Quantum Momentum FusionPurpose of the Indicator
"Quantum Momentum Fusion" aims to combine the strengths of RSI (Relative Strength Index) and Williams %R to create a hybrid momentum indicator tailored for volatile markets like crypto:
RSI: Measures the strength of price changes, great for understanding trend stability but can sometimes lag.
Williams %R: Assesses the position of the price relative to the highest and lowest levels over a period, offering faster responses but sensitive to noise.
Combination: By blending these two indicators with a weighted average (default 50%-50%), we achieve both speed and reliability.
Additionally, we use the indicator’s own SMA (Simple Moving Average) crossovers to filter out noise and generate more meaningful signals. The goal is to craft a simple yet effective tool, especially for short-term trading like scalping.
How Signals Are Generated
The indicator produces signals as follows:
Calculations:
RSI: Standard 14-period RSI based on closing prices.
Williams %R: Calculated over 14 periods using the highest high and lowest low, then normalized to a 0-100 scale.
Quantum Fusion: A weighted average of RSI and Williams %R (e.g., 50% RSI + 50% Williams %R).
Fusion SMA: 5-period Simple Moving Average of Quantum Fusion.
Signal Conditions:
Overbought Signal (Red Background):
Quantum Fusion crosses below Fusion SMA (indicating weakening momentum).
And Quantum Fusion is above 70 (in the overbought zone).
This is a sell signal.
Oversold Signal (Green Background):
Quantum Fusion crosses above Fusion SMA (indicating strengthening momentum).
And Quantum Fusion is below 30 (in the oversold zone).
This is a buy signal.
Filtering:
The background only changes color during crossovers, reducing “fake” signals.
The 70 and 30 thresholds ensure signals trigger only in extreme conditions.
On the chart:
Purple line: Quantum Fusion.
Yellow line: Fusion SMA.
Red background: Sell signal (overbought confirmation).
Green background: Buy signal (oversold confirmation).
Overall Assessment
This indicator can be a fast-reacting tool for scalping. However:
Volatility Warning: Sudden crypto pumps/dumps can disrupt signals.
Confirmation: Pair it with price action (candlestick patterns) or another indicator (e.g., volume) for validation.
Timeframe: Works best on 1-5 minute charts.
Suggested Settings for Long Timeframes
Here’s a practical configuration for, say, a 4-hour chart:
RSI Period: 20
Williams %R Period: 20
RSI Weight: 60%
Williams %R Weight: 40% (automatically calculated as 100 - RSI Weight)
SMA Period: 15
Overbought Level: 75
Oversold Level: 25
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MACD Volume Strategy for XAUUSD (15m) [PineIndicators]The MACD Volume Strategy is a momentum-based trading system designed for XAUUSD on the 15-minute timeframe. It integrates two key market indicators: the Moving Average Convergence Divergence (MACD) and a volume-based oscillator to identify strong trend shifts and confirm trade opportunities. This strategy uses dynamic position sizing, incorporates leverage customization, and applies structured entry and exit conditions to improve risk management.
⚙️ Core Strategy Components
1️⃣ Volume-Based Momentum Calculation
The strategy includes a custom volume oscillator to filter trade signals based on market activity. The oscillator is derived from the difference between short-term and long-term volume trends using Exponential Moving Averages (EMAs)
Short EMA (default = 5) represents recent volume activity.
Long EMA (default = 8) captures broader volume trends.
Positive values indicate rising volume, supporting momentum-based trades.
Negative values suggest weak market activity, reducing signal reliability.
By requiring positive oscillator values, the strategy ensures momentum confirmation before entering trades.
2️⃣ MACD Trend Confirmation
The strategy uses the MACD indicator as a trend filter. The MACD is calculated as:
Fast EMA (16-period) detects short-term price trends.
Slow EMA (26-period) smooths out price fluctuations to define the overall trend.
Signal Line (9-period EMA) helps identify crossovers, signaling potential trend shifts.
Histogram (MACD – Signal) visualizes trend strength.
The system generates trade signals based on MACD crossovers around the zero line, confirming bullish or bearish trend shifts.
📌 Trade Logic & Conditions
🔹 Long Entry Conditions
A buy signal is triggered when all the following conditions are met:
✅ MACD crosses above 0, signaling bullish momentum.
✅ Volume oscillator is positive, confirming increased trading activity.
✅ Current volume is at least 50% of the previous candle’s volume, ensuring market participation.
🔻 Short Entry Conditions
A sell signal is generated when:
✅ MACD crosses below 0, indicating bearish momentum.
✅ Volume oscillator is positive, ensuring market activity is sufficient.
✅ Current volume is less than 50% of the previous candle’s volume, showing decreasing participation.
This multi-factor approach filters out weak or false signals, ensuring that trades align with both momentum and volume dynamics.
📏 Position Sizing & Leverage
Dynamic Position Calculation:
Qty = strategy.equity × leverage / close price
Leverage: Customizable (default = 1x), allowing traders to adjust risk exposure.
Adaptive Sizing: The strategy scales position sizes based on account equity and market price.
Slippage & Commission: Built-in slippage (2 points) and commission (0.01%) settings provide realistic backtesting results.
This ensures efficient capital allocation, preventing overexposure in volatile conditions.
🎯 Trade Management & Exits
Take Profit & Stop Loss Mechanism
Each position includes predefined profit and loss targets:
Take Profit: +10% of risk amount.
Stop Loss: Fixed at 10,100 points.
The risk-reward ratio remains balanced, aiming for controlled drawdowns while maximizing trade potential.
Visual Trade Tracking
To improve trade analysis, the strategy includes:
📌 Trade Markers:
"Buy" label when a long position opens.
"Close" label when a position exits.
📌 Trade History Boxes:
Green for profitable trades.
Red for losing trades.
📌 Horizontal Trade Lines:
Shows entry and exit prices.
Helps identify trend movements over multiple trades.
This structured visualization allows traders to analyze past performance directly on the chart.
