Cyclical CALL/PUT StrategyThis script identifies optimal CALL (long) and PUT (short) entries using a cyclical price wave modeled from a sine function and confirmed with trend direction via a 200 EMA.
Strategy Highlights:
Cycle-Based Signal: Detects market rhythm with a smoothed sinusoidal wave.
Trend Confirmation: Filters entries using a customizable EMA (default: 200).
Auto-Scaling: Wave height adjusts dynamically to price action volatility.
Risk Parameters:
Take Profit: Default 5% (customizable)
Stop Loss: Default 2% (customizable)
Signal Triggers:
CALL Entry: Price crosses above the scaled wave and in an uptrend
PUT Entry: Price crosses below the scaled wave and in a downtrend
Inputs:
Cycle Length
Smoothing
Wave Height
EMA Trend Length
Take Profit %
Stop Loss %
Visuals:
Gray line = Scaled Cycle Wave
Orange line = 200 EMA Trend Filter
Best For: Traders looking to make 1–2 high-probability trades per week on SPY or other highly liquid assets.
Timeframes: Works well on 2-min, 15-min, and daily charts.
Cerca negli script per "stop loss"
TrendTwisterV1.5 (Forex Ready + Indicators)A Precision Trend-Following TradingView Strategy for Forex**
HullShiftFX is a Pine Script strategy for TradingView that combines the power of the **Hull Moving Average (HMA)** and a **shifted Exponential Moving Average (EMA)** with multi-layered momentum filters including **RSI** and **dual Stochastic Oscillators**.
It’s designed for traders looking to catch high-probability breakouts with tight risk management and visual clarity.
Chart settings:
1. Select "Auto - Fits data to screen"
2. Please Select "Scale Price Chart Only" (To make the chart not squished)
### ✅ Entry Conditions
**Long Position:**
- Price closes above the 12-period Hull Moving Average.
- Price closes above the 5-period EMA shifted forward by 2 bars.
- RSI is above 50.
- Stochastic Oscillator (12,3,3) %K is above 50.
- Stochastic Oscillator (5,3,3) %K is above 50.
- Hull MA crosses above the shifted EMA.
**Short Position:**
- Price closes below the 12-period Hull Moving Average.
- Price closes below the 5-period EMA shifted forward by 2 bars.
- RSI is below 50.
- Stochastic Oscillator (12,3,3) %K is below 50.
- Stochastic Oscillator (5,3,3) %K is below 50.
- Hull MA crosses below the shifted EMA.
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## 📉 Risk Management
- **Stop Loss:** Set at the low (for long) or high (for short) of the previous 2 candles.
- **Take Profit:** Calculated at a risk/reward ratio of **1.65x** the stop loss distance.
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## 📊 Indicators Used
- **Hull Moving Average (12)**
- **Exponential Moving Average (5) **
- **Relative Strength Index (14)**
- **Stochastic Oscillators:**
- %K (12,3,3)
- %K (5,3,3)
NY First Candle Break and RetestStrategy Overview
Session and Time Parameters:
The strategy focuses on the New York trading session, starting at 9:30 AM and lasting for a predefined session length, typically 3 to 4 hours. This timing captures the most active market hours, providing ample trading opportunities.
Strategy Parameters:
Utilizes the Average True Range (ATR) to set dynamic stop-loss levels, ensuring risk is managed according to market volatility.
Employs a reward-to-risk ratio to determine take profit levels, aiming for a balanced approach between potential gains and losses.
Strategy Settings:
Incorporates simple moving averages (EMA) and the Volume Weighted Average Price (VWAP) to identify trend direction and price levels.
Volume confirmation is used to validate breakouts, ensuring trades are based on significant market activity.
Trade Management:
Features a trailing stop mechanism to lock in profits as the trade moves in favor, with multiple take profit levels to secure gains incrementally.
The strategy is designed to handle both long and short positions, adapting to market conditions.
Alert Settings:
Provides alerts for key events such as session start, breakout, retest, and entry signals, helping traders stay informed and act promptly.
Visual cues on the chart highlight entry and exit points, making it easier for beginners to follow the strategy.
This strategy is particularly suited for the current volatile market environment, where simplicity and clear guidelines can help beginner traders navigate the complexities of trading. It emphasizes risk management and uses straightforward indicators to make informed trading decisions.
I put together this Trading View scalping strategy for futures markets with some help from Claude AI. Shoutout to everyone who gave me advice along the way—I really appreciate it! I’m sure there’s room for improvement, so feel free to share your thoughts… just go easy on me. :)
Scalping 15min: EMA + MACD + RSI + ATR-based SL/TP📈 Strategy: 15-Minute Scalping — EMA + MACD + RSI + ATR-based SL/TP
This scalping strategy is designed for 15-minute charts and combines trend-following and momentum confirmation with dynamic stop loss and take profit levels based on volatility.
🔧 Indicators Used:
EMA 50 — identifies the main trend
MACD Histogram — confirms momentum direction
RSI (14) — filters overbought/oversold conditions
ATR (14) — dynamically sets SL and TP based on market volatility
📊 Entry Conditions:
Long Entry:
Price is above EMA 50
MACD histogram is positive
RSI is above 50 but below 70
Short Entry:
Price is below EMA 50
MACD histogram is negative
RSI is below 50 but above 30
🛑 Risk Management:
Stop Loss: 1×ATR (user-configurable)
Take Profit: 2×ATR (user-configurable)
These values can be adjusted in the script inputs depending on your risk/reward preference or market conditions.
⚠️ Notes:
Strategy is optimized for scalping fast-moving pairs (e.g. crypto, forex).
Works best in trending markets.
Use backtesting and forward testing before live trading.
Smart Grid Scalping (Pullback) Strategy[BullByte]The Smart Grid Scalping (Pullback) Strategy is a high-frequency trading strategy designed for short-term traders who seek to capitalize on market pullbacks. This strategy utilizes a dynamic ATR-based grid system to define optimal entry points, ensuring precise trade execution. It integrates volatility filtering and an RSI-based confirmation mechanism to enhance signal accuracy and reduce false entries.
This strategy is specifically optimized for scalping by dynamically adjusting trade levels based on current market conditions. The grid-based system helps capture retracement opportunities while maintaining strict trade management through predefined profit targets and trailing stop-loss mechanisms.
Key Features :
1. ATR-Based Grid System :
- Uses a 10-period ATR to dynamically calculate grid levels for entry points.
- Prevents chasing trades by ensuring price has reached key levels before executing entries.
2. No Trade Zone Protection :
- Avoids low-volatility zones where price action is indecisive.
- Ensures only high-momentum trades are executed to improve success rate.
3. RSI-Based Entry Confirmation :
- Long trades are triggered when RSI is below 30 (oversold) and price is in the lower grid zone.
- Short trades are triggered when RSI is above 70 (overbought) and price is in the upper grid zone.
4. Automated Trade Execution :
- Long Entry: Triggered when price drops below the first grid level with sufficient volatility.
- Short Entry: Triggered when price exceeds the highest grid level with sufficient volatility.
5. Take Profit & Trailing Stop :
- Profit target set at a customizable percentage (default 0.2%).
- Adaptive trailing stop mechanism using ATR to lock in profits while minimizing premature exits.
6. Visual Trade Annotations :
- Clearly labeled "LONG" and "SHORT" markers appear at trade entries for better visualization.
- Grid levels are plotted dynamically to aid decision-making.
Strategy Logic :
- The script first calculates the ATR-based grid levels and ensures price action has sufficient volatility before allowing trades.
- An additional RSI filter is used to ensure trades are taken at ideal market conditions.
- Once a trade is executed, the script implements a trailing stop and predefined take profit to maximize gains while reducing risks.
