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.
Indicatori e strategie
Profit Trailing BBandsProfit Trailing Trend BBands v4.7.5 with Double Trailing SL
A TradingView Pine Script Strategy
Created by Kevin Bourn and refined with the help of Grok 3 (xAI)
Overview
Welcome to Profit Trailing Trend BBands v4.7.5, a dynamic trading strategy designed to ride trends and lock in profits with a unique double trailing stop-loss mechanism. Built for TradingView’s Pine Script v6, this strategy combines Bollinger Bands for trend detection with a smart trailing system that doubles down on profit protection. Whether you’re trading XRP or any other asset, this tool aims to maximize gains while keeping risk in check—all with a clean, visual interface.
What It Does
Identifies Trends: Uses Bollinger Bands to spot uptrends (price crossing above the upper band) and downtrends (price crossing below the lower band).
Enters Positions: Opens long or short trades based on trend signals, with customizable position sizing and leverage.
Trails Profits: Employs a two-stage trailing stop-loss:
Initial Trailing SL: Acts as a take-profit level, set as a percentage (%) or dollar ($) distance from the entry price.
Tightened Trailing SL: Once the initial profit target is hit, the stop-loss tightens to half the initial distance, locking in gains as the trend continues.
Manages Risk: Includes a margin call feature to exit losing positions before they blow up your account.
Visualizes Everything: Plots Bollinger Bands (blue upper, orange lower) and a red stepped trailing stop-loss line for easy tracking.
Why Built It?
Captures Trends: Bollinger Bands are a proven way to catch momentum, and we tuned them for responsiveness (short length, moderate multiplier).
Secures Profits: Traditional trailing stops often leave money on the table or exit too early. The double trailing SL first takes a chunk of profit, then tightens up to ride the rest of the move.
Stays Flexible: Traders can tweak price sources, stop-loss types (% or $), and position sizing to fit their style.
Looks Good: Clear visuals help you see the strategy in action without cluttering your chart.
Originally refined for XRP, it’s versatile enough for most markets — crypto, forex, stocks, you name it.
How It Works
Core Components
Bollinger Bands:
Calculated using a simple moving average (SMA) and standard deviation.
Default settings: 6-period length, 1.66 multiplier.
Upper Band (blue): SMA + (1.66 × StdDev).
Lower Band (orange): SMA - (1.66 × StdDev).
Trend signals: Price crossing above the upper band triggers a long, below the lower band triggers a short.
Double Trailing Stop-Loss:
Initial SL: Set via "Trailing Stop-Loss Value" (default 6% or $6). Trails the price at this distance and doubles as the first profit target.
Tightened SL: Once price hits the initial SL distance in profit (e.g., +6%), the SL tightens to half (e.g., 3%) and continues trailing, locking in gains.
Visualized as a red stepped line, only visible during active positions.
Position Sizing:
Choose "% of Equity" (default 30%) or "Amount in $" to set trade size.
Leverage (default 10x) amplifies positions, capped by available equity to avoid overexposure.
Margin Call:
Exits positions if drawdown exceeds the "Margin %" (default 10%) to protect your account.
Backtesting Filter:
Starts trading after a user-defined date (default: Jan 1, 2020) for focused historical analysis.
Trade Logic
Long Entry: Price crosses above the upper Bollinger Band → Closes any short position, opens a long.
Short Entry: Price crosses below the lower Bollinger Band → Closes any long position, opens a short.
Exit: Position closes when price hits the trailing stop-loss or triggers a margin call.
How to Use It
Setup
Add to TradingView:
Open TradingView, go to the Pine Editor, paste the script, and click "Add to Chart."
Ensure you’re using Pine Script v6 (the script includes @version=6).
Configure Inputs:
Start Date for Backtesting: Set the date to begin historical testing (default: Jan 1, 2020).
BB Length & Mult: Adjust Bollinger Band sensitivity (default: 6, 1.66).
BB Price Source: Choose the price for BBands (default: Close).
Trend Price Source: Choose the price for trend detection (default: Close).
Trailing Stop-Loss Type: Pick "%" or "$" (default: Trailing SL %).
Trailing Stop-Loss Value: Set the initial SL distance (default: 6).
Margin %: Define the max drawdown before exit (default: 10%).
Order Size Type & Value: Set position size as % of equity (default: 30%) or $ amount.
Leverage: Adjust leverage (default: 10x).
Run It:
Use the Strategy Tester tab to backtest on your chosen asset and timeframe.
Watch the chart for blue/orange Bollinger Bands and the red trailing SL line.
Tips for Traders
Timeframes: Works on any timeframe, but test 1H or 4H for XRP—great balance of signals and noise.
Assets: Optimized for XRP, but tweak slValue and mult for other markets (e.g., tighter SL for low-volatility pairs).
Risk Management: Keep marginPercent low (5-10%) for volatile assets; adjust leverage based on your risk tolerance.
Visuals: The red stepped SL line shows only during trades—zoom in to see its tightening in action.
Visuals on the Chart
Blue Line: Upper Bollinger Band (trend entry for longs).
Orange Line: Lower Bollinger Band (trend entry for shorts).
Red Stepped Line: Trailing Stop-Loss (shifts tighter after the first profit target).
Order Labels: Short tags like "OL" (Open Long), "CS" (Close Short), "LSL" (Long Stop-Loss), etc., mark trades.
Disclaimer
Trading involves risk. This strategy is for educational and experimental use—backtest thoroughly and use at your own risk. Past performance doesn’t guarantee future results. Not financial advice—just a tool from traders, for traders.
Uptrick X PineIndicators: Z-Score Flow StrategyThis strategy is based on the Z-Score Flow Indicator developed by Uptrick. Full credit for the original concept and logic goes to Uptrick.
The Z-Score Flow Strategy combines statistical mean-reversion logic with trend filtering, RSI confirmation, and multi-mode trade execution, offering a flexible and structured approach to trading both reversals and trend continuations.
Core Concepts Behind Z-Score Flow
1. Z-Score Mean Reversion Logic
The Z-score measures how far current price deviates from its statistical mean, in standard deviations.
A high positive Z-score (e.g. > 2) suggests price is overbought and may revert downward.
A low negative Z-score (e.g. < -2) suggests price is oversold and may revert upward.
The strategy uses Z-score thresholds to trigger signals when price deviates far enough from its mean.
2. Trend Filtering with EMA
To prevent counter-trend entries, the strategy includes a trend filter based on a 50-period EMA:
Only allows long entries if price is below EMA (mean-reversion in downtrends).
Only allows short entries if price is above EMA (mean-reversion in uptrends).
3. RSI Confirmation and Lockout System
An RSI smoothing mechanism helps confirm signals and avoid whipsaws:
RSI must be below 30 and rising to allow buys.
RSI must be above 70 and falling to allow sells.
Once a signal occurs, it is "locked out" until RSI re-enters the neutral zone (30–70).
This avoids multiple signals in overextended zones and reduces overtrading.
Entry Signal Logic
A buy or sell is triggered when:
Z-score crosses below (buy) or above (sell) the threshold.
RSI smoothed condition is met (oversold and rising / overbought and falling).
The trend condition (EMA filter) aligns.
A cooldown period has passed since the last opposite trade.
This layered approach helps ensure signal quality and timing precision.
Trade Modes
The strategy includes three distinct trade modes to adapt to various market behaviors:
1. Standard Mode
Trades are opened using the Z-score + RSI + trend filter logic.
Each signal must pass all layered conditions.
2. Zero Cross Mode
Trades are based on the Z-score crossing zero.
This mode is useful in trend continuation setups, rather than mean reversion.
3. Trend Reversal Mode
Trades occur when the mean slope direction changes, i.e., basis line changes color.
Helps capture early trend shifts with less lag.
Each mode can be customized for long-only, short-only, or long & short execution.
Visual Components
1. Z-Score Mean Line
The basis (mean) line is colored based on slope direction.
Green = bullish slope, Purple = bearish slope, Gray = flat.
A wide shadow band underneath reflects current trend momentum.
2. Gradient Fill to Price
A gradient zone between price and the mean reflects:
Price above mean = bearish zone with purple overlay.
Price below mean = bullish zone with teal overlay.
This visual aid quickly reveals market positioning relative to equilibrium.
3. Signal Markers
"𝓤𝓹" labels appear for buy signals.
"𝓓𝓸𝔀𝓷" labels appear for sell signals.
These are colored and positioned according to trend context.
Customization Options
Z-Score Period & Thresholds: Define sensitivity to price deviations.
EMA Trend Filter Length: Filter entries with long-term bias.
RSI & Smoothing Periods: Fine-tune RSI confirmation conditions.
Cooldown Period: Prevent signal spam and enforce timing gaps.
Slope Index: Adjust how far back to compare mean slope.
Visual Settings: Toggle mean lines, gradients, and more.
Use Cases & Strategy Strengths
1. Mean-Reversion Trading
Ideal for catching pullbacks in trending markets or fading overextended price moves.
2. Trend Continuation or Reversal
With multiple trade modes, traders can choose between fading price extremes or trading slope momentum.
3. Signal Clarity and Risk Control
The combination of Z-score, RSI, EMA trend, and cooldown logic provides high-confidence signals with built-in filters.
Conclusion
The Z-Score Flow Strategy by Uptrick X PineIndicators is a versatile and structured trading system that:
Fuses statistical deviation (Z-score) with technical filters.
Provides both mean-reversion and trend-based entry logic.
Uses visual overlays and signal labels for clarity.
Prevents noise-driven trades via cooldown and lockout systems.
This strategy is well-suited for traders seeking a data-driven, multi-condition entry framework that can adapt to various market types.
Full credit for the original concept and indicator goes to Uptrick.
ATM Option Selling StrategyATM Option Selling Strategy – Explained
This strategy is designed for intraday option selling based on the 9/15 EMA crossover, 50/80 MA trend filter, and RSI 50 level. It ensures that all trades are exited before market close (3:24 PM IST).
. Indicators Used:
9 EMA & 15 EMA → For short-term trend identification.
50 MA & 80 MA → To determine the overall trend.
RSI (14) → To confirm momentum (above or below 50 level).
2. Entry Conditions:
🔴 Sell ATM Call (CE) when:
Price is below 50 & 80 MA (Bearish trend).
9 EMA crosses below 15 EMA (Short-term trend turns bearish).
RSI is below 50 (Momentum confirms weakness).
🟢 Sell ATM Put (PE) when:
Price is above 50 & 80 MA (Bullish trend).
