P T Supertrend CustomPT Supertrend Custom Indicator Description
The PT Supertrend Custom indicator is a dual Supertrend-based tool designed to help traders identify market trends and potential reversals with enhanced accuracy. This custom indicator plots two Supertrend lines with different ATR (Average True Range) lengths and multipliers, providing a broader perspective on price movements across varying market conditions.
Key Features:
1. Dual Supertrend Lines:
- The indicator calculates two separate Supertrend values using customizable ATR lengths (default: 7 and 21) and factors (default: 3.0 for both).
- This dual-layered approach helps identify both short-term and long-term trends for better decision-making.
2. Customizable Parameters:
- ATR Length (ATR Length & ATR Length2): Determines the lookback period for volatility calculation.
- Factor (Factor & Factor2): Defines the multiplier for the ATR, controlling the sensitivity of the Supertrend lines.
3. Visual Trend Representation:
- Green and red line plots represent uptrends and downtrends, respectively.
- The indicator overlays on the price chart, offering a clear visual representation of trend direction.
- Trend fill areas provide additional clarity, with green shading for uptrends and red shading for downtrends.
4. Dynamic Trend Shifts:
- The indicator adapts dynamically based on price action, switching from an uptrend to a downtrend and vice versa when conditions change.
- Two independent trend signals allow traders to compare short-term and long-term trend confirmations.
5. Overlay on Price Chart:
- The indicator is plotted directly on the price chart for easy visualization without cluttering the workspace.
How to Use:
- Trend Identification:
- A green Supertrend line below price indicates an uptrend.
- A red Supertrend line above price signals a downtrend.
- When both Supertrends align, it indicates a strong trend; divergence may signal potential reversals.
- Entry & Exit Signals:
- Consider long positions when both Supertrend lines turn green.
- Consider short positions when both Supertrend lines turn red.
- Use the shorter ATR period for quicker entries and exits, while the longer ATR period provides confirmation.
- Risk Management:
- The Supertrend lines can serve as dynamic support/resistance levels for placing stop-loss orders.
Best Used In:
- Trend-following strategies
- Swing trading and day trading
- Volatile markets where ATR-based signals are effective
This indicator provides a comprehensive view of market trends by combining short- and long-term trend filters, making it a valuable tool for traders seeking precision and clarity in their trading decisions.
Created by Prince Thomas
Volatilität
Uptrick: Zero Lag HMA Trend Suite1. Name and Purpose
Uptrick: Zero Lag HMA Trend Suite is a Pine Version 6 script that builds upon the Hull Moving Average (HMA) to offer an advanced trend analysis tool. Its purpose is to help traders identify trend direction, potential reversals, and overall market momentum with reduced lag compared to traditional moving averages. By combining the HMA with Average True Range (ATR) thresholds, slope-dependent coloring, Volume Weighted Average Price (VWAP) ribbons, and optional reversal signals, the script aims to give a detailed view of price activity in various market environments.
2. Overview
This script begins with the calculation of a Hull Moving Average, a method that blends Weighted Moving Averages in a way designed to cut down on lag while still smoothing out price fluctuations. Next, several enhancements are applied. The script compares current HMA values to previous ones for slope-based coloring, which highlights uptrends and downtrends at a glance. It also plots buy and sell signals when price moves beyond or below thresholds determined by the ATR and the user’s chosen signal multiplier. An optional VWAP ribbon can be shown to confirm bullish or bearish conditions relative to a volume-weighted benchmark. Additionally, the script can plot reversal signals (labeled with B) at points where price crosses back toward the HMA from above or below. Taken together, these elements allow traders to visualize both the short-term momentum and the broader context of how price interacts with volatility and overall market direction.
3. Why These Indicators Have Been Linked Together
The reason the Hull Moving Average, the Average True Range, and the VWAP have been integrated into one script is to tackle multiple facets of market analysis in a single tool. The Zero Lag Hull Moving Average provides a responsive trend line, the ATR offers a measure of volatility that helps distinguish significant price shifts from typical fluctuations, and the VWAP acts as a reference for fair value based on traded volume. By layering all three, the script helps traders avoid the need to juggle multiple separate indicators and offers a holistic perspective. The slope-based coloring focuses on trend direction, the ATR-based thresholds refine possible buy and sell zones, and the VWAP ribbons provide insight into how price stands relative to an important volume-weighted level. The inclusion of up and down signals and reversal B labels further refines entries and exits.
4. Why Use Uptrick: Zero Lag HMA Trend Suite
The Hull Moving Average is already known for reacting more quickly to price changes compared to other moving averages while retaining a degree of smoothness. This suite enhances the basic HMA by showing colored gradients that make it easy to spot trend direction changes, highlighting potential entry or exit points based on volatility-driven thresholds, and optionally layering a volume-based measure of bullish or bearish market sentiment. By relying on a zero lag approach and additional data points, the script caters to those wanting a more responsive method of identifying shifts in market dynamics. The added reversal signals and up or down alerts give traders extra confirmation for potential turning points.
5. How This Extension Improves on the Basic HMA
This extension not only plots the Hull Moving Average but also includes data-driven alerts and visual cues that traditional HMA lines do not provide. First, it offers multi-layered slope coloring, making up or down trends quickly apparent. Second, it uses ATR-based thresholds to pinpoint moments when price may be extending beyond normal volatility, thus generating buy or sell signals. Third, the script introduces an optional VWAP ribbon to indicate whether the market is trading above or below this pivotal volume-weighted benchmark, adding a further confirmation step for bullish or bearish conditions. Finally, it incorporates optional reversal signals labeled with B, indicating points where price might swing back toward the main HMA line.
6. Core Components
The script can be broken down into several primary functions and features.
a. Zero Lag HMA Calculation
Uses two Weighted Moving Averages (half-length and full-length) combined through a smoothing step based on the square root of the chosen length. This approach is designed to reduce lag significantly compared to other moving averages.
b. Slope Detection
Compares current and prior HMA values to determine if the trend is up or down. The slope-based coloring changes between turquoise shades for upward movement and magenta shades for downward movement, making trend direction immediately visible.
c. ATR-Based Thresholding for Up and Down Signals
The script calculates an Average True Range over a user-defined period, then multiplies it by a signal factor to form two bands around the HMA. When price crosses below the lower band, an up (buy) signal appears; when it crosses above the upper band, a down (sell) signal is shown.
d. Reversal Signals (B Labels)
Tracks when price transitions back toward the main HMA from an extreme zone. When enabled, these reversal points are labeled with a B and can help traders see potential turning points or mean-reversion setups.
e. VWAP Bands
An optional Volume Weighted Average Price ribbon that plots above or below the HMA, indicating bullish or bearish conditions relative to a volume-weighted price benchmark. This can also act as a kind of support/ resistance.
7. User Inputs
a. HMA Length
Controls how quickly the moving average responds to price changes. Shorter lengths react faster but can lead to more frequent signals, whereas longer lengths produce smoother lines.
b. Source
Specifies the price input, such as close or an alternative source, for the calculation. This can help align the HMA with specific trading strategies.
c. ATR Length and Signal Multiplier
Defines how the script calculates average volatility and sets thresholds for buy or sell alerts. Adjusting these values can help filter out noise or highlight more aggressive signals.
d. Slope Index
Determines how many bars to look back for detecting slope direction, influencing how sensitive the slope coloring is to small fluctuations.
e. Show Buy and Sell Signals, Reversal Signals, and VWAP
Lets users toggle the display of these features. Turning off certain elements can reduce chart clutter if traders prefer a simpler layout.
8. Calculation Process
The script’s calculation follows a step-by-step approach. It first computes two Weighted Moving Averages of the selected price source, one over half the specified length and one over the full length. It then combines these using 2*wma1 minus wma2 to reduce lag, followed by applying another weighted average using the square root of the length. Simultaneously, it computes the ATR for a user-defined period. By multiplying ATR by the signal multiplier, it establishes upper and lower bands around the HMA, where crossovers generate buy (up) or sell (down) signals. The script can also plot reversal signals (B labels) when price crosses back from these bands in the opposite direction. For the optional VWAP feature, Pine Script’s ta.vwap function is used, and differences between the HMA and VWAP levels determine the color and opacity of the ribbon.
9. Signal Generation and Filtering
The ATR-based thresholds reduce the influence of small, inconsequential price swings. When price falls below the lower band, the script issues an up (buy) signal. If price breaks above the upper band, a down (sell) signal appears. These signals are visible through labels placed near the bars. Reversal signals, labeled with B, can be turned on to help detect when price retraces from an extended area back toward the main HMA line. Traders can disable or enable these signals to match their preferred level of chart detail or risk tolerance.
10. Visualization on the Chart
The Zero HMA Lag Trend Suite aims for visual clarity. The HMA line is plotted multiple times with increasing transparency to create a gradient effect. Turquoise gradients indicate upward slopes, and magenta gradients signify downward slopes. Bar coloring can be configured to align with the slope direction, providing quick insight into current momentum. When enabled, buy or sell labels are placed under or above the bars as price crosses the ATR-defined boundaries. If the reversal option is active, B labels appear around areas where price changes direction. The optional VWAP ribbons form background bands, using distinct coloration to signal whether price is above or below the volume-weighted metric.
11. Market Adaptability
Because the script’s parameters (HMA length, ATR length, signal multiplier, and slope index) are user-configurable, it can adapt to a wide range of markets and timeframes. Intraday traders may prefer a shorter HMA length for quick signals, while swing or position traders might use a longer HMA length to filter out short-lived price changes. The source setting can also be adjusted, allowing for specialized data inputs beyond just close or open values.
12. Risk Management Considerations
The script’s signals and labels are based on past price data and volatility readings, and they do not guarantee profitable outcomes. Sharp market reversals or unforeseen fundamental events can produce false signals. Traders should combine this tool with broader risk management strategies, including stop-loss placement, position sizing, and independent market analyses. The Zero HMA Lag Trend Suite can help highlight potential opportunities, but it should not be relied upon as the sole basis for trade decisions.
13. Combining with Other Tools
Many traders choose to verify signals from the Zero HMA Lag Trend Suite using popular indicators like the Relative Strength Index (RSI), Moving Average Convergence Divergence (MACD), or even simple volume-based metrics to confirm whether a price movement has sufficient momentum. Conventional techniques such as support and resistance levels, chart patterns, or candlestick analysis can also supplement signals generated by the script’s up, down, or reversal B labels.
14. Parameter Customization and Examples
a. Short-Term Day Trading
Using a shorter HMA length (for instance, 9 or 14) and a slightly higher ATR multiplier might provide timely buy and sell signals, though it may also produce more whipsaws in choppy markets.
b. Swing or Position Trading
Selecting a longer HMA length (such as 50 or 100) with a moderate ATR multiplier can help users track more significant and sustained market moves, potentially reducing the effect of minor fluctuations.
c. Multiple Timeframe Blends
Some traders load two versions of the indicator on the same chart, one for short-term signals (with frequent B label reversals) and another for the broader trend direction, aligning entry and exit decisions with the bigger picture.
15. Realistic Expectations
Even though the Hull Moving Average helps minimize lag and the script incorporates volatility-based filters and optional VWAP overlays, it cannot predict future market behavior with complete accuracy. Periods of low liquidity or sudden market shocks can still lead to signals that do not reflect longer-term trends. Frequent parameter review and manual confirmation are advised before executing trades based solely on the script’s outputs.
16. Theoretical Background
The Hull Moving Average formula aims to balance smoothness with reactivity, accomplished by combining Weighted Moving Averages at varying lengths. By subtracting a slower average from a faster one and then applying another smoothing step with the square root of the original length, the HMA is designed to respond more promptly to price changes than typical exponential or simple moving averages. The ATR component, introduced by J. Welles Wilder, calculates the average range of price movement over a user-defined period, allowing the script to assess volatility and adapt signals accordingly. VWAP provides a volume-weighted benchmark that many institutional traders track to gauge fair intraday value.
17. Originality and Uniqueness
Although multiple HMA-based indicators can be found, Uptrick: Zero Lag HMA Trend Suite sets itself apart by merging slope-based coloring, ATR thresholds, VWAP ribbons, up or down labels, and optional reversal signals all in one cohesive platform. This synergy aims to reduce chart clutter while still giving traders a comprehensive look at trend direction, volatility, and volume-based sentiment.
18. Summary
Uptrick: Zero Lag HMA Trend Suite is a specialized trading script designed to highlight potential market trends and reversals with minimal delay. It leverages the Hull Moving Average for an adaptive yet smooth price line, pairs ATR-based thresholds for detecting possible breakouts or dips, and provides VWAP-based ribbons for added volume-weighted context. Traders can further refine their entries and exits by enabling up or down signals and reversal labels (B) where price may revert toward the HMA. Suitable for a wide range of timeframes and instrument types, the script encourages a disciplined approach to trade management and risk control.
19. Disclaimer
This script is provided for informational and educational purposes only. Trading and investing involve significant financial risk, and no indicator can guarantee success under all conditions. Users should practice robust risk management, including the placement of stop losses and position sizing, and should confirm signals with additional analysis tools. The developer of this script assumes no liability for any trading decisions or outcomes resulting from its use.
Price Oscillator Indicator (for Grid Stratagy)What is this?
This indicator represents the range that the price travels from its lowest to its highest point within a single candlestick. It is calculated as follows: (Highest Price - Lowest Price) / Closing Price * 100.
What is its purpose?
The indicator is specifically designed for grid trading, allowing traders to evaluate the arbitrage efficiency of conducting grid trading on a particular asset.
How to use this indicator?
Add it to your TradingView chart and switch the chart to a 1-minute timeframe. You can adjust the 'slow sma length' parameter to calculate the price oscillator for a specific period (the default value is 4320, which equals 3 days). The higher the amplitude of an asset, the more efficient it may be to apply a grid trading strategy on that asset.
Please note, this indicator is solely for assessing the price fluctuation range of assets and should not be taken as investment advice.
Currency ComparatorIndicator Description
This script helps you compare the price changes of various cryptocurrencies against each other.
While TradingView provides some pairs like ETH/BTC or BNB/BTC, it lacks support for comparing lower-market-cap coins against BTC or other currencies. That’s where this script comes in, allowing you to easily view ratios like DOGS/BTC, LSD/BTC, and more.
You can also analyze the relationship between two high-market-cap assets, such as ETH/SOL, which is often not available directly on TradingView.
Additionally, this indicator enables you to view the changes of two cryptocurrencies alongside a base currency. For example, you can observe how Bitcoin's rise impacts LSD and whether it strengthens or weakens relative to BTC.
Features
Maximized View: You can open the indicator in a maximized chart view and use it like any other chart for your technical analysis.
Customizable Comparisons: Compare any two assets with ease by configuring the indicator inputs.
Important Notes
1.Preserving Drawings:
Drawings and tools applied to the indicator chart are not tied to the indicator’s settings. This means changing the inputs won’t affect them. To avoid losing your work:
Open the chart of the base asset (e.g., LSD/USDT) where you want to analyze a specific pair (e.g., LSD/BTC).
Use the indicator there. This way, whenever you want to revisit your analysis, you only need to open the base chart (e.g., LSD/USDT) and update the indicator inputs to the desired pair (e.g., LSD/BTC).
2.Deleting the Indicator:
Removing the indicator from the chart will also delete all your drawings. If you need to keep them, do not delete the indicator.
3.Precision Settings:
By default, the indicator displays up to 12 decimal places (precision). For pairs where such precision isn’t required, you can adjust it in the settings under the "Style" section to your preferred value. If you need higher precision again, simply reset it to the default value.
Sunil BB Blast Heikin Ashi StrategySunil BB Blast Heikin Ashi Strategy
The Sunil BB Blast Heikin Ashi Strategy is a trend-following trading strategy that combines Bollinger Bands with Heikin-Ashi candles for precise market entries and exits. It aims to capitalize on price volatility while ensuring controlled risk through dynamic stop-loss and take-profit levels based on a user-defined Risk-to-Reward Ratio (RRR).
