3_SMA_Strategy_V-Singhal by ParthibIndicator Name: 3_SMA_Strategy_V-Singhal by Parthib
Description:
The 3_SMA_Strategy_V-Singhal by Parthib is a dynamic trend-following strategy that combines three key simple moving averages (SMA) — SMA 20, SMA 50, and SMA 200 — to generate buy and sell signals. This strategy uses these SMAs to capture and follow market trends, helping traders identify optimal entry (buy) and exit (sell) points. Additionally, the strategy highlights the closing price (CP), which plays a critical role in confirming buy and sell signals.
The strategy also features a Second Buy Signal triggered if the price falls more than 10% after an initial buy signal, providing a re-entry opportunity with a different visual highlight for the second buy signal.
Features:
Three Simple Moving Averages (SMA):
SMA 20: Short-term moving average reflecting immediate market trends.
SMA 50: Medium-term moving average showing the prevailing trend.
SMA 200: Long-term moving average that indicates the overall market trend.
Buy Signal (B1):
Triggered when:
SMA 200 > SMA 50 > SMA 20, indicating a bullish market structure.
The closing price is positioned below all three SMAs, confirming a potential upward reversal.
A green label appears at the low of the bar with the text B1-Price, indicating the price at which the buy signal is generated.
Second Buy Signal (B2):
Triggered if the price falls more than 10% after the first buy signal, providing an opportunity to re-enter the market at a potentially better price.
A blue label appears at the low of the bar with the text B2-Price, showing the price at which the second buy opportunity arises.
Sell Signal (S):
Triggered when:
SMA 20 > SMA 50 > SMA 200, indicating a bearish trend.
The closing price (CP) is positioned above all three SMAs, confirming a potential downward movement.
A red label appears at the high of the bar with the text S-Price, showing the price at which the sell signal is triggered.
How It Works:
Buy Conditions:
SMA 200 > SMA 50 > SMA 20: Indicates a bullish market where the long-term trend (SMA 200) is above the medium-term (SMA 50), and the medium-term trend is above the short-term (SMA 20).
Closing price below all three SMAs: Confirms that the price is in a favorable position for a potential upward reversal.
Sell Conditions:
SMA 20 > SMA 50 > SMA 200: This setup indicates a bearish trend.
Closing price above all three SMAs: Confirms that the price is in a favorable position for a potential downward movement.
Second Buy Signal (B2): If the price falls more than 10% after the first buy signal, the strategy triggers a second buy opportunity (B2) at a potentially better price. This helps traders take advantage of pullbacks or corrections after an initial favorable entry.
Labeling System:
B1-Price: The first buy signal label, appearing when the market is bullish and the closing price is below all three SMAs.
B2-Price: The second buy signal label, triggered if the price falls more than 10% after the initial buy signal.
S-Price: The sell signal label, appearing when the market turns bearish and the closing price is above all three SMAs.
How to Use:
Add the Indicator: Add "3_SMA_Strategy_V-Singhal by Parthib" to your chart on TradingView.
Interpret Buy Signals (B1): Look for green labels with the text "B1-Price" when the closing price (CP) is below all three SMAs and the trend is bullish.
Interpret Second Buy Signals (B2): If the price falls more than 10% after the first buy, look for blue labels with "B2-Price" and a re-entry opportunity.
Interpret Sell Signals (S): Look for red labels with the text "S-Price" when the market turns bearish, and the closing price (CP) is above all three SMAs.
Conclusion:
The 3_SMA_Strategy_V-Singhal by Parthib is an efficient and simple trend-following tool for traders looking to make informed buy and sell decisions. By combining the power of three SMAs and the closing price (CP) confirmation, this strategy helps traders to buy when the market shows a strong bullish setup and sell when the trend turns bearish. Additionally, the second buy signal feature ensures that traders don’t miss out on re-entry opportunities after price corrections, giving them a chance to re-enter the market at a favorable price.
Moving Averages
Smart DCA Strategy (Public)INSPIRATION
While Dollar Cost Averaging (DCA) is a popular and stress-free investment approach, I noticed an opportunity for enhancement. Standard DCA involves buying consistently, regardless of market conditions, which can sometimes mean missing out on optimal investment opportunities. This led me to develop the Smart DCA Strategy – a 'set and forget' method like traditional DCA, but with an intelligent twist to boost its effectiveness.
The goal was to build something more profitable than a standard DCA strategy so it was equally important that this indicator could backtest its own results in an A/B test manner against the regular DCA strategy.
WHY IS IT SMART?
The key to this strategy is its dynamic approach: buying aggressively when the market shows signs of being oversold, and sitting on the sidelines when it's not. This approach aims to optimize entry points, enhancing the potential for better returns while maintaining the simplicity and low stress of DCA.
WHAT THIS STRATEGY IS, AND IS NOT
This is an investment style strategy. It is designed to improve upon the common standard DCA investment strategy. It is therefore NOT a day trading strategy. Feel free to experiment with various timeframes, but it was designed to be used on a daily timeframe and that's how I recommend it to be used.
You may also go months without any buy signals during bull markets, but remember that is exactly the point of the strategy - to keep your buying power on the sidelines until the markets have significantly pulled back. You need to be patient and trust in the historical backtesting you have performed.
HOW IT WORKS
The Smart DCA Strategy leverages a creative approach to using Moving Averages to identify the most opportune moments to buy. A trigger occurs when a daily candle, in its entirety including the high wick, closes below the threshold line or box plotted on the chart. The indicator is designed to facilitate both backtesting and live trading.
HOW TO USE
Settings:
The input parameters for tuning have been intentionally simplified in an effort to prevent users falling into the overfitting trap.
The main control is the Buying strictness scale setting. Setting this to a lower value will provide more buying days (less strict) while higher values mean less buying days (more strict). In my testing I've found level 9 to provide good all round results.
Validation days is a setting to prevent triggering entries until the asset has spent a given number of days (candles) in the overbought state. Increasing this makes entries stricter. I've found 0 to give the best results across most assets.
In the backtest settings you can also configure how much to buy for each day an entry triggers. Blind buy size is the amount you would buy every day in a standard DCA strategy. Smart buy size is the amount you would buy each day a Smart DCA entry is triggered.
