail Points & 📏 Trail Offset ATR Multipliers: These control the trailing stop's behavior. Trail Points defines how much profit is needed before the trail activates. Trail Offset defines how far the stop will trail behind the current price. Both are based on ATR, making them fully adaptive to market volatility.
⏰ Maximum Bars in Trade: This is a time-based stop. It forces an exit if a trade has been open for a specified number of bars, preventing positions from being held indefinitely in stagnant markets.
⏰ Session Management
These inputs allow you to confine the strategy's trading activity to specific market hours, which is crucial for day trading instruments that have defined high-volume sessions (e.g., stock market open).
🎨 Visual Effects & Dashboard
These toggles give you complete control over the on-chart visuals and the dashboard. You can disable any element to declutter your chart or focus only on the information that matters most to you.
📊 THE DASHBOARD: YOUR AT-A-GLANCE COMMAND CENTER
The dashboard centralizes all critical information into one compact, easy-to-read panel. It provides a real-time summary of the market state and strategy performance.
🎯 VOVIX ANALYSIS
Fast & Slow: Displays the current numerical values of the fastDEVMA and slowDEVMA. The color indicates their direction: green for rising, red for falling. This lets you see the underlying momentum of each line.
Regime: This is your most important environmental cue. It tells you the market's current state based on the DEVMA relationship. 🚀 EXPANSION (Green) signifies a bullish volatility regime where explosive moves are more likely. ⚛️ CONTRACTION (Purple) signifies a bearish volatility regime, where the market may be consolidating or entering a smoother trend.
Quality: Measures the strength of the last signal based on the magnitude of the DEVMA difference. An ELITE or STRONG signal indicates a high-conviction setup where the crossover had significant force.
PERFORMANCE
Win Rate & Trades: Displays the historical win rate of the strategy from the backtest, along with the total number of closed trades. This provides immediate feedback on the strategy's historical effectiveness on the current chart.
EXECUTION
Trade Qty: Shows your configured position size per trade.
Session: Indicates whether trading is currently OPEN (allowed) or CLOSED based on your session management settings.
POSITION
Position & PnL: Displays your current position (LONG, SHORT, or FLAT) and the real-time Profit or Loss of the open trade.
🧠 ADAPTIVE STATUS
Stop/Profit Mult: In this simplified version, these are placeholders. The primary adaptive feature currently modifies the time-based exit, which is reflected in how long trades are held on the chart.
🎨 THE VISUAL UNIVERSE: DECIPHERING MARKET GEOMETRY
The visuals are not mere decorations; they are geometric representations of the underlying mathematical concepts, designed to give you an intuitive feel for the market's state.
The Core Lines:
FastDEVMA (Green/Maroon Line): The primary signal line. Green when rising, indicating an increase in short-term volatility chaos. Maroon when falling.
SlowDEVMA (Aqua/Orange Line): The baseline. Aqua when rising, indicating a long-term increase in volatility chaos. Orange when falling.
🌊 Morphism Flow (Flowing Lines with Circles):
What it represents: This visualizes the momentum and strength of the fastDEVMA. The width and intensity of the "beam" are proportional to the signal strength.
Interpretation: A thick, steep, and vibrant flow indicates powerful, committed momentum in the current volatility regime. The floating '●' particles represent kinetic energy; more particles suggest stronger underlying force.
📐 Homotopy Paths (Layered Transparent Boxes):
What it represents: These layered boxes are centered between the two DEVMA lines. Their height is determined by the DEV value.
Interpretation: This visualizes the overall "volatility of volatility." Wider boxes indicate a chaotic, unpredictable market. Narrower boxes suggest a more stable, predictable environment.
🧠 Consciousness Field (The Grid):
What it represents: This grid provides a historical lookback at the DEV range.
Interpretation: It maps the recent "consciousness" or character of the market's volatility. A consistently wide grid suggests a prolonged period of chaos, while a narrowing grid can signal a transition to a more stable state.
📏 Functorial Levels (Projected Horizontal Lines):
What it represents: These lines extend from the current fastDEVMA and slowDEVMA values into the future.
Interpretation: Think of these as dynamic support and resistance levels for the volatility structure itself. A crossover becomes more significant if it breaks cleanly through a prior established level.
🌊 Flow Boxes (Spaced Out Boxes):
What it represents: These are compact visual footprints of the current regime, colored green for Expansion and red for Contraction.
Interpretation: They provide a quick, at-a-glance confirmation of the dominant volatility flow, reinforcing the background color.
Background Color:
This provides an immediate, unmistakable indication of the current volatility regime. Light Green for Expansion and Light Aqua/Blue for Contraction, allowing you to assess the market environment in a split second.