9 EMA crosses above 15 EMA (Short-term trend turns bullish).
RSI is above 50 (Momentum confirms strength).
3. Position Sizing & Risk Management:
Sell 375 quantity per trade (Lot size).
50-Point Stop Loss → If option premium moves against us by 50 points, exit.
50-Point Take Profit → If option premium moves in our favor by 50 points, book profit.
Exit all trades at 3:24 PM IST → No overnight positions.
4. Exit Conditions:
✅ Stop Loss or Take Profit Hits → Automatically exits based on a 50-point move.
✅ Time-Based Exit at 3:24 PM → Ensures no open positions at market close.
Why This Works?
✔ Trend Confirmation → 50/80 MA ensures we only sell options in the direction of the market trend.
✔ Momentum Confirmation → RSI prevents entering weak trades.
✔ Controlled Risk → SL and TP protect against large losses.
✔ No Overnight Risk → All trades close before market close.
IBAC Strategy - ZygoraIBAC - Intrinsic Binary Averaging based Contrarian
A contrarian scalping strategy in the futures market, designed to stabilize market efficiency by capitalizing on price reversals. The strategy has no stop loss, instead employing a cascading approach—adding to the position size each time the price moves in the wrong direction—and closes the full position when the target profit is reached. Without delving into intricate details, the strategy adheres to the following basic rules:
Position sizing is determined by a customized indicator based on cumulative reversal probability, which also contributes to identifying the signal’s direction.
Direction is determined by the Moving Average: price above the Moving Average signals a Short position, while price below it signals a Long position.
The threshold for entries and exits is adjusted based on the range between extremes (highest high minus lowest low) over the past 100 historical bars.
The next limit entry is placed at a distance equal to the threshold length below (for Long) or above (for Short) the current average price.
The next target profit is set at a distance equal to the threshold length above (for Long) or below (for Short) the current average price.
A signal is triggered when there is a sudden price movement detected by the RSI (Relative Strength Index).
When a signal is identified, the strategy starts with a risk-reward ratio (RR) of 1:1. However, the RR worsens as the cascading steps—referred to as inventory I—increase, because the average entry price shifts unfavorably with each new position added. To mitigate the risk of liquidation, the strategy aims to hold a smaller inventory amount over time. This is achieved by using a multiple threshold multiplier: when a specified inventory limit is reached, the threshold for the next entry increases, and the threshold for the next target profit decreases. As a result, with higher inventory levels, the strategy accepts a lower RR but increases the likelihood of hitting the target profit.
The target profit is always set above the average entry price (for Long) or below it (for Short), ensuring that the strategy eventually closes at a profit. This leads to a 100% win rate but comes with relatively high drawdowns due to the absence of a stop loss and the cascading nature of the positions. The strategy performs best in a consolidation market in 1 minute timeframe, where price tends to oscillate within a range, allowing the contrarian approach to capitalize on reversals. The strategy’s name is derived from its customized indicator for position sizing, which leverages cumulative reversal probability to optimize position sizes and assist in determining the signal’s direction.
Enhanced Range Filter Strategy with ATR TP/SLBuilt by Omotola
## **Enhanced Range Filter Strategy: A Comprehensive Overview**
### **1. Introduction**
The **Enhanced Range Filter Strategy** is a powerful technical trading system designed to identify high-probability trading opportunities while filtering out market noise. It utilizes **range-based trend filtering**, **momentum confirmation**, and **volatility-based risk management** to generate precise entry and exit signals. This strategy is particularly useful for traders who aim to capitalize on trend-following setups while avoiding choppy, ranging market conditions.
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### **2. Key Components of the Strategy**
#### **A. Range Filter (Trend Determination)**
- The **Range Filter** smooths price fluctuations and helps identify clear trends.
- It calculates an **adjusted price range** based on a **sampling period** and a **multiplier**, ensuring a dynamic trend-following approach.
- **Uptrends:** When the current price is above the range filter and the trend is strengthening.
- **Downtrends:** When the price falls below the range filter and momentum confirms the move.
#### **B. RSI (Relative Strength Index) as Momentum Confirmation**
- RSI is used to **filter out weak trades** and prevent entries during overbought/oversold conditions.
- **Buy Signals:** RSI is above a certain threshold (e.g., 50) in an uptrend.
- **Sell Signals:** RSI is below a certain threshold (e.g., 50) in a downtrend.
#### **C. ADX (Average Directional Index) for Trend Strength Confirmation**
- ADX ensures that trades are only taken when the trend has **sufficient strength**.
- Avoids trading in low-volatility, ranging markets.
- **Threshold (e.g., 25):** Only trade when ADX is above this value, indicating a strong trend.
#### **D. ATR (Average True Range) for Risk Management**
- **Stop Loss (SL):** Placed **one ATR below** (for long trades) or **one ATR above** (for short trades).
- **Take Profit (TP):** Set at a **3:1 reward-to-risk ratio**, using ATR to determine realistic price targets.
- Ensures volatility-adjusted risk management.
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### **3. Entry and Exit Conditions**
#### **📈 Buy (Long) Entry Conditions:**
1. **Price is above the Range Filter** → Indicates an uptrend.
2. **Upward trend strength is positive** (confirmed via trend counter).
3. **RSI is above the buy threshold** (e.g., 50, to confirm momentum).
4. **ADX confirms trend strength** (e.g., above 25).
5. **Volatility is supportive** (using ATR analysis).
#### **📉 Sell (Short) Entry Conditions:**
1. **Price is below the Range Filter** → Indicates a downtrend.
2. **Downward trend strength is positive** (confirmed via trend counter).
3. **RSI is below the sell threshold** (e.g., 50, to confirm momentum).
4. **ADX confirms trend strength** (e.g., above 25).
5. **Volatility is supportive** (using ATR analysis).
#### **🚪 Exit Conditions:**
- **Stop Loss (SL):**
- **Long Trades:** 1 ATR below entry price.
- **Short Trades:** 1 ATR above entry price.
- **Take Profit (TP):**
- Set at **3x the risk distance** to achieve a favorable risk-reward ratio.
- **Ranging Market Exit:**
- If ADX falls below the threshold, indicating a weakening trend.
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### **4. Visualization & Alerts**
- **Colored range filter line** changes based on trend direction.
- **Buy and Sell signals** appear as labels on the chart.
- **Stop Loss and Take Profit levels** are plotted as dashed lines.
- **Gray background highlights ranging markets** where trading is avoided.
- **Alerts trigger on Buy, Sell, and Ranging Market conditions** for automation.
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### **5. Advantages of the Enhanced Range Filter Strategy**
✅ **Trend-Following with Noise Reduction** → Helps avoid false signals by filtering out weak trends.
✅ **Momentum Confirmation with RSI & ADX** → Ensures that only strong, valid trades are executed.
✅ **Volatility-Based Risk Management** → ATR ensures adaptive stop loss and take profit placements.
✅ **Works on Multiple Timeframes** → Effective for day trading, swing trading, and scalping.
✅ **Visually Intuitive** → Clearly displays trade signals, SL/TP levels, and trend conditions.
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### **6. Who Should Use This Strategy?**
✔ **Trend Traders** who want to enter trades with momentum confirmation.
✔ **Swing Traders** looking for medium-term opportunities with a solid risk-reward ratio.
✔ **Scalpers** who need precise entries and exits to minimize false signals.
✔ **Algorithmic Traders** using alerts for automated execution.
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### **7. Conclusion**
The **Enhanced Range Filter Strategy** is a powerful trading tool that combines **trend-following techniques, momentum indicators, and risk management** into a structured, rule-based system. By leveraging **Range Filters, RSI, ADX, and ATR**, traders can improve trade accuracy, manage risk effectively, and filter out unfavorable market conditions.
This strategy is **ideal for traders looking for a systematic, disciplined approach** to capturing trends while **avoiding market noise and false breakouts**. 🚀
MACD Volume Strategy (BBO + MACD State, Reversal Type)Overview
MACD Volume Strategy (BBO + MACD State, Reversal Type) is a momentum-based reversal system that combines MACD crossover logic with volume filtering to enhance signal accuracy and minimize noise. It aims to identify structural trend shifts and manage risk using predefined parameters.
※This strategy is for educational and research purposes only. All results are based on historical simulations and do not guarantee future performance.
Strategy Objectives
Identify early trend transitions with high probability
Filter entries using volume dynamics to validate momentum
Maintain continuous exposure using a reversal-style model
Apply a consistent 1:1.5 risk-to-reward ratio per trade
Key Features
Integrated MACD and volume oscillator filtering
Zero repainting (all signals confirmed on closed candles)
Automatic position flipping for seamless direction shifts
Stop-loss and take-profit based on recent structural highs/lows
Trading Rules
Long Entry Conditions
MACD crosses above the zero line (BBO Buy arrow)
Volume oscillator is positive (short EMA > long EMA)
MACD is above the signal line
Close any existing short and enter a new long
Short Entry Conditions
MACD crosses below the zero line (BBO Sell arrow)
Volume oscillator is positive
MACD is below the signal line
Close any existing long and enter a new short
Exit Rules
Take Profit (TP) = Entry ± (risk distance × 1.5)
Stop Loss (SL) = Recent swing low (for long) or high (for short)
Early Exit = Triggered when a reversal signal appears (flip logic)
Risk Management Parameters
Pair: ETH/USD
Timeframe: 10-minute
Starting Capital: $3,000
Commission: 0.02%
Slippage: 2 pip
Risk per Trade: 5% of account equity (adjusted for sustainable practice)
Total Trades: 312 (backtest on selected dataset)
※Risk parameters are fully configurable and should be adjusted to suit each trader's personal setup and broker conditions.
Parameters & Configurations
Volume Short Length: 6
Volume Long Length: 12
MACD Fast Length: 11
MACD Slow Length: 21
Signal Smoothing: 10
Oscillator MA Type: SMA
Signal Line MA Type: SMA
Visual Support
Green arrow = Long entry
Red arrow = Short entry
MACD lines, signal line, and histogram
SL/TP markers plotted directly on the chart
Strategic Advantages & Uniqueness
Volume filtering eliminates low-participation, weak signals
Structurally aligned SL/TP based on recent market pivots
No repainting — decisions are made only on closed candles
Always in the market due to the reversal-style framework
Inspirations & Attribution
This strategy is inspired by the excellent work of:
Bitcoinblockchainonline – “BBO_Roxana_Signals MACD + vol”
Leveraging MACD zero-line cross and volume oscillator for intuitive signal generation.