You can also experiment with backtesting your strategy over different historical datasets by using the Start date and End date settings. The results table will not calculate for any trades outside what you've set in the date range settings.
Backtesting:
When backtesting you should use the results table on the top right to tune and optimise the results of your strategy. As with all backtests, be careful to avoid overfitting the parameters. It's better to have a setup which works well across many currencies and historical periods than a setup which is excellent on one dataset but bad on most others. This gives a much higher probability that it will be effective when you move to live trading.
The results table provides a clear visual representation as to which strategy, standard or smart, is more profitable for the given dataset. You will notice the columns are dynamically coloured red and green. Their colour changes based on which strategy is more profitable in the A/B style backtest - green wins, red loses. The key metrics to focus on are GOA (Gain on Account) and Avg Cost.
Live Trading:
After you've finished backtesting you can proceed with configuring your alerts for live trading.
But first, you need to estimate the amount you should buy on each Smart DCA entry. We can use the Total invested row in the results table to calculate this. Assuming we're looking to trade on
BTCUSD
Decide how much USD you would spend each day to buy BTC if you were using a standard DCA strategy. Lets say that is $5 per day
Enter that USD amount in the Blind buy size settings box
Check the Blind Buy column in the results table. If we set the backtest date range to the last 10 years, we would expect the amount spent on blind buys over 10 years to be $18,250 given $5 each day
Next we need to tweak the value of the Smart buy size parameter in setting to get it as close as we can to the Total Invested amount for Blind Buy
By following this approach it means we will invest roughly the same amount into our Smart DCA strategy as we would have into a standard DCA strategy over any given time period.
After you have calculated the Smart buy size, you can go ahead and set up alerts on Smart DCA buy triggers.
BOT AUTOMATION
In an effort to maintain the 'set and forget' stress-free benefits of a standard DCA strategy, I have set my personal Smart DCA Strategy up to be automated. The bot runs on AWS and I have a fully functional project for the bot on my GitHub account. Just reach out if you would like me to point you towards it. You can also hook this into any other 3rd party trade automation system of your choice using the pre-configured alerts within the indicator.
PLANNED FUTURE DEVELOPMENTS
Currently this is purely an accumulation strategy. It does not have any sell signals right now but I have ideas on how I will build upon it to incorporate an algorithm for selling. The strategy should gradually offload profits in bull markets which generates more USD which gives more buying power to rinse and repeat the same process in the next cycle only with a bigger starting capital. Watch this space!
MARKETS
Crypto:
This strategy has been specifically built to work on the crypto markets. It has been developed, backtested and tuned against crypto markets and I personally only run it on crypto markets to accumulate more of the coins I believe in for the long term. In the section below I will provide some backtest results from some of the top crypto assets.
Stocks:
I've found it is generally more profitable than a standard DCA strategy on the majority of stocks, however the results proved to be a lot more impressive on crypto. This is mainly due to the volatility and cycles found in crypto markets. The strategy makes its profits from capitalising on pullbacks in price. Good stocks on the other hand tend to move up and to the right with less significant pullbacks, therefore giving this strategy less opportunity to flourish.
Forex:
As this is an accumulation style investment strategy, I do not recommend that you use it to trade Forex.
For more info about this strategy including backtest results, please see the full description on the invite only version of this strategy named "Smart DCA Strategy"
Market StructureThis is an advanced, non-repainting Market Structure indicator that provides a robust framework for understanding market dynamics across any timeframe and instrument.
Key Features:
- Non-repainting market structure detection using swing highs/lows
- Clear identification of internal and general market structure levels
- Breakout threshold system for structure adjustments
- Integrated multi-timeframe compatibility
- Rich selection of 30+ moving average types, from basic to advanced adaptive variants
What Makes It Different:
Unlike most market structure indicators that repaint or modify past signals, this implementation uses a fixed-length lookback period to identify genuine swing points.
This means once a structure level or pivot is identified, it stays permanent - providing reliable signals for analysis and trading decisions.
The indicator combines two layers of market structure:
1. Internal Structure (lighter lines) - More sensitive to local price action
2. General Structure (darker lines) - Shows broader market context
Technical Details:
- Uses advanced pivot detection algorithm with customizable swing size
- Implements consecutive break counting for structure adjustments
- Supports both close and high/low price levels for breakout detection
- Includes offset option for better visual alignment
- Each structure break is validated against multiple conditions to prevent false signals
Offset on:
Offset off:
Moving Averages Library:
Includes comprehensive selection of moving averages, from traditional to advanced adaptive types:
- Basic: SMA, EMA, WMA, VWMA
- Advanced: KAMA, ALMA, VIDYA, FRAMA
- Specialized: Hull MA, Ehlers Filter Series
- Adaptive: JMA, RPMA, and many more
Perfect for:
- Price action analysis
- Trend direction confirmation
- Support/resistance identification
- Market structure trading strategies
- Multiple timeframe analysis
This open-source tool is designed to help traders better understand market dynamics and make more informed trading decisions. Feel free to use, modify, and enhance it for your trading needs.
[blackcat] L1 Simple Dual Channel Breakout█ OVERVIEW
The script " L1 Simple Dual Channel Breakout" is an indicator designed to plot dual channel breakout bands and their long-term EMAs on a chart. It calculates short-term and long-term moving averages and deviations to establish upper, lower, and middle bands, which traders can use to identify potential breakout opportunities.
█ LOGICAL FRAMEWORK
Structure:
The script is structured into several main sections:
• Input Parameters: The script does not explicitly define input parameters for the user to adjust, but it uses default values for short_term_length (5) and long_term_length (181).
• Calculations: The calculate_dual_channel_breakout function performs the core calculations, including the blast condition, typical price, short-term and long-term moving averages, and dynamic moving averages.
• Plotting: The script plots the short-term bands (upper, lower, and middle) and their long-term EMAs. It also plots conditional line breaks when the short-term bands cross the long-term EMAs.
Flow of Data and Logic:
1 — The script starts by defining the calculate_dual_channel_breakout function.
2 — Inside the function, it calculates various moving averages and deviations based on the input prices and lengths.
3 — The function returns the calculated bands and EMAs.
4 — The script then calls this function with predefined lengths and plots the resulting bands and EMAs on the chart.