Key Features:
Trading Window:
The strategy operates within a user-defined time window (e.g., from 09:20 to 15:00) to align with market hours or other preferred trading sessions.
Trade Direction:
Users can select between Long Only, Short Only, or Long/Short trade directions, allowing flexibility depending on market conditions.
Bollinger Bands:
Bollinger Bands are used to identify potential breakout or breakdown zones. The strategy enters trades when price breaks through the upper or lower Bollinger Band, indicating a possible trend continuation.
Heikin-Ashi Candles:
Heikin-Ashi candles help smooth price action and filter out market noise. The strategy uses these candles to confirm trend direction and improve entry accuracy.
Risk Management (Risk-to-Reward Ratio):
The strategy automatically adjusts the take-profit (TP) level and stop-loss (SL) based on the selected Risk-to-Reward Ratio (RRR). This ensures that trades are risk-managed effectively.
Automated Alerts and Webhooks:
The strategy includes automated alerts for trade entries and exits. Users can set up JSON webhooks for external execution or trading automation.
Active Position Tracking:
The strategy tracks whether there is an active position (long or short) and only exits when price hits the pre-defined SL or TP levels.
Exit Conditions:
The strategy exits positions when either the take-profit (TP) or stop-loss (SL) levels are hit, ensuring risk management is adhered to.
Default Settings:
Trading Window:
09:20-15:00
This setting confines the strategy to the specified hours, ensuring trading only occurs during active market hours.
Strategy Direction:
Default: Long/Short
This allows for both long and short trades depending on market conditions. You can select "Long Only" or "Short Only" if you prefer to trade in one direction.
Bollinger Band Length (bbLength):
Default: 19
Length of the moving average used to calculate the Bollinger Bands.
Bollinger Band Multiplier (bbMultiplier):
Default: 2.0
Multiplier used to calculate the upper and lower bands. A higher multiplier increases the width of the bands, leading to fewer but more significant trades.
Take Profit Multiplier (tpMultiplier):
Default: 2.0
Multiplier used to determine the take-profit level based on the calculated stop-loss. This ensures that the profit target aligns with the selected Risk-to-Reward Ratio.
Risk-to-Reward Ratio (RRR):
Default: 1.0
The ratio used to calculate the take-profit relative to the stop-loss. A higher RRR means larger profit targets.
Trade Automation (JSON Webhooks):
Allows for integration with external systems for automated execution:
Long Entry JSON: Customizable entry condition for long positions.
Long Exit JSON: Customizable exit condition for long positions.
Short Entry JSON: Customizable entry condition for short positions.
Short Exit JSON: Customizable exit condition for short positions.
Entry Logic:
Long Entry:
The strategy enters a long position when:
The Heikin-Ashi candle shows a bullish trend (green close > open).
The price is above the upper Bollinger Band, signaling a breakout.
The previous candle also closed higher than it opened.
Short Entry:
The strategy enters a short position when:
The Heikin-Ashi candle shows a bearish trend (red close < open).
The price is below the lower Bollinger Band, signaling a breakdown.
The previous candle also closed lower than it opened.
Exit Logic:
Take-Profit (TP):
The take-profit level is calculated as a multiple of the distance between the entry price and the stop-loss level, determined by the selected Risk-to-Reward Ratio (RRR).
Stop-Loss (SL):
The stop-loss is placed at the opposite Bollinger Band level (lower for long positions, upper for short positions).
Exit Trigger:
The strategy exits a trade when either the take-profit or stop-loss level is hit.
Plotting and Visuals:
The Heikin-Ashi candles are displayed on the chart, with green candles for uptrends and red candles for downtrends.
Bollinger Bands (upper, lower, and basis) are plotted for visual reference.
Entry points for long and short trades are marked with green and red labels below and above bars, respectively.
Strategy Alerts:
Alerts are triggered when:
A long entry condition is met.
A short entry condition is met.
A trade exits (either via take-profit or stop-loss).
These alerts can be used to trigger notifications or webhook events for automated trading systems.
Notes:
The strategy is designed for use on intraday charts but can be applied to any timeframe.
It is highly customizable, allowing for tailored risk management and trading windows.
The Sunil BB Blast Heikin Ashi Strategy combines two powerful technical analysis tools (Bollinger Bands and Heikin-Ashi candles) with strong risk management, making it suitable for both beginners and experienced traders.
Feebacks are welcome from the users.
Supertrend with Buy/Sell SignalsThis simple Supertrend with Buy/Sell Signals is a trend-following indicator that helps identify market direction and potential entry/exit points. It uses the Average True Range (ATR) to calculate a dynamic support and resistance line:
Buy Signal: A green "BUY" label appears when the price crosses above the Supertrend line, indicating a possible bullish trend.
Sell Signal: A red "SELL" label appears when the price crosses below the Supertrend line, signaling a potential bearish trend.
The indicator also adapts to market volatility and displays the trend line in green for uptrends and red for downtrends. It is best used in trending markets.
Cumulative Price AverageThe Cumulative Price Average (CPA) indicator calculates and plots the overall average of candlestick prices, providing a smoothed representation of the market's long-term price trend. This is achieved by aggregating the averages of each candle (Open, High, Low, Close) and dynamically updating the overall average as new candles are added.
Key Features
Long-Term Price Perspective: Displays the cumulative average of all candles from the start of the chart.
Trend Visualization: Smooths out short-term price fluctuations to highlight the overall trend.
Dynamic Updates: The average adjusts with each new bar for real-time analysis.
Usage
Trend Analysis:
Identify long-term bullish or bearish trends by observing the slope of the CPA line.
Support/Resistance:
The CPA line can act as a dynamic support or resistance level for the price.
Price Comparison:
Compare the current price to the CPA to assess whether the market is overbought or oversold relative to its historical average.
This indicator is especially useful for traders seeking to incorporate a historical perspective into their analysis, providing insights into the broader market behavior beyond short-term volatility.
Composite Indicator (CCI + ATR)Composite Indicator (CCI + ATR)
The Composite Indicator (CCI + ATR) combines the Commodity Channel Index (CCI) with the Average True Range (ATR) , providing traders with a dynamic tool for identifying entry and exit points based on momentum and volatility. This indicator is particularly useful for markets like cryptocurrencies, which often exhibit sharp sell-offs and gradual upward trends.
Key Features
Momentum Analysis with CCI: The CCI calculates price momentum by comparing the current price level to its average over a specific period. The indicator generates signals when CCI crosses predefined thresholds.
- Buy Signal: Triggered when CCI crosses above the lower threshold (e.g., -100).
- Sell Signal: Triggered when CCI crosses below the upper threshold (e.g., +100).
Volatility Filtering with ATR: The ATR measures market volatility, ensuring signals occur only during significant price movements.
Separate multipliers for buy and sell signals allow tailored filtering based on market behavior.
Stop Loss Calculation: Dynamic stop loss levels are calculated using the ATR multiplier to adapt to market volatility, offering better risk management.
How It Works
CCI Calculation: The CCI is calculated using the typical price ((High + Low + Close) / 3) and a user-defined length. It detects momentum changes by measuring deviations from the average price.
ATR Calculation: The ATR determines the average price range over a specified period, identifying the market’s volatility. The ATR SMA acts as a baseline to filter signals.
Buy Signal: A buy signal is triggered when:
- CCI crosses above the lower threshold (e.g., -100).
- ATR exceeds its SMA multiplied by the buy multiplier (e.g., 1.0).
Sell Signal: A sell signal is triggered when:
- CCI crosses below the upper threshold (e.g., +100).
- ATR exceeds its SMA multiplied by the sell multiplier (e.g., 0.95).
Stop Loss Integration:
- Long positions: Stop loss = Low – (ATR * ATR Multiplier)
- Short positions: Stop loss = High + (ATR * ATR Multiplier)
Advantages
Combines momentum (CCI) and volatility (ATR) for precise signal generation.
Customizable thresholds and multipliers for different market conditions.
Dynamic stop loss ensures better risk management in volatile markets.
Suggested Parameter Settings
CCI Length: 20 (default). Adjust as follows:
- 10–15: Shorter timeframes (e.g., 5-15 minutes).
- 20: General use for 1-hour timeframes.
- 30–50: Longer timeframes (e.g., 4-hour or daily charts).
CCI Threshold: 100 (default). Adjust as follows:
- 50–75: For more frequent signals in ranging markets.
- 100: Balanced for most trading conditions.
- 150–200: For strong trends to reduce noise.
ATR Length: 14 (default). Adjust as follows:
- 10–14: For assets with moderate volatility.
- 20: For assets with lower volatility.
ATR Buy Multiplier: 1.0 (default). Adjust as follows:
- 0.9–1.0: For gradual uptrends in crypto markets.
- 1.1–1.2: For stronger trend filtering.
ATR Sell Multiplier: 0.95 (default). Adjust as follows:
- 0.8–0.95: For sharp sell-offs.
- 1.0–1.1: For stable downward trends.
ATR Multiplier (Stop Loss): 1.5 (default). Adjust as follows:
- 1.0–1.2: For shorter timeframes or less volatile markets.
- 2.0–2.5: For highly volatile markets like cryptocurrencies.
Example Use Cases
Scalping (5-15 minute charts): Use CCI Length = 10, CCI Threshold = 75, ATR Buy Multiplier = 0.9, ATR Sell Multiplier = 0.8.
Day Trading (1-hour charts): Use CCI Length = 20, CCI Threshold = 100, ATR Buy Multiplier = 1.0, ATR Sell Multiplier = 0.95.
Swing Trading (4-hour or daily charts): Use CCI Length = 30, CCI Threshold = 150, ATR Buy Multiplier = 1.2, ATR Sell Multiplier = 1.0.
Final Thoughts The Composite Indicator (CCI + ATR) is a versatile tool designed to enhance trading decisions by combining momentum analysis with volatility filtering. Whether scalping or swing trading, this indicator provides actionable insights and robust risk management to navigate complex markets effectively.
Composite Indicator (Donchian + OBV)Composite Indicator (Donchian + OBV)
The Composite Indicator (Donchian + OBV) is a powerful tool designed to evaluate the strength of market breakouts and momentum trends , offering traders a comprehensive perspective on price action. This indicator combines the Donchian Channel with On-Balance Volume (OBV) to create a dynamic and easy-to-interpret metric scaled between -1 and 1 .
Key Features
Breakout Strength Analysis:
- The indicator assesses the strength of price breakouts relative to the upper and lower bounds of the Donchian Channel.
- Positive values close to 1 indicate a strong bullish breakout.
- Negative values close to -1 indicate a strong bearish breakout.
Momentum Detection with OBV:
- On-Balance Volume (OBV) tracks the cumulative buying and selling volume to gauge market momentum.
- The smoothed OBV trend ensures the momentum component aligns with price action, reducing noise.
Integrated Composite Value:
- Combines breakout strength and OBV momentum into a single metric for enhanced clarity.
- The final composite value highlights whether the market is bullish, bearish, or neutral.
Divergence Detection:
- Spot bullish divergences when the indicator rises while price falls, suggesting a potential upward reversal.
- Identify bearish divergences when the indicator falls while price rises, hinting at a potential downward reversal.
How It Works
Donchian Channel Analysis:
- Calculates the highest high and lowest low over a user-defined period to establish the upper and lower channels .
- Breakouts beyond these channels contribute to the breakout strength component.
OBV Momentum:
- Measures cumulative volume trends to validate price movements.
- Momentum is derived from the rate of change in smoothed OBV values.
Composite Calculation:
- Combines breakout strength and OBV momentum, normalized and scaled to -1 to 1 for clarity.
How to Use
Bullish Breakout:
- When the indicator value approaches 1 , it signals a strong upward breakout supported by positive OBV momentum.
- Example Action: Consider a Buy if price breaks the upper Donchian Channel with increasing OBV.
Bearish Breakout:
- When the indicator value approaches -1 , it indicates a strong downward breakout supported by negative OBV momentum.
- Example Action: Consider a Sell if price breaks the lower Donchian Channel with decreasing OBV.
Neutral Market:
- When the value is near 0 , the market is likely balanced with no significant breakout or momentum detected.
Divergence Opportunities:
- Bullish Divergence: Price makes lower lows, but the indicator trends upward → Potential upward reversal.
- Bearish Divergence: Price makes higher highs, but the indicator trends downward → Potential downward reversal.
Customization Options
Donchian Channel Length: Adjust the period for the upper and lower bounds.
OBV Smoothing Length: Modify the smoothing period for OBV to fine-tune momentum detection.
Scaling Adjustments: The composite value is automatically normalized for consistency across timeframes.
Ideal Use Cases
Breakout Trading: Identify and confirm strong breakouts in volatile markets.
Momentum Confirmation: Validate price movements with volume-based momentum.
Reversal Detection: Leverage divergences to spot potential market reversals.
Example Applications
Strong Bullish Signal:
- Price breaks the upper channel , and OBV shows increasing volume → Composite value near 1 .
- Action: Enter a Buy position and set a Stop Loss below the upper channel.
Strong Bearish Signal:
- Price breaks the lower channel , and OBV shows decreasing volume → Composite value near -1 .
- Action: Enter a Sell position and set a Stop Loss above the lower channel.
Neutral Market:
- Composite value near 0 suggests indecision or consolidation. Wait for a breakout.
Limitations
Best used alongside additional tools like RSI or MACD for filtering noise and improving decision-making.
Requires careful parameter tuning based on the asset and timeframe.
Final Thoughts
The Composite Indicator (Donchian + OBV) offers traders a versatile tool to navigate complex markets. By blending breakout analysis with volume-based momentum, this indicator provides an actionable edge for identifying high-probability opportunities and potential reversals.
RSI Volatility Suppression Zones [BigBeluga]RSI Volatility Suppression Zones is an advanced indicator that identifies periods of suppressed RSI volatility and visualizes these suppression zones on the main chart. It also highlights breakout dynamics, giving traders actionable insights into potential market momentum.
🔵 Key Features:
Detection of Suppression Zones:
Identifies periods where RSI volatility is suppressed and marks these zones on the main price chart.
Breakout Visualization:
When the price breaks above the suppression zone, the box turns aqua, and an upward label is drawn to indicate a bullish breakout.
If the price breaks below the zone, the box turns purple, and a downward label is drawn for a bearish breakout.
Breakouts accompanied by a "+" label represent strong moves caused by short-lived, tight zones, signaling significant momentum.
Wave Labels for Consolidation:
If the suppression zone remains unbroken, a "wave" label is displayed within the gray box, signifying continued price stability within the range.
Gradient Intensity Below RSI:
A gradient strip below the RSI line increases in intensity based on the duration of the suppressed RSI volatility period.
This visual aid helps traders gauge how extended the low volatility phase is.
🔵 Usage:
Identify Breakouts: Use color-coded boxes and labels to detect breakouts and their direction, confirming potential trend continuation or reversals.
Evaluate Market Momentum: Leverage "+" labels for strong breakout signals caused by short suppression phases, indicating significant market moves.
Monitor Price Consolidation: Observe gray boxes and wave labels to understand ongoing consolidation phases.
Analyze RSI Behavior: Utilize the gradient strip to measure the longevity of suppressed volatility phases and anticipate breakout potential.
RSI Volatility Suppression Zones provides a powerful visual representation of RSI volatility suppression, breakout signals, and price consolidation, making it a must-have tool for traders seeking to anticipate market movements effectively.
Volatility Footprint CandlesVolatility Footprint is an innovative volume profile indicator that dynamically adapts to real-time market conditions, providing traders with a powerful tool to visualize and interpret market structure, order flow, and potential areas of support and resistance.
At its core, Volatility Footprint combines the concepts of market profile, volume analysis, and volatility measurement to create a unique and adaptive charting experience. The indicator intelligently adjusts its display based on the current market volatility, ensuring that traders always have a clear and readable chart, regardless of the instrument or timeframe they are analyzing.