HasanRifat – “MACD Fake Filter ”
Introduced a signal filter using MACD wave height averaging to reduce false positives.
This strategy builds upon those ideas to create a more automated, risk-aware, and technically adaptive system.
Summary
MACD Volume Strategy is a clean, logic-first automated trading system built for precision-seeking traders. It avoids discretionary bias and provides consistent signal logic under backtested historical conditions.
100% mechanical — no discretionary input required
Designed for high-confidence entries
Can be extended with filters, alerts, or trailing stops
※Strategy performance depends on market context. Past performance is not indicative of future results. Use with proper risk management and careful configuration.
VIDYA Auto-Trading(Reversal Logic)Overview
This script is a dynamic trend-following strategy based on the Variable Index Dynamic Average (VIDYA). It adapts in real time to market volatility, aiming to enhance entry precision and optimize risk management.
⚠️ This strategy is intended for educational and research purposes. Past performance does not guarantee future results. All results are based on historical simulations using fixed parameters.
Strategy Objectives
The objective of this strategy is to respond swiftly to sudden price movements and trend reversals, providing consistent and reliable trade signals under historical testing conditions. It is designed to be intuitive and efficient for traders of all levels.
Key Features
Momentum Sensitivity via VIDYA: Reacts quickly to momentum shifts, allowing for accurate trend-following entries.
Volatility-Based ATR Bands: Automatically adjusts stop levels and entry conditions based on current market volatility.
Intuitive Trend Visualization: Uptrends are marked with green zones, and downtrends with red zones, giving traders clear visual guidance.
Trading Rules
Long Entry: Triggered when price crosses above the upper band. Any existing short position is closed.
Short Entry: Triggered when price crosses below the lower band. Any existing long position is closed.
Exit Conditions: Positions are reversed based on signal changes, using a position reversal strategy.
Risk Management Parameters
Market: ETHUSD(5M)
Account Size: $3,000 (reasonable approximation for individual traders)
Commission: 0.02%
Slippage: 2 pip
Risk per Trade: 5% of account equity (adjusted to comply with TradingView guidelines for realistic risk levels)
Number of Trades: 251 (based on backtest over the selected dataset)
⚠️ The risk per trade and other values can be customized. Users are encouraged to adapt these to their individual needs and broker conditions.
Trading Parameters & Considerations
VIDYA Length: 10
VIDYA Momentum: 20
Distance factor for upper/lower bands: 2
Source: close
Visual Support
Trend zones, entry points, and directional shifts are clearly plotted on the chart. These visual cues enhance the analytical experience and support faster decision-making.
Visual elements are designed to improve interpretability and are not intended as financial advice or trade signals.
Strategy Improvements & Uniqueness
Inspired by the public work of BigBeluga, this script evolves the original concept with meaningful enhancements. By combining VIDYA and ATR bands, it offers greater adaptability and practical value compared to conventional trend-following strategies.
This adaptation is original work and not a direct copy. Improvements are designed to enhance usability, risk control, and market responsiveness.
Summary
This strategy offers a responsive and adaptive approach to trend trading, built on momentum detection and volatility-adjusted risk management. It balances clarity, precision, and practicality—making it a powerful tool for traders seeking reliable trend signals.
⚠️ All results are based on historical data and are subject to change under different market conditions. This script does not guarantee profit and should be used with caution and proper risk management.
VWAP StrategyVWAP and volatility filters for structured intraday trades.
How the Strategy Works
1. VWAP Anchored to Session
VWAP is calculated from the start of each trading day.
Standard deviations are used to create bands above/below the VWAP.
2. Entry Triggers: Al Brooks H1/H2 and L1/L2
H1/H2 (Long Entry): Opens below 2nd lower deviation, closes above it.
L1/L2 (Short Entry): Opens above 2nd upper deviation, closes below it.
3. Volatility Filter (ATR)
Skips trades when deviation bands are too tight (< 3 ATRs).
4. Stop Loss
Based on the signal bar’s high/low ± stop buffer.
Longs: signalBarLow - stopBuffer
Shorts: signalBarHigh + stopBuffer
5. Take Profit / Exit Target
Exit logic is customizable per side:
VWAP, Deviation Band, or None
6. Safety Exit
Exits early if X consecutive bars go against the trade.
Longs: X red bars
Shorts: X green bars
Explanation of Strategy Inputs
- Stop Buffer: Distance from signal bar for stop-loss.
- Long/Short Exit Rule: VWAP, Deviation Band, or None
- Long/Short Target Deviation: Standard deviation for target exit.
- Enable Safety Exit: Toggle emergency exit.
- Opposing Bars: Number of opposing candles before safety exit.
- Allow Long/Short Trades: Enable or disable entry side.
- Show VWAP/Entry Bands: Toggle visual aids.
- Highlight Low Vol Zones: Orange shading for low volatility skips.
Tuning Tips
- Stop buffer: Use 1–5 points.
- Target deviation: Start with VWAP. In strong trends use 2nd deviation and turn off the counter-trend entry.
- Safety exit: 3 bars recommended.
- Disable short/long side to focus on one type of reversal.
Backtest Setup Suggestions
- initial_capital = 2000
- default_qty_value = 1 (fixed contracts or percent-of-equity)
GQT GPT - Volume-based Support & Resistance Zones V2搞钱兔，搞钱是为了更好的生活。
Title: GQT GPT - Volume-based Support & Resistance Zones V2
Overview:
This strategy is implemented in PineScript v5 and is designed to identify key support and resistance zones based on volume-driven fractal analysis on a 1-hour timeframe. It computes fractal high points (for resistance) and fractal low points (for support) using volume moving averages and specific price action criteria. These zones are visually represented on the chart with customizable lines and zone fills.
Trading Logic:
• Entry: The strategy initiates a long position when the price crosses into the support zone (i.e., when the price drops into a predetermined support area).
• Exit: The long position is closed when the price enters the resistance zone (i.e., when the price rises into a predetermined resistance area).
• Time Frame: Trading signals are generated solely from the 1-hour chart. The strategy is only active within a specified start and end date.
• Note: Only long trades are executed; short selling is not part of the strategy.
Visualization and Parameters:
• Support/Resistance Zones: The zones are drawn based on calculated fractal values, with options to extend the lines to the right for easier tracking.
• Customization: Users can configure the appearance, such as line style (solid, dotted, dashed), line width, colors, and label positions.
• Volume Filtering: A volume moving average threshold is used to confirm the fractal signals, enhancing the reliability of the support and resistance levels.
• Alerts: The strategy includes alert conditions for when the price enters the support or resistance zones, allowing for timely notifications.
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搞钱兔，搞钱是为了更好的生活。
标题： GQT GPT - 基于成交量的支撑与阻力区间 V2
概述：
本策略使用 PineScript v5 实现，旨在基于成交量驱动的分形分析，在1小时级别的图表上识别关键支撑与阻力区间。策略通过成交量移动平均线和特定的价格行为标准计算分形高点（阻力）和分形低点（支撑），并以自定义的线条和区间填充形式直观地显示在图表上。
交易逻辑：
• 进场条件： 当价格进入支撑区间（即价格跌入预设支撑区域）时，策略在没有持仓的情况下发出做多信号。
• 离场条件： 当价格进入阻力区间（即价格上升至预设阻力区域）时，持有多头头寸则会被平仓。
• 时间范围： 策略的信号仅基于1小时级别的图表，并且仅在指定的开始日期与结束日期之间生效。
• 备注： 本策略仅执行多头交易，不进行空头操作。
可视化与参数设置：
• 支撑/阻力区间： 根据计算得出的分形值绘制支撑与阻力线，可选择将线条延伸至右侧，便于后续观察。
• 自定义选项： 用户可以调整线条样式（实线、点线、虚线）、线宽、颜色及标签位置，以满足个性化需求。
• 成交量过滤： 策略使用成交量移动平均阈值来确认分形信号，提高支撑和阻力区间的有效性。
• 警报功能： 当价格进入支撑或阻力区间时，策略会触发警报条件，方便用户及时关注市场变化。
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Smart Money Pivot Strategy [Jason Kasei]This strategy is designed to identify key pivot points (Pivot High and Pivot Low) in the market and leverage the "Smart Money" concept to capture price breakout opportunities. It supports both long and short trades, offering customizable stop-loss (SL) and take-profit (TP) settings, while visually plotting pivot points and breakout signals on the chart.
Core Features
Pivot Point Detection:
Utilizes ta.pivothigh and ta.pivotlow functions to detect the highest (Pivot High) and lowest (Pivot Low) points within a specified period (default: 20 bars).
Trading Signals:
Long Signal: Triggered when the price breaks above a previous Pivot High, indicating a potential uptrend.
Short Signal: Triggered when the price breaks below a previous Pivot Low, indicating a potential downtrend.
How It Works
Detects Pivot High (PH) and Pivot Low (PL) over the specified period and records their price and time.
Triggers a long entry when the price breaks above a Pivot High and a short entry when it falls below a Pivot Low.
Sets exit conditions automatically based on predefined SL and TP percentages after entry.
Plots breakout points and levels on the chart for analysis.
Considerations
The strategy relies on accurate pivot point detection; adjust the period parameter based on market volatility.
In highly volatile markets, consider widening the stop loss to avoid frequent triggering.
Combine with other indicators or analysis methods to validate signals and avoid blind trading.
2:45 AM Candle High/Low Crossing Bars2:45 AM Candle High/Low Crossing Bars is an indicator that focuses on the trading view 2:45am NY TIME high and low indicating green for buy and red bars for sell, with the 2:45am new york time highlight/ If the next candle sweeps the low we buy while if it sweeps the high we sell, all time zoon must be the new York UTC time.
Supertrend + MACD CrossoverKey Elements of the Template:
Supertrend Settings:
supertrendFactor: Adjustable to control the sensitivity of the Supertrend.
supertrendATRLength: ATR length used for Supertrend calculation.
MACD Settings:
macdFastLength, macdSlowLength, macdSignalSmoothing: These settings allow you to fine-tune the MACD for better results.
Risk Management:
Stop-Loss: The stop-loss is based on the ATR (Average True Range), a volatility-based indicator.
Take-Profit: The take-profit is based on the risk-reward ratio (set to 3x by default).
Both stop-loss and take-profit are dynamic, based on ATR, which adjusts according to market volatility.
Buy and Sell Signals:
Buy Signal: Supertrend is bullish, and MACD line crosses above the Signal line.
Sell Signal: Supertrend is bearish, and MACD line crosses below the Signal line.