5 — Conditional plots are added to highlight breakouts when the short-term bands cross the long-term EMAs.
█ CUSTOM FUNCTIONS
The script defines one custom function:
• calculate_dual_channel_breakout(close_price, high_price, low_price, short_term_length, long_term_length): This function calculates the short-term and long-term bands and EMAs. It takes five parameters: close_price, high_price, low_price, short_term_length, and long_term_length. It returns an array containing the upper band, lower band, middle band, long-term upper EMA, long-term lower EMA, and long-term middle EMA.
█ KEY POINTS AND TECHNIQUES
• Typical Price Calculation: The script uses a modified typical price calculation (2 * close_price + high_price + low_price) / 4 instead of the standard (high_price + low_price + close_price) / 3.
• Short-term and Long-term Bands: The script calculates short-term bands using a simple moving average (SMA) of the typical price and long-term bands using a relative moving average (RMA) of the close price.
• Conditional Plotting: The script uses conditional plotting to highlight breakouts when the short-term bands cross the long-term EMAs, enhancing visual identification of trading signals.
• EMA for Long-term Trends: The use of Exponential Moving Averages (EMAs) for long-term bands helps in smoothing out short-term fluctuations and focusing on long-term trends.
█ EXTENDED KNOWLEDGE AND APPLICATIONS
• Modifications: Users can add input parameters to allow customization of short_term_length and long_term_length, making the indicator more flexible.
• Enhancements: The script could be extended to include alerts for breakout conditions, providing traders with real-time notifications.
• Alternative Bands: Users might experiment with different types of moving averages (e.g., WMA, HMA) for the short-term and long-term bands to see if they yield better results.
• Additional Indicators: Combining this indicator with other technical indicators (e.g., RSI, MACD) could provide a more comprehensive trading strategy.
• Backtesting: Users can backtest the strategy using Pine Script's strategy functions to evaluate its performance over historical data.
VWAP SlopeThis script calculates and displays the slope of the Volume Weighted Average Price (VWAP) . It compares the current VWAP with its value from a user-defined lookback period to determine the slope. The slope is color-coded: green for an upward trend (positive slope) and red for a downward trend (negative slope) .
Key Points:
VWAP Calculation: The script calculates the VWAP based on a user-defined timeframe (default: daily), which represents the average price weighted by volume.
Slope Determination: The slope is calculated by comparing the current VWAP to its value from a previous period, providing insight into market trends.
Color-Coding: The slope line is color-coded to visually indicate the market direction: green for uptrend and red for downtrend.
This script helps traders identify the direction of the market based on VWAP , offering a clear view of trends and potential turning points.
VWAP - TrendThis Pine Script calculates the Volume Weighted Average Price (VWAP) for a specified timeframe and plots its Linear Regression over a user-defined lookback period . The regression line is color-coded: green indicates an uptrend and red indicates a downtrend. The line is broken at the end of each day to prevent it from extending into the next day, ensuring clarity on a daily basis.
Key Features:
VWAP Calculation: The VWAP is calculated based on a selected timeframe, providing a smoothed average price considering volume.
Linear Regression: The script calculates a linear regression of the VWAP over a custom lookback period to capture the underlying trend.
Color-Coding: The regression line is color-coded to easily identify trends—green for an uptrend and red for a downtrend.
Day-End Break: The regression line breaks at the end of each day to prevent continuous plotting across days, which helps keep the analysis focused within daily intervals.
User Inputs: The user can adjust the VWAP timeframe and the linear regression lookback period to tailor the indicator to their preferences.
This script provides a visual representation of the VWAP trend, helping traders identify potential market directions and turning points based on the linear regression of the VWAP.
Moving Average Cross; Linear RegressionThis Pine Script is designed to display smoothed linear regression lines on a chart, with an option to adjust the regression period lengths and smoothing factor. The script calculates short-term and long-term linear regression lines based on the selected timeframe. These regression lines act as a regressed moving average cross , visually representing the interaction between the two smoothed linear regressions.
Short Regression Line: A linear regression line based on a short lookback period, colored blue for an uptrend and orange for a downtrend .
Long Regression Line: A linear regression line based on a longer lookback period, similarly colored blue for an uptrend and orange for a downtrend .
The script provides input options to adjust:
The length of short and long regression periods.
The smoothing length for the regression lines.
The timeframe for the linear regression calculations.
This tool can help traders observe the crossovers between the two smoothed linear regression lines, which are similar to moving average crossovers, but with the added benefit of regression-based smoothing to reduce noise. The color-coding allows for easy trend identification, with blue indicating an uptrend and orange indicating a downtrend.
AuriumFlowAURIUM (GOLD-Weighted Average with Fractal Dynamics)
Aurium is a cutting-edge indicator that blends volume-weighted moving averages (VWMA), fractal geometry, and Fibonacci-inspired calculations to deliver a precise and holistic view of market trends. By dynamically adjusting to price and volume, Aurium uncovers key levels of confluence for trend reversals and continuations, making it a powerful tool for traders.
Key Features:
Dynamic Trendline (GOLD):
The central trendline is a weighted moving average based on price and volume, tuned using Fibonacci-based fast (34) and slow (144) exponential moving average lengths. This ensures the trendline adapts seamlessly to the flow of market dynamics.
Formula:
GOLD = VWMA(34) * Volume Factor + VWMA(144) * (1 - Volume Factor)
Fractal Highs and Lows:
Detects pivotal market points using a fractal lookback period (default 5, odd-numbered). Fractals identify local highs and lows over a defined window, capturing the structure of market cycles.
Trend Background Highlighting:
Bullish Zone: Price above the GOLD line with a green background.
Bearish Zone: Price below the GOLD line with a red background.
Buy and Sell Alerts:
Generates actionable signals when fractals align with GOLD. Bullish fractals confirm continuation or reversal in an uptrend, while bearish fractals validate a downtrend.
The Math Behind Aurium:
Volume-Weighted Adjustments:
By integrating volume into the calculation, Aurium dynamically emphasizes price levels with greater participation, giving traders insight into zones of institutional interest.
Formula:
VWMA = EMA(Close * Volume) / EMA(Volume)
Fractal Calculations:
Fractals are identified as local maxima (highs) or minima (lows) based on the surrounding bars, leveraging the natural symmetry in price behavior.