The footprint chart is composed of a series of color-coded boxes, each representing a specific price level. The color of the box indicates whether there is a net buying or selling pressure at that level, while the opacity reflects the relative strength of the volume. This intuitive visualization allows traders to quickly identify areas of high and low volume, as well as potential imbalances in order flow.
In addition to the individual box volumes, Volatility Footprint also calculates and displays the cumulative volume delta. This running total of buy and sell volumes across all price levels provides valuable insight into the overall market sentiment and potential trends.
One of the key features of Volatility Footprint is its ability to identify and highlight the Point of Control (POC). The POC represents the price level with the highest volume concentration and serves as a key reference point for potential support or resistance. By drawing attention to this crucial level, the indicator helps traders make more informed decisions about potential entry and exit points.
Volatility Footprint is designed to be highly customizable, allowing traders to tailor the appearance of the footprint chart to their specific preferences. Users can easily modify the colors, opacity, and size of the boxes, labels, and POC marker to enhance readability and clarity.
The indicator's versatility makes it suitable for a wide range of trading styles and strategies. Whether you are a scalper looking for short-term opportunities or a swing trader aiming to identify potential trend reversals, Volatility Footprint can provide valuable insights into market dynamics.
By combining Volatility Footprint with other forms of analysis, such as price action, key levels, and technical indicators, traders can gain a more comprehensive understanding of market behavior and make better-informed trading decisions.
Volatility Footprint's adaptive approach to volume profile analysis sets it apart from traditional fixed-resolution volume profile indicators. By dynamically adjusting to the unique characteristics of each instrument and timeframe, the indicator ensures that traders always have a clear and meaningful representation of market structure and order flow.
Volatility Footprint is a powerful tool that traders can incorporate into their market analysis and decision-making process. By providing a dynamic, visual representation of volume and order flow at different price levels, this indicator offers valuable insights into market structure, sentiment, and potential areas of support and resistance. Let's explore how traders might effectively utilize Volatility Footprint in their trading approach.
1. Identifying Key Levels:
One of the primary uses of Volatility Footprint is to identify key price levels where significant trading activity has occurred. The color-coded boxes allow traders to quickly spot areas of high volume concentration, which may indicate potential support or resistance zones. For example, if a trader notices a cluster of boxes with high opacity at a specific price level, they may interpret this as a strong support or resistance area, depending on the prevailing market context. By paying attention to these key levels, traders can make more informed decisions about potential entry and exit points, as well as placement of stop-loss orders and profit targets.
2. Assessing Market Sentiment:
The cumulative volume delta feature of Volatility Footprint provides traders with a valuable gauge of overall market sentiment. By analyzing the running total of buy and sell volumes across all price levels, traders can gain insight into the dominant market forces at play. If the cumulative delta is significantly positive, it may suggest a bullish sentiment, as buying pressure has been consistently outpacing selling pressure. Conversely, a negative cumulative delta may indicate a bearish sentiment. Traders can use this information to confirm or question their bias and adjust their trading plan accordingly.
3. Confirming Breakouts and Trend Reversals:
Volatility Footprint can be particularly useful in confirming the strength and validity of breakouts and potential trend reversals. When a price level is breached, traders can refer to the footprint chart to assess the volume and order flow characteristics around that level. If the breakout is accompanied by a surge in volume and a clear imbalance between buying and selling pressure, it may suggest a strong and sustainable move. On the other hand, if the volume is relatively low or evenly distributed, the breakout may be less reliable. By using Volatility Footprint to confirm breakouts, traders can make more informed decisions about whether to enter or exit a trade, or to adjust their position size.
4. Detecting Imbalances and Potential Reversals:
Imbalances between buying and selling pressure at specific price levels can often precede significant market moves or reversals. Volatility Footprint makes it easy for traders to spot these imbalances visually. For instance, if a trader observes a price level with a significantly larger number of sell boxes compared to buy boxes, it may indicate a potential exhaustion point for a bullish trend, and a reversal might be imminent. Traders can use this information in conjunction with other technical analysis tools, such as trendlines, moving averages, or momentum oscillators, to identify high-probability trading opportunities.
5. Adapting to Market Conditions:
One of the key strengths of Volatility Footprint is its ability to dynamically adapt to the unique volatility characteristics of different instruments and timeframes. This adaptability ensures that the indicator remains relevant and informative across a wide range of market conditions. Traders can use Volatility Footprint to gauge the relative volatility and volume of a particular instrument or timeframe, and adjust their trading approach accordingly. For example, in a highly volatile market, traders may opt for wider stop-loss levels and smaller position sizes to account for the increased risk.
Incorporating Volatility Footprint into a trading strategy requires a combination of technical analysis, market understanding, and risk management. Traders should use this indicator as part of a comprehensive approach, combining it with other forms of analysis, such as price action, key levels, and technical indicators. By doing so, traders can gain a more complete picture of market dynamics and make better-informed trading decisions.
It's important to note that while Volatility Footprint provides valuable insights, it should not be relied upon as a standalone trading signal. Traders should always consider the broader market context, their risk tolerance, and their overall trading plan when making decisions based on the information provided by this indicator.
In conclusion, Volatility Footprint offers traders a dynamic and visually intuitive way to analyze market structure, volume, and order flow. By identifying key levels, assessing market sentiment, confirming breakouts, detecting imbalances, and adapting to market conditions, traders can leverage this powerful tool to make more informed and confident trading decisions. As with any technical analysis tool, Volatility Footprint should be used in conjunction with sound risk management principles and a well-defined trading strategy to maximize its effectiveness.
Mr. Filter Kalman - [by Oberlunar]The "Mr. Filter Kalman" is an advanced trading indicator designed for in-depth market analysis and decision-making by combining PID systems and Kalman filter.
The PID system is a feedback mechanism that adjusts outputs based on the error between the current price and its volatility. The proportional component reacts to the size of the current error, providing immediate feedback. The integral component accumulates past errors, addressing persistent trends or biases in price movements. The derivative component predicts future price changes by analyzing the rate of error change, offering a forward-looking dimension to the system. Together, these components smooth out noisy price data and identify meaningful trend shifts.
The Kalman filter adds a layer of sophistication by serving as a powerful noise reduction tool. It estimates the underlying trend of the price by dynamically adjusting its sensitivity to volume and price movements. By using a smoothing factor (𝛼), the filter calculates a weighted difference between the current price and its previous estimate, adapting to new data while minimizing the impact of short-term fluctuations. This ensures that the signals generated by the PID system are clear and reliable.
The integration of these two systems works synergistically. The PID system detects deviations and trend changes by analyzing historical and real-time data, while the Kalman filter ensures these signals are free from noise and distortions.
How it works
When the smoothed PID signal crosses below the Kalman filter, it reflects a shift in market dynamics where recent price deviations are indicating potential bearish momentum. The PID signal, being highly responsive to changes in price through its proportional, integral, and derivative components, captures the immediate transition towards selling pressure. Meanwhile, the Kalman filter, with its noise reduction capabilities, represents the smoothed and lagging trend of the market. This lag allows the Kalman filter to act as a reference point, ensuring that the short signal is not triggered by insignificant fluctuations or false movements.
Conversely, when the smoothed PID signal crosses above the Kalman filter, it indicates a strengthening of bullish momentum. The crossing suggests that price deviations are showing a consistent upward movement that outweighs the smoothed trend captured by the Kalman filter. In this case, the Kalman filter again acts as a stabilizing reference point, confirming that the upward movement is not merely transient noise but part of a larger trend.
PID System
The PID system (Proportional, Integral, Derivative) is used to create trading signals based on the difference (error) between the current price and its volatility:
Proportional (P) : Reacts to the current error.
Integral (I) : Accounts for accumulated past errors.
Derivative (D) : Predicts future changes based on the error's rate of change.
The output is a smoothed PID signal, which is ideal for detecting trends and reversals.
Kalman filter
The Kalman filter is a powerful tool to reduce market noise and provide clearer signals:
Smoothing Factor (α) : Adjusts the filter’s sensitivity.
Ideal for volatile markets and medium term strategies.
This feature combines signals from 10- and 15-minute charts, paired with a higher timeframe of 1D, to:
Confirm long-term trends.
Enhance the reliability of entry and exit signals.
Note: Due to this configuration, the indicator is best suited for intraday trading or, at most, weekly strategies . Avoid using timeframes larger than 15 minutes for the primary analysis to ensure optimal signal precision.
Customizable Parameters
Proportional Coefficient (kP): Controls sensitivity to current errors.
Integral Coefficient (kI): Adjusts the weight of accumulated errors.
Derivative Coefficient (kD): Enhances reactivity to error changes.
Lookback Period: Defines the period for moving average calculations.
Kalman Smoothing Factor (α): Determines the intensity of Kalman filtering.
Higher Timeframe: Specifies the timeframe for confirmation signals.
Important Notes
Originality: This script leverages advanced and innovative techniques to provide unique value to traders. It is entirely original, with no borrowed source code from other developers. The methods implemented are distinct and do not rely on basic approaches such as simple moving averages or similar conventional techniques.
Detailed Description: Every component is designed to improve signal reliability and simplify decision-making.
Publishing Guidelines: This guide adheres to TradingView’s rules for invite-only - closed-source scripts.
My long-term promise: The script will be updated following your suggestitions.
Relative Volume Index [PhenLabs]Relative Volume Index (RVI)
Version: PineScript™ v6
Description
The Relative Volume Index (RVI) is a sophisticated volume analysis indicator that compares real-time trading volume against historical averages for specific time periods. By analyzing volume patterns and statistical deviations, it helps traders identify unusual market activity and potential trading opportunities. The indicator uses dynamic color visualization and statistical overlays to provide clear, actionable volume analysis.
Components
• Volume Comparison: Real-time volume relative to historical averages
• Statistical Bands: Upper and lower deviation bands showing volume volatility
• Moving Average Line: Smoothed trend of relative volume
• Color Gradient Display: Visual representation of volume strength
• Statistics Dashboard: Real-time metrics and calculations
Usage Guidelines
Volume Strength Analysis:
• Values > 1.0 indicate above-average volume
• Values < 1.0 indicate below-average volume
• Watch for readings above the threshold (default 6.5x) for exceptional volume
Trading Signals:
• Strong volume confirms price moves
• Divergences between price and volume suggest potential reversals
• Use extreme readings as potential reversal signals
Optimal Settings:
• Start with default 15-bar lookback for general analysis
• Adjust threshold (6.5x) based on market volatility
• Use with multiple timeframes for confirmation
Best Practices:
• Combine with price action and other indicators
• Monitor deviation bands for volatility expansion
• Use the statistics panel for precise readings
• Pay attention to color gradients for quick assessment
Limitations
• Requires quality volume data for accurate calculations
• May produce false signals during pre/post market hours
• Historical comparisons may be skewed during unusual market conditions
• Best suited for liquid markets with consistent volume patterns
Note: For optimal results, use in conjunction with price action analysis and other technical indicators. The indicator performs best during regular market hours on liquid instruments.
Rosiz Support 1### Description of the Custom Indicator: MACD + CMF + MOM
This custom indicator combines three powerful technical analysis tools: **MACD (Moving Average Convergence Divergence)**, **CMF (Chaikin Money Flow)**, and **MOM (Momentum)**, to provide a comprehensive view of market trends, momentum, and money flow in a single pane. Here's what each component offers:
---
#### 1. **MACD (Moving Average Convergence Divergence)**
The **MACD** is a trend-following momentum indicator that shows the relationship between two moving averages of an asset’s price.
- **Purpose**: Identifies trend direction and momentum strength.
- **Key Components**:
- **MACD Line**: Difference between the fast and slow exponential moving averages (EMA).
- **Signal Line**: A smoothed moving average of the MACD line, acting as a trigger for buy/sell signals.
- **Histogram**: The difference between the MACD line and the signal line. Positive values indicate bullish momentum, while negative values indicate bearish momentum.
- **Usage**: Look for crossovers (MACD crossing the signal line) to identify potential trend changes.
---
#### 2. **CMF (Chaikin Money Flow)**
The **CMF** measures the volume-weighted average of accumulation and distribution over a specific period. It shows whether money is flowing into or out of an asset.
- **Purpose**: Detects buying or selling pressure based on price and volume.
- **Key Components**:
- **Positive CMF**: Indicates that the asset is being accumulated (buying pressure).
- **Negative CMF**: Indicates that the asset is being distributed (selling pressure).
- **Usage**: Values above 0 suggest bullish strength, while values below 0 suggest bearish strength.
---
#### 3. **MOM (Momentum)**
The **Momentum Indicator** measures the rate of change of an asset's price over a specified period. It helps traders identify the speed of price movements.
- **Purpose**: Highlights the strength and direction of price momentum.
- **Key Components**:
- **Momentum Line**: Positive values indicate upward momentum, while negative values indicate downward momentum.
- **Usage**: A rising momentum line suggests strengthening price trends, while a falling line indicates weakening trends.
---
### Benefits of Combining These Indicators:
1. **Trend Confirmation**: MACD provides a clear picture of trend direction and potential reversals.
2. **Volume-Based Insights**: CMF adds a layer of confirmation by analyzing money flow based on price and volume.
3. **Momentum Analysis**: MOM reveals the speed and strength of price movements, helping traders confirm breakouts or trend exhaustion.
4. **Enhanced Decision-Making**: The combination of these indicators allows traders to make more informed decisions by evaluating different aspects of market behavior in one pane.
---
### How to Use:
- **Identify Trends**: Use MACD to identify overall trend direction and reversals.
- **Confirm Momentum**: Check MOM to validate the strength of the trend.
- **Gauge Buying/Selling Pressure**: Refer to CMF to confirm whether the price movement is backed by accumulation or distribution.
- **Entry/Exit Points**: Look for MACD crossovers, CMF shifts above/below zero, and momentum changes to refine entry and exit strategies.
This powerful tool integrates the strengths of three indicators, making it ideal for traders looking to analyze market conditions holistically and improve their timing and accuracy.
ATR Combined IndicatorHow to Use and Adjust the ATR Stop-Loss & Risk Manager Indicator in TradingView
The ATR Stop-Loss & Risk Manager indicator is designed to help traders visualize Average True Range (ATR)-based stop-loss levels and assess risk. Here's a step-by-step guide on how to use it and adjust its settings.
Adding the Indicator to Your Chart
Open TradingView and select your desired chart and time frame.
Click on the Pine Editor at the bottom of the screen.
Paste the provided script into the editor and click Add to Chart.
Once added, the indicator will appear on your chart with ATR values, stop-loss levels, and a risk table.
Indicator Outputs
ATR Line: A line representing the Average True Range (ATR) value, providing a measure of market volatility.
Stop-Loss Levels:
Stop Loss High: A green line above the current price, representing the suggested stop-loss level for long positions.
Stop Loss Low: A red line below the current price, representing the suggested stop-loss level for short positions.
Risk Table:
Displays the ATR value multiplied by a user-defined risk multiplier in a table on the chart.
Configuring the Settings
To customize the indicator for your trading strategy, click the gear icon next to the indicator’s name in the Indicators pane.
1. ATR Settings
ATR Period: Adjust the number of bars used to calculate the ATR. Common values include 14 (default) or 20. Shorter periods respond faster to price changes, while longer periods smooth volatility.
Smoothing Method:
Choose between RMA, SMA, EMA, or WMA for the ATR calculation:
RMA (default): A variation of the moving average commonly used in ATR.
SMA: Simple Moving Average, giving equal weight to all bars in the calculation.
EMA: Exponential Moving Average, which gives more weight to recent bars.
WMA: Weighted Moving Average, emphasizing recent prices linearly.
2. Multipliers
ATR Multiplier for Table: Adjust this to scale the ATR value displayed in the table. For example:
Set it to 1.0 to display the exact ATR.
Increase or decrease it to align with your risk tolerance.