⚡ How to Use This Strategy
1️⃣ Apply the script to a XAUUSD (Gold) 15m chart in TradingView.
2️⃣ Adjust leverage settings as needed.
3️⃣ Enable backtesting to assess past performance.
4️⃣ Monitor volume and MACD conditions to understand trade triggers.
5️⃣ Use the visual trade markers to review historical performance.
The MACD Volume Strategy is designed for short-term trading, aiming to capture momentum-driven opportunities while filtering out weak signals using volume confirmation.
GWAP (Gamma Weighted Average Price)Gamma Weighted Average Price (GWAP) Indicator
The Gamma Weighted Average Price (GWAP) is a dynamic financial indicator that applies exponentially decaying weights to historical prices to calculate a weighted average. The method leverages the exponential decay function, controlled by a gamma factor, to prioritize recent price data while gradually diminishing the influence of older observations. This approach builds upon techniques commonly found in time-series analysis, including Exponentially Weighted Moving Averages (EWMA), which are extensively used in financial modeling (Campbell, Lo & MacKinlay, 1997).
Theoretical Context and Justification
The gamma-weighted approach follows principles similar to those in Exponentially Weighted Moving Averages (EWMA), often used in volatility modeling, where weights decay exponentially over time. The exponential decay model can improve signal responsiveness compared to simple moving averages (Hyndman & Athanasopoulos, 2018). This design helps capture recent market dynamics without ignoring past trends, a common requirement in high-frequency trading systems (Bandi & Russell, 2006).
Practical Applications
1. Trend Detection:
The GWAP can help identify bullish and bearish trends:
• When the price is above GWAP, the market exhibits bullish momentum.
• Conversely, when the price is below GWAP, bearish momentum prevails.
2. Volatility Filtering:
Because of the gamma weighting mechanism, GWAP reduces the noise commonly seen in volatile markets, making it a useful tool for traders looking to smooth price fluctuations while retaining actionable signals.
3. Crossovers for Trade Signals:
Similar to moving average strategies, traders can use price crossovers with the GWAP as trade signals:
• Buy Signal: When the price crosses above the GWAP.
• Sell Signal: When the price crosses below the GWAP.
4. Adaptive Gamma Weighting:
The gamma factor allows for further customization.
• Higher gamma values (>1) place greater emphasis on older data, suitable for long-term trend analysis.
• Lower gamma values (<1) heavily weight recent price movements, ideal for fast-moving markets.
Example Use Case
A trader analyzing the S&P 500 may use a gamma factor of 0.92 with a 14-period GWAP to detect shifts in market sentiment during periods of heightened volatility. When the index price crosses above the GWAP, this could signal a potential recovery, prompting a buy entry. Conversely, when the price moves below the GWAP during a correction, it may suggest a short-selling opportunity.
Scientific References
• Campbell, J. Y., Lo, A. W., & MacKinlay, A. C. (1997). The Econometrics of Financial Markets. Princeton University Press.
• Hyndman, R. J., & Athanasopoulos, G. (2018). Forecasting: Principles and Practice. OTexts.
• Bandi, F. M., & Russell, J. R. (2006). Microstructure Noise, Realized Variance, and Optimal Sampling. Econometrica.
Adaptive Resonance Oscillator [AlgoAlpha]Introducing the Adaptive Resonance Oscillator , an advanced momentum-based oscillator designed to dynamically adjust to changing market conditions. This innovative indicator detects market frequency through a Hilbert Transform approach, adapting in real-time to identify overbought and oversold conditions with improved accuracy. With built-in divergence detection, trend analysis, and customizable smoothing, this tool is perfect for traders looking to refine their entries and exits based on adaptive oscillation mechanics.
🚀 Key Features :
🔹 Adaptive Frequency Detection – Uses Hilbert Transform principles to dynamically determine market cycle length for precise oscillator calculation.
⚙️ Customizable Smoothing – Option to apply a Hull Moving Average (HMA) for enhanced signal clarity.
📈 Divergence Detection – Identifies bullish and bearish divergences with visual markers, helping traders spot early trend reversals.
🟢 Overbought & Oversold Signals – Highlights extreme momentum conditions with adjustable thresholds.
🔔 Real-Time Alerts – Get notified for crossovers, divergences, and strong trend shifts directly on your TradingView chart.
🎨 Fully Customizable Appearance – Modify colors, divergence sensitivity, and smoothing options to fit your trading style.
🛠 How to Use :
Add the Adaptive Resonance Oscillator to your TradingView chart by clicking the ★ to favorite it.
Monitor the Charts , switch between smoothed and I smoothed modes to identify trend and price swings, use divergences and reversal signals for potential entry/exits.
Set alerts for bullish/bearish crossovers and divergence signals to stay ahead of market moves.
⚙ How It Works :
The indicator begins by applying a Hilbert Transform frequency estimation to the price series, identifying the dominant market cycle length. This is used to calculate a period for the RSI that matches its resonant frequency with the dominant market frequency, dynamically adjusting the Oscillator. The oscillator then applies an optional Hull Moving Average (HMA) smoothing for signal refinement. Additionally, the indicator scans for bullish and bearish divergences by comparing oscillator movements against price action, plotting signals accordingly. When overbought/oversold conditions or divergence events occur, alerts are triggered to notify the trader in real time.
Arpeet MACDOverview
This strategy is based on the zero-lag version of the MACD (Moving Average Convergence Divergence) indicator, which captures short-term trends by quickly responding to price changes, enabling high-frequency trading. The strategy uses two moving averages with different periods (fast and slow lines) to construct the MACD indicator and introduces a zero-lag algorithm to eliminate the delay between the indicator and the price, improving the timeliness of signals. Additionally, the crossover of the signal line and the MACD line is used as buy and sell signals, and alerts are set up to help traders seize trading opportunities in a timely manner.
Strategy Principle
Calculate the EMA (Exponential Moving Average) or SMA (Simple Moving Average) of the fast line (default 12 periods) and slow line (default 26 periods).