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Disclaimer :
Risk Warning :
This strategy is provided for educational and informational purposes only. Trading involves significant risk, and past performance is not indicative of future results. Users are advised to conduct their own due diligence and risk management before using this strategy in live trading.
The developer and publisher of this script are not responsible for any financial losses incurred by the use of this strategy. Market conditions, slippage, and execution quality can affect real-world trading outcomes.
Use this script at your own discretion and always trade responsibly.
PVSRA v5Overview of the PVSRA Strategy
This strategy is designed to detect and capitalize on volume-driven threshold breaches in price candles. It operates on the premise that when a high-volume candle breaks a critical price threshold, not all orders are filled within that candle’s range. This creates an imbalance—similar to a physical system being perturbed—causing the price to revert toward the level where the breach occurred to “absorb” the residual orders.
Key Features and Their Theoretical Underpinnings
Dynamic Volume Analysis and Threshold Detection
Volume Surges as Market Perturbations:
The script computes a moving average of volume over a short window and flags moments when the current volume significantly exceeds this average. These surges act as a perturbation—injecting “energy” into the market.
Adaptive Abnormal Volume Threshold:
By calculating a dynamic abnormal threshold using a daily volume average (via an 89-period VWMA) and standard deviation, the strategy identifies when the current volume is abnormally high. This mechanism mirrors the idea that when a system is disturbed (here, by a volume surge), it naturally seeks to return to equilibrium.
Candle Coloring and Visual Signal Identification
Differentiation of Candle Types:
The script distinguishes between bullish (green) and bearish (red) candles. It applies different colors based on the strength of the volume signal, providing a clear, visual representation of whether a candle is likely to trigger a price reversion.
Implication of Unfilled Orders:
A red (bearish) candle with high volume implies that sell pressure has pushed the price past a critical threshold—yet not all buy orders have been fulfilled. Conversely, a green (bullish) candle indicates that aggressive buying has left pending sell orders. In both cases, the market is expected to reverse toward the breach point to restore balance.
Trade Execution Logic: Normal and Reversal Trades
Normal Trades:
When a high-volume candle breaches a threshold and meets the directional conditions (e.g., a red candle paired with price above a daily upper band), the strategy enters a trade anticipating a reversion. The underlying idea is that the market will move back to the level where the threshold was crossed—clearing the residual orders in a manner analogous to a system following the path of least resistance.
Reversal Trades:
The strategy also monitors for clusters of consecutive signals within a short lookback period. When multiple signals accumulate, it interprets this as the market having overextended and, in a corrective move, reverses the typical trade direction. This inversion captures the market’s natural tendency to “correct” itself by moving in discrete, quantized steps—each step representing the absorption of a minimum quantum of order imbalance.
Risk and Trade Management
Stop Loss and Take Profit Buffers:
Both normal and reversal trades include predetermined buffers for stop loss and take profit levels. This systematic risk management approach is designed to capture the anticipated reversion while minimizing potential losses, aligning with the idea that market corrections follow the most energy-efficient path back to equilibrium.
Symbol Flexibility:
An option to override the chart’s symbol allows the strategy to be applied consistently across different markets, ensuring that the volume and price dynamics are analyzed uniformly.
Conceptual Bridge: From Market Dynamics to Trade Execution
At its core, the strategy treats market price movements much like a physical system that seeks to minimize “transactional energy” or inefficiency. When a price candle breaches a key threshold on high volume, it mimics an injection of energy into the system. The subsequent price reversion is the market’s natural response—moving in the most efficient path back to balance. This perspective is akin to the principle of least action, where the system evolves along the trajectory that minimizes cumulative imbalance, and it acknowledges that these corrections occur in discrete steps reflective of quantized order execution.
This unified framework allows the PVSRA strategy to not only identify when significant volume-based threshold breaches occur but also to systematically execute trades that benefit from the expected corrective moves.
Liquidity Sweep Filter Strategy [AlgoAlpha X PineIndicators]This strategy is based on the Liquidity Sweep Filter developed by AlgoAlpha. Full credit for the concept and original indicator goes to AlgoAlpha.
The Liquidity Sweep Filter Strategy is a non-repainting trading system designed to identify liquidity sweeps, trend shifts, and high-impact price levels. It incorporates volume-based liquidation analysis, trend confirmation, and dynamic support/resistance detection to optimize trade entries and exits.
This strategy helps traders:
Detect liquidity sweeps where major market participants trigger stop losses and liquidations.
Identify trend shifts using a volatility-based moving average system.
Analyze volume distribution with a built-in volume profile visualization.
Filter noise by differentiating between major and minor liquidity sweeps.
How the Liquidity Sweep Filter Strategy Works
1. Trend Detection Using Volatility-Based Filtering
The strategy applies a volatility-adjusted moving average system to determine trend direction:
A central trend line is calculated using an EMA smoothed over a user-defined length.
Upper and lower deviation bands are created based on the average price deviation over multiple periods.
If price closes above the upper band, the strategy signals an uptrend.
If price closes below the lower band, the strategy signals a downtrend.
This approach ensures that trend shifts are confirmed only when price significantly moves beyond normal market fluctuations.
2. Liquidity Sweep Detection
Liquidity sweeps occur when price temporarily breaks key levels, triggering stop-loss liquidations or margin call events. The strategy tracks swing highs and lows, marking potential liquidity grabs:
Bearish Liquidity Sweeps – Price breaks a recent high, then reverses downward.
Bullish Liquidity Sweeps – Price breaks a recent low, then reverses upward.
Volume Integration – The strategy analyzes trading volume at each sweep to differentiate between major and minor sweeps.
Key levels where liquidity sweeps occur are plotted as color-coded horizontal lines:
Red lines indicate bearish liquidity sweeps.
Green lines indicate bullish liquidity sweeps.
Labels are displayed at each sweep, showing the volume of liquidated positions at that level.
3. Volume Profile Analysis
The strategy includes an optional volume profile visualization, displaying how trading volume is distributed across different price levels.
Features of the volume profile:
Point of Control (POC) – The price level with the highest traded volume is marked as a key area of interest.
Bounding Box – The profile is enclosed within a transparent box, helping traders visualize the price range of high trading activity.
Customizable Resolution & Scale – Traders can adjust the granularity of the profile to match their preferred time frame.
The volume profile helps identify zones of strong support and resistance, making it easier to anticipate price reactions at key levels.
Trade Entry & Exit Conditions
The strategy allows traders to configure trade direction:
Long Only – Only takes long trades.
Short Only – Only takes short trades.
Long & Short – Trades in both directions.
Entry Conditions
Long Entry:
A bullish trend shift is confirmed.
A bullish liquidity sweep occurs (price sweeps below a key level and reverses).
The trade direction setting allows long trades.
Short Entry:
A bearish trend shift is confirmed.
A bearish liquidity sweep occurs (price sweeps above a key level and reverses).
The trade direction setting allows short trades.
Exit Conditions
Closing a Long Position:
A bearish trend shift occurs.
The position is liquidated at a predefined liquidity sweep level.
Closing a Short Position:
A bullish trend shift occurs.
The position is liquidated at a predefined liquidity sweep level.
Customization Options
The strategy offers multiple adjustable settings:
Trade Mode: Choose between Long Only, Short Only, or Long & Short.
Trend Calculation Length & Multiplier: Adjust how trend signals are calculated.
Liquidity Sweep Sensitivity: Customize how aggressively the strategy identifies sweeps.
Volume Profile Display: Enable or disable the volume profile visualization.
Bounding Box & Scaling: Control the size and position of the volume profile.
Color Customization: Adjust colors for bullish and bearish signals.