Fibonacci Relationships:
The 34 and 144 EMA lengths are Fibonacci numbers, offering a natural alignment with price cycles and market rhythms.
Ideal For:
Traders seeking a precise and intuitive indicator for aligning with trends and detecting reversals.
Strategies inspired by Bill Williams, with added volume and fractal-based insights.
Short-term scalpers and long-term trend-followers alike.
Unlock deeper market insights and trade with precision using Aurium!
Trend Strength/DirectionThis is a really good, though complex indicator, so I will add two different explanations so to appease both the laymen and those who take the time to read thoroughly.
Simple Explanation
This indicator utilizes 6HMA's to display their angles
The greater the angle ---> the stronger the trend
If more angles are positive, then trend is very strong
If more are negative, then very negative
Comprehensive Explanation
6 angles, each of a different time frame are used to represent direction and trend strength. Angles are used because they intrinsically represent momentum and speed. An angle of 45 represents a perfect balance between something that can cover the furthest distance without compensating for speed. 1 of the 6 angles is intended(though customizable) to represent the 5 hma's angle. This is because the 5hma is very good at representing very near term price action.
Angle Levels
Its important to understand what the angle levels mean for the underlying hma's. The 0 level represents a hma that is horizontal. This is important because this is the point at which it decides to be bullish or bearish. +/- 45, as noted before, represent bullishness/bearishness that represent strong trends without compensating for speed. A continuous increase/decrease and or a cross of these levels generally indicate significant change in sentiment, of which trades may be taken.
Strategy
You should weigh your decision by those angles that represent the longer time frame. If more angles represent a certain sentiment, it is obviously unwise to fight against that long term sentiment. The purpose of this indicator was to provide a proper representation of trend direction and strength, but also solve the problem of when you should 'dip' buy.
For an example: if all angles are increase or decreasing, then you may use the 5hma's angle to find the proper points at which you will enter a position.
***NOTE: I dont think the +/- 45 bands should indicate 'overbought' or 'oversold' zones that some might assume. Instead you should wait for a crossing of this zone.
Adaptive MAAdaptive Moving Average (AMA)
Overview
The Adaptive Moving Average (AMA) script is designed to calculate and plot a moving average that adapts dynamically based on market conditions. This script uses pivot-based periods for its calculation, allowing it to adjust its behavior in response to market volatility and trends. It supports both Simple Moving Average (SMA) and Exponential Moving Average (EMA).
Features
Dynamic Period Calculation: Leverages the DynamicPeriodPublic library to compute periods based on pivot points, providing an adaptive length for the moving average.
Customizable Parameters: Users can choose predefined "Fast" and "Slow" settings or manually configure the parameters for greater control.
Supports SMA and EMA: Flexibility to choose between SMA and EMA for the moving average calculation.
Inputs
Source ( src ): Data source for the moving average (e.g., close price).
Default: close
Length Type ( length_type ): Determines the type of period calculation.
Options: Fast, Slow, Manual
MA Type ( ma_type ): Specifies the type of moving average to calculate.
Options: SMA, EMA
Manual Parameters (used when length_type is set to Manual):
Left Bars ( left_bars ): Number of left-hand bars for pivot detection.
Right Bars ( right_bars ): Number of right-hand bars for pivot detection.
Number of Pivots ( num_pivots ): Minimum number of pivots for dynamic period calculation.
Length Multiplier ( length_mult ): Multiplier applied to the calculated period.
Use Cases
Trend Analysis: Identify market trends with an average that adapts to changing conditions.
Volatility-Based Strategies: Adjust strategies dynamically in response to market volatility.
Custom Configurations: Fine-tune pivot parameters for specific markets or assets using the "Manual" mode.
Example Usage
Select the desired length type (Fast, Slow, or Manual).
If Manual is selected, configure the pivot detection parameters and length multiplier.
Choose the moving average type (SMA or EMA).
Observe the adaptive moving average plotted on the chart.
Loacally Weighted MA (LWMA) Direction HistogramThe Locally Weighted Moving Average (LWMA) Direction Histogram indicator is designed to provide traders with a visual representation of the price momentum and trend direction. This Pine Script, written in version 6, calculates an LWMA by assigning higher weights to recent data points, emphasizing the most current market movements. The script incorporates user-defined input parameters, such as the LWMA length and a direction lookback period, making it flexible to adapt to various trading strategies and preferences.
The histogram visually represents the difference between the current LWMA and a previous LWMA value (based on the lookback period). Positive values are colored blue, indicating upward momentum, while negative values are yellow, signaling downward movement. Additionally, the script colors candlesticks according to the histogram's value, enhancing clarity for users analyzing market trends. The LWMA line itself is plotted on the chart but hidden by default, enabling traders to toggle its visibility as needed. This blend of histogram and candlestick visualization offers a comprehensive tool for identifying shifts in momentum and potential trading opportunities.
Zero-Lag MA CandlesThe Zero-Lag MA Candles indicator combines the efficiency of a Zero-Lag Moving Average (ZLMA) with dynamic candlestick coloring to provide a clear visual representation of market trends. By leveraging a dual EMA-based calculation, the ZLMA achieves reduced lag, enhancing its responsiveness to price changes. The indicator plots candles on the chart with colors determined by the trend direction of the ZLMA over a user-defined lookback period. Blue candles signify an uptrend, while yellow candles indicate a downtrend, offering traders an intuitive way to identify market sentiment.
This indicator is particularly useful for trend-following strategies, as the crossover and crossunder between the ZLMA and the standard EMA highlight potential reversal points or trend continuation zones. With customizable inputs for ZLMA length, trend lookback period, and color schemes, it caters to diverse trading preferences. Its ability to plot directly on the chart ensures seamless integration with other analysis tools, making it a valuable addition to a trader's toolkit.
Happy trading...
Strength of Divergence Across Multiple Indicators (+CMF&VWMACD)Modified Version of Strength of Divergence Across Multiple Indicators by reees
Purpose:
This Pine Script indicator is designed to identify and evaluate the strength of bullish and bearish divergences across multiple technical indicators. Divergences occur when the price of an asset is moving in one direction while a technical indicator is moving in the opposite direction, potentially signaling a trend reversal.