Use the zero-lag algorithm to double-smooth the fast and slow lines, eliminating the delay between the indicator and the price.
The MACD line is formed by the difference between the zero-lag fast line and the zero-lag slow line.
The signal line is formed by the EMA (default 9 periods) or SMA of the MACD line.
The MACD histogram is formed by the difference between the MACD line and the signal line, with blue representing positive values and red representing negative values.
When the MACD line crosses the signal line from below and the crossover point is below the zero axis, a buy signal (blue dot) is generated.
When the MACD line crosses the signal line from above and the crossover point is above the zero axis, a sell signal (red dot) is generated.
The strategy automatically places orders based on the buy and sell signals and triggers corresponding alerts.
Advantage Analysis
The zero-lag algorithm effectively eliminates the delay between the indicator and the price, improving the timeliness and accuracy of signals.
The design of dual moving averages can better capture market trends and adapt to different market environments.
The MACD histogram intuitively reflects the comparison of bullish and bearish forces, assisting in trading decisions.
The automatic order placement and alert functions make it convenient for traders to seize trading opportunities in a timely manner, improving trading efficiency.
Risk Analysis
In volatile markets, frequent crossover signals may lead to overtrading and losses.
Improper parameter settings may cause signal distortion and affect strategy performance.
The strategy relies on historical data for calculations and has poor adaptability to sudden events and black swan events.
Optimization Direction
Introduce trend confirmation indicators, such as ADX, to filter out false signals in volatile markets.
Optimize parameters to find the best combination of fast and slow line periods and signal line periods, improving strategy stability.
Combine other technical indicators or fundamental factors to construct a multi-factor model, improving risk-adjusted returns of the strategy.
Introduce stop-loss and take-profit mechanisms to control single-trade risk.
Summary
The MACD Dual Crossover Zero Lag Trading Strategy achieves high-frequency trading by quickly responding to price changes and capturing short-term trends. The zero-lag algorithm and dual moving average design improve the timeliness and accuracy of signals. The strategy has certain advantages, such as intuitive signals and convenient operation, but also faces risks such as overtrading and parameter sensitivity. In the future, the strategy can be optimized by introducing trend confirmation indicators, parameter optimization, multi-factor models, etc., to improve the robustness and profitability of the strategy.
Buy Signal Forex & Crypto v0 ImprovedPurpose of the Script:
This script is designed to generate buy and sell signals for trading Forex and cryptocurrencies by analyzing price trends using exponential moving averages (EMAs), volatility, and volume filters. The signals are displayed as arrows on the chart.
What the Script Does
Input Settings:
The script allows the user to configure various settings, such as the lengths of EMAs, a higher timeframe for trend confirmation, and thresholds for volume and volatility (ATR - Average True Range).
Key settings:
5 EMA Length – Length of the short-term EMA.
13 EMA Length – Length of the medium-term EMA.
26 EMA Length – Length of the long-term EMA.
21 EMA Length – Used for trend confirmation on a higher timeframe.
Higher Timeframe – Lets you select a timeframe (e.g., daily) for confirming the overall trend.
ATR Threshold – Filters out signals when the market's volatility is too low.
Volume Filter – Ensures sufficient trading activity before generating signals.
Calculating EMAs (Exponential Moving Averages):
Four EMAs are calculated:
ema5 (short-term), ema13 (medium-term), ema26 (long-term), and ema21 (higher timeframe confirmation).
These EMAs help determine price trends and crossovers, which are critical for identifying buy and sell opportunities.
Trend Confirmation Using a Higher Timeframe:
The 21 EMA on the higher timeframe (e.g., daily) is used to confirm the overall direction of the market.
Defining Signal Conditions:
Buy Signal:
A buy signal is generated when:
ema5 crosses above ema13 (indicating a bullish trend).
ema5 crosses above ema26 (stronger bullish confirmation).
The closing price is above ema5, ema13, ema26, and the 21 EMA on the higher timeframe.
The market's volatility (ATR) is above the defined threshold.
The volume meets the conditions or volume filtering is disabled.
Sell Signal:
A sell signal is generated when:
ema5 crosses below ema13 (indicating a bearish trend).
ema5 crosses below ema26 (stronger bearish confirmation).
The closing price is below ema5, ema13, ema26, and the 21 EMA on the higher timeframe.
The market's volatility (ATR) is above the defined threshold.
The volume meets the conditions or volume filtering is disabled.
Volume Filtering:
Ensures there’s enough trading activity by comparing the current volume to a 20-period moving average of volume.
Persistent Variables:
These variables (crossed13 and crossed13Sell) help track whether the short-term EMA (ema5) has crossed the medium-term EMA (ema13). This prevents false or repeated signals.
Displaying Signals on the Chart:
Buy signals are displayed as green upward arrows below the price.
Sell signals are displayed as red downward arrows above the price.
How It Helps Traders:
This script provides visual cues for potential entry and exit points by combining moving average crossovers, volatility, volume, and higher timeframe trend confirmation. It works well for trending markets and ensures signals are filtered for stronger conditions to reduce noise.
Rosiz Support 2### **Indicator Name**: Custom RSI, Stochastic, and ADX
### **Description**:
This is a multi-functional indicator that combines three popular technical analysis tools—**RSI (Relative Strength Index)**, **Stochastic Oscillator**, and **ADX (Average Directional Index)**—into a single, customizable pane. This indicator helps traders analyze momentum, overbought/oversold conditions, and trend strength simultaneously, making it a powerful tool for making informed trading decisions.
---
### **Features**:
1. **RSI (Relative Strength Index)**:
- Measures the speed and change of price movements.
- Helps identify overbought (>70) and oversold (<30) conditions.
- Includes customizable length and source options.
- Background shading visually highlights overbought and oversold zones.
2. **Stochastic Oscillator**:
- Determines momentum by comparing a security's closing price to its price range over a specific period.
- Includes %K and %D lines for crossovers, which signal potential entry or exit points.
- Highlights overbought (>80) and oversold (<20) zones with background fill.