Considerations & Limitations
Liquidity sweeps do not always result in reversals. Some price sweeps may continue in the same direction.
Works best in volatile markets. In low-volatility environments, liquidity sweeps may be less reliable.
Trend confirmation adds a slight delay. The strategy ensures valid signals, but this may result in slightly later entries.
Large volume imbalances may distort the volume profile. Adjusting the scale settings can help improve visualization.
Conclusion
The Liquidity Sweep Filter Strategy is a volume-integrated trading system that combines liquidity sweeps, trend analysis, and volume profile data to optimize trade execution.
By identifying key price levels where liquidations occur, this strategy provides valuable insight into market behavior, helping traders make better-informed trading decisions.
Key use cases for this strategy:
Liquidity-Based Trading – Capturing moves triggered by stop hunts and liquidations.
Volume Analysis – Using volume profile data to confirm high-activity price zones.
Trend Following – Entering trades based on confirmed trend shifts.
Support & Resistance Trading – Using liquidity sweep levels as dynamic price zones.
This strategy is fully customizable, allowing traders to adapt it to different market conditions, timeframes, and risk preferences.
Full credit for the original concept and indicator goes to AlgoAlpha.
NSE Index Strategy with Entry/Exit MarkersExplanation of the Code
Trend Filter (200 SMA):
The line trendSMA = ta.sma(close, smaPeriod) calculates the 200‑period simple moving average. By trading only when the current price is above this SMA (inUptrend = close > trendSMA), we aim to trade in the direction of the dominant trend.
RSI Entry Signal:
The RSI is calculated with rsiValue = ta.rsi(close, rsiPeriod). The script checks for an RSI crossover above the oversold threshold using ta.crossover(rsiValue, rsiOversold). This helps capture a potential reversal from a minor pullback in an uptrend.
ATR-Based Exits:
ATR is computed by atrValue = ta.atr(atrPeriod) and is used to set the stop loss and take profit levels:
Stop Loss: stopLossPrice = close - atrMultiplier * atrValue
Take Profit: takeProfitPrice = close + atrMultiplier * atrValue
This dynamic approach allows the exit levels to adjust according to the current market volatility.
Risk and Money Management:
The strategy uses a fixed percentage of equity (10% by default) for each trade. The built‑in commission parameter helps simulate real-world trading costs.
Simple Time-Based Strategy(Price Action Hypothesis)Core Theory: Trend Continuation Pattern Recognition**
1. **Price Action Hypothesis**
The strategy is built on the assumption that consecutive price movements (3-bar patterns) indicate momentum continuation:
- *Long Pattern*: Three consecutive higher closes combined with ascending highs
- *Short Pattern*: Three consecutive lower closes combined with descending lows
This reflects a belief that sustained directional price movement creates self-reinforcing trends that can be captured through simple pattern recognition.
2. **Time-Based Risk Management**
Implements a dynamic exit mechanism:
- *Training Phase*: 5-bar holding period (quick turnover)
- *Testing Phase*: 10-bar holding period (extended exposure)
This dual timeframe approach suggests the hypothesis that market conditions may require different holding durations in different market eras.
3. **Adaptive Market Hypothesis**
The structure incorporates two distinct phases:
- *Training Period (11 years)*: Pattern recognition without stop losses
- *Testing Period*: Pattern recognition with stop losses
This assumes markets may change character over time, requiring different risk parameters in different epochs.
4. **Asymmetric Risk Control**
Implements stop-losses only in the testing phase:
- Fixed 500-pip (point) stop distance
- Activated post-training period
This reflects a belief that historical patterns might need different risk constraints than real-time trading.
5. **Dual-Path Validation**
The split between training/testing phases suggests:
- Pattern validity should first be confirmed without protective stops
- Real-world implementation requires added risk constraints
6. **Market Efficiency Paradox**
The simultaneous use of both long/short entries assumes:
- Markets exhibit persistent inefficiencies
- These inefficiencies manifest differently in bullish/bearish conditions
- A symmetric approach can capture opportunities in both directions
7. **Behavioral Finance Elements**
The 3-bar pattern recognition potentially exploits:
- Herd mentality in trend formation
- Delayed reaction to price momentum
- Cognitive bias in trend confirmation
8. **Quantitative Time Segmentation**
The annual-based period division (training vs testing) implies:
- Market cycles operate on multi-year timeframes
- Strategy robustness requires validation across different market regimes
- Parameter sensitivity needs temporal validation
This strategy combines elements of technical pattern recognition, temporal adaptability, and phased risk management to create a systematic approach to trend exploitation. The theoretical framework suggests markets exhibit persistent but evolving patterns that can be systematically captured through rule-based execution.
Advanced Multi-Timeframe Trading System (Risk Managed)Description:
This strategy is an original approach that combines two main analytical components to identify potential trade opportunities while simulating realistic trading conditions:
1. Market Trend Analysis via an Approximate Hurst Exponent
• What It Does:
The strategy computes a rough measure of market trending using an approximate Hurst exponent. A value above 0.5 suggests persistent, trending behavior, while a value below 0.5 indicates a tendency toward mean-reversion.
• How It’s Used:
The Hurst exponent is calculated on both the chart’s current timeframe and a higher timeframe (default: Daily) to capture both local and broader market dynamics.
2. Fibonacci Retracement Levels
• What It Does:
Using daily high and low data from a selected timeframe (default: Daily), the script computes key Fibonacci retracement levels.
• How It’s Used:
• The 61.8% level (Golden Ratio) serves as a key threshold:
• A long entry is signaled when the price crosses above this level if the daily Hurst exponent confirms a trending market.
• The 38.2% level is used to identify short-entry opportunities when the price crosses below it and the daily Hurst indicates non-trending conditions.
Signal Logic:
• Long Entry:
When the price crosses above the 61.8% Fibonacci level (Golden Ratio) and the daily Hurst exponent is greater than 0.5, suggesting a trending market.
• Short Entry:
When the price crosses below the 38.2% Fibonacci level and the daily Hurst exponent is less than 0.5, indicating a less trending or potentially reversing market.
Risk Management & Trade Execution:
• Stop-Loss:
Each trade is risk-managed with a stop-loss set at 2% below (for longs) or above (for shorts) the entry price. This ensures that no single trade risks more than a small, sustainable portion of the account.
• Take Profit:
A take profit order targets a risk-reward ratio of 1:2 (i.e., the target profit is twice the amount risked).
• Position Sizing:
Trades are executed with a fixed position size equal to 10% of account equity.
• Trade Frequency Limits:
• Daily Limit: A maximum of 5 trades per day
• Overall Limit: No more than 510 trades during the backtesting period (e.g., since 2019)
These limits are imposed to simulate realistic trading frequency and to avoid overtrading in backtest results.
Backtesting Parameters:
• Initial Capital: $10,000
• Commission: 0.1% per trade
• Slippage: 1 tick per bar
These settings aim to reflect the conditions faced by the average trader and help ensure that the backtesting results are realistic and not misleading.
Chart Overlays & Visual Aids:
• Fibonacci Levels:
The key Fibonacci retracement levels are plotted on the chart, and the zone between the 61.8% and 38.2% levels is highlighted to show a key retracement area.
• Market Trend Background:
The chart background is tinted green when the daily Hurst exponent indicates a trending market (value > 0.5) and red otherwise.
• Information Table:
An on-chart table displays key parameters such as the current Hurst exponent, daily Hurst value, the number of trades executed today, and the global trade count.
Disclaimer:
Past performance is not indicative of future results. This strategy is experimental and provided solely for educational purposes. It is essential that you backtest and paper trade using your own settings before considering any live deployment. The Hurst exponent calculation is an approximation and should be interpreted as a rough gauge of market behavior. Adjust the parameters and risk management settings according to your personal risk tolerance and market conditions.