Key Features:
1. Multiple Indicator Support: The script now analyzes divergences for the following indicators:
* RSI (Relative Strength Index)
* OBV (On-Balance Volume)
* MACD (Moving Average Convergence/Divergence)
* STOCH (Stochastic Oscillator)
* CCI (Commodity Channel Index)
* MFI (Money Flow Index)
* AO (Awesome Oscillator)
* CMF (Chaikin Money Flow) - Newly added
* VWMACD (Volume-Weighted MACD) - Newly added
2. Customizable Divergence Parameters:
* Bullish/Bearish: Enable or disable the detection of bullish and bearish divergences independently.
* Regular/Hidden: Detect both regular and hidden divergences (hidden divergences can indicate trend continuation).
* Broken Trendline Exclusion: Optionally ignore divergences where the trendline connecting price pivots is broken by an intermediate pivot.
* Pivot Lookback Periods: Adjust the number of bars used to identify valid pivot highs and lows for divergence calculations.
* Weighting: Assign different weights to regular vs. hidden divergences and to the relative change in price vs. the indicator.
3. Indicator-Specific Settings:
* Weight: Each indicator can be assigned a weight, influencing its contribution to the overall divergence strength calculation.
* Extreme Value: Define a threshold above which an indicator's divergence is considered "extreme," giving it a higher strength rating.
4. Divergence Strength Calculation:
* For each indicator, the script calculates a divergence "degree" based on the magnitude of the divergence and the user-defined weightings.
* The total divergence strength is the sum of the individual indicator divergence degrees.
* Strength is categorized as "Extreme," "Very strong," "Strong," "Moderate," "Weak," or "Very weak."
5. Visualization:
* Divergence Lines: The script draws lines on the chart connecting the price and indicator pivots that form a divergence (optional, with customizable transparency).
* Labels: Labels display the total divergence strength and a breakdown of each indicator's contribution. The size and visibility of labels are based on the strength.
6. Alerts:
* The script can generate alerts when the total divergence strength exceeds a user-defined threshold.
New Indicators (CMF and VWMACD):
* Chaikin Money Flow (CMF):
* Purpose: Measures the buying and selling pressure by analyzing the relationship between price, volume, and the accumulation/distribution line.
* Divergence: A bullish CMF divergence occurs when the price makes a lower low, but the CMF makes a higher low (suggesting increasing buying pressure). A bearish divergence is the opposite.
* Volume-Weighted MACD (VWMACD):
* Purpose: Similar to the standard MACD but uses volume-weighted moving averages instead of simple moving averages, giving more weight to periods with higher volume.
* Divergence: Divergences are interpreted similarly to the standard MACD, but the VWMACD can be more sensitive to volume changes.
How It Works (Simplified):
1. Pivot Detection: The script identifies pivot highs and lows in both price and the selected indicators using the specified lookback periods.
2. Divergence Check: For each indicator:
* It checks if a series of pivots in price and the indicator are diverging (e.g., price makes a lower low, but the indicator makes a higher low for a bullish divergence).
* It calculates the divergence degree based on the difference in price and indicator values, weightings, and whether it's a regular or hidden divergence.
3. Strength Aggregation: The script sums up the divergence degrees of all enabled indicators to get the total divergence strength.
4. Visualization and Alerts: It draws lines and labels on the chart to visualize the divergences and generates alerts if the total strength exceeds the set threshold.
Benefits:
* Comprehensive Divergence Analysis: By considering multiple indicators, the script provides a more robust assessment of potential trend reversals.
* Customization: The many adjustable parameters allow traders to fine-tune the script to their specific trading style and preferences.
* Objective Strength Evaluation: The divergence strength calculation and categorization offer a more objective way to evaluate the significance of divergences.
* Early Warning System: Divergences can often precede significant price movements, making this script a valuable tool for anticipating potential trend changes.
* Volume Confirmation: The inclusion of CMF and VWMACD add volume-based confirmation to the divergence signals, potentially increasing their reliability.
Limitations:
* Lagging Indicators: Most of the indicators used are lagging, meaning they are based on past price data. Divergences may sometimes occur after a significant price move has already begun.
* False Signals: No indicator is perfect, and divergences can sometimes produce false signals, especially in choppy or ranging markets.
* Subjectivity: While the script aims for objectivity, some settings (like weightings and extreme values) still involve a degree of subjective judgment.
SMA Ribbon [A]SMA Ribbon with Adjustable MA200
20, 50, 100, and 200 -period Simple Moving Averages (SMAs) for trend analysis.
The SMA200 dynamically changes color based on its direction—green when rising and red when falling. Additionally, you can lock the SMA200 to the daily timeframe , allowing it to display the 200-day moving average on lower timeframes, such as 4-hour or 1-hour charts.
Features:
Dynamic SMA200 Color: Automatically adjusts to show upward (green) or downward (red) trends.
Daily SMA200 Option: Enables the SMA200 to represent the 200-day moving average on intraday charts for long-term trend insights.
Smart Adaptation: The daily SMA200 setting is automatically disabled on daily or higher timeframes, ensuring accurate period calculations.
How to Use:
Use this script to identify key support/resistance levels and overall market trends.
Adjust the "Daily MA for MA200" option in the settings to toggle between timeframe-specific and daily-locked SMA200.
This script is ideal for traders seeking a clean and customizable tool for long-term and short-term trend analysis.
PheonixLegend3MAPineScript indicator called "PhoenixLegend3MA" with the following features:
Display Options:
Each MA line can be individually enabled/disabled
Customizable colors for each MA line (default: blue for M15, red for M30, green for H1)
Adjustable line width (default is 2)
MA Options:
Choice between EMA and SMA
Default length is 1440
Displays for 3 timeframes: M15, M30, and H1
Code Organization:
Uses groups to categorize input settings
Dedicated function for MA calculation
Uses request.security to fetch data from different timeframes
This indicator helps traders visualize moving averages across multiple timeframes in a single chart, making it easier to identify trends and potential trading opportunities. Perfect for technical analysis and trend following strategies.
High/Mid/Low of the Previous Month, Week and Day + MAIntroducing the Ultimate Price Action Indicator
Take your trading to the next level with this feature-packed indicators. Designed to provide key price insights, this tool offers:
- Monthly, Weekly, and Daily Levels : Displays the High, Midpoint, and Low of the previous month, week, and day.