3. **ADX (Average Directional Index)**:
- Measures trend strength (higher values indicate stronger trends).
- Includes customizable smoothing and DI (Directional Indicator) length.
---
### **How to Use**:
- **RSI**: Look for overbought or oversold conditions for potential reversal points. Divergences between price and RSI may signal weakening trends.
- **Stochastic Oscillator**: Watch for %K and %D crossovers near overbought or oversold zones to confirm buy or sell signals.
- **ADX**: Use ADX values to assess trend strength:
- **ADX > 25**: Strong trend.
- **ADX < 20**: Weak or ranging market.
---
### **Customization Options**:
- **RSI Settings**: Adjust length, source, and visual parameters.
- **Stochastic Settings**: Modify %K and %D lengths and smoothing factors.
- **ADX Settings**: Fine-tune smoothing and directional index lengths.
---
### **Advantages**:
- Combines three indicators into one, reducing chart clutter.
- Customizable inputs for flexibility in various trading strategies.
- Visual enhancements (background fills and lines) for better readability.
This indicator is perfect for traders looking to combine momentum analysis, overbought/oversold signals, and trend strength in a single tool!
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.
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.
supertrendLibrary "supertrend"
supertrend : Library dedicated to different variations of supertrend
supertrend_atr(length, multiplier, atrMaType, source, highSource, lowSource, waitForClose, delayed)
supertrend_atr: Simple supertrend based on atr but also takes into consideration of custom MA Type, sources
Parameters:
length (simple int) : : ATR Length
multiplier (simple float) : : ATR Multiplier
atrMaType (simple string) : : Moving Average type for ATR calculation. This can be sma, ema, hma, rma, wma, vwma, swma
source (float) : : Default is close. Can Chose custom source
highSource (float) : : Default is high. Can also use close price for both high and low source
lowSource (float) : : Default is low. Can also use close price for both high and low source
waitForClose (simple bool) : : Considers source for direction change crossover if checked. Else, uses highSource and lowSource.
delayed (simple bool) : : if set to true lags supertrend atr stop based on target levels.
Returns: dir : Supertrend direction
supertrend : BuyStop if direction is 1 else SellStop
supertrend_bands(bandType, maType, length, multiplier, source, highSource, lowSource, waitForClose, useTrueRange, useAlternateSource, alternateSource, sticky)
supertrend_bands: Simple supertrend based on atr but also takes into consideration of custom MA Type, sources
Parameters:
bandType (simple string) : : Type of band used - can be bb, kc or dc
maType (simple string) : : Moving Average type for Bands. This can be sma, ema, hma, rma, wma, vwma, swma
length (simple int) : : Band Length
multiplier (float) : : Std deviation or ATR multiplier for Bollinger Bands and Keltner Channel
source (float) : : Default is close. Can Chose custom source
highSource (float) : : Default is high. Can also use close price for both high and low source
lowSource (float) : : Default is low. Can also use close price for both high and low source
waitForClose (simple bool) : : Considers source for direction change crossover if checked. Else, uses highSource and lowSource.
useTrueRange (simple bool) : : Used for Keltner channel. If set to false, then high-low is used as range instead of true range
useAlternateSource (simple bool) : - Custom source is used for Donchian Chanbel only if useAlternateSource is set to true
alternateSource (float) : - Custom source for Donchian channel
sticky (simple bool) : : if set to true borders change only when price is beyond borders.
Returns: dir : Supertrend direction
supertrend : BuyStop if direction is 1 else SellStop
supertrend_zigzag(length, history, useAlternativeSource, alternativeSource, source, highSource, lowSource, waitForClose, atrlength, multiplier, atrMaType)
supertrend_zigzag: Zigzag pivot based supertrend
Parameters:
length (simple int) : : Zigzag Length
history (simple int) : : number of historical pivots to consider
useAlternativeSource (simple bool)
alternativeSource (float)
source (float) : : Default is close. Can Chose custom source
highSource (float) : : Default is high. Can also use close price for both high and low source
lowSource (float) : : Default is low. Can also use close price for both high and low source
waitForClose (simple bool) : : Considers source for direction change crossover if checked. Else, uses highSource and lowSource.
atrlength (simple int) : : ATR Length
multiplier (simple float) : : ATR Multiplier
atrMaType (simple string) : : Moving Average type for ATR calculation. This can be sma, ema, hma, rma, wma, vwma, swma
Returns: dir : Supertrend direction
supertrend : BuyStop if direction is 1 else SellStop
zupertrend(length, history, useAlternativeSource, alternativeSource, source, highSource, lowSource, waitForClose, atrlength, multiplier, atrMaType)
zupertrend: Zigzag pivot based supertrend
Parameters:
length (simple int) : : Zigzag Length
history (simple int) : : number of historical pivots to consider
useAlternativeSource (simple bool)
alternativeSource (float)
source (float) : : Default is close. Can Chose custom source
highSource (float) : : Default is high. Can also use close price for both high and low source
lowSource (float) : : Default is low. Can also use close price for both high and low source
waitForClose (simple bool) : : Considers source for direction change crossover if checked. Else, uses highSource and lowSource.
atrlength (simple int) : : ATR Length
multiplier (simple float) : : ATR Multiplier
atrMaType (simple string) : : Moving Average type for ATR calculation. This can be sma, ema, hma, rma, wma, vwma, swma
Returns: dir : Supertrend direction
supertrend : BuyStop if direction is 1 else SellStop
zsupertrend(zigzagpivots, history, source, highSource, lowSource, waitForClose, atrMaType, atrlength, multiplier)
zsupertrend: Same as zigzag supertrend. But, works on already calculated array rather than Calculating fresh zigzag
Parameters:
zigzagpivots (array) : : Precalculated zigzag pivots
history (simple int) : : number of historical pivots to consider
source (float) : : Default is close. Can Chose custom source
highSource (float) : : Default is high. Can also use close price for both high and low source
lowSource (float) : : Default is low. Can also use close price for both high and low source
waitForClose (simple bool) : : Considers source for direction change crossover if checked. Else, uses highSource and lowSource.
atrMaType (simple string) : : Moving Average type for ATR calculation. This can be sma, ema, hma, rma, wma, vwma, swma
atrlength (simple int) : : ATR Length
multiplier (simple float) : : ATR Multiplier
Returns: dir : Supertrend direction
supertrend : BuyStop if direction is 1 else SellStop
Adaptive Supertrend with Dynamic Optimization [EdgeTerminal]The Enhanced Adaptive Supertrend represents a significant evolution of the traditional Supertrend indicator, incorporating advanced mathematical optimization, dynamic volatility adjustment, intelligent signal filtering, reduced noise and false positives.