Additional Notes:
• Originality & Usefulness:
This script is an original mashup that combines trend analysis with Fibonacci retracement methods. The description above explains how these components work together to provide trading signals.
• Realistic Results:
The strategy uses realistic account sizes, commission rates, slippage, and risk management rules to generate backtesting results that are representative of real-world trading.
• Educational Purpose:
This script is intended to support the TradingView community by offering insights into combining multiple analysis techniques in one strategy. It is not a “get-rich-quick” system but rather an educational tool to help traders understand risk management and trade signal logic.
By using this script, you acknowledge that trading involves risk and that you are responsible for testing and adjusting the strategy to fit your own trading environment. This publication is fully open source, and any modifications should include proper attribution if significant portions of the code are reused.
FRAMA-LRO📌 FRAMA × LRO Auto-Trading Strategy - Adaptive Trend & Momentum System
Overview
This Pine Script provides an automated trading strategy that combines FRAMA (Fractal Adaptive Moving Average) and LRO (Linear Regression Oscillator) to enhance trend detection and momentum analysis. Unlike traditional moving averages, FRAMA dynamically adjusts to price volatility, while LRO effectively measures momentum for high-precision entries.
📌 Key Features
1. Dynamic Trend & Momentum Synergy
FRAMA: Detects price trends by adjusting to market conditions using fractal dimensions.
LRO: Filters trades based on linear regression slope momentum.
Breakout Confirmation: Entry is validated when price breaks FRAMA bands with LRO support.
2. Realistic Backtesting Settings
Initial Capital: $5,000 (more in line with retail traders).
Risk Management: 5% equity per trade.
Slippage & Commission: Adjusted to realistic values (1 pip slippage, 94 pips spread per trade).
Backtest Data: Covers at least 100 trades for statistical significance.
3. Clear Trade Logic
Long Entry: Price breaks above FRAMA upper band & LRO > 0.
Short Entry: Price breaks below FRAMA lower band & LRO < 0.
Stop-Loss: Dynamic ATR-based calculation.
Take-Profit: Fixed risk-reward ratio (1:2).
📌 How It Works
The system identifies trend strength with FRAMA, then confirms momentum shifts with LRO before executing trades. This ensures higher accuracy and filters false breakouts.
📌 Visual Aids for Clarity
Color-Coded Candles:
🟢 Uptrend (LRO > 0)
🔵 Downtrend (LRO < 0)
⚪ Neutral (LRO ≈ 0)
Chart Annotations: Clearly marked trade signals for easy reference.
📌 Risk Management & Automation
Fully automated execution of entries, stop-loss, and take-profit.
ATR-based volatility adaptation for dynamic SL adjustments.
Customizable parameters (period, volatility settings, risk percentage).
📌 Originality & Enhancements
This script is not just a combination of FRAMA & LRO, but an optimized system designed to:
Improve signal accuracy using adaptive trend detection.
Eliminate noise with LRO-based momentum filtering.
Implement dynamic risk management via ATR-based SL.
Influences & Acknowledgments
This strategy builds on methodologies inspired by ChartPrime and BigBeluga, refining their concepts for a systematic approach.
📌 Disclaimer
This script is for educational purposes only. Past performance does not guarantee future results. Always manage risk appropriately.
Optimized Engulfing StrategyOptimized Engulfing Strategy
The Optimized Engulfing Strategy is a trend-following system designed to capitalize on bullish and bearish engulfing patterns in the market. It uses a combination of price action, trend direction, and volatility-based risk management to execute high-probability trades.
Key Components:
Bullish Engulfing Pattern:
A bullish engulfing candle is identified when:
The current candle closes above its open (bullish).
The previous candle closes below its open (bearish).
The current candle's close is higher than the previous candle's open.
The current candle's open is lower than the previous candle's close.
This pattern signals potential bullish momentum.
Bearish Engulfing Pattern:
A bearish engulfing candle is identified when:
The current candle closes below its open (bearish).
The previous candle closes above its open (bullish).
The current candle's close is lower than the previous candle's open.
The current candle's open is higher than the previous candle's close.
This pattern signals potential bearish momentum.
Trend Confirmation:
Trades are only taken in the direction of the trend:
Buy: When the 50-period SMA (simple moving average) is above the 200-period SMA, indicating an uptrend.
Sell: When the 50-period SMA is below the 200-period SMA, indicating a downtrend.
Risk Management:
Stop Loss: Placed below the low of the engulfing candle (for buys) or above the high (for sells), with an additional buffer based on the ATR (Average True Range) multiplied by a user-defined factor (default: 1.5).
Take Profit: Calculated using a fixed risk-to-reward ratio (default: 1:2), ensuring a potential reward that is double the risk.
Session Filtering:
Trades can be limited to specific trading hours using a customizable session filter (default: 24 hours).
Trade Execution:
Separate logic is implemented for buy and sell trades, allowing independent toggling of long or short positions via user inputs.
Visualization:
Bullish and bearish engulfing candles are highlighted on the chart for clarity.
The ATR value is displayed in the top-right corner of the chart for reference.
How It Works:
Identify a bullish or bearish engulfing pattern.
Confirm the direction of the trend using the 50 SMA and 200 SMA.
Ensure the market is within the allowed session filter (e.g., London or New York sessions).
Enter a trade if all conditions are met:
Long trades for bullish engulfing patterns in an uptrend.
Short trades for bearish engulfing patterns in a downtrend.
Manage the trade using a stop loss and take profit based on ATR and the risk-reward ratio.
HOD/LOD/PMH/PML/PDH/PDL Strategy by @tradingbauhaus This script is a trading strategy @tradingbauhaus designed to trade based on key price levels, such as the High of Day (HOD), Low of Day (LOD), Premarket High (PMH), Premarket Low (PML), Previous Day High (PDH), and Previous Day Low (PDL). Below, I’ll explain in detail what the script does:
Core Functionality of the Script:
Calculates Key Price Levels:
HOD (High of Day): The highest price of the current day.
LOD (Low of Day): The lowest price of the current day.
PMH (Premarket High): The highest price during the premarket session (before the market opens).
PML (Premarket Low): The lowest price during the premarket session.
PDH (Previous Day High): The highest price of the previous day.
PDL (Previous Day Low): The lowest price of the previous day.
Draws Horizontal Lines on the Chart:
Plots horizontal lines on the chart for each key level (HOD, LOD, PMH, PML, PDH, PDL) with specific colors for easy visual identification.
Defines Entry and Exit Rules:
Long Entry (Buy): If the price crosses above the PMH (Premarket High) or the PDH (Previous Day High).
Short Entry (Sell): If the price crosses below the PML (Premarket Low) or the PDL (Previous Day Low).
Long Exit: If the price reaches the HOD (High of Day) during a long position.
Short Exit: If the price reaches the LOD (Low of Day) during a short position.
How the Script Works Step by Step:
Calculates Key Levels:
Uses the request.security function to fetch the HOD and LOD of the current day, as well as the highs and lows of the previous day (PDH and PDL).
Calculates the PMH and PML during the premarket session (before 9:30 AM).
Plots Levels on the Chart:
Uses the plot function to draw horizontal lines on the chart representing the key levels (HOD, LOD, PMH, PML, PDH, PDL).
Each level has a specific color for easy identification:
HOD: White.
LOD: Purple.
PDH: Orange.
PDL: Blue.
PMH: Green.
PML: Red.
Defines Trading Rules:
Uses conditions with ta.crossover and ta.crossunder to detect when the price crosses key levels.