📊 BACKTESTING PERFORMANCE REVIEW & ANALYSIS
The following is a factual, transparent review of a backtest conducted using the strategy's default settings on a specific instrument and timeframe. This information is presented for educational purposes to demonstrate how the strategy's mechanics performed over a historical period. It is crucial to understand that these results are historical, apply only to the specific conditions of this test, and are not a guarantee or promise of future performance. Market conditions are dynamic and constantly change.
Test Parameters & Conditions
To ensure the backtest reflects a degree of real-world conditions, the following parameters were used. The goal is to provide a transparent baseline, not an over-optimized or unrealistic scenario.
Instrument: CME E-mini Nasdaq 100 Futures (NQ1!)
Timeframe: 5-Minute Chart
Backtesting Range: March 24, 2024, to July 09, 2024
Initial Capital: $100,000
Commission: $0.62 per contract (A realistic cost for futures trading).
Slippage: 3 ticks per trade (A conservative setting to account for potential price discrepancies between order placement and execution).
Trade Size: 1 contract per trade.
Performance Overview (Historical Data)
The test period generated 465 total trades , providing a statistically significant sample size for analysis, which is well above the recommended minimum of 100 trades for a strategy evaluation.
Profit Factor: The historical Profit Factor was 2.663 . This metric represents the gross profit divided by the gross loss. In this test, it indicates that for every dollar lost, $2.663 was gained.
Percent Profitable: Across all 465 trades, the strategy had a historical win rate of 84.09% . While a high figure, this is a historical artifact of this specific data set and settings, and should not be the sole basis for future expectations.
Risk & Trade Characteristics
Beyond the headline numbers, the following metrics provide deeper insight into the strategy's historical behavior.
Sortino Ratio (Downside Risk): The Sortino Ratio was 6.828 . Unlike the Sharpe Ratio, this metric only measures the volatility of negative returns. A higher value, such as this one, suggests that during this test period, the strategy was highly efficient at managing downside volatility and large losing trades relative to the profits it generated.
Average Trade Duration: A critical characteristic to understand is the strategy's holding period. With an average of only 2 bars per trade , this configuration operates as a very short-term, or scalping-style, system. Winning trades averaged 2 bars, while losing trades averaged 4 bars. This indicates the strategy's logic is designed to capture quick, high-probability moves and exit rapidly, either at a profit target or a stop loss.
Conclusion and Final Disclaimer
This backtest demonstrates one specific application of the VoVix+ framework. It highlights the strategy's behavior as a short-term system that, in this historical test on NQ1!, exhibited a high win rate and effective management of downside risk. Users are strongly encouraged to conduct their own backtests on different instruments, timeframes, and date ranges to understand how the strategy adapts to varying market structures. Past performance is not indicative of future results, and all trading involves significant risk.
🔧 THE DEVELOPMENT PHILOSOPHY: FROM VOLATILITY TO CLARITY
The journey to create VoVix+ began with a simple question: "What drives major market moves?" The answer is often not a change in price direction, but a fundamental shift in market volatility. Standard indicators are reactive to price. We wanted to create a system that was predictive of market state. VoVix+ was designed to go one level deeper—to analyze the behavior, character, and momentum of volatility itself.
The challenge was twofold. First, to create a robust mathematical model to quantify these abstract concepts. This led to the multi-layered analysis of ATR differentials and standard deviations. Second, to make this complex data intuitive and actionable. This drove the creation of the "Visual Universe," where abstract mathematical values are translated into geometric shapes, flows, and fields. The adaptive system was intentionally kept simple and transparent, focusing on a single, impactful parameter (time-based exits) to provide performance feedback without becoming an inscrutable "black box." The result is a tool that is both profoundly deep in its analysis and remarkably clear in its presentation.
⚠️ RISK DISCLAIMER AND BEST PRACTICES
VoVix+ is an advanced analytical tool, not a guarantee of future profits. All financial markets carry inherent risk. The backtesting results shown by the strategy are historical and do not guarantee future performance. This strategy incorporates realistic commission and slippage settings by default, but market conditions can vary. Always practice sound risk management, use position sizes appropriate for your account equity, and never risk more than you can afford to lose. It is recommended to use this strategy as part of a comprehensive trading plan. This was developed specifically for Futures
"The prevailing wisdom is that markets are always right. I take the opposite view. I assume that markets are always wrong. Even if my assumption is occasionally wrong, I use it as a working hypothesis."
— George Soros
— Dskyz, Trade with insight. Trade with anticipation.