Visual Elements:
The Supertrend line is plotted in green (bullish) and red (bearish).
Buy and Sell signals are shown with green and red triangles on the chart.
Next Steps for Optimization:
Backtesting:
Run backtests on BTC in the 5-minute timeframe and adjust parameters (Supertrend factor, MACD settings, risk-reward ratio) to find the optimal configuration for the 60% win ratio.
Fine-Tuning Parameters:
Adjust supertrendFactor and macdFastLength to find more optimal values based on BTC's market behavior.
Tweak the risk-reward ratio to maximize profitability while maintaining a good win ratio.
Evaluate Market Conditions:
The performance of the strategy can vary based on market volatility. It may be helpful to evaluate performance in different market conditions or pair it with a filter like RSI or volume.
Let me know if you'd like further tweaks or explanations!
Box Chart Overlay StrategyExploring the Box Chart Overlay Strategy with RSI & Bollinger Confirmation
The “Box Chart Overlay Strategy by BD” is a sophisticated TradingView strategy script written in Pine Script (version 5). It combines a box charting method with two widely used technical indicators—Relative Strength Index (RSI) and Bollinger Bands—to generate trade entries. In this article, we break down the strategy’s components, its logic, and how it visually represents trading signals on the chart.
1. Strategy Setup and User Inputs
Strategy Declaration
At the top of the script, the strategy is declared with key parameters:
Overlay: The indicator is plotted directly on the price chart.
Initial Capital & Position Sizing: It uses a simulated trading account with an initial capital of 10,000 and positions sized as a percentage of equity (10% by default).
Commission: A commission of 0.1% is factored into trades.
Input Parameters
The strategy is highly customizable. Users can adjust various inputs such as:
Box Settings:
Box Size (RSboxSize): Defines the size of each price “box.”
Box Options: Choose from three modes:
Standard: Boxes are calculated continuously from the start of the chart.
Anchored: The first box is fixed at a specified time and price.
Daily Reset: The boxes reset each day based on a defined session time.
Color Customizations:
Options to customize the appearance of boxes, borders, labels, and even repainting the candles based on the current price’s relation to box levels.
RSI Settings:
Length, overbought, and oversold levels are set to filter trades.
Bollinger Bands Settings:
Users can set the length of the moving average and the multiplier for standard deviation, which will be used to compute the upper and lower bands.
2. The Box Chart Mechanism
Box Construction
The core idea of a box chart is to group price movement into discrete blocks—or boxes—of a fixed size. In this strategy:
Standard Mode:
The script calculates boxes starting at a rounded price level. When the price moves sufficiently above or below the current box’s boundaries, a new box is drawn.
Anchored and Daily Reset Modes:
These modes allow traders to control where the box calculations begin or to reset them during a specific intraday session.
Visual Elements
Several custom functions handle the visual components:
drawBoxUp() and drawBoxDn():
These functions create boxes in bullish or bearish directions respectively, based on whether the price has exceeded the current box’s high or low.
drawLines() and drawLabels():
Lines are drawn to extend the current box levels, and labels are updated to display key levels or the “remainder” (the difference needed to trigger a new box).
Projected Boxes:
A “projected” box is drawn to indicate potential upcoming box levels, providing an additional visual cue about the price action.
3. Integrating RSI and Bollinger Bands for Trade Confirmation
RSI Integration
The strategy computes the RSI using a user-defined length. It then uses the following conditions to validate entries:
Long Trades (Box Up):
The strategy waits for the RSI to be at or below the oversold level before considering a long entry.
Short Trades (Box Down):
It requires the RSI to be at or above the overbought level before triggering a short entry.
Bollinger Bands Confirmation
In addition to the RSI filter:
For Long Entries:
The price must be at or below the lower Bollinger Band.
For Short Entries:
The price must be at or above the upper Bollinger Band.
By combining these filters with the box breakout logic, the strategy aims to enhance the quality of its trade signals.
4. Dynamic Trade Entries and Alerts
Box Logic and Entry Functions
Two key functions—BoxUpFunc() and BoxDownFunc()—handle the creation of new boxes and also check if trade conditions are met:
When a new box is drawn, the script evaluates if the RSI and Bollinger conditions align.
If conditions are satisfied, the script places an entry order:
Long Entry: Initiated when the price moves upward, RSI indicates oversold, and the price touches or falls below the lower Bollinger Band.
Short Entry: Triggered when the price falls downward, RSI signals overbought, and the price touches or exceeds the upper Bollinger Band.
Alerts
Built-in alert functions notify traders when a new box level is reached. Users can set custom alert messages to ensure they are aware of potential trade opportunities as soon as the conditions are met.
5. Visual Enhancements and Candle Repainting
The script also includes options for repainting candles based on their relation to the current box’s boundaries:
Above, Below, or Within the Box:
Candles are color-coded using user-defined colors, making it easier to visually assess where the price is in relation to the box levels.
Labels and Lines:
These continuously update to reflect current levels and provide an immediate visual reference for potential breakout points.
Conclusion
The Box Chart Overlay Strategy by BD is a multi-faceted approach that marries the traditional box chart technique with modern technical indicators—RSI and Bollinger Bands—to refine entry signals. By offering various customization options for box creation, visual styling, and confirmation criteria, the strategy allows traders to adapt it to different market conditions and personal trading styles. Whether you prefer a continuously running “Standard” mode or a more controlled “Anchored” or “Daily Reset” approach, this strategy provides a robust framework for integrating price action with momentum and volatility measures.
Triangular Hull Moving Average [BigBeluga X PineIndicators]This strategy is based on the original Triangular Hull Moving Average (THMA) + Volatility indicator by BigBeluga. Full credit for the concept and design goes to BigBeluga.
The strategy blends smoothed trend-following logic using a Triangular Hull Moving Average with dynamic volatility overlays, providing actionable trade signals with responsive visual feedback. It's designed for traders who want a non-lagging trend filter while also monitoring market volatility in real time.
How the Strategy Works
1. Triangular Hull Moving Average (THMA) Core
At its core, the strategy uses a Triangular Hull Moving Average (THMA) — a variation of the traditional Hull Moving Average with triple-smoothing logic:
It combines multiple weighted moving averages (WMAs) to create a faster and smoother trend line.
This reduces lag without compromising trend accuracy.
The THMA reacts more responsively to price movements than classic MAs.
THMA Formula:
thma(_src, _length) =>
ta.wma(ta.wma(_src,_length / 3) * 3 - ta.wma(_src, _length / 2) - ta.wma(_src, _length), _length)
This logic filters out short-term noise while still being sensitive to genuine trend shifts.
2. Volatility-Enhanced Candle Plotting
An optional volatility mode overlays the chart with custom candles that incorporate volatility bands:
Wicks expand and contract dynamically based on market volatility.
The volatility value is computed using a HMA of high-low range over a user-defined length.
The candle bodies reflect THMA values, while the wicks reflect the current volatility spread.
This feature allows traders to visually gauge the strength of price moves and anticipate possible breakouts or slowdowns.
3. Trend Reversal Signal Detection
The strategy identifies trend reversals when the THMA line crosses over/under its own past value:
A bullish signal is triggered when THMA crosses above its value from two bars ago.
A bearish signal is triggered when THMA crosses below its value from two bars ago.
These shifts are marked on the chart with triangle-shaped signals for clear visibility.
This logic helps detect momentum shifts early and enables reactive trade entries.
Trade Entry & Exit Logic
Trade Modes Supported
Users can choose between:
Only Long – Enters long trades only.
Only Short – Enters short trades only.
Long & Short – Enables both directions.
Entry Conditions
Long Entry:
Triggered when a bullish crossover is detected.
Active only if the strategy mode allows long trades.
Short Entry:
Triggered when a bearish crossover is detected.
Active only if the strategy mode allows short trades.
Exit Conditions
In Only Long mode, the strategy closes long positions when a bearish signal appears.
In Only Short mode, the strategy closes short positions when a bullish signal appears.
In Long & Short mode, the strategy does not auto-close positions — instead, it opens new positions on each confirmed signal.
Dashboard Visualization
In the bottom-right corner of the chart, a live dashboard displays:
The current trend direction (🢁 for bullish, 🢃 for bearish).
The current volatility level as a percentage.
This helps traders quickly assess market status and adjust their decisions accordingly.
Customization Options
THMA Length: Adjust how smooth or reactive the trend detection should be.
Volatility Toggle & Length: Enable or disable volatility visualization and set sensitivity.
Color Settings: Choose colors for up/down trend visualization.
Trade Direction Mode: Limit the strategy to long, short, or both types of trades.
Use Cases & Strategy Strengths
1. Trend Following
Use the THMA-based candles and triangle signals to enter with momentum. The indicator adapts quickly, reducing lag and improving trade timing.
2. Volatility Monitoring
Visualize the strength of the trend with volatility wicks. Use expanding bands to confirm breakouts and contracting ones to detect weakening moves.
3. Signal Confirmation
Combine this tool with other indicators or use the trend shift triangles as confirmations for manual entries.
Conclusion
The THMA + Volatility Strategy is a non-repainting trend-following system that integrates:
Triangular Hull MA for advanced trend detection.
Real-time volatility visualization.
Clear entry signals based on trend reversals.
Configurable trade direction settings.
It is ideal for traders who:
Prefer smoothed price analysis.
Want to follow trends with precision.
Value visual volatility feedback for breakout detection.
Full credit for the original concept and indicator goes to BigBeluga.
Litecoin Trailing-Stop StrategyAltcoins Trailing-Stop Strategy
This strategy is based on a momentum breakout approach using PKAMA (Powered Kaufman Adaptive Moving Average) as a trend filter, and a delayed trailing stop mechanism to manage risk effectively.
It has been designed and fine-tuned Altcoins, which historically shows consistent volatility patterns and clean trend structures, especially on intraday timeframes like 15m and 30m.
Strategy Logic:
Entry Conditions:
Long when PKAMA indicates an upward move
Short when PKAMA detects a downward trend
Minimum spacing of 30 bars between trades to avoid overtrading
Trailing Stop:
Activated only after a customizable delay (delayBars)
User can set trailing stop % and delay independently
Helps avoid premature exits due to short-term volatility
Customizable Parameters:
This strategy uses a custom implementation of PKAMA (Powered Kaufman Adaptive Moving Average), inspired by the work of alexgrover
PKAMA is a volatility-aware moving average that adjusts dynamically to market conditions, making it ideal for altcoins where trend strength and direction change frequently.