Stop Loss Multiplier: Adjust this to change how far the stop-loss levels are plotted from the current price. For example:
Use 1.5 (default) for moderate levels.
Increase for wider stops or decrease for tighter stops.
3. Table Customization
Table Position: Select where the table appears on the chart:
Top Right (default), Top Left, Bottom Right, Bottom Left, Middle Right, or Middle Left.
Border Color: Choose the border color for the table.
Background Color: Set the table's background color.
Text Color: Customize the table text color for better visibility.
4. Visualization
Stop-Loss High and Low Lines:
Use these lines to determine potential stop-loss levels for your trades based on the ATR and stop-loss multiplier.
Green for Stop Loss High (long positions).
Red for Stop Loss Low (short positions).
Practical Use Cases
Volatility-Based Stop Losses:
Use the stop-loss lines to set dynamic stop-loss levels based on market volatility.
Adjust the multipliers to match your trading style:
Tight stops for scalping or day trading.
Wider stops for swing or position trading.
Risk Assessment:
Use the ATR value in the table to gauge market volatility before entering trades.
Higher ATR values indicate more volatile markets, requiring wider stops.
Position Sizing:
Incorporate the ATR value into your position-sizing strategy. For example:
Divide your account risk (e.g., 1% of equity) by the ATR to calculate position size.
Monthly, Quarterly OPEX & Vix expirations
OPEX Indicator:
The OPEX indicator is designed to provide traders with a visual representation of key options expiration dates, particularly for monthly, quarterly, and VIX options expirations. This indicator can be particularly helpful for market participants who focus on options-based strategies or those who track the impact of options expiration on price action.
The indicator overlays vertical lines and labels on the chart to highlight three key types of expiration events:
Monthly Equity and Index Expiration (OPEX): This marks the standard monthly options expiration dates for equity and index options.
Quarterly Index Expiration (Q): This indicates the quarterly expiration dates for index options, which tend to have a larger impact on the market.
Monthly VIX Expiration (VIXEX): This marks the monthly expiration of VIX options and futures, which are important for volatility traders.
How to Use the OPEX Indicator:
Expiration Dates on the Chart: The OPEX indicator marks expiration dates with vertical lines and labels that appear on the chart. These are customizable, allowing you to adjust the line and label colors to suit your preferences. The lines and labels will appear at specific times, such as the closing of the market on expiration days, allowing traders to prepare for potential volatility or other market dynamics associated with these events.
Customizable Colors and Label Positions: The indicator offers flexibility in customizing the appearance of expiration lines and labels. For each expiration type (OPEX, Quarterly, and VIXEX), you can adjust the line color, label color, and label text color. Additionally, the label text size and position can be customized (e.g., above the bar, below the bar, top or bottom of the chart). This allows for a tailored display that suits your trading style and chart layout.
Visualizing Impact of Expiration Events: Traders who track the influence of expiration events can use this indicator to spot potential market moves around expiration dates. For example, significant price swings often occur near expiration days as options traders adjust their positions. With this indicator, you can visualize these dates on your chart and analyze market behavior in the lead-up to, during, and after the expirations.
Input Options:
Expiration Types:
Monthly Equity, Index Expiration (OPEX): Turn on or off the monthly equity expiration markers.
Quarterly Index Expiration (Q): Turn on or off the quarterly expiration markers.
Monthly VIX Expiration (VIXEX): Turn on or off the VIX expiration markers.
Line and Label Customization:
Line Color: Adjust the color of the vertical lines marking the expiration events.
Label Color: Customize the color of the expiration labels.
Label Text Color: Adjust the color of the text inside the labels.
Label Position: Choose the position of the labels (e.g., top, bottom, above bar, below bar).
Use Cases:
Options Traders: Track options expiration dates to assess potential price swings or liquidity changes.
Volatility Traders: Watch for patterns around VIX options expirations.
Index Traders: Monitor quarterly expirations for potential market-moving events.
Example Use:
As a trader, you can apply this indicator to your chart and observe how price action reacts near expiration dates. For instance, on the monthly OPEX expiration day, you might notice increased volatility or an uptick in options-related price moves. By observing this trend over time, you can align your trades to capitalize on predictable movements around key expiration days.
Additionally, you may use the quarterly expiration markers to assess whether there’s typically a market shift during these periods, providing insights for long-term traders.
This indicator can be a helpful tool for preparing and managing trades around critical options expiration dates, helping to forecast potential market behavior based on historical patterns.
TradingView Community Guidelines Compliance: This script complies with TradingView's community guidelines by offering a clear and valuable function for traders, providing customizable inputs for enhanced usability. The script is focused on chart visualizations without manipulating or misrepresenting market data. It serves as an educational tool and a functional indicator, with no claims or misleading functionality. The indicator does not promote financial products or services and focuses solely on charting for better trading decision-making.
RSI Toolkitᴛʜᴇ ʀꜱɪ ᴛᴏᴏʟᴋɪᴛ ɪɴᴅɪᴄᴀᴛᴏʀ ɪꜱ ᴀ ᴛʀᴀᴅɪɴɢ ᴛᴏᴏʟ ᴅᴇꜱɪɢɴᴇᴅ ᴛᴏ ᴩʀᴏᴠɪᴅᴇ ᴛʀᴀᴅᴇʀꜱ ᴡɪᴛʜ ᴅʏɴᴀᴍɪᴄ ɪɴꜱɪɢʜᴛꜱ ɪɴᴛᴏ ᴍᴀʀᴋᴇᴛ ᴄᴏɴᴅɪᴛɪᴏɴꜱ ᴜꜱɪɴɢ ᴛʜᴇ ʀᴇʟᴀᴛɪᴠᴇ ꜱᴛʀᴇɴɢᴛʜ ɪɴᴅᴇx (ʀꜱɪ) . ᴛʜᴇ ɪɴᴅɪᴄᴀᴛᴏʀ ɪɴᴛᴇɢʀᴀᴛᴇꜱ ᴍᴜʟᴛɪᴩʟᴇ ꜰᴇᴀᴛᴜʀᴇꜱ ᴀɴᴅ ᴇɴʜᴀɴᴄᴇᴍᴇɴᴛꜱ, ꜱᴜᴄʜ ᴀꜱ ᴍᴜʟᴛɪ-ᴛɪᴍᴇꜰʀᴀᴍᴇ ᴀɴᴀʟʏꜱɪꜱ, ᴀᴅᴠᴀɴᴄᴇᴅ ᴠɪꜱᴜᴀʟ ꜱᴛʏʟɪɴɢ ᴏᴩᴛɪᴏɴꜱ, ᴛʀᴀɪʟɪɴɢ ꜱᴛᴏᴩꜱ, ᴀɴᴅ ꜰᴏᴜʀ ᴅɪꜰꜰᴇʀᴇɴᴛ ꜱɪɢɴᴀʟ ɢᴇɴᴇʀᴀᴛɪᴏɴ ᴍᴏᴅᴇꜱ. ᴛʜɪꜱ ᴍᴀᴋᴇꜱ ɪᴛ ᴀɴ ɪᴅᴇᴀʟ ᴛᴏᴏʟ ꜰᴏʀ ᴛʀᴀᴅᴇʀꜱ ʟᴏᴏᴋɪɴɢ ᴛᴏ ɪᴅᴇɴᴛɪꜰʏ ᴏᴠᴇʀʙᴏᴜɢʜᴛ/ᴏᴠᴇʀꜱᴏʟᴅ ᴄᴏɴᴅɪᴛɪᴏɴꜱ, ʀᴇᴠᴇʀꜱᴀʟꜱ, ᴛʀᴇɴᴅ ᴄᴏɴᴛɪɴᴜᴀᴛɪᴏɴꜱ, ᴀɴᴅ ᴍᴏᴍᴇɴᴛᴜᴍ-ᴅʀɪᴠᴇɴ ᴏᴩᴩᴏʀᴛᴜɴɪᴛɪᴇꜱ.
---
ᴋᴇʏ ꜰᴇᴀᴛᴜʀᴇꜱ
1. ᴍᴜʟᴛɪ-ᴛɪᴍᴇꜰʀᴀᴍᴇ ʀꜱɪ
ᴛʜᴇ ʀꜱɪ ɪꜱ ᴄᴀʟᴄᴜʟᴀᴛᴇᴅ ʙᴀꜱᴇᴅ ᴏɴ ᴀ ᴜꜱᴇʀ-ᴅᴇꜰɪɴᴇᴅ ᴛɪᴍᴇꜰʀᴀᴍᴇ, ᴀʟʟᴏᴡɪɴɢ ꜰᴏʀ ᴄʀᴏꜱꜱ-ᴛɪᴍᴇꜰʀᴀᴍᴇ ᴀɴᴀʟʏꜱɪꜱ. ᴛʜɪꜱ ᴇɴꜱᴜʀᴇꜱ ᴛʜᴇ ɪɴᴅɪᴄᴀᴛᴏʀ ᴀʟɪɢɴꜱ ᴡɪᴛʜ ᴛʜᴇ ᴜꜱᴇʀ'ꜱ ᴛʀᴀᴅɪɴɢ ꜱᴛʀᴀᴛᴇɢʏ, ᴡʜᴇᴛʜᴇʀ ɪɴᴛʀᴀᴅᴀʏ ᴏʀ ʟᴏɴɢ-ᴛᴇʀᴍ.
2. ᴅʏɴᴀᴍɪᴄ ᴠɪꜱᴜᴀʟɪᴢᴀᴛɪᴏɴ ᴏᴩᴛɪᴏɴꜱ
ᴛʜᴇ ʀꜱɪ ᴛᴏᴏʟᴋɪᴛ ᴏꜰꜰᴇʀꜱ ᴀᴅᴠᴀɴᴄᴇᴅ ɢʀᴀᴅɪᴇɴᴛ-ʙᴀꜱᴇᴅ ʀꜱɪ ᴠɪꜱᴜᴀʟɪᴢᴀᴛɪᴏɴ ᴏᴩᴛɪᴏɴ ᴛᴏ ʜᴇʟᴩ ᴛʀᴀᴅᴇʀꜱ ꞯᴜɪᴄᴋʟʏ ᴀꜱꜱᴇꜱꜱ ᴍᴀʀᴋᴇᴛ ꜱᴇɴᴛɪᴍᴇɴᴛ:
ɴᴏɴᴇ : ʙᴀʀꜱ ᴀʀᴇ ɴᴏᴛ ᴄᴏʟᴏʀᴇᴅ.
ɢʀᴀᴅɪᴇɴᴛ : ʙᴀʀꜱ ᴀʀᴇ ᴄᴏʟᴏʀᴇᴅ ᴅʏɴᴀᴍɪᴄᴀʟʟʏ ʙᴀꜱᴇᴅ ᴏɴ ᴛʜᴇ ʀꜱɪ'ꜱ ᴩᴏꜱɪᴛɪᴏɴ ᴡɪᴛʜɪɴ ɪᴛꜱ ʀᴀɴɢᴇ.
3. ᴛʀᴀɪʟɪɴɢ ꜱᴛᴏᴩ
ᴀ ʙᴜɪʟᴛ-ɪɴ ᴛʀᴀɪʟɪɴɢ ꜱᴛᴏᴩ ꜰᴇᴀᴛᴜʀᴇ ᴅʏɴᴀᴍɪᴄᴀʟʟʏ ᴀᴅᴊᴜꜱᴛꜱ ꜱᴛᴏᴩ-ʟᴏꜱꜱ ʟᴇᴠᴇʟꜱ ʙᴀꜱᴇᴅ ᴏɴ ᴩʀɪᴄᴇ ᴍᴏᴠᴇᴍᴇɴᴛꜱ. ᴛʜɪꜱ ʜᴇʟᴩꜱ ᴩʀᴏᴛᴇᴄᴛ ᴩʀᴏꜰɪᴛꜱ ᴀɴᴅ ʀᴇᴅᴜᴄᴇ ʀɪꜱᴋ ꜰᴏʀ ᴀᴄᴛɪᴠᴇ ᴩᴏꜱɪᴛɪᴏɴꜱ.
4. ꜱɪɢɴᴀʟ ᴍᴏᴅᴇꜱ
ᴛʜᴇ ʀꜱɪ ᴛᴏᴏʟᴋɪᴛ ᴏꜰꜰᴇʀꜱ ꜰᴏᴜʀ ᴅɪꜱᴛɪɴᴄᴛ ꜱɪɢɴᴀʟ-ɢᴇɴᴇʀᴀᴛɪᴏɴ ᴍᴏᴅᴇꜱ ᴛᴏ ᴄᴀᴛᴇʀ ᴛᴏ ᴅɪꜰꜰᴇʀᴇɴᴛ ᴛʀᴀᴅɪɴɢ ꜱᴛʏʟᴇꜱ:
ʀᴇᴠᴇʀꜱᴀʟ : ɪᴅᴇɴᴛɪꜰɪᴇꜱ ᴋᴇʏ ʀᴇᴠᴇʀꜱᴀʟ ᴩᴏɪɴᴛꜱ ʙʏ ᴛʀᴀᴄᴋɪɴɢ ᴏᴠᴇʀʙᴏᴜɢʜᴛ/ᴏᴠᴇʀꜱᴏʟᴅ ᴄᴏɴᴅɪᴛɪᴏɴꜱ ᴀɴᴅ ᴩʟᴏᴛᴛɪɴɢ ꜱɪɢɴᴀʟꜱ ᴡʜᴇɴ ʀꜱɪ ᴛʀᴇɴᴅꜱ ʀᴇᴠᴇʀꜱᴇ.
ʜᴀʟꜰ-ʟɪꜰᴇ : ᴄᴀᴩᴛᴜʀᴇꜱ ᴏᴠᴇʀʙᴏᴜɢʜᴛ ᴏʀ ᴏᴠᴇʀꜱᴏʟᴅ ꜱᴛʀᴇᴀᴋꜱ (ᴇ.ɢ., ʟᴏɴɢ ʀꜱɪ ꜱᴛʀᴇᴀᴋꜱ) ᴀɴᴅ ɢᴇɴᴇʀᴀᴛᴇꜱ ᴍɪᴅ-ᴩᴏɪɴᴛ ᴛʀᴀᴅɪɴɢ ꜱɪɢɴᴀʟꜱ ʙᴀꜱᴇᴅ ᴏɴ ᴩʀɪᴄᴇ ᴄᴏɴꜱᴏʟɪᴅᴀᴛɪᴏɴꜱ.
ʙᴏᴜɴᴄᴇ : ɪᴅᴇɴᴛɪꜰɪᴇꜱ ʙᴏᴜɴᴄᴇ ᴏᴩᴩᴏʀᴛᴜɴɪᴛɪᴇꜱ ᴀꜰᴛᴇʀ ꜱᴜꜱᴛᴀɪɴᴇᴅ ʀꜱɪ ʟᴇᴠᴇʟꜱ (ᴇ.ɢ., ᴩʀɪᴄᴇ ʀᴇᴊᴇᴄᴛɪᴏɴꜱ ᴏʀ ɪɴᴠᴀʟɪᴅ ʙʀᴇᴀᴋᴏᴜᴛꜱ ᴀʀᴏᴜɴᴅ ᴏᴠᴇʀꜱᴏʟᴅ/ᴏᴠᴇʀʙᴏᴜɢʜᴛ ʟᴇᴠᴇʟꜱ).
ꜰᴏᴍᴏ : ᴅᴇᴛᴇᴄᴛꜱ ᴩʀᴏʟᴏɴɢᴇᴅ ᴏᴠᴇʀʙᴏᴜɢʜᴛ/ᴏᴠᴇʀꜱᴏʟᴅ ʀꜱɪ ʟᴇᴠᴇʟꜱ ᴀɴᴅ ʜɪɢʜʟɪɢʜᴛꜱ ʙʀᴇᴀᴋᴏᴜᴛ ᴛʀᴀᴅɪɴɢ ᴏᴩᴩᴏʀᴛᴜɴɪᴛɪᴇꜱ ᴅʀɪᴠᴇɴ ʙʏ ᴍᴏᴍᴇɴᴛᴜᴍ.