Key Features
Dynamic volatility-adjusted bands
Self-optimizing multiplier
Intelligent signal filtering system
Cooldown period to prevent signal clustering
Clear buy/sell signals with optimal positioning
Smooth trend visualization
RSI and MACD integration for confirmation
Performance-based optimization
Dynamic Band Calculation
Dynamic Band Calculation automatically adapts to market volatility, generates wider bands in volatile periods, reducing false signals. It also generates tighter bands in stable periods, capturing smaller moves and smooth transitions between different volatility regimes.
RSI Integration
The RSI and MACD play multiple crucial roles in the Adaptive Supertrend.
It first helps with momentum factor calculation. This dynamically adjusts band width based on momentum conditions. When the RSI is oversold, bands widen by 20% to prevent false signals during strong downtrends and provide more room for price movements in extreme conditions.
When the RSI is overbought, brands tighten by 20% and they become more sensitive to potential reversals to help catch trend changes earlier.
This reduces false signals in strong trends, helps detect potential reversals earlier than the usual, create adaptive band width based on market conditions and finally, better protection against whipsaws.
MACD Integration
The MACD in this supertrend indicator serves as a trend confirmation tool. The idea is to use MACD crossovers to confirm trend changes to reduce false trend change signals and enhance the signal quality.
For this to become a signal, MACD crossovers must align with price movement to help filter out weak or false signals, which acts as an additional layer of trend confirmation.
Additionally, MACD line position relative to signal line indicates trend strength, helps maintain positions in strong trends and assists in early detection of trend weakening.
Momentum Integration
Momentum Integration prevents false signals in extreme conditions, It adjusts dynamic bands based on market momentum, improves trend confirmation in strong moves and reduces whipsaws during consolidations.
Improved signals
There are a few systems to generate better signals, allowing for generally faster signals compared to original supertrend, such as:
Enforced cooldown period between signals
Prevents signal clustering
Clearer entry/exit points
Reduced false signals during choppy markets
Performance Optimization
This script implements a Sharpe ratio-inspired optimization algorithm to balance returns against risk, penalize large drawdowns, adapt parameters in real-time and improve risk-adjusted performance
Parameter Settings
ATR Period: 10 (default) - adjust based on timeframe
Initial Multiplier: 3.0 (default) - will self-optimize
Optimization Period: 50 (default) - longer periods for more stability
Smoothing Period: 3 (default) - adjust for signal smoothness
Best Practices
Use on multiple timeframes for confirmation
Allow the optimization process to run for at least 50 bars
Monitor the adaptive multiplier for trend strength indication
Consider RSI and MACD alignment for stronger signals
Exposure Oscillator (Cumulative 0 to ±100%)
Exposure Oscillator (Cumulative 0 to ±100%)
This Pine Script indicator plots an "Exposure Oscillator" on the chart, which tracks the cumulative market exposure from a range of technical buy and sell signals. The exposure is measured on a scale from -100% (maximum short exposure) to +100% (maximum long exposure), helping traders assess the strength of their position in the market. It provides an intuitive visual cue to aid decision-making for trend-following strategies.
Buy Signals (Increase Exposure Score by +10%)
Buy Signal 1 (Cross Above 21 EMA):
This signal is triggered when the price crosses above the 21-period Exponential Moving Average (EMA), where the current bar closes above the EMA21, and the previous bar closed below the EMA21. This indicates a potential upward price movement as the market shifts into a bullish trend.
buySignal1 = ta.crossover(close, ema21)
Buy Signal 2 (Trending Above 21 EMA):
This signal is triggered when the price closes above the 21-period EMA for each of the last 5 bars, indicating a sustained bullish trend. It confirms that the price is consistently above the EMA21 for a significant period.
buySignal2 = ta.barssince(close <= ema21) > 5
Buy Signal 3 (Living Above 21 EMA):
This signal is triggered when the price has closed above the 21-period EMA for each of the last 15 bars, demonstrating a strong, prolonged uptrend.
buySignal3 = ta.barssince(close <= ema21) > 15
Buy Signal 4 (Cross Above 50 SMA):
This signal is triggered when the price crosses above the 50-period Simple Moving Average (SMA), where the current bar closes above the 50 SMA, and the previous bar closed below it. It indicates a shift toward bullish momentum.
buySignal4 = ta.crossover(close, sma50)
Buy Signal 5 (Cross Above 200 SMA):
This signal is triggered when the price crosses above the 200-period Simple Moving Average (SMA), where the current bar closes above the 200 SMA, and the previous bar closed below it. This suggests a long-term bullish trend.
buySignal5 = ta.crossover(close, sma200)
Buy Signal 6 (Low Above 50 SMA):
This signal is true when the lowest price of the current bar is above the 50-period SMA, indicating strong bullish pressure as the price maintains itself above the moving average.
buySignal6 = low > sma50
Buy Signal 7 (Accumulation Day):
An accumulation day occurs when the closing price is in the upper half of the daily range (greater than 50%) and the volume is larger than the previous bar's volume, suggesting buying pressure and accumulation.
buySignal7 = (close - low) / (high - low) > 0.5 and volume > volume
Buy Signal 8 (Higher High):
This signal occurs when the current bar’s high exceeds the highest high of the previous 14 bars, indicating a breakout or strong upward momentum.