This script is for educational and experimental purposes only. It is not financial advice. Please test thoroughly before using it in live conditions, and always adapt parameters to your specific asset and time frame.
Feedback is welcome! Feel free to clone and adapt it for your own trading style.
Cycle Biologique Strategy // (\_/)
// ( •.•)
// (")_(")
//@fr33domz
Experimental Research: Cycle Biologique Strategy
Overview
The "Cycle Biologique Strategy" is an experimental trading algorithm designed to leverage periodic cycles in price movements by utilizing a sinusoidal function. This strategy aims to identify potential buy and sell signals based on the behavior of a custom-defined biological cycle.
Key Parameters
Cycle Length: This parameter defines the duration of the cycle, set by default to 30 periods. The user can adjust this value to optimize the strategy for different asset classes or market conditions.
Amplitude: The amplitude of the cycle influences the scale of the sinusoidal wave, allowing for customization in the sensitivity of buy and sell signals.
Offset: The offset parameter introduces phase shifts to the cycle, adjustable within a range of -360 to 360 degrees. This flexibility allows the strategy to align with various market rhythms.
Methodology
The core of the strategy lies in the calculation of a periodic cycle using a sinusoidal function.
Trading Signals
Buy Signal: A buy signal is generated when the cycle value crosses above zero, indicating a potential upward momentum.
Sell Signal: Conversely, a sell signal is triggered when the cycle value crosses below zero, suggesting a potential downtrend.
Execution
The strategy executes trades based on these signals:
Upon receiving a buy signal, the algorithm enters a long position.
When a sell signal occurs, the strategy closes the long position.
Visualization
To enhance user experience, the periodic cycle is plotted visually on the chart in blue, allowing traders to observe the cyclical nature of the strategy and its alignment with market movements.
Multi-EMA Crossover StrategyMulti-EMA Crossover Strategy
This strategy uses multiple exponential moving average (EMA) crossovers to identify bullish trends and execute long trades. The approach involves progressively stronger signals as different EMA pairs cross, indicating increasing bullish momentum. Each crossover triggers a long entry, and the intensity of bullish sentiment is reflected in the color of the bars on the chart. Conversely, bearish trends are represented by red bars.
Strategy Logic:
First Long Entry: When the 1-day EMA crosses above the 5-day EMA, it signals initial bullish momentum.
Second Long Entry: When the 3-day EMA crosses above the 10-day EMA, it confirms stronger bullish sentiment.
Third Long Entry: When the 5-day EMA crosses above the 20-day EMA, it indicates further trend strength.
Fourth Long Entry: When the 10-day EMA crosses above the 40-day EMA, it suggests robust long-term bullish momentum.
The bar colors reflect these conditions:
More blue bars indicate stronger bullish sentiment as more short-term EMAs are above their longer-term counterparts.
Red bars represent bearish conditions when short-term EMAs are below longer-term ones.
Example: Bitcoin Trading on a Daily Timeframe
Bullish Scenario:
Imagine Bitcoin is trading at $30,000 on March 31, 2025:
First Signal: The 1-day EMA crosses above the 5-day EMA at $30,000. This suggests initial upward momentum, prompting a small long entry.
Second Signal: A few days later, the 3-day EMA crosses above the 10-day EMA at $31,000. This confirms strengthening bullish sentiment; another long position is added.
Third Signal: The 5-day EMA crosses above the 20-day EMA at $32,500, indicating further upward trend development; a third long entry is executed.
Fourth Signal: Finally, the 10-day EMA crosses above the 40-day EMA at $34,000. This signals robust long-term bullish momentum; a fourth long position is entered.
Bearish Scenario:
Suppose Bitcoin reverses from $34,000 to $28,000:
The 1-day EMA crosses below the 5-day EMA at $33,500.
The 3-day EMA dips below the 10-day EMA at $32,000.
The 5-day EMA falls below the 20-day EMA at $30,000.
The final bearish signal occurs when the 10-day EMA drops below the 40-day EMA at $28,000.
The bars turn increasingly red as bearish conditions strengthen.
Advantages of This Strategy:
Progressive Confirmation: Multiple crossovers provide layered confirmation of trend strength.
Visual Feedback: Bar colors help traders quickly assess market sentiment and adjust positions accordingly.
Flexibility: Suitable for trending markets like Bitcoin during strong rallies or downturns.
Limitations:
Lagging Signals: EMAs are lagging indicators and may react slowly to sudden price changes.
False Breakouts: Crossovers in choppy markets can lead to whipsaws or false signals.
This strategy works best in trending markets and should be combined with additional risk management techniques, e.g., stop loss or optimal position sizes (Kelly Criterion).
Qullamaggie [Modified] | FractalystWhat's the purpose of this strategy?
The strategy aims to identify high-probability breakout setups in trending markets, inspired by Kristjan "Qullamaggie" Kullamägi’s approach.
It focuses on capturing explosive price moves after periods of consolidation, using technical criteria like moving averages, breakouts, trailing stop-loss and momentum confirmation.
Ideal for swing traders seeking to ride strong trends while managing risk.
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How does the strategy work?
The strategy follows a systematic process to capture high-momentum breakouts:
Pre-Breakout Criteria:
Prior Price Surge: Identifies stocks that have rallied 30-100%+ in recent month(s), signaling strong underlying momentum (per Qullamaggie’s volatility expansion principles).
Consolidation Phase: Looks for a tightening price range (e.g., flag, pennant, or tight base), indicating a potential "coiling" before continuation.
Trend Confirmation: Uses moving averages (e.g., 20/50/200 EMA) to ensure the stock is trading above key averages on the daily chart, confirming an uptrend.
Price Break: Enters when price clears the consolidation high with conviction.
Risk Management:
Initial Stop Loss: Placed below the consolidation low or a recent swing point to limit downside.
Break-Even Adjustment: Moves stop loss to breakeven once the trade reaches 1.5x risk-to-reward (RR), securing a "free trade" while letting winners run.
Trailing Stop (Unique Edge):
Market Structure Trailing: Instead of trailing via moving averages, the stop is dynamically adjusted using structural invalidation level. This adapts to price action, allowing the trade to stay open during volatile retracements while locking in gains as new structure forms.
Why This Matters: Most strategies use rigid trailing stops (e.g., below the 10EMA), which often exit prematurely in choppy markets. By trailing based on structure, this strategy avoids "noise" and captures larger trends, directly boosting overall returns.
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What markets or timeframes is this suited for?
This is a long-only strategy designed for trending markets, and it performs best in:
Markets: Stocks (especially high-growth, liquid equities), cryptocurrencies (major pairs with strong volatility), commodities (e.g., oil, gold), and futures (index/commodity futures).
Timeframes: Primarily daily charts for swing trades (1-30 day holds), though weekly charts can help confirm broader trends.
Key Advantage: The TradingView script allows instant backtesting with adjustable parameters
You can:
- Test historical performance across multiple markets to identify which assets align best with the strategy.
- Optimize settings (e.g., trailing stop sensitivity, moving averages etc.) to match a market’s volatility profile.
Build a diversified portfolio by filtering for markets that show consistent profitability in backtests.
For example, you might discover cryptos require tighter trailing stops due to volatility, while stocks thrive with wider structural stops. The script automates this analysis, letting you to trade confidently.
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What indicators or tools does the strategy use?
The strategy combines customizable technical tools with strict anti-lookahead safeguards:
Core Indicators:
Moving Averages: Adjustable periods (e.g., 20/50/200 EMA or SMA) and timeframes (daily/weekly) to confirm trend alignment. Users can test combinations (e.g., 10EMA vs. 20EMA) to optimize for specific markets.
Breakout Parameters:
Consolidation Length: Adjustable window to define the "tightness" of the pre-breakout pattern.
Entry Models: Flexible entry logics (Breakouts and fractals)
Anti-Lookahead Design:
All calculations (e.g., moving averages, consolidation ranges, volume averages) use only closed/confirmed data available at the time of the signal.
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How do I manage risk with this strategy?
The strategy prioritizes customizable risk controls to align with your trading style and account size:
User-Defined Risk Inputs:
Risk Per Trade: Set a % of Equity (e.g., 1-2%) to determine position size. The strategy auto-calculates shares/contracts to match your selected risk per trade.
Flexibility: Choose between fixed risk or equity-based scaling.
The script adjusts position sizing dynamically based on your selection.
Pyramiding Feature:
Customizable Entries: Adjust the number of pyramiding trades allowed (e.g., 1-3 additional positions) in the strategy settings. Each new entry is triggered only if the prior trade hits its 1.5x RR target and the trend remains intact.
Risk-Scaled Additions: New positions use profits from prior trades, compounding gains without increasing initial risk.
Risk-Free Trade Mechanic:
Once a trade reaches 1.5x RR, the stop loss is moved to breakeven, eliminating downside risk.
The strategy then opens a new position (if pyramiding is enabled) using a portion of the locked-in profit. This "snowballs" winners while keeping total capital exposure stable.
Impact on Net Profit & Drawdown:
Net Profit Boost: Pyramiding lets you ride multi-leg trends aggressively. For example, a 100% runner could generate 2-3x more profit vs. a single-entry approach.
Controlled Drawdowns: Since new positions are funded by profits (not initial capital), max drawdown stays anchored to your original risk per trade (e.g., 1-2% of account). Even if later entries fail, the breakeven stop on prior trades protects overall equity.
Why This Works: Most strategies either over-leverage (increasing drawdowns) or exit too early. By recycling profits into new positions only after securing risk-free capital, this approach mimics hedge fund "scaling in" tactics while staying retail-trader friendly.
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How does the strategy identify market structure for its trailing stoploss?
The strategy identifies market structure by utilizing an efficient logic with for loops to pinpoint the first swing candle that features a pivot of 2. This marks the beginning of the break of structure, where the market's previous trend or pattern is considered invalidated or changed.
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What are the underlying calculations?
The underlying calculations involve:
Identifying Swing Points: The strategy looks for swing highs (marked with blue Xs) and swing lows (marked with red Xs). A swing high is identified when a candle's high is higher than the highs of the candles before and after it. Conversely, a swing low is when a candle's low is lower than the lows of the candles before and after it.
Break of Structure (BOS):
Bullish BOS: This occurs when the price breaks above the swing high level of the previous structure, indicating a potential shift to a bullish trend.
Bearish BOS: This happens when the price breaks below the swing low level of the previous structure, signaling a potential shift to a bearish trend.
Structural Liquidity and Invalidation:
Structural Liquidity: After a break of structure, liquidity levels are updated to the first swing high in a bullish BOS or the first swing low in a bearish BOS.