5. ᴀʟᴇʀᴛꜱ
ɪɴᴛᴇɢʀᴀᴛᴇᴅ ᴛʀᴀᴅɪɴɢᴠɪᴇᴡ ᴀʟᴇʀᴛꜱ ꜰᴏʀ ᴀʟʟ ꜱɪɢɴᴀʟ ᴛʏᴩᴇꜱ (ʀᴇᴠᴇʀꜱᴀʟ, ʜᴀʟꜰ-ʟɪꜰᴇ, ʙᴏᴜɴᴄᴇ, ꜰᴏᴍᴏ) ᴇɴꜱᴜʀᴇ ᴛʜᴀᴛ ᴜꜱᴇʀꜱ ɴᴇᴠᴇʀ ᴍɪꜱꜱ ᴀ ᴛʀᴀᴅɪɴɢ ᴏᴩᴩᴏʀᴛᴜɴɪᴛʏ. ᴀᴅᴅɪᴛɪᴏɴᴀʟ ᴀʟᴇʀᴛꜱ ᴀʀᴇ ᴀᴠᴀɪʟᴀʙʟᴇ ꜰᴏʀ ᴛʀᴀɪʟɪɴɢ ꜱᴛᴏᴩ ʟᴏꜱꜱᴇꜱ .
6. ʜɪɢʜʟʏ ᴄᴏɴꜰɪɢᴜʀᴀʙʟᴇ
ʀꜱɪ ᴩᴀʀᴀᴍᴇᴛᴇʀꜱ ꜱᴜᴄʜ ᴀꜱ ᴩᴇʀɪᴏᴅ , ᴏᴠᴇʀʙᴏᴜɢʜᴛ/ᴏᴠᴇʀꜱᴏʟᴅ ᴛʜʀᴇꜱʜᴏʟᴅꜱ , ᴀɴᴅ ᴛɪᴍᴇꜰʀᴀᴍᴇꜱ ᴄᴀɴ ʙᴇ ᴄᴜꜱᴛᴏᴍɪᴢᴇᴅ.
ꜱɪɢɴᴀʟ ʙᴇʜᴀᴠɪᴏʀ ᴀɴᴅ ᴛʀᴀɪʟɪɴɢ ꜱᴛᴏᴩ ꜱᴇɴꜱɪᴛɪᴠɪᴛʏ ᴀʀᴇ ꜰᴜʟʟʏ ᴀᴅᴊᴜꜱᴛᴀʙʟᴇ, ᴀʟʟᴏᴡɪɴɢ ᴛʀᴀᴅᴇʀꜱ ᴛᴏ ᴛᴀɪʟᴏʀ ᴛʜᴇ ɪɴᴅɪᴄᴀᴛᴏʀ ᴛᴏ ᴛʜᴇɪʀ ꜱᴩᴇᴄɪꜰɪᴄ ᴛʀᴀᴅɪɴɢ ꜱᴛʏʟᴇ.
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ɪɴᴩᴜᴛꜱ & ᴩᴀʀᴀᴍᴇᴛᴇʀꜱ
1. ɢᴇɴᴇʀᴀʟ ꜱᴇᴛᴛɪɴɢꜱ
ᴛɪᴍᴇ ꜰʀᴀᴍᴇ : ꜱᴇʟᴇᴄᴛ ᴀ ᴄᴜꜱᴛᴏᴍ ᴛɪᴍᴇꜰʀᴀᴍᴇ ᴛᴏ ᴄᴀʟᴄᴜʟᴀᴛᴇ ʀꜱɪ, ᴡʜɪᴄʜ ᴄᴀɴ ᴅɪꜰꜰᴇʀ ꜰʀᴏᴍ ᴛʜᴇ ᴄʜᴀʀᴛ’ꜱ ᴍᴀɪɴ ᴛɪᴍᴇꜰʀᴀᴍᴇ.
ᴄᴏʟᴏʀ ᴏᴩᴛɪᴏɴ : ᴄʜᴏᴏꜱᴇ ʜᴏᴡ ʙᴀʀꜱ ᴀʀᴇ ᴠɪꜱᴜᴀʟʟʏ ꜱᴛʏʟᴇᴅ:
- `ɴᴏɴᴇ`: ɴᴏ ꜱᴩᴇᴄɪᴀʟ ᴄᴏʟᴏʀɪɴɢ.
- `ɢʀᴀᴅɪᴇɴᴛ`: ʀꜱɪ-ʙᴀꜱᴇᴅ ɢʀᴀᴅɪᴇɴᴛ ᴄᴏʟᴏʀɪɴɢ ꜰᴏʀ ᴛʀᴇɴᴅ ꜱᴛʀᴇɴɢᴛʜ ᴠɪꜱᴜᴀʟɪᴢᴀᴛɪᴏɴ.
2. ʀꜱɪ ꜱᴇᴛᴛɪɴɢꜱ
ᴩᴇʀɪᴏᴅ : ᴅᴇꜰᴀᴜʟᴛ ʀꜱɪ ᴄᴀʟᴄᴜʟᴀᴛɪᴏɴ ᴩᴇʀɪᴏᴅ (14 ʙʏ ᴅᴇꜰᴀᴜʟᴛ).
ᴏᴠᴇʀʙᴏᴜɢʜᴛ ʟᴇᴠᴇʟ : ʀꜱɪ ᴛʜʀᴇꜱʜᴏʟᴅ ꜰᴏʀ ᴏᴠᴇʀʙᴏᴜɢʜᴛ ᴄᴏɴᴅɪᴛɪᴏɴꜱ (ᴅᴇꜰᴀᴜʟᴛ: 70).
ᴏᴠᴇʀꜱᴏʟᴅ ʟᴇᴠᴇʟ : ʀꜱɪ ᴛʜʀᴇꜱʜᴏʟᴅ ꜰᴏʀ ᴏᴠᴇʀꜱᴏʟᴅ ᴄᴏɴᴅɪᴛɪᴏɴꜱ (ᴅᴇꜰᴀᴜʟᴛ: 30).
3. ᴛʀᴀɪʟɪɴɢ ꜱᴛᴏᴩ ꜱᴇᴛᴛɪɴɢꜱ
ᴇɴᴀʙʟᴇ ᴛʀᴀɪʟɪɴɢ ꜱᴛᴏᴩ : ᴛᴏɢɢʟᴇꜱ ᴛʜᴇ ᴛʀᴀɪʟɪɴɢ ꜱᴛᴏᴩ ꜰᴇᴀᴛᴜʀᴇ.
ᴩᴇʀᴄᴇɴᴛ : ᴅᴇꜰɪɴᴇꜱ ᴛʜᴇ ᴛʀᴀɪʟɪɴɢ ꜱᴛᴏᴩ ᴅɪꜱᴛᴀɴᴄᴇ ᴀꜱ ᴀ ᴩᴇʀᴄᴇɴᴛᴀɢᴇ ᴏꜰ ᴛʜᴇ ᴩʀɪᴄᴇ.
4. ꜱɪɢɴᴀʟ ᴏᴩᴛɪᴏɴꜱ
ᴄʜᴏᴏꜱᴇ ʙᴇᴛᴡᴇᴇɴ ᴛʜᴇ ꜰᴏᴜʀ ꜱɪɢɴᴀʟ-ɢᴇɴᴇʀᴀᴛɪᴏɴ ᴍᴏᴅᴇꜱ:
ʀᴇᴠᴇʀꜱᴀʟ : ɪᴅᴇɴᴛɪꜰɪᴇꜱ ʀᴇᴠᴇʀꜱᴀʟ ᴏᴩᴩᴏʀᴛᴜɴɪᴛɪᴇꜱ.
ʜᴀʟꜰ-ʟɪꜰᴇ : ᴛʀᴀᴄᴋꜱ ꜱᴛʀᴇᴀᴋꜱ ɪɴ ʀꜱɪ ᴀɴᴅ ʜɪɢʜʟɪɢʜᴛꜱ ᴍɪᴅ-ᴩᴏɪɴᴛ ʀᴇᴠᴇʀꜱᴀʟꜱ.
ʙᴏᴜɴᴄᴇ : ᴅᴇᴛᴇᴄᴛꜱ ʙᴏᴜɴᴄᴇꜱ ᴀꜰᴛᴇʀ ᴏᴠᴇʀꜱᴏʟᴅ/ᴏᴠᴇʀʙᴏᴜɢʜᴛ ꜱᴛʀᴇᴀᴋꜱ.
ꜰᴏᴍᴏ : ʜɪɢʜʟɪɢʜᴛꜱ ᴍᴏᴍᴇɴᴛᴜᴍ-ᴅʀɪᴠᴇɴ ʙʀᴇᴀᴋᴏᴜᴛ ᴏᴩᴩᴏʀᴛᴜɴɪᴛɪᴇꜱ.
5. ᴄᴏʟᴏʀ ᴄᴜꜱᴛᴏᴍɪᴢᴀᴛɪᴏɴ
ꜰᴜʟʟʏ ᴄᴜꜱᴛᴏᴍɪᴢᴀʙʟᴇ ʙᴀʀ ᴄᴏʟᴏʀꜱ ꜰᴏʀ ᴅɪꜰꜰᴇʀᴇɴᴛ ᴄᴏɴᴅɪᴛɪᴏɴꜱ (ᴇ.ɢ., ᴜᴩᴛʀᴇɴᴅ, ᴅᴏᴡɴᴛʀᴇɴᴅ, ᴏᴠᴇʀʙᴏᴜɢʜᴛ, ᴏᴠᴇʀꜱᴏʟᴅ)
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ʜᴏᴡ ɪᴛ ᴡᴏʀᴋꜱ
1. ʀꜱɪ ᴄᴀʟᴄᴜʟᴀᴛɪᴏɴ
ᴛʜᴇ ꜱᴄʀɪᴩᴛ ᴄᴀʟᴄᴜʟᴀᴛᴇꜱ ʀꜱɪ ᴜꜱɪɴɢ ᴛʜᴇ ᴛʀᴀᴅɪᴛɪᴏɴᴀʟ ꜰᴏʀᴍᴜʟᴀ ʙᴜᴛ ᴀʟʟᴏᴡꜱ ᴄᴜꜱᴛᴏᴍɪᴢᴀᴛɪᴏɴ ᴏꜰ ᴛʜᴇ ᴩᴇʀɪᴏᴅ ᴀɴᴅ ᴛɪᴍᴇꜰʀᴀᴍᴇ. ɪᴛ ᴀʟꜱᴏ ᴜꜱᴇꜱ ᴡᴇɪɢʜᴛᴇᴅ ᴍᴏᴠɪɴɢ ᴀᴠᴇʀᴀɢᴇꜱ ᴛᴏ ʀᴇᴅᴜᴄᴇ ʟᴀɢ, ᴩʀᴏᴅᴜᴄɪɴɢ ᴀ ꜱᴍᴏᴏᴛʜᴇʀ ʀꜱɪ.
2. ᴅʏɴᴀᴍɪᴄ ʙᴀʀ ᴄᴏʟᴏʀɪɴɢ
ʙᴀʀꜱ ᴀʀᴇ ᴄᴏʟᴏʀᴇᴅ ᴅʏɴᴀᴍɪᴄᴀʟʟʏ ʙᴀꜱᴇᴅ ᴏɴ ᴛʜᴇ ʀꜱɪ’ꜱ ᴠᴀʟᴜᴇ, ᴡɪᴛʜ ɢʀᴀᴅɪᴇɴᴛ ᴄᴏʟᴏʀɪɴɢ ᴛʀᴀɴꜱɪᴛɪᴏɴɪɴɢ ʙᴇᴛᴡᴇᴇɴ ᴜꜱᴇʀ-ꜱᴩᴇᴄɪꜰɪᴇᴅ ᴄᴏʟᴏʀꜱ.
3. ꜱɪɢɴᴀʟ ɢᴇɴᴇʀᴀᴛɪᴏɴ
ᴇᴀᴄʜ ᴍᴏᴅᴇ ʜᴀꜱ ɪᴛꜱ ᴏᴡɴ ʟᴏɢɪᴄ ꜰᴏʀ ɪᴅᴇɴᴛɪꜰʏɪɴɢ ᴛʀᴀᴅɪɴɢ ᴏᴩᴩᴏʀᴛᴜɴɪᴛɪᴇꜱ:
ᴀ. ʀᴇᴠᴇʀꜱᴀʟ ᴍᴏᴅᴇ
- ᴍᴏɴɪᴛᴏʀꜱ ᴡʜᴇɴ ʀꜱɪ ᴄʀᴏꜱꜱᴇꜱ ᴏᴠᴇʀʙᴏᴜɢʜᴛ ᴏʀ ᴏᴠᴇʀꜱᴏʟᴅ ʟᴇᴠᴇʟꜱ ᴀɴᴅ ʀᴇᴠᴇʀꜱᴇꜱ ᴅɪʀᴇᴄᴛɪᴏɴ. ɪᴛ ᴩʟᴏᴛꜱ ᴅᴀꜱʜᴇᴅ ʟɪɴᴇꜱ ꜰᴏʀ ᴩᴏᴛᴇɴᴛɪᴀʟ ʀᴇᴠᴇʀꜱᴀʟ ᴩᴏɪɴᴛꜱ ᴀɴᴅ ꜱɪɢɴᴀʟꜱ ᴡɪᴛʜ ʟᴀʙᴇʟꜱ.
ʙ. ʜᴀʟꜰ-ʟɪꜰᴇ ᴍᴏᴅᴇ
- ᴛʀᴀᴄᴋꜱ ᴏᴠᴇʀʙᴏᴜɢʜᴛ ᴏʀ ᴏᴠᴇʀꜱᴏʟᴅ ꜱᴛʀᴇᴀᴋꜱ ᴏꜰ ᴄᴏɴᴛɪɴᴜᴏᴜꜱ ʙᴀʀꜱ. ɪᴛ ᴛʜᴇɴ ɪᴅᴇɴᴛɪꜰɪᴇꜱ ᴄᴏɴꜱᴏʟɪᴅᴀᴛɪᴏɴ ᴏᴩᴩᴏʀᴛᴜɴɪᴛɪᴇꜱ ᴀɴᴅ ᴩʟᴏᴛꜱ ᴅᴀꜱʜᴇᴅ ʟɪɴᴇꜱ ᴡɪᴛʜ ᴀʟᴇʀᴛꜱ.
ᴄ. ʙᴏᴜɴᴄᴇ ᴍᴏᴅᴇ
- ᴛʀᴀᴄᴋꜱ ʀꜱɪ ꜱᴛᴀʏɪɴɢ ʙᴇʟᴏᴡ ᴏᴠᴇʀꜱᴏʟᴅ (ᴏʀ ᴀʙᴏᴠᴇ ᴏᴠᴇʀʙᴏᴜɢʜᴛ) ꜰᴏʀ ᴩʀᴏʟᴏɴɢᴇᴅ ᴩᴇʀɪᴏᴅꜱ. ɪᴛ ɪᴅᴇɴᴛɪꜰɪᴇꜱ ʙᴏᴜɴᴄᴇ ᴏᴩᴩᴏʀᴛᴜɴɪᴛɪᴇꜱ ᴡʜᴇɴ ᴩʀɪᴄᴇ ʙʀᴇᴀᴋꜱ ᴏᴜᴛ ᴏꜰ ᴛʜᴇ ᴏᴠᴇʀꜱᴏʟᴅ/ᴏᴠᴇʀʙᴏᴜɢʜᴛ ᴄᴏɴᴅɪᴛɪᴏɴꜱ.