- Logarithmic Price Lines : Option to plot price levels logarithmically for enhanced accuracy.
- Customizable Labels : Display labels on price lines for better clarity. (This feature is optional.)
- Dual Moving Averages : Add two customizable Moving Averages (Simple, Exponential, or Weighted) directly on the price chart. (This feature is optional.)
This code combines features from the Moving Average Exponential and Daily Weekly Monthly Highs & Lows (sbtnc) indicators, with custom modifications to implement unique personal ideas.
Perfect for traders who want to combine precision with simplicity. Whether you're analyzing historical levels or integrating moving averages into your strategy, this indicator provides everything you need for informed decision-making.
To prevent change chart scale, right click on Price Scale and enable "Scale price chart only"
MA Direction Histogram
The MA Direction Histogram is a simple yet powerful tool for visualizing the momentum of a moving average (MA). It highlights whether the MA is trending up or down, making it ideal for identifying market direction quickly.
Key Features:
1. Custom MA Options: Choose from SMA, EMA, WMA, VWMA, or HMA for flexible analysis.
2. Momentum Visualization: Bars show the difference between the MA and its value from a lookback period.
- Blue Bars: Upward momentum.
- Yellow Bars: Downward momentum.
3. Easy Customization: Adjust the MA length, lookback period, and data source.
How to Use:
- Confirm Trends: Positive bars indicate uptrends; negative bars suggest downtrends.
- *Spot Reversals: Look for bar color changes as potential reversal signals.
Compact, intuitive, and versatile, the "MA Direction Histogram" helps traders stay aligned with market momentum. Perfect for trend-based strategies!
Adaptive Price Zone Oscillator [QuantAlgo]Adaptive Price Zone Oscillator 🎯📊
The Adaptive Price Zone (APZ) Oscillator by QuantAlgo is an advanced technical indicator designed to identify market trends and reversals through adaptive price zones based on volatility-adjusted bands. This sophisticated system combines typical price analysis with dynamic volatility measurements to help traders and investors identify trend direction, potential reversals, and market volatility conditions. By evaluating both price action and volatility together, this tool enables users to make informed trading decisions while adapting to changing market conditions.
💫 Dynamic Zone Architecture
The APZ Oscillator provides a unique framework for assessing market trends through a blend of smoothed typical prices and volatility-based calculations. Unlike traditional oscillators that use fixed parameters, this system incorporates dynamic volatility measurements to adjust sensitivity automatically, helping users determine whether price movements are significant relative to current market conditions. By combining smoothed price trends with adaptive volatility zones, it evaluates both directional movement and market volatility, while the smoothing parameters ensure stable yet responsive signals. This adaptive approach allows users to identify trending conditions while remaining aware of volatility expansions and contractions, enhancing both trend-following and mean-reversion strategies.
📊 Indicator Components & Mechanics
The APZ Oscillator is composed of several technical components that create a dynamic trending system:
Typical Price: Utilizes HLC3 (High, Low, Close average) as a balanced price representation
Volatility Measurement: Computes exponential moving average of price changes to determine dynamic zones
Smoothed Calculations: Applies additional smoothing to reduce noise while maintaining responsiveness
Trend Detection: Evaluates price position relative to adaptive zones to determine market direction
📈 Key Indicators and Features
The APZ Oscillator utilizes typical price with customizable length and threshold parameters to adapt to different trading styles. Volatility calculations are applied to determine zone boundaries, providing context-aware levels for trend identification. The trend detection component evaluates price action relative to the adaptive zones, helping validate trends and identify potential reversals.
The indicator also incorporates multi-layered visualization with:
Color-coded trend representation (bullish/bearish)
Clear trend state indicators (+1/-1)
Mean reversion signals with distinct markers
Gradient fills for better visual clarity
Programmable alerts for trend changes
⚡️ Practical Applications and Examples
✅ Add the Indicator : Add the indicator to your TradingView chart by clicking on the star icon to add it to your favorites ⭐️
👀 Monitor Trend State : Watch the oscillator's position relative to the zero line to identify trend direction and potential reversals. The step-line visualization with diamonds makes trend changes clearly visible.
🎯 Track Signals : Pay attention to the mean reversion markers that appear above and below the price chart:
→ Upward triangles (⤻) signal potential bullish reversals
→ X crosses (↷) indicate potential bearish reversals
🔔 Set Alerts : Configure alerts for trend changes in both bullish and bearish directions, ensuring you can act on significant technical developments promptly.
🌟 Summary and Tips
The Adaptive Price Zone Oscillator by QuantAlgo is a versatile technical tool, designed to support both trend following and mean reversion strategies across different market environments. By combining smoothed typical price analysis with dynamic volatility-based zones, it helps traders and investors identify significant trend changes while measuring market volatility, providing reliable technical signals. The tool's adaptability through customizable length, threshold, and smoothing parameters makes it suitable for various trading timeframes and styles, allowing users to capture opportunities while maintaining awareness of changing market conditions.
Key parameters to optimize for your trading style:
APZ Length: Adjust for more or less sensitivity to price changes
Threshold: Fine-tune the volatility multiplier for wider or narrower zones
Smoothing: Balance noise reduction with signal responsiveness
Granville Entry GuideThis indicator is designed to identify trade entry points using patterns 2 and 3 of the Granville's Law. It is compatible with version 6.
Determining Entry Points
・ Long Entry : When the medium-term moving average is rising, if the stock price falls close to or below the moving average and then begins to rise, with that bar being a bullish candle, it is determined as an entry point. At this time, a red circle will be displayed above the bar.
・ Short Entry : When the medium-term moving average is falling, if the stock price rises close to or above the moving average and then begins to fall, with that bar being a bearish candle, it is determined as an entry point. At this time, a blue circle will be displayed below the bar.
Trend Filter
Entry points will only be displayed if the following trend conditions are met:
・In an uptrend, the order of moving averages should be: short-term moving average, medium-term moving average, and long-term moving average from top to bottom. In a downtrend, the order should be: long-term moving average, medium-term moving average, and short-term moving average from top to bottom. The order of the short-term moving average is flexible.