Structural Invalidation: If the price moves back to the level of the first swing low before the bullish BOS or the first swing high before the bearish BOS, it invalidates the break of structure, suggesting a potential reversal or continuation of the previous trend.
This method provides users with a technical approach to filter market regimes, offering an advantage by minimizing the risk of overfitting to historical data, which is often a concern with traditional indicators like moving averages.
By focusing on identifying pivotal swing points and the subsequent breaks of structure, the strategy maintains a balance between sensitivity to market changes and robustness against historical data anomalies, ensuring a more adaptable and potentially more reliable market analysis tool.
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What entry criteria are used in this script?
The script uses two entry models for trading decisions: BreakOut and Fractal.
Underlying Calculations:
Breakout: The script records the most recent swing high by storing it in a variable. When the price closes above this recorded level, and all other predefined conditions are satisfied, the script triggers a breakout entry. This approach is considered conservative because it waits for the price to confirm a breakout above the previous high before entering a trade. As shown in the image, as soon as the price closes above the new candle (first tick), the long entry gets taken. The stop-loss is initially set and then moved to break-even once the price moves in favor of the trade.
Fractal: This method involves identifying a swing low with a period of 2, which means it looks for a low point where the price is lower than the two candles before and after it. Once this pattern is detected, the script executes the trade. This is an aggressive approach since it doesn't wait for further price confirmation. In the image, this is represented by the 'Fractal 2' label where the script identifies and acts on the swing low pattern.
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What type of stop-loss identification method are used in this strategy?
This strategy employs two types of stop-loss methods: Initial Stop-loss and Trailing Stop-Loss.
Underlying Calculations:
Initial Stop-loss:
ATR Based: The strategy uses the Average True Range (ATR) to set an initial stop-loss, which helps in accounting for market volatility without predicting price direction.
Calculation:
- First, the True Range (TR) is calculated for each period, which is the greatest of:
- Current Period High - Current Period Low
- Absolute Value of Current Period High - Previous Period Close
- Absolute Value of Current Period Low - Previous Period Close
- The ATR is then the moving average of these TR values over a specified period, typically 14 periods by default. This ATR value can be used to set the stop-loss at a distance from the entry price that reflects the current market volatility.
Swing Low Based:
For this method, the stop-loss is set based on the most recent swing low identified in the market structure analysis. This approach uses the lowest point of the recent price action as a reference for setting the stop-loss.
Trailing Stop-Loss:
The strategy uses structural liquidity and structural invalidation levels across multiple timeframes to adjust the stop-loss once the trade is profitable. This method involves:
Detecting Structural Liquidity: After a break of structure, the liquidity levels are updated to the first swing high in a bullish scenario or the first swing low in a bearish scenario. These levels serve as potential areas where the price might find support or resistance, allowing the stop-loss to trail the price movement.
Detecting Structural Invalidation: If the price returns to the level of the first swing low before a bullish break of structure or the first swing high before a bearish break of structure, it suggests the trend might be reversing or invalidating, prompting the adjustment of the stop-loss to lock in profits or minimize losses.
By using these methods, the strategy dynamically adjusts the initial stop-loss based on market volatility, helping to protect against adverse price movements while allowing for enough room for trades to develop. The ATR-based stop-loss adapts to the current market conditions by considering the volatility, ensuring that the stop-loss is not too tight during volatile periods, which could lead to premature exits, nor too loose during calm markets, which might result in larger losses. Similarly, the swing low based stop-loss provides a logical exit point if the market structure changes unfavorably.
Each market behaves differently across various timeframes, and it is essential to test different parameters and optimizations to find out which trailing stop-loss method gives you the desired results and performance. This involves backtesting the strategy with different settings for the ATR period, the distance from the swing low, and how the trailing stop-loss reacts to structural liquidity and invalidation levels.
Through this process, you can tailor the strategy to perform optimally in different market environments, ensuring that the stop-loss mechanism supports the trade's longevity while safeguarding against significant drawdowns.
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What type of break-even method is used in this strategy? What are the underlying calculations?
Moves the initial stop-loss to the entry price when the price reaches a certain RR ratio.
Calculation:
Break-even level = Entry Price + (Initial Risk * RR Ratio)
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What tables are available in this script?
- Summary: Provides a general overview, displaying key performance parameters such as Net Profit, Profit Factor, Max Drawdown, Average Trade, Closed Trades and more.
Total Commission: Displays the cumulative commissions incurred from all trades executed within the selected backtesting window. This value is derived by summing the commission fees for each trade on your chart.
Average Commission: Represents the average commission per trade, calculated by dividing the Total Commission by the total number of closed trades. This metric is crucial for assessing the impact of trading costs on overall profitability.
Avg Trade: The sum of money gained or lost by the average trade generated by a strategy. Calculated by dividing the Net Profit by the overall number of closed trades. An important value since it must be large enough to cover the commission and slippage costs of trading the strategy and still bring a profit.
MaxDD: Displays the largest drawdown of losses, i.e., the maximum possible loss that the strategy could have incurred among all of the trades it has made. This value is calculated separately for every bar that the strategy spends with an open position.
Profit Factor: The amount of money a trading strategy made for every unit of money it lost (in the selected currency). This value is calculated by dividing gross profits by gross losses.
Avg RR: This is calculated by dividing the average winning trade by the average losing trade. This field is not a very meaningful value by itself because it does not take into account the ratio of the number of winning vs losing trades, and strategies can have different approaches to profitability. A strategy may trade at every possibility in order to capture many small profits, yet have an average losing trade greater than the average winning trade. The higher this value is, the better, but it should be considered together with the percentage of winning trades and the net profit.
Winrate: The percentage of winning trades generated by a strategy. Calculated by dividing the number of winning trades by the total number of closed trades generated by a strategy. Percent profitable is not a very reliable measure by itself. A strategy could have many small winning trades, making the percent profitable high with a small average winning trade, or a few big winning trades accounting for a low percent profitable and a big average winning trade. Most mean-reversion successful strategies have a percent profitability of 40-80% but are profitable due to risk management control.
BE Trades: Number of break-even trades, excluding commission/slippage.
Losing Trades: The total number of losing trades generated by the strategy.
Winning Trades: The total number of winning trades generated by the strategy.
Total Trades: Total number of taken traders visible your charts.
Net Profit: The overall profit or loss (in the selected currency) achieved by the trading strategy in the test period. The value is the sum of all values from the Profit column (on the List of Trades tab), taking into account the sign.
- Monthly: Displays performance data on a month-by-month basis, allowing users to analyze performance trends over each month and year.
- Weekly: Displays performance data on a week-by-week basis, helping users to understand weekly performance variations.
- UI Table: A user-friendly table that allows users to view and save the selected strategy parameters from user inputs. This table enables easy access to key settings and configurations, providing a straightforward solution for saving strategy parameters by simply taking a screenshot with Alt + S or ⌥ + S.
User-input styles and customizations:
Please note that all background colors in the style are disabled by default to enhance visualization.
How to Use This Strategy to Create a Profitable Edge and Systems?
Choose Your Strategy mode:
- Decide whether you are creating an investing strategy or a trading strategy.
Select a Market:
- Choose a one-sided market such as stocks, indices, or cryptocurrencies.
Historical Data:
- Ensure the historical data covers at least 10 years of price action for robust backtesting.
Timeframe Selection:
- Choose the timeframe you are comfortable trading with. It is strongly recommended to use a timeframe above 15 minutes to minimize the impact of commissions/slippage on your profits.
Set Commission and Slippage:
- Properly set the commission and slippage in the strategy properties according to your broker/prop firm specifications.
Parameter Optimization:
- Use trial and error to test different parameters until you find the performance results you are looking for in the summary table or, preferably, through deep backtesting using the strategy tester.
Trade Count:
- Ensure the number of trades is 200 or more; the higher, the better for statistical significance.
Positive Average Trade:
- Make sure the average trade is above zero.
(An important value since it must be large enough to cover the commission and slippage costs of trading the strategy and still bring a profit.)
Performance Metrics:
- Look for a high profit factor, and net profit with minimum drawdown.
- Ideally, aim for a drawdown under 20-30%, depending on your risk tolerance.
Refinement and Optimization:
- Try out different markets and timeframes.
- Continue working on refining your edge using the available filters and components to further optimize your strategy.
What Makes This Strategy Unique?
This strategy combines flexibility, smart risk management, and momentum focus in a way that’s rare and practical:
1. Adapts to Any Market Rhythm
Works on daily, weekly, or intraday charts without code changes.
Uses two entry types: classic breakouts (like trending stocks) or fractal patterns (to avoid false starts).
2. Smarter Stop-Loss System
No rigid rules: Stops adjust based on price structure (e.g., new “higher lows”), not fixed percentages.
Avoids whipsaws: Tightens stops only when the trend strengthens, not in choppy markets.
3. Safe Profit-Boosting Pyramiding
Adds new positions only after prior trades are risk-free (stops moved above breakeven).
Scales up using locked-in profits, not new capital, to grow gains safely.
4. Built-In Momentum Check
Tracks 1/3/6-month price growth to spotlight stocks with strong, lasting momentum.
Terms and Conditions | Disclaimer
Our charting tools are provided for informational and educational purposes only and should not be construed as financial, investment, or trading advice. They are not intended to forecast market movements or offer specific recommendations. Users should understand that past performance does not guarantee future results and should not base financial decisions solely on historical data.
Built-in components, features, and functionalities of our charting tools are the intellectual property of @Fractalyst Unauthorized use, reproduction, or distribution of these proprietary elements is prohibited.
- By continuing to use our charting tools, the user acknowledges and accepts the Terms and Conditions outlined in this legal disclaimer and agrees to respect our intellectual property rights and comply with all applicable laws and regulations.
02 SMC + BB Breakout (Improved)This strategy combines Smart Money Concepts (SMC) with Bollinger Band breakouts to identify potential trading opportunities. SMC focuses on identifying key price levels and market structure shifts, while Bollinger Bands help pinpoint overbought/oversold conditions and potential breakout points. The strategy also incorporates higher timeframe trend confirmation to filter out trades that go against the prevailing trend.
Key Components:
Bollinger Bands:
Calculated using a Simple Moving Average (SMA) of the closing price and a standard deviation multiplier.
The strategy uses the upper and lower bands to identify potential breakout points.
The SMA (basis) acts as a centerline and potential support/resistance level.
The fill between the upper and lower bands can be toggled by the user.