ᴅ. ꜰᴏᴍᴏ
- ᴅᴇᴛᴇᴄᴛꜱ ʀꜱɪ ꜱᴛʀᴇᴀᴋꜱ ᴏꜰ ʙᴀʀꜱ ɪɴ ᴇxᴛʀᴇᴍᴇ ᴢᴏɴᴇꜱ. ᴀ "ꜰᴏᴍᴏ" ꜱɪɢɴᴀʟ ɪꜱ ɢᴇɴᴇʀᴀᴛᴇᴅ ᴡʜᴇɴ ᴩʀɪᴄᴇ ʙʀᴇᴀᴋꜱ ᴩᴀꜱᴛ ᴋᴇʏ ʟᴇᴠᴇʟꜱ.
4. ᴛʀᴀɪʟɪɴɢ ꜱᴛᴏᴩ
- ᴡʜᴇɴ ᴇɴᴀʙʟᴇᴅ, ᴛʜᴇ ᴛʀᴀɪʟɪɴɢ ꜱᴛᴏᴩ ᴅʏɴᴀᴍɪᴄᴀʟʟʏ ᴀᴅᴊᴜꜱᴛꜱ ɪᴛꜱ ʟᴇᴠᴇʟ ʙᴀꜱᴇᴅ ᴏɴ ᴛʜᴇ ᴩᴇʀᴄᴇɴᴛᴀɢᴇ ɪɴᴩᴜᴛ. ᴀʟᴇʀᴛꜱ ᴀʀᴇ ɢᴇɴᴇʀᴀᴛᴇᴅ ᴡʜᴇɴ ᴛʜᴇ ꜱᴛᴏᴩ-ʟᴏꜱꜱ ʟᴇᴠᴇʟ ɪꜱ ʙʀᴇᴀᴄʜᴇᴅ.
5. ᴀʟᴇʀᴛꜱ
- ᴀʟᴇʀᴛꜱ ᴀʀᴇ ɪɴᴛᴇɢʀᴀᴛᴇᴅ ꜰᴏʀ ᴀʟʟ ꜱɪɢɴᴀʟ ᴛʏᴩᴇꜱ ᴀɴᴅ ᴛʀᴀɪʟɪɴɢ ꜱᴛᴏᴩ ᴇᴠᴇɴᴛꜱ. ᴜꜱᴇʀꜱ ᴄᴀɴ ᴄᴜꜱᴛᴏᴍɪᴢᴇ ᴀʟᴇʀᴛ ᴍᴇꜱꜱᴀɢᴇꜱ ᴏʀ ᴜꜱᴇ ᴛʜᴇ ᴩʀᴇᴄᴏɴꜰɪɢᴜʀᴇᴅ ᴏɴᴇꜱ.
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ᴠɪꜱᴜᴀʟ ᴇʟᴇᴍᴇɴᴛꜱ
ʀꜱɪ ᴩʟᴏᴛ
ᴛʜᴇ ᴍᴀɪɴ ʀꜱɪ ʟɪɴᴇ ɪꜱ ᴩʟᴏᴛᴛᴇᴅ ᴏɴ ᴛʜᴇ ᴄʜᴀʀᴛ ᴡɪᴛʜ ᴅʏɴᴀᴍɪᴄ ᴄᴏʟᴏʀɪɴɢ. ʜᴏʀɪᴢᴏɴᴛᴀʟ ʟɪɴᴇꜱ ᴅᴇɴᴏᴛᴇ ᴏᴠᴇʀʙᴏᴜɢʜᴛ ᴀɴᴅ ᴏᴠᴇʀꜱᴏʟᴅ ʟᴇᴠᴇʟꜱ.
ꜱɪɢɴᴀʟꜱ
ʀᴇᴠᴇʀꜱᴀʟ : ᴅᴀꜱʜᴇᴅ ʟɪɴᴇꜱ ᴀᴛ ʀᴇᴠᴇʀꜱᴀʟ ᴩᴏɪɴᴛꜱ. "ʙᴜʏ" ᴀɴᴅ "ꜱᴇʟʟ" ꜱɪɢɴᴀʟꜱ ᴀʀᴇ ᴩʟᴏᴛᴛᴇᴅ ᴡɪᴛʜ ᴀʀʀᴏᴡꜱ.
ʜᴀʟꜰ-ʟɪꜰᴇ : ʜɪɢʜʟɪɢʜᴛᴇᴅ ᴍɪᴅ-ᴩᴏɪɴᴛ ᴄᴏɴꜱᴏʟɪᴅᴀᴛɪᴏɴꜱ ᴡɪᴛʜ ᴅᴀꜱʜᴇᴅ ʟɪɴᴇꜱ.
ʙᴏᴜɴᴄᴇ : ᴏᴠᴇʀʙᴏᴜɢʜᴛ/ᴏᴠᴇʀꜱᴏʟᴅ ʟᴇᴠᴇʟꜱ ᴀʀᴇ ᴍᴀʀᴋᴇᴅ ᴡɪᴛʜ ᴇxᴛᴇɴᴅᴇᴅ ʟɪɴᴇꜱ, ᴀɴᴅ ꜱɪɢɴᴀʟꜱ ᴀʀᴇ ᴅɪꜱᴩʟᴀʏᴇᴅ ᴡɪᴛʜ ᴀʀʀᴏᴡꜱ.
ꜰᴏᴍᴏ : ʜᴏʀɪᴢᴏɴᴛᴀʟ ʟɪɴᴇꜱ ᴀʀᴇ ᴩʟᴏᴛᴛᴇᴅ ᴛᴏ ʀᴇᴩʀᴇꜱᴇɴᴛ ꜱᴛʀᴇᴀᴋ-ᴅʀɪᴠᴇɴ ʙʀᴇᴀᴋᴏᴜᴛ ʟᴇᴠᴇʟꜱ.
ᴛʀᴀɪʟɪɴɢ ꜱᴛᴏᴩ
ᴩʟᴏᴛꜱ ᴀ ᴛʀᴀɪʟɪɴɢ ꜱᴛᴏᴩ ʟɪɴᴇ ᴀʙᴏᴠᴇ ᴏʀ ʙᴇʟᴏᴡ ᴛʜᴇ ᴩʀɪᴄᴇ, ᴡʜɪᴄʜ ᴍᴏᴠᴇꜱ ᴅʏɴᴀᴍɪᴄᴀʟʟʏ ʙᴀꜱᴇᴅ ᴏɴ ᴛʜᴇ ᴛʀᴀɪʟɪɴɢ ꜱᴛᴏᴩ ᴩᴇʀᴄᴇɴᴛᴀɢᴇ.
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ᴀʟᴇʀᴛꜱ
ᴄᴜꜱᴛᴏᴍ ᴀʟᴇʀᴛꜱ ᴇɴꜱᴜʀᴇ ᴛʀᴀᴅᴇʀꜱ ꜱᴛᴀʏ ɪɴꜰᴏʀᴍᴇᴅ ɪɴ ʀᴇᴀʟ-ᴛɪᴍᴇ. ᴀʟᴇʀᴛꜱ ɪɴᴄʟᴜᴅᴇ:
1. ʀᴇᴠᴇʀꜱᴀʟ ꜱɪɢɴᴀʟꜱ
- ʙᴜʏ: "ʀᴇᴠᴇʀꜱᴀʟ: ʙᴜʏ ꜱɪɢɴᴀʟ ᴛʀɪɢɢᴇʀᴇᴅ"
- ꜱᴇʟʟ: "ʀᴇᴠᴇʀꜱᴀʟ: ꜱᴇʟʟ ꜱɪɢɴᴀʟ ᴛʀɪɢɢᴇʀᴇᴅ"
2. ʜᴀʟꜰ-ʟɪꜰᴇ ꜱɪɢɴᴀʟꜱ
- ʙᴜʏ: "ʜᴀʟꜰ-ʟɪꜰᴇ ʙᴜʏ ꜱɪɢɴᴀʟ ᴛʀɪɢɢᴇʀᴇᴅ"
- ꜱᴇʟʟ: "ʜᴀʟꜰ-ʟɪꜰᴇ ꜱᴇʟʟ ꜱɪɢɴᴀʟ ᴛʀɪɢɢᴇʀᴇᴅ"
3. ʙᴏᴜɴᴄᴇ ꜱɪɢɴᴀʟꜱ
- ʙᴜʏ: "ʙᴏᴜɴᴄᴇ: ʙᴜʏ ꜱɪɢɴᴀʟ ᴛʀɪɢɢᴇʀᴇᴅ"
- ꜱᴇʟʟ: "ʙᴏᴜɴᴄᴇ: ꜱᴇʟʟ ꜱɪɢɴᴀʟ ᴛʀɪɢɢᴇʀᴇᴅ"
4. ꜰᴏᴍᴏ ꜱɪɢɴᴀʟꜱ
- ʙᴜʏ: "ꜰᴏᴍᴏ: ʙᴜʏ ꜱɪɢɴᴀʟ ᴛʀɪɢɢᴇʀᴇᴅ"
- ꜱᴇʟʟ: "ꜰᴏᴍᴏ: ꜱᴇʟʟ ꜱɪɢɴᴀʟ ᴛʀɪɢɢᴇʀᴇᴅ"
5. ᴛʀᴀɪʟɪɴɢ ꜱᴛᴏᴩ
- ʟᴏɴɢ: "ᴛʀᴀɪʟɪɴɢ ꜱᴛᴏᴩ ʟᴏꜱꜱ ʜɪᴛ: ᴇxɪᴛ ʟᴏɴɢ ᴩᴏꜱɪᴛɪᴏɴ"
- ꜱʜᴏʀᴛ: "ᴛʀᴀɪʟɪɴɢ ꜱᴛᴏᴩ ʟᴏꜱꜱ ʜɪᴛ: ᴇxɪᴛ ꜱʜᴏʀᴛ ᴩᴏꜱɪᴛɪᴏɴ"
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ᴜꜱᴇ ᴄᴀꜱᴇꜱ
ᴛʜᴇ ʀꜱɪ ᴛᴏᴏʟᴋɪᴛ ɪꜱ ɪᴅᴇᴀʟ ꜰᴏʀ
ʀᴇᴠᴇʀꜱᴀʟ ᴛʀᴀᴅᴇʀꜱ : ꜱᴩᴏᴛᴛɪɴɢ ᴛᴜʀɴɪɴɢ ᴩᴏɪɴᴛꜱ ɪɴ ᴛʜᴇ ᴍᴀʀᴋᴇᴛ.
ᴛʀᴇɴᴅ ᴄᴏɴᴛɪɴᴜᴀᴛɪᴏɴ : ɪᴅᴇɴᴛɪꜰʏɪɴɢ ᴏᴩᴩᴏʀᴛᴜɴɪᴛɪᴇꜱ ᴀꜰᴛᴇʀ ꜱᴜꜱᴛᴀɪɴᴇᴅ ᴛʀᴇɴᴅꜱ.
ʙʀᴇᴀᴋᴏᴜᴛ ᴛʀᴀᴅᴇʀꜱ : ᴄᴀᴩᴛᴜʀɪɴɢ ᴍᴏᴍᴇɴᴛᴜᴍ-ʙᴀꜱᴇᴅ ᴍᴏᴠᴇꜱ.
ʀɪꜱᴋ ᴍᴀɴᴀɢᴇᴍᴇɴᴛ : ᴜᴛɪʟɪᴢ ɪɴɢ ᴛʀᴀɪʟɪɴɢ ꜱᴛᴏᴩꜱ ᴛᴏ ᴩʀᴏᴛᴇᴄᴛ ᴩʀᴏꜰɪᴛꜱ.
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ᴄᴏɴᴄʟᴜꜱɪᴏɴ
ᴛʜᴇ ʀꜱɪ ᴛᴏᴏʟᴋɪᴛ ɪꜱ ᴀ ʀᴏʙᴜꜱᴛ ᴀɴᴅ ᴄᴜꜱᴛᴏᴍɪᴢ ᴀʙʟᴇ ɪɴᴅɪᴄᴀᴛᴏʀ ᴅᴇꜱɪɢɴᴇᴅ ᴛᴏ ᴇɴʜᴀɴᴄᴇ ᴛʀᴀᴅɪɴɢ ᴅᴇᴄɪꜱɪᴏɴꜱ ʙʏ ᴩʀᴏᴠɪᴅɪɴɢ ᴀᴄᴛɪᴏɴᴀʙʟᴇ ɪɴꜱɪɢʜᴛꜱ ʙᴀꜱᴇᴅ ᴏɴ ʀꜱɪ ᴀɴᴅ ᴩʀɪᴄᴇ ᴅʏɴᴀᴍɪᴄꜱ. ᴡɪᴛʜ ɪᴛꜱ ᴍᴜʟᴛɪ-ꜱɪɢɴᴀʟ ᴍᴏᴅᴇꜱ, ᴅʏɴᴀᴍɪᴄ ᴠɪꜱᴜᴀʟꜱ, ᴀɴᴅ ʙᴜɪʟᴛ-ɪɴ ᴀʟᴇʀᴛꜱ, ᴛʜɪꜱ ɪɴᴅɪᴄᴀᴛᴏʀ ɪꜱ ꜱᴜɪᴛᴀʙʟᴇ ꜰᴏʀ ᴛʀᴀᴅᴇʀꜱ ᴀᴄʀᴏꜱꜱ ᴀʟʟ ᴇxᴩᴇʀɪᴇɴᴄᴇ ʟᴇᴠᴇʟꜱ. ᴡʜᴇᴛʜᴇʀ ʏᴏᴜ'ʀᴇ ᴛʀᴀᴅɪɴɢ ʀᴇᴠᴇʀꜱᴀʟꜱ, ʙʀᴇᴀᴋᴏᴜᴛꜱ, ᴏʀ ᴛʀᴇɴᴅ ᴄᴏɴᴛɪɴᴜᴀᴛɪᴏɴꜱ, ᴛʜᴇ ʀꜱɪ ᴛᴏᴏʟᴋɪᴛ ɪꜱ ᴀ ᴠᴀʟᴜᴀʙʟᴇ ᴀᴅᴅɪᴛɪᴏɴ ᴛᴏ ʏᴏᴜʀ ᴛʀᴀᴅɪɴɢ ᴀʀꜱᴇɴᴀʟ.
IU Trailing Stop Loss MethodsThe 'IU Trailing Stop Loss Methods' it's a risk management tool which allows users to apply 12 trailing stop-loss (SL) methods for risk management of their trades and gives live alerts when the trailing Stop loss has hit. Below is a detailed explanation of each input and the working of the Script.
Main Inputs:
- bar_time: Specifies the date from which the trade begins and entry price will be the open of the first candle.
- entry_type: Choose between 'Long' or 'Short' positions.
- trailing_method: Select the trailing stop-loss method. Options include ATR, Parabolic SAR, Supertrend, Point/Pip based, Percentage, EMA, Highest/Lowest, Standard Deviation, and multiple target-based methods.
- exit_after_close: If checked, exits the trade only after the candle closes.
Optional Inputs:
ATR Settings:
- atr_Length: Length for the ATR calculation.
- atr_factor: ATR multiplier for SL calculation.
Parabolic SAR Settings:
- start, increment, maximum: Parameters for the Parabolic SAR indicator.
Supertrend Settings:
- supertrend_Length, supertrend_factor: Length and factor for the Supertrend indicator.
Point/Pip Based:
- point_base: Set trailing SL in points/pips.
Percentage Based:
- percentage_base: Set SL as a percentage of entry price.
EMA Settings:
- ema_Length: Length for EMA calculation.
Standard Deviation Settings:
- std_Length, std_factor: Length and factor for standard deviation calculation.
Highest/Lowest Settings:
- highest_lowest_Length: Length for the highest/lowest SL calculation.
Target-Based Inputs:
- ATR, Point, Percentage, and Standard Deviation based target SL settings with customizable lengths and multipliers.
Entry Logic:
- Trades initiate based on the entry_type selected and the specified bar_time.
- If Long is selected, a long trade is initiated when the conditions match, and vice versa for Short.