・The medium-term and long-term moving averages should be inclined in the direction of the trend. The inclination of the short-term moving average is flexible.
Adjusting Parameters
・ Stock Selection : You can choose whether to use the stock price from candlesticks or the short-term moving average for determining entry points. Selecting candlesticks allows for quicker determination but increases noise, while selecting the short-term moving average slows down determination but reduces noise. The default value is the short-term moving average.
・ Determining Pullbacks or Retracements : This is determined by the number of bars on either side of the lowest point of the pullback. Increasing the number of bars reduces noise but may result in missed opportunities. The default values are 3 bars on the left and 1 bar on the right.
・ Use of Trend Filter : You can choose whether to use the trend filter. The default setting is to use it.
・ Conditions for Moving Average Inclination : You can choose whether to include the trend direction inclination in the trend filter conditions. The default setting is to include it.
・ Bar Background Color : The trend filter is displayed with the bar's background color, but it can also be set to not display.
このインジケーターは、グランビルの法則のパターン2とパターン3を利用して、トレードのエントリーポイントを見つけるためのものです。version6に対応しています。
エントリーポイントの判定方法
ロングエントリー :中期移動平均線が上昇しているとき、株価が移動平均線の近くまで落ちるか、割り込んだ後に上昇を始め、そのバーが陽線である場合にエントリーポイントと判定します。このとき、赤い丸がバーの上に表示されます。
ショートエントリー :中期移動平均線が下落しているとき、株価が移動平均線の近くまで上昇するか、上抜けた後に下落を始め、そのバーが陰線である場合にエントリーポイントと判定します。このとき、青い丸がバーの下に表示されます。
トレンドフィルター
エントリーポイントは、次のトレンド条件を満たす場合のみ表示されます。
・上昇トレンドの場合、移動平均線が上から中期移動平均線、長期移動平均線の順になっている。下降トレンドの場合、移動平均線が上から長期移動平均線、中期移動平均線の順になっている。なお短期移動平均線の順番は任意です。
・中期移動平均線と長期移動平均線がトレンド方向に傾いている。なお短期移動平均線の傾きは任意です。
パラメーターの調整方法
・ 株価の選択 : エントリーポイントの判定に使用する株価を、ローソク足か短期移動平均線から選べます。ローソク足を選ぶと判定が早くなりますがノイズが増え、短期移動平均線を選ぶと判定が遅くなりますがノイズが減ります。初期値は短期移動平均線です。
・ 押しや戻りの判定 : 押しの最下点の左右のバーの数で判定します。バーの数を増やすとノイズが減りますが、機会を逃すこともあります。初期値は左が3、右が1です。
・ トレンドフィルターの使用 : トレンドフィルターを使うかどうかを選べます。初期値は使用する設定です。
・ 移動平均線の傾きの条件 : トレンドフィルターのうち、トレンド方向の傾きを条件に入れるかどうかを選べます。初期値は条件に入れる設定です。
バーの背景色: トレンドフィルターはバーの背景色で表示されますが、非表示に設定することもできます。
Prediction Based on Linreg & Atr
We created this algorithm with the goal of predicting future prices 📊, specifically where the value of any asset will go in the next 20 periods ⏳. It uses linear regression based on past prices, calculating a slope and an intercept to forecast future behavior 🔮. This prediction is then adjusted according to market volatility, measured by the ATR 📉, and the direction of trend signals, which are based on the MACD and moving averages 📈.
How Does the Linreg & ATR Prediction Work?
1. Trend Calculation and Signals:
o Technical Indicators: We use short- and long-term exponential moving averages (EMA), RSI, MACD, and Bollinger Bands 📊 to assess market direction and sentiment (not visually presented in the script).
o Calculation Functions: These include functions to calculate slope, average, intercept, standard deviation, and Pearson's R, which are crucial for regression analysis 📉.
2. Predicting Future Prices:
o Linear Regression: The algorithm calculates the slope, average, and intercept of past prices to create a regression channel 📈, helping to predict the range of future prices 🔮.
o Standard Deviation and Pearson's R: These metrics determine the strength of the regression 🔍.
3. Adjusting the Prediction:
o The predicted value is adjusted by considering market volatility (ATR 📉) and the direction of trend signals 🔮, ensuring that the prediction is aligned with the current market environment 🌍.
4. Visualization:
o Prediction Lines and Bands: The algorithm plots lines that display the predicted future price along with a prediction range (upper and lower bounds) 📉📈.
5. EMA Cross Signals:
o EMA Conditions and Total Score: A bullish crossover signal is generated when the total score is positive and the short EMA crosses above the long EMA 📈. A bearish crossover signal is generated when the total score is negative and the short EMA crosses below the long EMA 📉.
6. Additional Considerations:
o Multi-Timeframe Regression Channel: The script calculates regression channels for different timeframes (5m, 15m, 30m, 4h) ⏳, helping determine the overall market direction 📊 (not visually presented).
Confidence Interpretation:
• High Confidence (close to 100%): Indicates strong alignment between timeframes with a clear trend (bullish or bearish) 🔥.
• Low Confidence (close to 0%): Shows disagreement or weak signals between timeframes ⚠️.
Confidence complements the interpretation of the prediction range and expected direction 🔮, aiding in decision-making for market entry or exit 🚀.
Español
Creamos este algoritmo con el objetivo de predecir los precios futuros 📊, específicamente hacia dónde irá el valor de cualquier activo en los próximos 20 períodos ⏳. Utiliza regresión lineal basada en los precios pasados, calculando una pendiente y una intersección para prever el comportamiento futuro 🔮. Esta predicción se ajusta según la volatilidad del mercado, medida por el ATR 📉, y la dirección de las señales de tendencia, que se basan en el MACD y las medias móviles 📈.
¿Cómo Funciona la Predicción con Linreg & ATR?
Cálculo de Tendencias y Señales:
Indicadores Técnicos: Usamos medias móviles exponenciales (EMA) a corto y largo plazo, RSI, MACD y Bandas de Bollinger 📊 para evaluar la dirección y el sentimiento del mercado (no presentados visualmente en el script).
Funciones de Cálculo: Incluye funciones para calcular pendiente, media, intersección, desviación estándar y el coeficiente de correlación de Pearson, esenciales para el análisis de regresión 📉.