buySignal8 = high > ta.highest(high, 14)
Buy Signal 9 (Key Reversal Bar):
This signal is generated when the stock opens below the low of the previous bar but rallies to close above the previous bar’s high, signaling a potential reversal from bearish to bullish.
buySignal9 = open < low and close > high
Buy Signal 10 (Distribution Day Fall Off):
This signal is triggered when a distribution day (a day with high volume and a close near the low of the range) "falls off" the rolling 25-bar period, indicating the end of a bearish trend or selling pressure.
buySignal10 = ta.barssince(close < sma50 and close < sma50) > 25
Sell Signals (Decrease Exposure Score by -10%)
Sell Signal 1 (Cross Below 21 EMA):
This signal is triggered when the price crosses below the 21-period Exponential Moving Average (EMA), where the current bar closes below the EMA21, and the previous bar closed above it. It suggests that the market may be shifting from a bullish trend to a bearish trend.
sellSignal1 = ta.crossunder(close, ema21)
Sell Signal 2 (Trending Below 21 EMA):
This signal is triggered when the price closes below the 21-period EMA for each of the last 5 bars, indicating a sustained bearish trend.
sellSignal2 = ta.barssince(close >= ema21) > 5
Sell Signal 3 (Living Below 21 EMA):
This signal is triggered when the price has closed below the 21-period EMA for each of the last 15 bars, suggesting a strong downtrend.
sellSignal3 = ta.barssince(close >= ema21) > 15
Sell Signal 4 (Cross Below 50 SMA):
This signal is triggered when the price crosses below the 50-period Simple Moving Average (SMA), where the current bar closes below the 50 SMA, and the previous bar closed above it. It indicates the start of a bearish trend.
sellSignal4 = ta.crossunder(close, sma50)
Sell Signal 5 (Cross Below 200 SMA):
This signal is triggered when the price crosses below the 200-period Simple Moving Average (SMA), where the current bar closes below the 200 SMA, and the previous bar closed above it. It indicates a long-term bearish trend.
sellSignal5 = ta.crossunder(close, sma200)
Sell Signal 6 (High Below 50 SMA):
This signal is true when the highest price of the current bar is below the 50-period SMA, indicating weak bullishness or a potential bearish reversal.
sellSignal6 = high < sma50
Sell Signal 7 (Distribution Day):
A distribution day is identified when the closing range of a bar is less than 50% and the volume is larger than the previous bar's volume, suggesting that selling pressure is increasing.
sellSignal7 = (close - low) / (high - low) < 0.5 and volume > volume
Sell Signal 8 (Lower Low):
This signal occurs when the current bar's low is less than the lowest low of the previous 14 bars, indicating a breakdown or strong downward momentum.
sellSignal8 = low < ta.lowest(low, 14)
Sell Signal 9 (Downside Reversal Bar):
A downside reversal bar occurs when the stock opens above the previous bar's high but falls to close below the previous bar’s low, signaling a reversal from bullish to bearish.
sellSignal9 = open > high and close < low
Sell Signal 10 (Distribution Cluster):
This signal is triggered when a distribution day occurs three times in the rolling 7-bar period, indicating significant selling pressure.
sellSignal10 = ta.valuewhen((close < low) and volume > volume , 1, 7) >= 3
Theme Mode:
Users can select the theme mode (Auto, Dark, or Light) to match the chart's background or to manually choose a light or dark theme for the oscillator's appearance.
Exposure Score Calculation: The script calculates a cumulative exposure score based on a series of buy and sell signals.
Buy signals increase the exposure score, while sell signals decrease it. Each signal impacts the score by ±10%.
Signal Conditions: The buy and sell signals are derived from multiple conditions, including crossovers with moving averages (EMA21, SMA50, SMA200), trend behavior, and price/volume analysis.
Oscillator Visualization: The exposure score is visualized as a line on the chart, changing color based on whether the exposure is positive (long position) or negative (short position). It is limited to the range of -100% to +100%.
Position Type: The indicator also indicates the position type based on the exposure score, labeling it as "Long," "Short," or "Neutral."
Horizontal Lines: Reference lines at 0%, 100%, and -100% visually mark neutral, increasing long, and increasing short exposure levels.
Exposure Table: A table displays the current exposure level (in percentage) and position type ("Long," "Short," or "Neutral"), updated dynamically based on the oscillator’s value.
Inputs:
Theme Mode: Choose "Auto" to use the default chart theme, or manually select "Dark" or "Light."
Usage:
This oscillator is designed to help traders track market sentiment, gauge exposure levels, and manage risk. It can be used for long-term trend-following strategies or short-term trades based on moving average crossovers and volume analysis.
The oscillator operates in conjunction with the chart’s price action and provides a visual representation of the market’s current trend strength and exposure.
Important Considerations:
Risk Management: While the exposure score provides valuable insight, it should be combined with other risk management tools and analysis for optimal trading decisions.
Signal Sensitivity: The accuracy and effectiveness of the signals depend on market conditions and may require adjustments based on the user’s trading strategy or timeframe.
Disclaimer:
This script is for educational purposes only. Trading involves significant risk, and users should carefully evaluate all market conditions and apply appropriate risk management strategies before using this tool in live trading environments.
MTFHTS with Moving Average Ribbon and Buy/Sell Signals 3.2Multi-Timeframe Moving Average Strategy with Buy and Sell Signals
Purpose
This strategy is designed to provide clear, data-driven buy and sell signals based on moving average crossovers across multiple timeframes. It aims to help traders identify potential trend reversals and entry/exit points using a systematic approach.
How it Works
Moving Averages Across Multiple Timeframes:
Five customizable moving averages (MA №1 to MA №5) are calculated using different lengths and types, including SMA, EMA, WMA, and VWMA, to suit various trading styles.
The MAs are plotted on different timeframes, allowing traders to visualize trend alignment and identify market momentum across short, medium, and long terms.
Signals for Buying and Selling:
Buy Signals: When the shorter-term MA (MA №1) crosses above a longer-term MA (MA №2 or MA №3), the strategy triggers a buy signal, indicating potential upward momentum.