Long Entry: If the price crosses above the PMH or PDH, a long position (buy) is opened.
Short Entry: If the price crosses below the PML or PDL, a short position (sell) is opened.
Long Exit: If the price reaches the HOD during a long position, the position is closed.
Short Exit: If the price reaches the LOD during a short position, the position is closed.
Executes Orders Automatically:
Uses the strategy.entry and strategy.close functions to open and close positions automatically based on the defined rules.
Advantages of This Strategy:
Based on Key Levels: Uses important price levels that often act as support and resistance.
Easy to Visualize: Horizontal lines on the chart make it easy to identify levels.
Automated: Entries and exits are executed automatically based on the defined rules.
Limitations of This Strategy:
Dependent on Volatility: Works best in markets with significant price movements.
False Crosses: There may be false crosses that generate incorrect signals.
No Advanced Risk Management: Does not include dynamic stop-loss or take-profit mechanisms.
How to Improve the Strategy:
Add Stop-Loss and Take-Profit: To limit losses and lock in profits.
Filter Signals with Indicators: Use RSI, MACD, or other indicators to confirm signals.
Optimize Levels: Adjust key levels based on the asset’s behavior.
In summary, this script is a trading strategy that operates based on key price levels, such as HOD, LOD, PMH, PML, PDH, and PDL. It is useful for traders who want to trade based on significant support and resistance levels.
DemaRSI StrategyThis is a repost to a old script that cant be updated anymore, the request was made on Feb, 27, 2016.
Here's a engaging description for the tradingview script:
**DemaRSI Strategy: A Proven Trading System**
Join thousands of traders who have already experienced the power of this highly effective strategy. The DemaRSI system combines two powerful indicators - DEMA (Double Exponential Moving Average) and RSI (Relative Strength Index) - to generate profitable trades with minimal risk.
**Key Features:**
* **Trend-Following**: Our algorithm identifies strong trends using a combination of DEMA and RSI, allowing you to ride the waves of market momentum.
* **Risk Management**: The system includes built-in stop-loss and take-profit levels, ensuring that your gains are protected and losses are minimized.
* **Session-Based Trading**: Trade during specific sessions only (e.g., London or New York) for even more targeted results.
* **Customizable Settings**: Adjust the length of moving averages, RSI periods, and other parameters to suit your trading style.
**What You'll Get:**
* A comprehensive strategy that can be used with any broker or platform
* Easy-to-use interface with customizable settings
* Real-time performance metrics and backtesting capabilities
**Start Trading Like a Pro Today!**
This script is designed for intermediate to advanced traders who want to take their trading game to the next level. With its robust risk management features, this strategy can help you achieve consistent profits in various market conditions.
**Disclaimer:** This script is not intended as investment advice and should be used at your own discretion. Trading carries inherent risks, and losses are possible.
~Llama3
DNSE VN301!, SMA & EMA Cross StrategyDiscover the tailored Pinescript to trade VN30F1M Future Contracts intraday, the strategy focuses on SMA & EMA crosses to identify potential entry/exit points. The script closes all positions by 14:25 to avoid holding any contracts overnight.
HNX:VN301!
www.tradingview.com
Setting & Backtest result:
1-minute chart, initial capital of VND 100 million, entering 4 contracts per time, backtest result from Jan-2024 to Nov-2024 yielded a return over 40%, executed over 1,000 trades (average of 4 trades/day), winning trades rate ~ 30% with a profit factor of 1.10.
The default setting of the script:
A decent optimization is reached when SMA and EMA periods are set to 60 and 15 respectively while the Long/Short stop-loss level is set to 20 ticks (2 points) from the entry price.
Entry & Exit conditions:
Long signals are generated when ema(15) crosses over sma(60) while Short signals happen when ema(15) crosses under sma(60). Long orders are closed when ema(15) crosses under sma(60) while Short orders are closed when ema(15) crosses over sma(60).
Exit conditions happen when (whichever came first):
Another Long/Short signal is generated
The Stop-loss level is reached
The Cut-off time is reached (14:25 every day)
*Disclaimers:
Futures Contracts Trading are subjected to a high degree of risk and price movements can fluctuate significantly. This script functions as a reference source and should be used after users have clearly understood how futures trading works, accessed their risk tolerance level, and are knowledgeable of the functioning logic behind the script.
Users are solely responsible for their investment decisions, and DNSE is not responsible for any potential losses from applying such a strategy to real-life trading activities. Past performance is not indicative/guarantee of future results, kindly reach out to us should you have specific questions about this script.
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Khám phá Pinescript được thiết kế riêng để giao dịch Hợp đồng tương lai VN30F1M trong ngày, chiến lược tập trung vào các đường SMA & EMA cắt nhau để xác định các điểm vào/ra tiềm năng. Chiến lược sẽ đóng tất cả các vị thế trước 14:25 để tránh giữ bất kỳ hợp đồng nào qua đêm.
Thiết lập & Kết quả backtest:
Chart 1 phút, vốn ban đầu là 100 triệu đồng, vào 4 hợp đồng mỗi lần, kết quả backtest từ tháng 1/2024 tới tháng 11/2024 mang lại lợi nhuận trên 40%, thực hiện hơn 1.000 giao dịch (trung bình 4 giao dịch/ngày), tỷ lệ giao dịch thắng ~ 30% với hệ số lợi nhuận là 1,10.
Thiết lập mặc định của chiến lược:
Đạt được một mức tối ưu ổn khi SMA và EMA periods được đặt lần lượt là 60 và 15 trong khi mức cắt lỗ được đặt thành 20 tick (2 điểm) từ giá vào.
Điều kiện Mở và Đóng vị thế:
Tín hiệu Long được tạo ra khi ema(15) cắt trên sma(60) trong khi tín hiệu Short xảy ra khi ema(15) cắt dưới sma(60). Lệnh Long được đóng khi ema(15) cắt dưới sma(60) trong khi lệnh Short được đóng khi ema(15) cắt lên sma(60).
Điều kiện đóng vị thể xảy ra khi (tùy điều kiện nào đến trước):
Một tín hiệu Long/Short khác được tạo ra
Giá chạm mức cắt lỗ
Lệnh chưa đóng nhưng tới giờ cut-off (14:25 hàng ngày)
*Tuyên bố miễn trừ trách nhiệm:
Giao dịch hợp đồng tương lai có mức rủi ro cao và giá có thể dao động đáng kể. Chiến lược này hoạt động như một nguồn tham khảo và nên được sử dụng sau khi người dùng đã hiểu rõ cách thức giao dịch hợp đồng tương lai, đã đánh giá mức độ chấp nhận rủi ro của bản thân và hiểu rõ về logic vận hành của chiến lược này.
Người dùng hoàn toàn chịu trách nhiệm về các quyết định đầu tư của mình và DNSE không chịu trách nhiệm về bất kỳ khoản lỗ tiềm ẩn nào khi áp dụng chiến lược này vào các hoạt động giao dịch thực tế. Hiệu suất trong quá khứ không chỉ ra/cam kết kết quả trong tương lai, vui lòng liên hệ với chúng tôi nếu bạn có thắc mắc cụ thể về chiến lược giao dịch này.
XAUUSD Trend Strategy### Description of the XAUUSD Trading Strategy with Pine Script
This strategy is designed to trade gold (**XAUUSD**) using proven technical analysis principles. It combines key indicators such as **Exponential Moving Averages (EMA)**, the **Relative Strength Index (RSI)**, and **Bollinger Bands** to identify trading opportunities in trending market conditions.
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#### Objective:
To maximize profits by identifying trend-aligned entry points while minimizing risks through well-defined Stop Loss and Take Profit levels.