Predicción de Precios Futuros:
Regresión Lineal: El algoritmo calcula la pendiente, la media y la intersección de los precios pasados para crear un canal de regresión 📈, ayudando a predecir el rango de precios futuros 🔮.
Desviación Estándar y Pearson's R: Estas métricas determinan la fuerza de la regresión 🔍.
Ajuste de la Predicción:
El valor predicho se ajusta considerando la volatilidad del mercado (ATR 📉) y la dirección de las señales de tendencia 🔮, asegurando que la predicción esté alineada con el entorno actual del mercado 🌍.
Visualización:
Líneas y Bandas de Predicción: El algoritmo traza líneas que muestran el precio futuro predicho, junto con un rango de predicción (límites superior e inferior) 📉📈.
Señales de Cruce de EMAs:
Condiciones de EMAs y Puntaje Total: Se genera una señal de cruce alcista cuando el puntaje total es positivo y la EMA corta cruza por encima de la EMA larga 📈. Se genera una señal de cruce bajista cuando el puntaje total es negativo y la EMA corta cruza por debajo de la EMA larga 📉.
Consideraciones Adicionales:
Canal de Regresión Multi-Timeframe: El script calcula canales de regresión para diferentes marcos de tiempo (5m, 15m, 30m, 4h) ⏳, ayudando a determinar la dirección general del mercado 📊 (no presentado visualmente).
Interpretación de la Confianza:
Alta Confianza (cerca del 100%): Indica una fuerte alineación entre los marcos temporales con una tendencia clara (alcista o bajista) 🔥.
Baja Confianza (cerca del 0%): Muestra desacuerdo o señales débiles entre los marcos temporales ⚠️.
La confianza complementa la interpretación del rango de predicción y la dirección esperada 🔮, ayudando en las decisiones de entrada o salida en el mercado 🚀.
Gauti Market Maker Killzone EMA1. Identifying the Trend
Use Daily (1D) and Hourly (1H) Exponential Moving Averages (EMAs) to define the overall trend:
Bullish Trend: Both 1D and 1H EMAs are upward sloping, and the price is above these EMAs.
Bearish Trend: Both 1D and 1H EMAs are downward sloping, and the price is below these EMAs.
2. Confirmation with Higher Timeframes
Bullish Conditions:
Check 1D and 4H charts for price action above the EMA bands.
Look for price forming higher highs and higher lows or respecting support at the EMA bands.
Bearish Conditions:
Check 1D and 4H charts for price action below the EMA bands.
Look for price forming lower highs and lower lows or respecting resistance at the EMA bands.
Note: Crossover of EMAs on higher timeframes is an optional extra confirmation, but not mandatory for entry.
3. Entry Strategy
Use the 15-Minute (15M) timeframe for entries.
Entries are taken only during Killzones:
Killzones: London Open, New York Open, or other intraday key trading sessions. (Define the time ranges for these zones based on your trading hours.)
Wait for the price to touch or pull back to the EMA band during the Killzones in the direction of the overall trend:
In a bullish trend, enter long when the price touches the EMA band and shows signs of rejection or reversal.
In a bearish trend, enter short when the price touches the EMA band and shows signs of rejection or reversal.
4. Checklist for Entry
Confirm the following before entering:
1D Trend aligns with the 1H Trend.
Price Action in 1D and 4H supports the trend.
Killzone session is active.
Price is reacting to the EMA band on the 15M chart in the trend direction.
Multi-Indicator Signal with TableThis indicator is a versatile multi-indicator tool designed for traders who want to combine signals from various popular indicators into a single framework. It not only visualizes buy and sell signals but also provides a clear, easy-to-read table that summarizes the included indicators and their respective signal colors.
Key Features:
RSI (Relative Strength Index):
Buy Signal: RSI falls below the oversold level (default: 30).
Sell Signal: RSI rises above the overbought level (default: 70).
Signal Color: Green.
MACD (Moving Average Convergence Divergence):
Buy Signal: MACD line crosses above the signal line.
Sell Signal: MACD line crosses below the signal line.
Signal Color: Blue.
MA Crossover (Moving Average Crossover):
Buy Signal: Short EMA (default: 7) crosses above Long SMA (default: 14).
Sell Signal: Short EMA crosses below Long SMA.
Signal Color: Purple.
Stochastic Oscillator:
Buy Signal: Stochastic %K falls below 20 and crosses above %D.
Sell Signal: Stochastic %K rises above 80 and crosses below %D.
Signal Color: Yellow.
TSI (True Strength Index):
Buy Signal: TSI crosses above the zero line.
Sell Signal: TSI crosses below the zero line.
Signal Color: Red.
Dynamic Signal Table:
A clean, compact table displayed at the top-right corner of the chart, summarizing the indicators and their respective signal colors for quick reference.
Customization:
All indicator parameters are fully adjustable, allowing users to fine-tune settings to match their trading strategy.
Signal colors and table design ensure a visually intuitive experience.
Usage:
This tool is ideal for traders who prefer a multi-indicator approach for generating buy/sell signals.
The combination of different indicators helps to filter out noise and increase the accuracy of trade setups.
Notes:
Signals appear only after the confirmation of the current bar to avoid false triggers.
This indicator is designed for educational purposes and should be used in conjunction with proper risk management strategies.
Bitcoin: Mayer MultipleMayer Multiple Indicator
The Mayer Multiple is a powerful tool designed to help traders assess market conditions and identify optimal buying or selling opportunities. It calculates the ratio between the current price and its 200-day simple moving average (SMA), visualizing key thresholds that indicate value zones, caution areas, and overheated markets.
Key Features:
Dynamic Market Zones: Clearly marked levels like "Smash Buy," "Boost DCA," and "Extreme Euphoria" to guide your trading decisions.
Customizable Input: Adjust the SMA length to fit your strategy.
Color-Coded Signals: Intuitive visualization of market sentiment for quick analysis.
Comprehensive Thresholds: Historical insights into price behavior with plotted reference levels based on probabilities.
This indicator is ideal for traders aiming to enhance their long-term strategies and improve decision-making in volatile markets. Use it to gain an edge in identifying potential turning points and managing risk effectively.