Trailing Stop-Loss (SL) Methods Explained:
The strategy dynamically adjusts stop-loss based on the chosen method. Each method has its calculation logic:
- ATR: Stop-loss calculated using ATR multiplied by a user-defined factor.
- Parabolic SAR: Uses the Parabolic SAR indicator for trailing stop-loss.
- Supertrend: Utilizes the Supertrend indicator as the stop-loss line.
- Point/Pip Based: Fixed point-based stop-loss.
- Percentage Based: SL set as a percentage of entry price.
- EMA: SL based on the Exponential Moving Average.
- Highest/Lowest: Uses the highest high or lowest low over a specified period.
- Standard Deviation: SL calculated using standard deviation.
Exit Conditions:
- If exit_after_close is enabled, the position will only close after the candle confirms the stop-loss hit.
- If exit_after_close is disabled, the strategy will close the trade immediately when the SL is breached.
Visualization:
The script plots the chosen trailing stop-loss method on the chart for easy visualization.
Target-Based Trailing SL Logic:
- When a position is opened, the strategy calculates the initial stop-loss and progressively adjusts it as the price moves favorably.
- Each SL adjustment is stored in an array for accurate tracking and visualization.
Alerts and Labels:
- When the Entry or trailing stop loss is hit this scripts draws a label and give alert to the user that trailing stop has been hit for the trade.
Note - on the historical data The Script will show nothing if the entry and the exit has happened on the same candle, because we don't know what was hit first SL or TP (basically how the candle was formed on the lower timeframe).
Summary:
This script offers flexible trailing stop-loss options for traders who want dynamic risk management in their strategies. By offering multiple methods like ATR, SAR, Supertrend, and EMA, it caters to various trading styles and risk preferences.
Market Volatility Momentum + Trend Filter Pro @MaxMaserati# 📊 Market Volatility Momentum + Trend Filter Pro
## 🎯 Overview
An enhanced version of the Market Momentum Indicator, combining the power of momentum analysis with adaptive volatility bands and trend filtering. This professional tool helps traders identify market direction and potential momentum shifts with greater precision.
## 🔄 Core Momentum Components
### 📈 Momentum Line
- Calculated using the midpoint between highest and lowest prices over 14 periods
- Provides a clear reference for price direction
- Acts as a dynamic support/resistance level
### 📉 Momentum Signal
- Offset from the Momentum Line by 0.25 tick size
- Creates a precise visual guide for momentum shifts
- Standard increment compatible with most markets
## 💫 Enhanced Features
### 🌊 Trend Filter
- Dynamic color-coding system showing trend strength
- Customizable length and damping parameters
- Visual identification of neutral market conditions
### 📊 Volatility Bands
- Adaptive bands that expand and contract with market volatility
- Choice between short-term and long-term trend adaptation
- Provides additional confirmation of trend strength
## 📝 Trading Signals
### 📈 Bullish Momentum
- Both momentum lines below price
- Enhanced by trend filter color confirmation
- Supported by volatility band positioning
### 📉 Bearish Momentum
- Both momentum lines above price
- Confirmed by trend filter color signals
- Reinforced by volatility band context
### ⚖️ Consolidation
- Momentum lines within price range
- Neutral trend indication with deep blue area
- Potential breakout preparation phase
## ⚙️ Multi-Timeframe Analysis
- Dual timeframe capability for comprehensive market view
- Custom timeframe selection with current chart reference
- Real-time timeframe display in top-right corner
## 🎨 Visual Features
- Dynamic bar coloring system reflecting trend strength
- Clear trend visualization through color gradients
- Optional line smoothing for reduced noise
- Customizable color schemes
## 💡 Tips for Usage
1. Monitor the position of price relative to momentum lines
2. Use trend filter colors for confirmation
3. Watch for convergence with volatility bands
4. Pay attention to neutral market signals
5. Utilize multi-timeframe analysis for better context
## ⚠️ Important Notes
- Originally designed without smoothing (smoothing optional)
- Best used with multiple timeframe analysis
- Provides clearest signals in trending markets
- Works effectively across all tradable assets
Note: Past performance doesn't guarantee future results. Always practice proper risk management and develop your trading plan.
Uptrick: Oracle Metrics +
Introduction
Uptrick: Oracle Metrics + is a multi-dimensional trading indicator designed to consolidate various technical and risk-oriented signals into one accessible framework. It allows traders to observe market volatility, identify potential reversal points, and assess numerous performance metrics, all within a single interface.
Purpose
The main goal of this indicator is to simplify a broad array of market insights. It merges trend analysis, volatility indicators, on-chart signals, and risk-performance metrics to help traders quickly evaluate the state of a market and make more informed decisions.
Features
1. Cloud Visualization
A colored cloud overlays the chart, indicating market conditions. When the cloud narrows, it can signal upcoming breakout scenarios, as volatility compresses and price movement may accelerate. In contrast, when the cloud is wide, this could hint at an extended trend that might be nearing a pullback or retracement. Observing shifts between narrow and wide phases helps anticipate shifts in momentum.
This can be seen here:
Simple Cloud Overlay
You can also use the cloud like this: when it turns purple you sell when it turns aqua color you buy. These signals are not very accurate in ranging markets but therefore they are usually better on almost all timeframes and assets in trending markets. :
Bounces of cloud. The cloud can also be used as a type of support/resistance. In the example below you can see how the trend bounces off of the cloud. For example, you could add up to your position every time it touches the cloud and then you could fully exit when the cloud turns purple or the trend breaks below the cloud:
An example of a way you could use this indicator as a confirmation is here. In the image below, a fake signal is generated, you can eliminate this signal by waiting for the cloud to turn purple in order to have confirmation for a potential downward move:
2. Bar Coloring for Volatility and System States
Traders can choose between two bar-coloring methods:
• Volatility: Bars change color intensity based on the level of current volatility relative to a historical average. This helps in spotting abrupt changes in market behavior, where bars become more pronounced when volatility is higher. You can see the volatility information in the volatility table.
• System Score: Bars receive a color gradient determined by the indicator’s final overall score. This simplifies spotting bullish, bearish, or neutral phases without needing to inspect multiple metrics separately. The closer the final score is to zero the less the color difference between bullish and bearish is.
3. Reversion Signals and Potential Reversal Alerts
Two sets of on-chart markers help in spotting sudden shifts in momentum:
• Reversion Signals marked with the letter R: These signals combine RSI thresholds, stochastic crossovers, and EMA confirmation to identify potential reversals. RSI highlights overbought (above 70) or oversold (below 30) conditions, while stochastic crossovers confirm shifts in momentum. The EMA ensures signals align with the broader trend, reducing false positives in volatile markets. Together, these components provide a reliable way to spot potential market corrections or reversals.
• Potential Reversal Signals marked with small circles: These signals detect subtle shifts in momentum using a smoothed RSI (via TEMA) and changes in its slope. When the slope turns positive or negative near key levels, it highlights early-stage reversals. This approach helps traders identify timely entry or exit opportunities by capturing potential trend changes before they fully develop.
4. Main Metrics Table
A primary dashboard shows detailed performance measures and market analytics. Next to each value, there is a bullish or bearish arrow to hint at the current direction of that metric. The table includes the following:
• Sharpe Ratio: Offers a view of risk-adjusted returns, hinting at whether rewards outweigh the variability in price.
• Sortino Ratio: A variation of risk-adjusted return focusing more on downside risk.
• Treynor Ratio: Displays returns relative to systematic risk, referencing a user-provided beta.
• Information Ratio: Shows how the instrument is outperforming or underperforming a benchmark, scaled by tracking error.
• ROC: Rate of change in price over a specified period, reflecting momentum.
• MACD Histogram: The difference between fast and slow moving average convergence, illustrating momentum shifts.
• CMF: Chaikin Money Flow, evaluating buying or selling pressure by combining price and volume.
• Ulcer Index: A measure of drawdown intensity to gauge how severe downtrends or pullbacks have been.
• Amihud Ratio: Assesses illiquidity by comparing price impact to volume.
• Market Depth Ratio: Looks at price ranges relative to volume activity, indicating how deeply the market can absorb trades.
• S2F Ratio: Incorporates the asset’s circulating supply relative to its yearly production, sometimes referenced in markets with a defined issuance schedule.
• NVT Ratio: A network value to transactions ratio, typically applied to on-chain data.
• MVRV Ratio: Compares the asset’s market value with its realized value, highlighting overall valuation conditions.
• Autocorrelation: Shows how current price movement may be echoing previous price changes.
• Alpha: Measures excess return over what might be expected from a risk-free rate plus systematic market exposure.
• Skewness: Reveals the asymmetry of the return distribution.
• Kurtosis: Looks at whether returns have heavier or lighter tails than typical distributions.
• Max Drawdown: The largest peak-to-trough drop within a lookback window, a key measure of downside risk.
• Calmar Ratio: Evaluates returns in light of drawdowns, relating performance to the severity of pullbacks.
• Omega Ratio: Considers gains versus losses around a threshold return level to measure reward-to-risk balance.
• January Performance: A snapshot of how price behaves in January over a lookback, connected to the idea of seasonality.
• Bid-Ask Spread: Reflects the percentage difference between highest and lowest price in a period, hinting at market liquidity costs.
5. Final Score Table
After analyzing individual metrics, the indicator calculates an overall score that determines if the broader environment appears bullish, bearish, or neutral. This final score then influences optional color schemes across the chart, allowing traders to see at a glance how multiple data points combine into one stance. For those who prefer a visual “gauge,” an additional grid table can be enabled, where boxes fill with varying color intensities based on the current score. The score calculation is complex and uses a similar technique to TPI. It assigns values to each metric and then divides the score by the amount of metrics. The score is then visualized in the System Generation bar coloring option according to how intense the signal is.
Grids (visualization of how much more the score needs to be a full signal.):
6. Volatility Table
A separate table focuses on how current volatility compares with an average measure. When current volatility differs significantly from historical norms, the bars become more vividly colored. If volatility nears its average, the bars are more subdued. This helps traders know when to be cautious of sudden moves or to adapt their position sizing.
Indicator Inputs
Users can tailor numerous inputs to suit the nature of each instrument:
• Risk-Free Rate (annualized rate used for risk calculations)
• Benchmark Return (expected return of the market benchmark)
• Beta (measure of systematic risk, particularly for Treynor Ratio calculations)
• Lookback Period (window of time used for many rolling calculations)
• ROC Period (time span for the rate of change calculation)
• CMF Period (window for the Chaikin Money Flow measure)
• Ulcer Index Period (depth for the Ulcer Index reading)
• Amihud Illiquidity Period (period for measuring price impact relative to volume)
• Market Depth Ratio Period (time range for examining price breadth versus volume)
• Circulating Supply (used for the stock-to-flow calculation)
• Yearly Production (helps update the stock-to-flow ratio)
• Market Cap (overall value of the instrument, often used in ratio metrics)
• Transaction Volume (on-chain or traded volume data for NVT ratio)
• Realized Value (alternative valuation data, used in MVRV calculation)
• Threshold Return for Omega (sets a custom threshold above which returns are considered favorable)
• Bar Coloring Method (choose between volatility-based or final-score-based color themes)
• Table Text Size (adjust the display size of table entries)
• Additional parameters related to internal signals (like RSI lengths or smoothing settings) can be fine-tuned for different market behaviors. It is important to customize these fields according to the characteristics of the specific asset you are trading.
Important!
Adjust the inputs according to your current asset! The inputs under the 'Vital' section have to be adjusted so that the metrics function properly. If not well adjusted to your asset, your final score will be mixed up and System Bar coloring as well! These inputs include: Circulating Supply, Yearly Production, Market Cap, Transaction Volume, and Realized Value!
Originality and Uniqueness
Uptrick: Oracle Metrics + stands out by combining complex metrics, including calculations similar to the Trend Probability Indicator (TPI), to provide a deeper analysis of market conditions. The indicator offers multiple signals tailored to different trading scenarios, allowing users to filter and customize them manually through a variety of features. This flexibility, combined with its advanced risk and trend analysis tools, makes it a versatile solution for both momentum and long-term trading strategies.
Warnings
In some scenarios, overlapping numbers or markers may crowd the chart. A practical fix for any visual overlap is removing the indicator and then reapplying it, which generally resets the tables and color overlays.
Summary
Uptrick: Oracle Metrics + merges cloud-based analytics, bar-coloring for volatility or system state, reversion alerts, and a detailed metrics dashboard into one seamless interface. This synergy of short-term signals and long-term performance metrics aims to give traders a fuller perspective on risk, trend changes, and valuation. By tuning the inputs to each asset, traders can capture more relevant data, while the color-coded approach simplifies quick decision-making in a dynamic market environment.
Disclaimer
The Uptrick: Oracle Metrics + indicator is a tool designed to assist traders in analyzing market conditions and making informed decisions. It is not a guarantee of future performance or a substitute for independent financial advice. Trading involves significant risk, and past results do not guarantee future outcomes. Users are advised to conduct their own research, consider their financial situation, and consult with a licensed financial professional if necessary. Uptrick and its affiliates are not responsible for any financial losses incurred while using this indicator. Use at your own discretion and risk.
RSI + ADX + ATR 18-01-25Combining RSI (Relative Strength Index), ADX (Average Directional Index), and ATR (Average True Range) creates a synergistic approach to technical analysis. This powerful trio covers momentum, trend strength, and volatility, providing comprehensive insights into market conditions. Here's a deeper exploration of their combined results:
1. Momentum Assessment with RSI
Purpose: RSI measures the speed and magnitude of recent price changes to determine overbought or oversold levels.
Benefit in Combination:
When RSI indicates overbought (above 70) or oversold (below 30) levels, it signals a potential reversal or correction.
However, these signals can be false in strongly trending markets, which is why ADX is used alongside it.
2. Trend Strength Confirmation with ADX
Purpose: ADX confirms the presence and strength of a trend.
Benefit in Combination:
If RSI shows a potential reversal but ADX indicates a strong trend (above 25), the trend is likely to continue, and RSI signals may need to be approached with caution.
Conversely, if ADX is below 20 (weak trend), RSI signals are more likely to indicate genuine reversals, as the market lacks a strong directional push.
3. Volatility Analysis with ATR
Purpose: ATR evaluates the level of price volatility.
Benefit in Combination:
High ATR values indicate volatile conditions where prices can move significantly; this helps in setting wider stop-loss levels to avoid premature exits.
Low ATR values suggest quieter markets, where tighter stop-losses and profit targets are more suitable.
[LeonidasCrypto]Volume Force IndexVolume Force Index (VFI)
Overview
The Volume Force Index (VFI) is a technical indicator that measures the balance between buying and selling pressure in the market by analyzing volume patterns. It helps traders identify potential trend reversals and confirm trend strength.
What It Measures
Buying vs. selling volume pressure
Market momentum
Potential overbought/oversold conditions
Volume trend strength
How to Read the Indicator
Main Components:
Main Line (Green/Red)
Green: Buying pressure is dominant
Red: Selling pressure is dominant
The steeper the slope, the stronger the pressure
Signal Line (Yellow)
Fast EMA that helps identify trend changes
Acts as an early warning system for potential reversals
Dynamic Bands (Red/Green lines)
Adapt to market volatility
Help identify extreme conditions
Based on actual market volatility rather than fixed levels
Signals to Watch
Trend Direction:
Rising oscillator = Increasing buying pressure
Falling oscillator = Increasing selling pressure
Signal Line Crossovers:
Main line crosses above signal line = Potential bullish signal
Main line crosses below signal line = Potential bearish signal
Band Touches:
Touching upper band = Possible buying exhaustion
Touching lower band = Possible selling exhaustion
Color Changes:
Green to Red = Shift to selling pressure
Red to Green = Shift to buying pressure
Best Practices
When to Use:
Trend confirmation
Identifying potential reversals
Volume analysis
Market strength assessment
Tips:
Use in conjunction with price action
Look for divergences with price
More reliable on higher timeframes
Consider market context
Default Settings:
MA Period: 14 (volume calculation)
Smooth Length: 3 (noise reduction)
EMA Period: 4 (signal line)
Volatility Period: 20 (band calculation)
Volatility Multiplier: 1.5 (band width)
Best Markets to Apply
Any market with reliable volume data
Summary
The VFI is a powerful tool that combines volume analysis with trend identification. Its adaptive nature makes it suitable for various market conditions, but it should be used as part of a complete trading strategy, not in isolation.