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### How It Works
1. **Indicators Used:**
- **Exponential Moving Averages (EMA):** Tracks short-term and long-term trends to confirm market direction.
- **Relative Strength Index (RSI):** Detects overbought or oversold conditions for potential reversals or trend continuation.
- **Bollinger Bands:** Measures volatility to identify breakout or reversion points.
2. **Entry Rules:**
- **Long (Buy):** Triggered when:
- The short-term EMA crosses above the long-term EMA (bullish trend confirmation).
- RSI exits oversold territory (<30), signaling buying momentum.
- The price breaks above the upper Bollinger Band, indicating a strong trend.
- **Short (Sell):** Triggered when:
- The short-term EMA crosses below the long-term EMA (bearish trend confirmation).
- RSI exits overbought territory (>70), signaling selling momentum.
- The price breaks below the lower Bollinger Band, indicating a strong downtrend.
3. **Risk Management:**
- **Stop Loss:** Automatically calculated based on a percentage of equity risk (customizable via inputs).
- **Take Profit:** Defined using a risk-to-reward ratio, ensuring consistent profitability when trades succeed.
4. **Visualization:**
- The chart displays the EMAs, Bollinger Bands, and entry/exit points for clear analysis.
---
### Key Features:
- **Customizable Parameters:** You can adjust EMAs, RSI thresholds, Bollinger Band settings, and risk levels to suit your trading style.
- **Alerts:** Automatic alerts for potential trade setups.
- **Backtesting-Ready:** Easily test historical performance on TradingView.
---
This strategy is ideal for gold traders looking for a systematic, rule-based approach to trading trends with minimal emotional interference.
Zero-Lag MA Trend FollowingScript Name: Zero-Lag MA Trend Following Auto-Trading
Purpose and Unique Features:
This script is designed to implement a trend-following auto-trading strategy by combining the Zero-Lag Moving Average (ZLMA), Exponential Moving Average (EMA), and ATR Bands. To differentiate it from similar scripts, the following key aspects are emphasized:
Zero-Lag MA (ZLMA):
Responds quickly to price changes, minimizing lag compared to EMA.
Detects crossovers with EMA and generates Diamond Signals to indicate trend reversals.
ATR Bands:
Measures market volatility to set stop-loss levels.
Helps optimize entry points and manage risk effectively.
Diamond Signals:
A vital visual cue indicating the early stages of trend reversals.
Green diamonds signal an uptrend, while red diamonds signal a downtrend.
Each component plays a distinct role, working synergistically to enhance trend detection and risk management. This system doesn’t merely combine indicators but optimizes them for comprehensive trend-following and risk control.
Usage Instructions:
Entry Conditions:
Long Entry:
Enter when a green Diamond Signal appears (ZLMA crosses above EMA).
Short Entry:
Enter when a red Diamond Signal appears (ZLMA crosses below EMA).
Exit Conditions:
Stop Loss:
Set at the lower boundary of the ATR band for BUY or the upper boundary for SELL at entry.
Take Profit:
Automatically executed based on a 1:2 risk-reward ratio.
Account Size: ¥100,0000
Commissions and Slippage: Assumed commission of 90 pips per trade and slippage of 1 pip.
Risk per Trade: 10% of account equity (adjustable based on risk tolerance).
Improvements and Original Features:
While based on open-source code, this script incorporates the following critical enhancements:
Diamond Signals from ZLMA and EMA Integration:
Improves entry accuracy with a proprietary trend detection strategy.
ATR Bands Utilization:
Adds a volatility-based risk management function.
Optimized Visual Entry Signals:
Includes plotted triangles (▲, ▼) to clearly indicate trend-following entry points.
Credits:
This script builds upon indicators developed by ChartPrime, whose innovative approach and insights have enabled a more advanced trend-following strategy. We extend our gratitude for their foundational work.
Additionally, it integrates technical methods based on Zero-Lag Moving Average (ZLMA), EMA, and ATR Bands, leveraging insights from the trading community.
Chart Display Options:
The script offers options to toggle the visual signals (Diamond Signals, trend lines, and entry points) on or off, keeping the chart clean while maximizing analytical efficiency.
Disclaimer:
This script is provided for educational purposes and past performance does not guarantee future results.
Use it responsibly with proper risk management.
Pavan CPR Strategy Pavan CPR Strategy (Pine Script)
The Pavan CPR Strategy is a trading system based on the Central Pivot Range (CPR), designed to identify price breakouts and generate long trade signals. This strategy uses key CPR levels (Pivot, Top CPR, and Bottom CPR) calculated from the daily high, low, and close to inform trade decisions. Here's an overview of how the strategy works:
Key Components:
CPR Calculation:
The strategy calculates three critical CPR levels for each trading day:
Pivot (P): The central value, calculated as the average of the high, low, and close prices.
Top Central Pivot (TC): The midpoint of the daily high and low, acting as the resistance level.
Bottom Central Pivot (BC): Derived from the pivot and the top CPR, providing a support level.
The script uses request.security to fetch these CPR values from the daily timeframe, even when applied on intraday charts.
Trade Entry Condition:
A long position is initiated when:
The current price crosses above the Top CPR level (TC).
The previous close was below the Top CPR level, signaling a breakout above a key resistance level.
This condition aims to capture upward momentum as the price breaks above a significant level.
Exit Strategy:
Take Profit: The position is closed with a profit target set 50 points above the entry price.
Stop Loss: A stop loss is placed at the Pivot level to protect against unfavorable price movements.
Visual Reference:
The script plots the three CPR levels on the chart:
Pivot: Blue line.
Top CPR (TC): Green line.
Bottom CPR (BC): Red line.
These plotted levels provide visual guidance for identifying potential support and resistance zones.
Use Case:
The Pavan CPR Strategy is ideal for intraday traders who want to capitalize on price movements and breakouts above critical CPR levels. It provides clear entry and exit signals based on price action and is best used in conjunction with proper risk management.
Note: The strategy is written in Pine Script v5 for use on TradingView, and it is recommended to backtest and optimize it for the asset or market you are trading.
Smart Money Concept Strategy - Uncle SamThis strategy combines concepts from two popular TradingView scripts:
Smart Money Concepts (SMC) : The strategy identifies key levels in the market (swing highs and lows) and draws trend lines to visualize potential breakouts. It uses volume analysis to gauge the strength of these breakouts.
Smart Money Breakouts : This part of the strategy incorporates the idea of "Smart Money" – institutional traders who often lead market movements. It looks for breakouts of established levels with significant volume, aiming to catch the beginning of new trends.
How the Strategy Works:
Identification of Key Levels: The script identifies swing highs and swing lows based on a user-defined lookback period. These levels are considered significant points where price has reversed in the past.
Drawing Trend Lines: Trend lines are drawn connecting these key levels, creating a visual representation of potential support and resistance zones.
Volume Analysis: The script analyzes the volume during the formation of these levels and during breakouts. Higher volume suggests stronger moves and increases the probability of a successful breakout.
Entry Conditions:
Long Entry: A long entry is triggered when the price breaks above a resistance line with significant volume, and the moving average trend filter (optional) is bullish.
Short Entry: A short entry is triggered when the price breaks below a support line with significant volume, and the moving average trend filter (optional) is bearish.
Exit Conditions:
Stop Loss: Customizable stop loss percentages are implemented to protect against adverse price movements.
Take Profit: Customizable take profit percentages are used to lock in profits.
Credits and Compliance:
This strategy is inspired by the concepts and code from "Smart Money Concepts (SMC) " and "Smart Money Breakouts ." I've adapted and combined elements of both scripts to create this strategy. Full credit is given to the original authors for their valuable contributions to the TradingView community.