Higher Timeframe Trend Confirmation:
The strategy allows for optional confirmation of the current trend using a higher timeframe (e.g., daily).
It calculates the SMA of the higher timeframe's closing prices.
A bullish trend is confirmed if the higher timeframe's closing price is above its SMA.
This helps filter out trades that go against the prevailing long-term trend.
Smart Money Concepts (SMC):
Order Blocks:
Simplified as recent price clusters, identified by the highest high and lowest low over a specified lookback period.
These levels are considered potential areas of support or resistance.
Liquidity Zones (Swing Highs/Lows):
Identified by recent swing highs and lows, indicating areas where liquidity may be present.
The Swing highs and lows are calculated based on user defined lookback periods.
Market Structure Shift (MSS):
Identifies potential changes in market structure.
A bullish MSS occurs when the closing price breaks above a previous swing high.
A bearish MSS occurs when the closing price breaks below a previous swing low.
The swing high and low values used for the MSS are calculated based on the user defined swing length.
Entry Conditions:
Long Entry:
The closing price crosses above the upper Bollinger Band.
If higher timeframe confirmation is enabled, the higher timeframe trend must be bullish.
A bullish MSS must have occurred.
Short Entry:
The closing price crosses below the lower Bollinger Band.
If higher timeframe confirmation is enabled, the higher timeframe trend must be bearish.
A bearish MSS must have occurred.
Exit Conditions:
Long Exit:
The closing price crosses below the Bollinger Band basis.
Or the Closing price falls below 99% of the order block low.
Short Exit:
The closing price crosses above the Bollinger Band basis.
Or the closing price rises above 101% of the order block high.
Position Sizing:
The strategy calculates the position size based on a fixed percentage (5%) of the strategy's equity.
This helps manage risk by limiting the potential loss per trade.
Visualizations:
Bollinger Bands (upper, lower, and basis) are plotted on the chart.
SMC elements (order blocks, swing highs/lows) are plotted as lines, with user-adjustable visibility.
Entry and exit signals are plotted as shapes on the chart.
The Bollinger band fill opacity is adjustable by the user.
Trading Logic:
The strategy aims to capitalize on Bollinger Band breakouts that are confirmed by SMC signals and higher timeframe trend. It looks for breakouts that align with potential market structure shifts and key price levels (order blocks, swing highs/lows). The higher timeframe filter helps avoid trades that go against the overall trend.
In essence, the strategy attempts to identify high-probability breakout trades by combining momentum (Bollinger Bands) with structural analysis (SMC) and trend confirmation.
Key User-Adjustable Parameters:
Bollinger Bands Length
Standard Deviation Multiplier
Higher Timeframe
Higher Timeframe Confirmation (on/off)
SMC Elements Visibility (on/off)
Order block lookback length.
Swing lookback length.
Bollinger band fill opacity.
This detailed description should provide a comprehensive understanding of the strategy's logic and components.
***DISCLAIMER: This strategy is for educational purposes only. It is not financial advice. Past performance is not indicative of future results. Use at your own risk. Always perform thorough backtesting and forward testing before using any strategy in live trading.***
Strategy Stats [presentTrading]Hello! it's another weekend. This tool is a strategy performance analysis tool. Looking at the TradingView community, it seems few creators focus on this aspect. I've intentionally created a shared version. Welcome to share your idea or question on this.
█ Introduction and How it is Different
Strategy Stats is a comprehensive performance analytics framework designed specifically for trading strategies. Unlike standard strategy backtesting tools that simply show cumulative profits, this analytics suite provides real-time, multi-timeframe statistical analysis of your trading performance.
Multi-timeframe analysis: Automatically tracks performance metrics across the most recent time periods (last 7 days, 30 days, 90 days, 1 year, and 4 years)
Advanced statistical measures: Goes beyond basic metrics to include Information Coefficient (IC) and Sortino Ratio
Real-time feedback: Updates performance statistics with each new trade
Visual analytics: Color-coded performance table provides instant visual feedback on strategy health
Integrated risk management: Implements sophisticated take profit mechanisms with 3-step ATR and percentage-based exits
BTCUSD Performance
The table in the upper right corner is a comprehensive performance dashboard showing trading strategy statistics.
Note: While this presentation uses Vegas SuperTrend as the underlying strategy, this is merely an example. The Stats framework can be applied to any trading strategy. The Vegas SuperTrend implementation is included solely to demonstrate how the analytics module integrates with a trading strategy.
⚠️ Timeframe Limitations
Important: TradingView's backtesting engine has a maximum storage limit of 10,000 bars. When using this strategy stats framework on smaller timeframes such as 1-hour or 2-hour charts, you may encounter errors if your backtesting period is too long.
Recommended Timeframe Usage:
Ideal for: 4H, 6H, 8H, Daily charts and above
May cause errors on: 1H, 2H charts spanning multiple years
Not recommended for: Timeframes below 1H with long history
█ Strategy, How it Works: Detailed Explanation
The Strategy Stats framework consists of three primary components: statistical data collection, performance analysis, and visualization.
🔶 Statistical Data Collection
The system maintains several critical data arrays:
equityHistory: Tracks equity curve over time
tradeHistory: Records profit/loss of each trade
predictionSignals: Stores trade direction signals (1 for long, -1 for short)
actualReturns: Records corresponding actual returns from each trade
For each closed trade, the system captures:
float tradePnL = strategy.closedtrades.profit(tradeIndex)
float tradeReturn = strategy.closedtrades.profit_percent(tradeIndex)
int tradeType = entryPrice < exitPrice ? 1 : -1 // Direction
🔶 Performance Metrics Calculation
The framework calculates several key performance metrics:
Information Coefficient (IC):
The correlation between prediction signals and actual returns, measuring forecast skill.
IC = Correlation(predictionSignals, actualReturns)
Where Correlation is the Pearson correlation coefficient:
Correlation(X,Y) = (nΣXY - ΣXY) / √
Sortino Ratio:
Measures risk-adjusted return focusing only on downside risk:
Sortino = (Avg_Return - Risk_Free_Rate) / Downside_Deviation
Where Downside Deviation is:
Downside_Deviation = √
R_i represents individual returns, T is the target return (typically the risk-free rate), and n is the number of observations.
Maximum Drawdown:
Tracks the largest percentage drop from peak to trough:
DD = (Peak_Equity - Trough_Equity) / Peak_Equity * 100
🔶 Time Period Calculation
The system automatically determines the appropriate number of bars to analyze for each timeframe based on the current chart timeframe:
bars_7d = math.max(1, math.round(7 * barsPerDay))
bars_30d = math.max(1, math.round(30 * barsPerDay))
bars_90d = math.max(1, math.round(90 * barsPerDay))
bars_365d = math.max(1, math.round(365 * barsPerDay))
bars_4y = math.max(1, math.round(365 * 4 * barsPerDay))
Where barsPerDay is calculated based on the chart timeframe:
barsPerDay = timeframe.isintraday ?
24 * 60 / math.max(1, (timeframe.in_seconds() / 60)) :
timeframe.isdaily ? 1 :
timeframe.isweekly ? 1/7 :
timeframe.ismonthly ? 1/30 : 0.01
🔶 Visual Representation
The system presents performance data in a color-coded table with intuitive visual indicators:
Green: Excellent performance
Lime: Good performance
Gray: Neutral performance
Orange: Mediocre performance
Red: Poor performance
█ Trade Direction
The Strategy Stats framework supports three trading directions:
Long Only: Only takes long positions when entry conditions are met
Short Only: Only takes short positions when entry conditions are met
Both: Takes both long and short positions depending on market conditions
█ Usage
To effectively use the Strategy Stats framework:
Apply to existing strategies: Add the performance tracking code to any strategy to gain advanced analytics
Monitor multiple timeframes: Use the multi-timeframe analysis to identify performance trends
Evaluate strategy health: Review IC and Sortino ratios to assess predictive power and risk-adjusted returns
Optimize parameters: Use performance data to refine strategy parameters
Compare strategies: Apply the framework to multiple strategies to identify the most effective approach
For best results, allow the strategy to generate sufficient trade history for meaningful statistical analysis (at least 20-30 trades).
█ Default Settings
The default settings have been carefully calibrated for cryptocurrency markets:
Performance Tracking:
Time periods: 7D, 30D, 90D, 1Y, 4Y
Statistical measures: Return, Win%, MaxDD, IC, Sortino Ratio
IC color thresholds: >0.3 (green), >0.1 (lime), <-0.1 (orange), <-0.3 (red)
Sortino color thresholds: >1.0 (green), >0.5 (lime), <0 (red)
Multi-Step Take Profit:
ATR multipliers: 2.618, 5.0, 10.0
Percentage levels: 3%, 8%, 17%
Short multiplier: 1.5x (makes short take profits more aggressive)
Stop loss: 20%
Scalping Strategy Signal v2 by [INFINITYTRADER]Overview
This Pine Script (v6) implements a scalping strategy that uses higher timeframe data (default: 4H) to generate entry and exit signals, originally designed for the 15-minute timeframe with an option for 30-minute charts. The "Scalping Strategy Signal v2 by " integrates moving averages, RSI, volume, ATR, and candlestick patterns to identify trading opportunities. It features adjustable risk management with ATR-based stop-loss, take-profit, and trailing stops, plus dynamic position sizing based on user-set capital. Trades trigger only on the higher timeframe candle close (e.g., 4H) to limit activity within the same period. This closed-source script offers a structured scalping approach, blending multiple entry methods and risk controls for adaptability across market conditions.
What Makes It Unique
Unlike typical scalping scripts relying on single-indicator triggers (e.g., RSI alone or basic MA crossovers), this strategy combines four distinct entry methods—standard MA crossovers, RSI-based momentum shifts, trend-following shorts, and candlestick pattern logic—evaluated on a 4H timeframe for confirmation. This multi-layered design, paired with re-entry logic after losses and a mix of manual, ATR-based, and trailing exits, aims to balance trade frequency and reliability. The higher timeframe filter adds precision not commonly found in simpler scalping tools, while the 30-minute option enhances consistency by reducing noise.
How It Works
Timeframe Logic
Runs on a base timeframe (designed for 15-minute charts, with a 30-minute option) while pulling data from a user-chosen higher timeframe (default: 4H) for signal accuracy.
Limits entries to the close of each 4H candle, ensuring one trade per period to avoid over-trading in volatile conditions.
Indicators and Data
Moving Averages : Employs 21-period and 50-period simple moving averages on the higher timeframe to detect trends and signal entries/exits.