Sell Signals: When MA №1 crosses below a longer-term MA (MA №2 or MA №3), a sell signal is triggered, suggesting potential downward movement.
Visual Aids and Alerts:
The strategy uses color fills between MAs to indicate bullish (green) or bearish (red) trends, helping traders assess market conditions at a glance.
Alerts for buy and sell signals keep traders notified in real-time, helping to avoid missed opportunities.
Important Note
This strategy is purely educational and does not constitute investment advice. It serves as a tool to help traders understand how multi-timeframe moving averages and crossovers can be used in technical analysis. As with any trading strategy, we recommend testing in a simulated environment and exercising caution.
XAUUSD 10-Minute StrategyThis XAUUSD 10-Minute Strategy is designed for trading Gold vs. USD on a 10-minute timeframe. By combining multiple technical indicators (MACD, RSI, Bollinger Bands, and ATR), the strategy effectively captures both trend-following and reversal opportunities, with adaptive risk management for varying market volatility. This approach balances high-probability entries with robust volatility management, making it suitable for traders seeking to optimise entries during significant price movements and reversals.
Key Components and Logic:
MACD (12, 26, 9):
Generates buy signals on MACD Line crossovers above the Signal Line and sell signals on crossovers below the Signal Line, helping to capture momentum shifts.
RSI (14):
Utilizes oversold (below 35) and overbought (above 65) levels as a secondary filter to validate entries and avoid overextended price zones.
Bollinger Bands (20, 2):
Uses upper and lower Bollinger Bands to identify potential overbought and oversold conditions, aiming to enter long trades near the lower band and short trades near the upper band.
ATR-Based Stop Loss and Take Profit:
Stop Loss and Take Profit levels are dynamically set as multiples of ATR (3x for stop loss, 5x for take profit), ensuring flexibility with market volatility to optimise exit points.
Entry & Exit Conditions:
Buy Entry: T riggered when any of the following conditions are met:
MACD Line crosses above the Signal Line
RSI is oversold
Price drops below the lower Bollinger Band
Sell Entry: Triggered when any of the following conditions are met:
MACD Line crosses below the Signal Line
RSI is overbought
Price moves above the upper Bollinger Band
Exit Strategy: Trades are closed based on opposing entry signals, with adaptive spread adjustments for realistic exit points.
Backtesting Configuration & Results:
Backtesting Period: July 21, 2024, to October 30, 2024
Symbol Info: XAUUSD, 10-minute timeframe, OANDA data source
Backtesting Capital: Initial capital of $700, with each trade set to 10 contracts (equivalent to approximately 0.1 lots based on the broker’s contract size for gold).
Users should confirm their broker's contract size for gold, as this may differ. This script uses 10 contracts for backtesting purposes, aligned with 0.1 lots on brokers offering a 100-contract specification.
Key Backtesting Performance Metrics:
Net Profit: $4,733.90 USD (676.27% increase)
Total Closed Trades: 526
Win Rate: 53.99%
Profit Factor: 1.44 (1.96 for Long trades, 1.14 for Short trades)
Max Drawdown: $819.75 USD (56.33% of equity)
Sharpe Ratio: 1.726
Average Trade: $9.00 USD (0.04% of equity per trade)
This backtest reflects realistic conditions, with a spread adjustment of 38 points and no slippage or commission applied. The settings aim to simulate typical retail trading conditions. However, please adjust the initial capital, contract size, and other settings based on your account specifics for best results.
Usage:
This strategy is tuned specifically for XAUUSD on a 10-minute timeframe, ideal for both trend-following and reversal trades. The ATR-based stop loss and take profit levels adapt dynamically to market volatility, optimising entries and exits in varied conditions. To backtest this script accurately, ensure your broker’s contract specifications for gold align with the parameters used in this strategy.
TEMA Crosses_AIT with Manual TEMA CalculationTitle: TEMA Crosses_AIT Indicator
Description:
The TEMA Crosses_AIT Indicator is designed for traders looking to leverage the Triple Exponential Moving Average (TEMA) to identify trend reversals and momentum shifts in the market. This indicator calculates both fast and slow TEMA lines and signals potential buy or sell opportunities based on crossovers between these two lines.
Key Features:
Fast TEMA (TEMAF):
Default period: 20 (adjustable)
Represents the short-term trend and reacts quickly to price changes.
Slow TEMA (TEMAS):
Default period: 200 (adjustable)
Represents the long-term trend, smoothing out price fluctuations to give a clearer view of the overall direction.
Signal Generation:
Long Signal: A long (buy) signal is generated when the fast TEMA crosses above the slow TEMA, indicating a potential upward trend.
Short Signal: A short (sell) signal is generated when the fast TEMA crosses below the slow TEMA, indicating a potential downward trend.
Color-coded Visualization:
The fast TEMA line is displayed in green when it is above the slow TEMA (bullish signal) and in red when below (bearish signal).
The slow TEMA line is displayed in white.
A yellow triangle appears below the price bar for long entries.
A fuchsia triangle appears above the price bar for short entries.
How It Works:
The indicator calculates the Triple Exponential Moving Average (TEMA) manually using exponential moving averages (EMA). The TEMA is calculated by subtracting the second EMA from three times the first EMA, then adding the third EMA. This provides a smoother trend line that reacts more quickly than a traditional EMA, making it ideal for spotting trend changes.
Customizable Inputs:
TEMAF Period: Adjust the period of the fast TEMA to fit your trading style.
TEMAS Period: Adjust the period of the slow TEMA to match the time frame you are analyzing.
Use Cases:
Trend Reversals: The crossovers between the fast and slow TEMA provide clear signals for potential trend reversals, which can be used to enter or exit trades.
Momentum Confirmation: The color-coded TEMA lines allow traders to easily identify whether the short-term momentum is aligned with the long-term trend, helping to confirm the strength of a move.