To comply with TradingView's House Rules, I've made the following adjustments:
Clearly Stated Inspiration: The description explicitly mentions the original scripts and authors as the inspiration for this strategy.
No Direct Copying: The code has been modified and combined, not directly copied from the original scripts.
Educational Purpose: The primary purpose of this strategy is for learning and backtesting. It's not intended as financial advice.
Important Note:
This strategy is intended for educational and backtesting purposes only. It should not be used for live trading without thorough testing and understanding of the underlying concepts. Past performance is not indicative of future results.
HMA Crossover 1H with RSI, Stochastic RSI, and Trailing StopThe strategy script provided is a trading algorithm designed to help traders make informed buy and sell decisions based on certain technical indicators. Here’s a breakdown of what each part of the script does and how the strategy works:
Key Components:
Hull Moving Averages (HMA):
HMA 5: This is a Hull Moving Average calculated over 5 periods. HMAs are used to smooth out price data and identify trends more quickly than traditional moving averages.
HMA 20: This is another HMA but calculated over 20 periods, providing a broader view of the trend.
Relative Strength Index (RSI):
RSI 14: This is a momentum oscillator that measures the speed and change of price movements over a 14-period timeframe. It helps identify overbought or oversold conditions in the market.
Stochastic RSI:
%K: This is the main line of the Stochastic RSI, which combines the RSI and the Stochastic Oscillator to provide a more sensitive measure of overbought and oversold conditions. It is smoothed with a 3-period simple moving average.
Trading Signals:
Buy Signal:
Generated when the 5-period HMA crosses above the 20-period HMA, indicating a potential upward trend.
Additionally, the RSI must be below 45, suggesting that the market is not overbought.
The Stochastic RSI %K must also be below 39, confirming the oversold condition.
Sell Signal:
Generated when the 5-period HMA crosses below the 20-period HMA, indicating a potential downward trend.
The RSI must be above 60, suggesting that the market is not oversold.
The Stochastic RSI %K must also be above 63, confirming the overbought condition.
Trailing Stop Loss:
This feature helps protect profits by automatically selling the position if the price moves against the trade by 5%.
For sell positions, an additional trailing stop of 100 points is included.
NASDAQ 100 Peak Hours StrategyNASDAQ 100 Peak Hours Trading Strategy
Description
Our NASDAQ 100 Peak Hours Trading Strategy leverages a carefully designed algorithm to trade within specific hours of high market activity, particularly focusing on the first two hours of the trading session from 09:30 AM to 11:30 AM GMT-5. This period is identified for its increased volatility and liquidity, offering numerous trading opportunities.
The strategy incorporates a blend of technical indicators to identify entry and exit points for both long and short positions. These indicators include:
Exponential Moving Averages (EMAs) : A short-term 9-period EMA and a longer-term 21-period EMA to determine the market trend and momentum.
Relative Strength Index (RSI) : A 14-period RSI to gauge the market's momentum.
Average True Range (ATR) : A 14-period ATR to assess market volatility and to set dynamic stop losses and trailing stops.
Volume Weighted Average Price (VWAP) : To identify the market's average price weighted by volume, serving as a benchmark for the trading day.
Our strategy uniquely applies a volatility filter using the ATR, ensuring trades are only executed in conditions that favor our setup. Additionally, we consider the direction of the EMAs to confirm the market's trend before entering trades.
Originality and Usefulness
This strategy stands out by combining these indicators within the NASDAQ 100's peak hours, exploiting the specific market conditions that prevail during these times. The inclusion of a volatility filter and dynamic stop-loss mechanisms based on the ATR provides a robust method for managing risk.
By focusing on the early trading hours, the strategy aims to capture the initial market movements driven by overnight news and the opening rush, often characterized by higher volatility. This approach is particularly useful for traders looking to maximize gains from short-term fluctuations while limiting exposure to longer-term market uncertainty.
Strategy Results
To ensure the strategy's effectiveness and reliability, it has undergone rigorous backtesting over a significant dataset to produce a sample size of more than 100 trades. This testing phase helps in identifying the strategy's potential in various market conditions, its consistency, and its risk-to-reward ratio.
Our backtesting adheres to realistic trading conditions, accounting for slippage and commission to reflect actual trading scenarios accurately. The strategy is designed with a conservative approach to risk management, advising not to risk more than 5-10% of equity on a single trade. The default settings in the script align with these principles, ensuring that users can replicate our tested conditions.
Using the Strategy
The strategy is designed for simplicity and ease of use:
Trade Hours : Focuses on 09:30 AM to 11:30 AM GMT-5, during the NASDAQ 100's peak activity hours.
Entry Conditions : Trades are initiated based on the alignment of EMAs, RSI, VWAP, and the ATR's volatility filter within the designated time frame.
Exit Conditions : Includes dynamic trailing stops based on ATR, a predefined time exit strategy, and a trend reversal exit condition for risk management.
This script is a powerful tool for traders looking to leverage the NASDAQ 100's peak hours, providing a structured approach to navigating the early market hours with a robust set of criteria for making informed trading decisions.
AI SuperTrend x Pivot Percentile - Strategy [PresentTrading]█ Introduction and How it is Different
The AI SuperTrend x Pivot Percentile strategy is a sophisticated trading approach that integrates AI-driven analysis with traditional technical indicators. Combining the AI SuperTrend with the Pivot Percentile strategy highlights several key advantages:
1. Enhanced Accuracy in Trend Prediction: The AI SuperTrend utilizes K-Nearest Neighbors (KNN) algorithm for trend prediction, improving accuracy by considering historical data patterns. This is complemented by the Pivot Percentile analysis which provides additional context on trend strength.
2. Comprehensive Market Analysis: The integration offers a multi-faceted approach to market analysis, combining AI insights with traditional technical indicators. This dual approach captures a broader range of market dynamics.
BTC 6H L/S Performance
Local
█ Strategy: How it Works - Detailed Explanation
🔶 AI-Enhanced SuperTrend Indicators
1. SuperTrend Calculation:
- The SuperTrend indicator is calculated using a moving average and the Average True Range (ATR). The basic formula is:
- Upper Band = Moving Average + (Multiplier × ATR)
- Lower Band = Moving Average - (Multiplier × ATR)
- The moving average type (SMA, EMA, WMA, RMA, VWMA) and the length of the moving average and ATR are adjustable parameters.
- The direction of the trend is determined based on the position of the closing price in relation to these bands.
2. AI Integration with K-Nearest Neighbors (KNN):
- The KNN algorithm is applied to predict trend direction. It uses historical price data and SuperTrend values to classify the current trend as bullish or bearish.
- The algorithm calculates the 'distance' between the current data point and historical points. The 'k' nearest data points (neighbors) are identified based on this distance.
- A weighted average of these neighbors' trends (bullish or bearish) is calculated to predict the current trend.
For more please check: Multi-TF AI SuperTrend with ADX - Strategy
🔶 Pivot Percentile Analysis
1. Percentile Calculation:
- This involves calculating the percentile ranks for high and low prices over a set of predefined lengths.
- The percentile function is typically defined as:
- Percentile = Value at (P/100) × (N + 1)th position
- Where P is the desired percentile, and N is the number of data points.
2. Trend Strength Evaluation:
- The calculated percentiles for highs and lows are used to determine the strength of bullish and bearish trends.
- For instance, a high percentile rank in the high prices may indicate a strong bullish trend, and vice versa for bearish trends.
For more please check: Pivot Percentile Trend - Strategy
🔶 Strategy Integration
1. Combining SuperTrend and Pivot Percentile:
- The strategy synthesizes the insights from both AI-enhanced SuperTrend and Pivot Percentile analysis.