Volume : Requires volume to exceed 70% of its 20-period average on the higher timeframe for momentum confirmation.
RSI : Uses a 14-period RSI for overbought/oversold filtering and a 6-period RSI for precise entry timing.
ATR : Applies a 14-period Average True Range on the higher timeframe to set adaptive stop-loss and take-profit levels.
Candlestick Patterns : Analyzes consecutive green or red 4H bars for trend continuation signals.
Why These Indicators
The blend of moving averages, RSI, volume, ATR, and candlestick patterns forms a robust scalping framework. Moving averages establish trend context, RSI filters momentum and avoids extremes, volume confirms market activity, ATR adjusts risk to volatility, and candlestick patterns enhance entry timing with price action insights. Together, they target small, frequent moves in flat or trending markets, with the 4H filter reducing false signals common in lower-timeframe scalping.
Entry Conditions
Four entry methods are evaluated at the 4H candle close:
Standard Long Entry: Price crosses above the 21-period moving average, volume exceeds 70% of its 20-period average, and the 1H 14-period RSI is below 70—confirms uptrend momentum.
Special Long Entry: The 6-period RSI crosses above 23, price is more than 1.5 times the ATR from the 21-period moving average, and price exceeds its prior close—targets oversold bounces with a stop-loss at the 4H candle’s low.
Short Entries:
- RSI-Based: The 6-period RSI crosses below 68 with volume support—catches overbought pullbacks.
- Trend-Based: Price crosses below the 21-period moving average, volume is above 70% of its average, and the 1H 14-period RSI is above 30—confirms downtrends.
Red/Green Bar Logic: Two consecutive green 4H bars for longs or red 4H bars for shorts—uses candlestick patterns for continuation, with a tight stop-loss from the base timeframe candle.
Re-Entry Logic
Long : After a losing special long, triggers when the 6-period RSI crosses 27 and price crosses the 21-period moving average.
Short : After a losing short, triggers when the 6-period RSI crosses 50 and price crosses below the 21-period moving average.
Purpose: Offers recovery opportunities with stricter conditions.
Exit Conditions
Manual Exits: Longs close if the 21-period MA crosses below the 50-period MA or the 1H 14-period RSI exceeds 68; shorts close if the 21-period MA crosses above the 50-period MA or RSI drops below 25.
ATR-Based TP/SL: Stop-loss is entry price ± ATR × 1.5 (default); take-profit is ± ATR × 4 (default), checked at 4H close.
Trailing Stop: Adjusts ±6x ATR from peak/trough, closing if price retraces within 1x ATR.
Special/Tight SL: Special longs exit if price opens below the 4H candle’s low; 4th method entries use the base timeframe candle’s low/high, checked every bar.
Position Sizing
Bases trade value on user-set capital (default: 100 USDT), dividing by the higher timeframe close price for dynamic sizing.
Visualization
Displays a table at the bottom-right with current/previous signals, TP/SL levels, equity, trading pair, and trade size—color-coded for clarity (green for buy, red for sell).
Inputs
Initial Capital (USDT): Sets trade value (default: 100, min: 1).
ATR Stop-Loss Multiplier: Adjusts SL distance (default: 1.5, min: 1).
ATR Take-Profit Multiplier: Adjusts TP distance (default: 4, min: 1).
Higher Timeframe: Selects analysis timeframe (options: 1m, 5m, 15m, 30m, 1H, 4H, D, W; default: 4H).
Usage Notes
Intended Timeframe: Designed for 15-minute charts with 4H confirmation for precision and frequency; 30-minute charts improve consistency by reducing noise.
Backtesting: Adjust ATR multipliers and capital to match your asset’s volatility and risk tolerance.
Risk Management: Combines manual, ATR, and trailing exits—monitor to avoid overexposure.
Limitations: 4H candle-close dependency may delay entries in fast markets; RSI/volume filters can reduce trades in low-momentum periods.
Backtest Observations
Tested on BTC/USDT (4H higher timeframe, default settings: Initial Capital: 100 USDT, ATR SL: 1.5x, ATR TP: 4x) across market conditions, comparing 15-minute and 30-minute charts:
Bull Market (Jul 2023 - Dec 2023):
15-Minute: 277 long, 219 short; Win Rate: 42.74%; P&L: 108%; Drawdown: 1.99%; Profit Factor: 3.074.
30-Minute: 257 long, 215 short; Win Rate: 49.58%; P&L: 116.85%; Drawdown: 2.34%; Profit Factor: 3.14.
Notes: Moving average crossovers and green bar patterns suited this bullish phase; 30-minute improved win rate and P&L by filtering weaker signals.
Bear Market (Jan 2022 - Jun 2022):
15-Minute: 262 long, 211 short; Win Rate: 44.4%; P&L: 239.80%; Drawdown: 3.74%; Profit Factor: 3.419.
30-Minute: 250 long, 200 short; Win Rate: 52.22%; P&L: 258.77%; Drawdown: 5.34%; Profit Factor: 3.461.
Notes: Red bar patterns and RSI shorts thrived in the downtrend; 30-minute cut choppy reversals for better consistency.
Flat Market (Jan 2021 - Jun 2021):
15-Minute: 280 long, 208 short; Win Rate: 51.84%; P&L: 340.33%; Drawdown: 9.59%; Profit Factor: 2.924.
30-Minute: 270 long, 209 short; Win Rate: 55.11%; P&L: 315.42%; Drawdown: 7.21%; Profit Factor: 2.598.
Notes: High trade frequency and P&L showed strength in ranges; 30-minute lowered drawdown for better risk control.
Results reflect historical performance on BTC/USDT with default settings—users should test on their assets and timeframes. Past performance does not guarantee future results and is shared only to illustrate the strategy’s behavior.
Why It Works Well in Flat Markets
A "flat market" lacks strong directional trends, with price oscillating around moving averages, as in Jan 2021 - Jun 2021 for BTC/USDT. This strategy excels here because its crossover-based entries trigger frequently in tight ranges. In trending markets, an exit might not be followed by a new entry without a pullback, but flat markets produce multiple crossovers, enabling more trades. ATR-based TP/SL and trailing stops capture these small swings, while RSI and volume filters ensure momentum, driving high P&L and win rates.
Technical Details
Built in Pine Script v6 for TradingView compatibility.
Prevents overlapping trades with long/short checks.
Handles edge cases like zero division and auto-detects the trading pair’s base currency (e.g., BTC from BTCUSDT).
This strategy suits scalpers seeking structured entries and risk management. Test on 15-minute or 30-minute charts to match your style and market conditions.
RSI Pro+ (Bear market, financial crisis and so on EditionIn markets defined by volatility, fear, and uncertainty – the battlegrounds of bear markets and financial crises – you need tools forged in resilience. Introducing RSI Pro+, a strategy built upon a legendary indicator born in 1978, yet engineered with modern visual clarity to remain devastatingly effective even in the chaotic financial landscapes of 3078.
This isn't about complex algorithms predicting the unpredictable. It's about harnessing the raw, time-tested power of the Relative Strength Index (RSI) to identify potential exhaustion points and capitalize on oversold conditions. RSI Pro+ cuts through the noise, providing clear, actionable signals when markets might be poised for a relief bounce or reversal.
Core Technology (The 1978 Engine):
RSI Crossover Entry: The strategy initiates a LONG position when the RSI (default period 11) crosses above a user-defined low threshold (default 30). This classic technique aims to enter when selling pressure may be waning, offering potential entry points during sharp downturns or periods of consolidation after a fall.
Modern Enhancements (The 3078 Cockpit):
RSI Pro+ isn't just about the signal; it's about providing a professional-grade visual experience directly on your chart:
Entry Bar Highlight: A subtle background flash on the chart signals the exact bar where the RSI crossover condition is met, alerting you to potential entry opportunities.
Trade Bar Coloring: Once a trade is active, the price bars are subtly colored, giving you immediate visual confirmation that the strategy is live in the market.
Entry Price Line: A clear, persistent line marks your exact average entry price for the duration of the trade, serving as a crucial visual anchor.
Take Profit Line: Your calculated Take Profit target is plotted as a distinct line, keeping your objective clearly in sight.
Custom Entry Marker: A precise shape (▲) appears below the bar where the trade entry was actually executed, pinpointing the start of the position.
On-Chart Info Table (HUD): A clean, customizable Heads-Up Display appears when a trade is active, showing vital information at a glance:
Entry Price: Your position's average cost basis.
TP Target: The calculated price level for your Take Profit exit.
Current PnL%: Real-time Profit/Loss percentage for the open trade.
Full Customization: Nearly every aspect is configurable via the settings menu:
RSI Period & Crossover Level
Take Profit Percentage
Toggle ALL visual enhancements on/off individually
Position the Info Table wherever you prefer on the chart.
How to Use RSI Pro+:
Add to Chart: Apply the "RSI Pro+ (Bear market...)" strategy to your TradingView chart. Ensure any previous versions are removed.
Access Settings: Click the cogwheel icon (⚙️) next to the strategy name on your chart.
Configure Inputs (Crucial Step):
RSI Crossover Level: This is key. The default (30) targets standard oversold conditions. In severe downturns, you might experiment with lower levels (e.g., 25, 20) or higher ones (e.g., 40) depending on the asset and timeframe. Observe where RSI(11) typically bottoms out on your chart.
Take Profit Percentage (%): Define your desired profit target per trade (e.g., enter 0.5 for 0.5%, 1.0 for 1%). The default is a very small 0.11%.
RSI Period: While default is 11, you can adjust this (e.g., the standard 14).
Visual Enhancements: Enable or disable the visual features (background highlights, bar coloring, lines, markers, table) according to your preference using the checkboxes. Adjust table position.
Observe & Backtest: Watch how the strategy behaves on your chosen asset and timeframe. Use TradingView's Strategy Tester to analyze historical performance based on your settings. No strategy works perfectly everywhere; testing is essential.
Important Considerations:
Risk Management: This specific script version focuses on a Take Profit exit. It does not include an explicit Stop Loss. You MUST manage risk through appropriate position sizing, potentially adding a Stop Loss manually, or by modifying the script.
Oversold ≠ Reversal: An RSI crossover is an indicator of potential exhaustion, not a guarantee of a price reversal.
Fixed TP: A fixed percentage TP ensures small wins but may exit before larger potential moves.
Backtesting Limitations: Past performance does not guarantee future results.
RSI Pro+ strips away complexity to focus on a robust, time-honored principle, enhanced with modern visuals for the discerning trader navigating today's (and tomorrow's) challenging markets