Liquidity Trading Algorithm (LTA)
The Liquidity Trading Algorithm is an algorithm designed to provide trade signals based on
liquidity conditions in the market. The underlying algorithm is based on the Liquidity
Dependent Price Movement (LDPM) metric and the Liquidity Dependent Price Stability (LDPS)
algorithm.
Together, LDPM and LDPS demonstrate statistically significant forecasting capabilities for price-
action on equities, cryptocurrencies, and futures. LTA takes these liquidity measurements and
translates them into actionable insights by way of entering or exiting a position based
on the future outlooks, as measured by the current liquidity status.
The benefit of LTA is that it can incorporate these powerful liquidity measurements into
actionable insights with several features designed to help you tailor LTA's behavior and
measurements to your desired vantage point. These customizable features come by the way of determining LTA's assessment style, and additional monitoring systems for avoiding bear and bull traps, along with various other quality of life features, discussed in more detail below.
First, a few quick facts:
- LTA is compatible on a wide array of instruments, including Equities, Futures, Cryptocurrencies, and Forex.
- LTA is compatible on most intervals in so long as the data can be calculated appropriately,
(be sure to do a backtest on timescales less than 1-minue to ensure the data can be computed).
- LTA only measures liquidity at the end of the interval of the chart chosen, and does not respond to conditions during the candle interval, unless specified (such as with `Stops`).
- LTA is interval-dependent, this means it will measure and behave differently on different
intervals as the underlying algorithms are dependent on the interval chosen.
- LTA can utilize fractional share sizing for cryptocurrencies.
- LTA can be restricted to either bullish or bearish indications.
- Additional Monitoring Systems are available for additional risk mitigation.
In short, LTA is a widely applicable, unique algorithm designed to translate liquidity measurements into liquidity insights.
Before getting more into the details, here is a quick list of the main features and settings
available for customization:
- Backtesting Start Date: Manual selection of the start date for the algorithm during backtesting.
- Assessment Style: adjust how LDPM and LDPS measure and respond to changes in liquidity.
- Impose Wait: force LTA to wait before entering or exiting a position to ensure conditions have remained conducive.
- Trade Direction Allowance: Restrict LTA to only long or only short, if desired.
- Position Sizing Method: determine how LTA calculates position sizing.
- Fractional Share Sizing: allow LTA to calculate fractional share sizes for cryptocurrencies
- Max Size Limit: Impose a maximum size on LTA's positions.
- Initial Capital: Indicate how much capital LTA should stat with.
- Portfolio Allotment: Indicate to LTA how much (in percentages) of the available balance should be considered when calculating position size.
- Enact Additional Monitoring Systems: Indicate if LTA should impose additional safety criteria when monitoring liquidity.
- Configure Take Profit, Stop-Loss, Trailing Stop Loss
- Display Information tables on the current position, overall strategy performance, along
with a text output showing LTA's processes.
- Real-time text output and updates on LTA's inner workings.
Let's get into some more of the details.
LTA's Assessment Style
LTA's assessment style determines how LTA collects and responds to changing data. In traditional terms, this is akin to (but not quite exactly the same as) the sensitivity versus specificity spectrum, whereby on one end (the sensitive end), an algorithm responds to changes in data in a reactive manner (which tends to lower its specificity, or how often it is correct in its indications), and on the other end, the opposite one, the algorithm foresakes quick changes for longevity of outlook.
While this is in part true, it is not a full view of the underlying mechanisms that changing the assessment style augments. A better analogy would be that the sensitive end of the spectrum (`Aggressive`) is in a state such that the algorithm wants to changing its outlooks, and as such, with changes in data, the algorithm has to be convinced as to why that is not a good idea to change outlooks, whereas the the more specific states (`Conservative`, `Diamond`) must be convinced that their view is no longer valid and that it needs to be changed.
This means the `Aggressive` and the `Diamond` settings fundamentally differ not just in their
data collection, but also in the data processing such that the `Aggressive` decision tree has to
be convinced that the data is the same (as its defualt is that it has changed),
and the `Diamond` decision tree has to be convinced that the data is not the same, and as such, the outlook need changed.
From there, the algorithm cooks through the data and determines to what the outlook should be changed to, given the current state of liquidity.
`Balanced` lies in the middle of this balance, attempting to balance being open to new ideas while not removing the wisdom of the past, as it were.
On a scale of most `sensitive` to most `specific`, it is as follows: `Aggressive`, `Balanced`,
`Conservative`, `Diamond`.
Functionally, these different modes can help in different liquidity environments, as certain
environments are more conducive to an eager approach (such as found near `Aggressive`) or are more conducive to a more conservative approach, where sudden changes in liquidity are known to be short-lived and unremarkable (such as many previously identified bull or bear traps).
For instance, on low interval views, it can often-times be beneficial to keep the algorithm towards the `Sensitive` end, since on the lower-timeframes, the crosswinds can change quite dramatically; whereas on the longer intervals, it may be useful to maintain a more `Specific` algorithm (such as found near `Diamond` mode) setting since longer intervals typically lend themselves to longer time-horizons, which themselves typically lend themselves to "weathering the storm", as it were.
LTA's Assessment Style is also supported by the Additional Monitoring Systems which works
to add sensitivity without sacrificing specificity by enacting a separate monitoring system, as described below.
Additional Monitoring Systems
The Additional Monitoring System (AMS) attempts to add more context to any changes in liquidity conditions as measured, such that LTA as a whole will have an expanded view into any rapidly changing liquidity conditions before these changes manifest in the traditional data streams. The ideal is that this allows for early exits or early entrances to positions "a head of time".
The traditional use of this system is to indicate when liquidity is suggestive of the end of a particular run (be it a bear run or a bull run), so an early exit can be initiated (and thus,
downside averted) even before the data officially showcase such changes. In such cases (when AMS becomes activated), the algorithm will signal to exit any open positions, and will restrict the opening of any new positions.
When a position is exited because of AMS, it is denoted as an `Early Exit` and if a position is prevented from being entered, the text output will display `AM prevented entry...` to indicate that conditions are not meeting AMS' additional standards.
The algorithm will wait to make any actions while `AMS` is `active` and will only enter into a new position once `AMS` has been `deactivated` and overall liquidity conditions are appropriate.
Functionally, the benefits of AMS translate to:
- Toggeling AMS on will typically see a net reduction in overall profitability, but
- AMS will typically (almost always) reduce max drawdown,
an increases in max runup, and increase return-over-maxdrawdown, and
- AMS can provide benefit for equities that experience a lot of "traps" by navigating early
entrance and early exits.
So in short, AMS is way of adding an additional level of liquidity monitoring that attempts to
exit positions if conditions look to be deteriorating, and to enter conditions if they look to be
improving. The cost of this additional monitoring, however, is a greater number of trades indicated, and a lower overall profitability.
Impose Wait
Note: `Impose Wait` will not force Take Profit, Stop Loss, or Trailing Stop Loss to
wait.
LTA can be indicated to `wait` before entering or exiting a position if desired. This means that if conditions change, whereas without a `wait` imposed, the algorithm would immediately indicate this change via a signal to alter the strategy's position, with a `wait` imposed, the algorithm will `wait` the indicated number of bars, and then re-check conditions before proceeding.
If, while waiting, conditions change to a state that is no longer compatible with the "order-in-
waiting", then the order-in-waiting is removed, and the counts reset (i.e.: conditions must remain favorable to the intended positional change throughout the wait period).
Since LTA works at the end-of-intervals, there is an inherently "built-in" wait of 1 bar when
switching directly from long to short (i.e.: if a full switch is indicated, then it is indicated as
conditions change -> exit new position -> wait until -> check conditions ->
enter new position as indicated). Thus, to impose a wait of `1 bar` would be to effectively have a total of two candles' ends prior to the entrance of the new position).
There are two main styles of `Impose Wait` that you can utilize:
- `Wait` : this mode will cause LTA to `wait` when both entering and exiting a position (in so long as it is not an exit signaled via a Take Profit, Stop Loss or Trailing Stop Loss).
- `Exit-Wait` : This mode will >not< cause LTA to `wait` if conditions require the closing of a position, but will force LTA to wait before entering into a position.
Position:
In addition to the availability to restrict LTA to either a long-only or short-only strategy, LTA
also comprises additional flexibility when deciding on how it should navigate the markets with
regards to sizing. Notably, this flexibility benefits several aspects of LTA's existence, namely the ability to determine the `Sizing Method`, or if `Fractional Share Sizing` should be employed, and more, as discussed below.
Position Sizing Method
There are two main ways LTA can determine the size of a position. Either via the `Fixed-Share` choice, or the `Fixed-Percentage` choice.
- `Fixed-Share` will use the amount indicated in the `Max Sizing Limit` field as the position size, always.
Note: With `Fixed-Share` sizing, LTA will >not< check if the balance is sufficient
prior to signaling an entrance.
- `Fixed-Percentage` will use the percentage amount indicated in the `Portfolio Allotment` field as the percentage of available funds to use when calculating the position size. Additionally, with the `Fixed-Percentage` choice, you can set the `Max Sizing Limit` if desired, which will ensure that no position will be entered greater than the amount indicated in the field.
Fractional Share Sizing
If the underlying instrument supports it (typically only cryptocurrencies), share sizing can be
fractionalized. If this is done, the resulting positin size is rounded to `4 digits`. This means any
position with a size less than `0.00005` will be rounded to `0.0000`
Note: Ensure that the underlying instrument supports fractional share sizing prior
to initiating.
Max Sizing Limit
As discussed above, the `Max Sizing Limit` will determine:
- The position size for every position, if `Sizing Method : Fixed-Share` is utilized, or
- The maximum allowed size, regardless of available capital, if `Sizing Method : Fixed-Percentage` is utilized.
Note: There is an internal maximum of 100,000 units.
Initial Capital
Note: There are 2 `Initial Capital` settings; one in LTA's settings and one in the
`Properties` tab. Ensure these two are the same when doing backtesting.
The initial capital field will be used to determine the starting balanace of the strategy, and
is used to calculate the internal data reporting (the data tables).
Portfolio Allotment
You can specify how much of the total available balance should be used when calculating the share size. The default is 100%.
Stops
Note: Stops over-ride `AMS` and `Impose Wait`, and are not restricted to only the
end-of-candle and will occur instantaneously upon their activation. Neither `AMS` nor `Impose Wait` can over-ride a signal from a `Take-Profit`, `Stop-Loss`, or a `Trailing-Stop Loss`.
LTA enhouses three stops that can be configured, a `Take-Profit`, a `Stop-Loss` and a `Trailing-Stop Loss`. The configurations can be set in the settings in percent terms. These exit signals will always over-ride AMS or any other restrictions on position exit.
Their configuration is rather standard; set the percentages you want the signal to be sent at and so it will be done.
Some quick notes on the `Trailing-Stop Loss`:
- The activation percentage must be reached (in profits) prior to the `Traililng-Stop Loss`
from activating the downside protection. For example, if the `Activation Percentage` is 10%, then unless the position reaches (at any point) a 10% profit, then it will not signal any exits on the downside, should it occur.
- The downside price-point is continuously updated and is calculated from the maximum profit reached in the given position and the loss percentage placed in the appropriate field.
Data Tables and Data Output
LTA provides real-time data output through a variety of mechanisms:
- `Position Table`
The `Position Table` displays information about the current position, including:
> Position Duration : how long the position has been open for.
> Indicates if the side is Long or Short, depending on if it is long or short.
> Entry Price: the price the position was entered at.
> Current Price (% Dif): the current price of the underlying and the %-difference between the entry price and the current price.
> Max Profit ($/%): the maximum profit reached in $ and % terms.
> Current PnL ($/%) : the current PnL for the open position.
- `Performance Table`
The `Performance Table` displays information regarding the overall performance of the algorithm since its `Start Date`. These data include:
> Initial Equity ($): The initial equity the algorithm started with.
> Current Equity ($): The current total equity of the account (including open positions)
> Net Profits ($|%) : The overall net profit in $ and % terms.
> Long / Short Trade Counts: The respective trade counts for the positions entered.
> Total Closed Trades: The running sum of the number of trades closed.
> Profitability: The calculation of the number of profitable trades over the total number of
trades.
> Avg. Profit / Trade: The calculation of the average profit per trade in both $ and % terms.
> Avg. Loss / Trade: The calculation of the average loss per trade in both $ and % terms.
> Max Run-Up: The maximum run-up the algorithm has seen in both $ and % terms.
> Max Drawdown: The maximum draw-down the algorithm has seen in both $ and % terms.
> Return-Over-Max-Drawdown: the ratio of the maximum drawdown against the current net profits.
- `Text Output`
LTA will output, if desired, signals to the text output field every time it analysis or performs and action. These messages can include information such as:
"
08:00:00 >> AM Protocol activated ... exiting position ...
08:00:00 >> Exit Order Created for qty: 2, profit: 380 (4.34%)
...
09:30:00 >> Checking conditions ...
09:30:00 >> AM protocol prevented entry ... waiting ...
"
This way, you can keep an eye out on what is happening "under the hood", as it were.
LTA will produce a message at the end of its assessment at the end of each candle interval, as well as when a position is exited due to a `Stop` or due to `AMS` being activated.
Additionally, the `Text Output` includes a initial message, but for space-constraints, this
can be toggled off with the `Blank Text Output` option within LTA's configurations.
For additional information, please refer to the Author's Instructions below.
Volume profile [Signals] - By Leviathan [Mindyourbuisness]Market Sessions and Volume Profile with Sweep Signals - Based on Leviathan's Volume Profile
This indicator is an enhanced version of Leviathan's Volume Profile indicator, adding session-based value area analysis and sweep detection signals. It combines volume profile analysis with market structure concepts to identify potential reversal opportunities.
Features
- Session-based volume profiles (Daily, Weekly, Monthly, Quarterly, Yearly)
- Forex sessions support (Tokyo, London, New York)
- Value Area analysis with POC, VAH, and VAL levels
- Extended level visualization for the last completed session
- Sweep detection signals for key value area levels
Sweep Signals Explanation
The indicator detects two types of sweeps at VAH, VAL, and POC levels:
Bearish Sweeps (Red Triangle Down)
Conditions:
- Price makes a high above the level (VAH/VAL/POC)
- Closes below the level
- Closes below the previous candle's low
- Previous candle must be bullish
Trading Implication: Suggests a failed breakout and potential reversal to the downside. These sweeps often indicate stop-loss hunting above key levels followed by institutional selling.
Bullish Sweeps (Green Triangle Up)
Conditions:
- Price makes a low below the level (VAH/VAL/POC)
- Closes above the level
- Closes above the previous candle's high
- Previous candle must be bearish
Trading Implication: Suggests a failed breakdown and potential reversal to the upside. These sweeps often indicate stop-loss hunting below key levels followed by institutional buying.
Trading Guidelines
1. Use sweep signals in conjunction with the overall trend
2. Look for additional confirmation like:
- Volume surge during the sweep
- Price action patterns
- Support/resistance levels
3. Consider the session's volatility and time of day
4. More reliable signals often occur at VAH and VAL levels
5. POC sweeps might indicate stronger reversals due to their significance as fair value levels
Notes
- The indicator works best on higher timeframes (1H and above)
- Sweep signals are more reliable during active market hours
- Consider using multiple timeframe analysis for better confirmation
- Past performance is not indicative of future results
Credits: Original Volume Profile indicator by Leviathan