- It compares the trend direction indicated by the SuperTrend with the strength of the trend as suggested by the Pivot Percentile analysis.
2. Signal Generation:
- A trading signal is generated when both the AI-enhanced SuperTrend and the Pivot Percentile analysis agree on the trend direction.
- For instance, a bullish signal is generated when both the SuperTrend is bullish, and the Pivot Percentile analysis shows strength in bullish trends.
🔶 Risk Management and Filters
- ADX and DMI Filter: The strategy uses the Average Directional Index (ADX) and the Directional Movement Index (DMI) as filters to assess the trend's strength and direction.
- Dynamic Trailing Stop Loss: Based on the SuperTrend indicator, the strategy dynamically adjusts stop-loss levels to manage risk effectively.
This strategy stands out for its ability to combine real-time AI analysis with established technical indicators, offering traders a nuanced and responsive tool for navigating complex market conditions. The equations and algorithms involved are pivotal in accurately identifying market trends and potential trade opportunities.
█ Usage
To effectively use this strategy, traders should:
1. Understand the AI and Pivot Percentile Indicators: A clear grasp of how these indicators work will enable traders to make informed decisions.
2. Interpret the Signals Accurately: The strategy provides bullish, bearish, and neutral signals. Traders should align these signals with their market analysis and trading goals.
3. Monitor Market Conditions: Given that this strategy is sensitive to market dynamics, continuous monitoring is crucial for timely decision-making.
4. Adjust Settings as Needed: Traders should feel free to tweak the input parameters to suit their trading preferences and to respond to changing market conditions.
█Default Settings and Their Impact on Performance
1. Trading Direction (Default: "Both")
Effect: Determines whether the strategy will take long positions, short positions, or both. Adjusting this setting can align the strategy with the trader's market outlook or risk preference.
2. AI Settings (Neighbors: 3, Data Points: 24)
Neighbors: The number of nearest neighbors in the KNN algorithm. A higher number might smooth out noise but could miss subtle, recent changes. A lower number makes the model more sensitive to recent data but may increase noise.
Data Points: Defines the amount of historical data considered. More data points provide a broader context but may dilute recent trends' impact.
3. SuperTrend Settings (Length: 10, Factor: 3.0, MA Source: "WMA")
Length: Affects the sensitivity of the SuperTrend indicator. A longer length results in a smoother, less sensitive indicator, ideal for long-term trends.
Factor: Determines the bandwidth of the SuperTrend. A higher factor creates wider bands, capturing larger price movements but potentially missing short-term signals.
MA Source: The type of moving average used (e.g., WMA - Weighted Moving Average). Different MA types can affect the trend indicator's responsiveness and smoothness.
4. AI Trend Prediction Settings (Price Trend: 10, Prediction Trend: 80)
Price Trend and Prediction Trend Lengths: These settings define the lengths of weighted moving averages for price and SuperTrend, impacting the responsiveness and smoothness of the AI's trend predictions.
5. Pivot Percentile Settings (Length: 10)
Length: Influences the calculation of pivot percentiles. A shorter length makes the percentile more responsive to recent price changes, while a longer length offers a broader view of price trends.
6. ADX and DMI Settings (ADX Length: 14, Time Frame: 'D')
ADX Length: Defines the period for the Average Directional Index calculation. A longer period results in a smoother ADX line.
Time Frame: Sets the time frame for the ADX and DMI calculations, affecting the sensitivity to market changes.
7. Commission, Slippage, and Initial Capital
These settings relate to transaction costs and initial investment, directly impacting net profitability and strategy feasibility.
LuxAlgo - Backtester (OSC)The OSC Backtester is an innovative strategy script that allows users to create a wide variety of strategies using various unique oscillators.
By utilizing our 'Step' and 'Match' algorithms, users can create custom and complex strategy entries from each of the supported oscillators and included conditions, as well as any external sources, allowing users to create entries from a sequence of conditions and/or multiple matching conditions.
We included a complete alert system that will send a notification for each action taken by the strategy and we also allow users to set custom messages for each action taken by a strategy.
🔶 Features
🔹 Step & Match Algorithm
More complex entry rules can be created by using multiple conditions together, this is done thanks to the Step dropdown setting on the right of each condition.
The Step setting is directly related to the Step & Match algorithm and works in two ways:
When two or more conditions have the same step number, both conditions are evaluated. Used to test matching conditions.
When two or more conditions have different step numbers, each conditions will be evaluated in order, testing for the first step and switching to the next step once the previous one is true. When the final step is true the strategy will open a market order. Used to create sequence of conditions.
This operation is complementary, as you can create a sequence of conditions with one step consisting of two or more matching conditions as long as they have the same step number.
🔹 Fully Customizable Entries From Various Oscillators And Conditions
We allow the users to set entries using our unique HyperWave, Smart Money Flow, and their derived conditions as entries.
The Hyper Wave is a normalized adaptive oscillator aiming to reflect price trends without returning a high amount of noise.
The Smart Money Flow aims to detect trends based on market activity, by doing a comparative analysis between current volume and historical volume. A Smart Money Flow above 50 suggest market participants are bullish, else bearish. Derived from this oscillator we have Overflow indications, this indicator detects when market is overbought or oversold based on participants activity.
Other entries include proprietary reversal signals, real-time divergence detection, oscillator confluence (indicating how aligned each oscillator is), as well as entries using external sources.
🔹 Complete Alert System
Users can get alerted for any action executed by a strategy, from opening positions to closing them.
The message field in the Alert Messages setting section allows for the strategy to send a custom alert message depending on the action taken by the strategy, if no messages are set the strategy will send default messages.
🔶 Usage
Users can create a wide variety of strategies from this script, whether they are trend-following or contrarian traders.
Let's see a contrarian (revesal-based) strategy example using the following entry conditions:
Long: Hyperwave bullish divergence and oversold Hyperwave (lower than 20).
Short: Hyperwave bearish divergence and overbought Hyperwave (greater than 20).
We can also introduce take-profit and stop-loss exit conditions based on external indicators, allowing more control over exits in our strategy. For example:
Long: Hyperwave crossing over 50 while money flow is bearish.
Short: Hyperwave crossing under 50 while money flow is bullish.
Exit Long on a profit (long exit tp): Hyperwave crossing 80.
Exit Short on a profit (short exit tp): Hyperwave crossing 20.
While this strategy script can be used as a standalone, we recommend using other indicators creatively to assist with entries and exits as well as TP/SLs.
Our Step & Match algorithm can magnify interoperability, allowing for way more complete strategies through complex conditions, let's demonstrate this using the following entries:
Long: Any bullish reversal occurring after the price crosses over the lowest upper reversal zone of the Signals & Overlays™.
Short: Any bearish reversal occurring after the price crosses under the highest lower reversal zone of the Signals & Overlays™.
Long TP/SL: 5 ATR's away from the entry price.
Short TP/SL: 5 ATR's away from the entry price.
🔶 Strategy Properties (Important)
This script backtest is done on daily EURGBP, using the following backtesting properties:
Balance (default): 10 000 (default base currency)
Order Size: 10% of the equity
Comission: 3.4 pips (average spread for EURGBP)
Slippage: 3 tick
Stop Loss: 0.02 points away from entry price
We use these properties to ensure a realistic preview of the backtesting system, do note that default properties can be different for various reasons described below:
Order Size: 1 contract by default, this is to allow the strategy to run properly on most instruments such as futures.
Comission: Comission can vary depending on the market and instrument, there is no default value that might return realistic results.
We strongly recommend all users to ensure they adjust the Properties within the script settings to be in line with their accounts & trading platforms of choice to ensure results from the strategies built are realistic.
🔶 How To Access
You can see the Author's Instructions below to learn how to get access.