Recommendations:
This indicator works well with other momentum-based tools like RSI or MACD for confirming signals and identifying overbought or oversold conditions. It is suitable for use across different asset classes, including stocks, cryptocurrencies, forex, and commodities.
Disclaimer:
The TEMA Crosses_AIT indicator should not be used as a standalone trading strategy. It is recommended to combine this indicator with other forms of analysis and risk management techniques. Always backtest the indicator on historical data before applying it to live trades.
VIDYA ProTrend Multi-Tier ProfitHello! This time is about a trend-following system.
VIDYA is quite an interesting indicator that adjusts dynamically to market volatility, making it more responsive to price changes compared to traditional moving averages. Balancing adaptability and precision, especially with the more aggressive short trade settings, challenged me to fine-tune the strategy for a variety of market conditions.
█ Introduction and How it is Different
The "VIDYA ProTrend Multi-Tier Profit" strategy is a trend-following system that combines the VIDYA (Variable Index Dynamic Average) indicator with Bollinger Bands and a multi-step take-profit mechanism.
Unlike traditional trend strategies, this system allows for more adaptive profit-taking, adjusting for long and short positions through distinct ATR-based and percentage-based targets. The innovation lies in its dynamic multi-tier approach to profit-taking, especially for short trades, where more aggressive percentages are applied using a multiplier. This flexibility helps adapt to various market conditions by optimizing trade management and profit allocation based on market volatility and trend strength.
BTCUSD 6hr performance
█ Strategy, How it Works: Detailed Explanation
The core of the "VIDYA ProTrend Multi-Tier Profit" strategy lies in the dual VIDYA indicators (fast and slow) that analyze price trends while accounting for market volatility. These indicators work alongside Bollinger Bands to filter trade entries and exits.
🔶 VIDYA Calculation
The VIDYA indicator is calculated using the following formula:
Smoothing factor (𝛼):
alpha = 2 / (Length + 1)
VIDYA formula:
VIDYA(t) = alpha * k * Price(t) + (1 - alpha * k) * VIDYA(t-1)
Where:
k = |Chande Momentum Oscillator (MO)| / 100
🔶 Bollinger Bands as a Volatility Filter
Bollinger Bands are calculated using a rolling mean and standard deviation of price over a specified period:
Upper Band:
BB_upper = MA + (K * stddev)
Lower Band:
BB_lower = MA - (K * stddev)
Where:
MA is the moving average,
K is the multiplier (typically 2), and
stddev is the standard deviation of price over the Bollinger Bands length.
These bands serve as volatility filters to identify potential overbought or oversold conditions, aiding in the entry and exit logic.
🔶 Slope Calculation for VIDYA
The slopes of both fast and slow VIDYAs are computed to assess the momentum and direction of the trend. The slope for a given VIDYA over its length is:
Slope = (VIDYA(t) - VIDYA(t-n)) / n
Where:
n is the length of the lookback period. Positive slope indicates bullish momentum, while negative slope signals bearish momentum.
LOCAL picture
🔶 Entry and Exit Conditions
- Long Entry: Occurs when the price moves above the slow VIDYA and the fast VIDYA is trending upward. Bollinger Bands confirm the signal when the price crosses the upper band, indicating bullish strength.
- Short Entry: Happens when the price drops below the slow VIDYA and the fast VIDYA trends downward. The signal is confirmed when the price crosses the lower Bollinger Band, showing bearish momentum.
- Exit: Based on VIDYA slopes flattening or reversing, or when the price hits specific ATR or percentage-based profit targets.
🔶 Multi-Step Take Profit Mechanism
The strategy incorporates three levels of take profit for both long and short trades:
- ATR-based Take Profit: Each step applies a multiple of the ATR (Average True Range) to the entry price to define the exit point.
The first level of take profit (long):
TP_ATR1_long = Entry Price + (2.618 * ATR)
etc.
█ Trade Direction
The strategy offers flexibility in defining the trading direction:
- Long: Only long trades are considered based on the criteria for upward trends.
- Short: Only short trades are initiated in bearish trends.
- Both: The strategy can take both long and short trades depending on the market conditions.
█ Usage
To use the strategy effectively:
- Adjust the VIDYA lengths (fast and slow) based on your preference for trend sensitivity.
- Use Bollinger Bands as a filter for identifying potential breakout or reversal scenarios.
- Enable the multi-step take profit feature to manage positions dynamically, allowing for partial exits as the price reaches specified ATR or percentage levels.
- Leverage the short trade multiplier for more aggressive take profit levels in bearish markets.
This strategy can be applied to different asset classes, including equities, forex, and cryptocurrencies. Adjust the input parameters to suit the volatility and characteristics of the asset being traded.
█ Default Settings
The default settings for this strategy have been designed for moderate to trending markets:
- Fast VIDYA Length (10): A shorter length for quick responsiveness to price changes. Increasing this length will reduce noise but may delay signals.
- Slow VIDYA Length (30): The slow VIDYA is set longer to capture broader market trends. Shortening this value will make the system more reactive to smaller price swings.
- Minimum Slope Threshold (0.05): This threshold helps filter out weak trends. Lowering the threshold will result in more trades, while raising it will restrict trades to stronger trends.
Multi-Step Take Profit Settings
- ATR Multipliers (2.618, 5.0, 10.0): These values define how far the price should move before taking profit. Larger multipliers widen the profit-taking levels, aiming for larger trend moves. In higher volatility markets, these values might be adjusted downwards.
- Percentage Levels (3%, 8%, 17%): These percentage levels define how much the price must move before taking profit. Increasing the percentages will capture larger moves, while smaller percentages offer quicker exits.
- Short TP Multiplier (1.5): This multiplier applies more aggressive take profit levels for short trades. Adjust this value based on the aggressiveness of your short trade management.
Each of these settings directly impacts the performance and risk profile of the strategy. Shorter VIDYA lengths and lower slope thresholds will generate more trades but may result in more whipsaws. Higher ATR multipliers or percentage levels can delay profit-taking, aiming for larger trends but risking partial gains if the trend reverses too early.
