Pivot Based Volume Weighted Breakout Reversal Strategy

Pine ScriptBreakout Mean reversion Machine learning EMA SMA ATR ADX / DMI Volume Pivots / S&R

Author: ianzeng123
Complexity: Starter · 74 lines
Parameters: 0
Backtest bar: 1d · swing
Tested on: DOGE/USDT · futures

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Overview

This strategy combines support/resistance (S/R) breakout/reversal, volume filtering, and alert systems to capture key market turning points. It identifies price breakout/reversal signals validated by abnormal volume activity to improve reliability. The strategy employs a fixed 2% stop loss and adjustable take profit (default 3%) for risk management.

Strategy Logic

S/R Identification: Uses ta.pivothigh() and ta.pivotlow() to detect key price levels within a specified period (pivotLen). Signals trigger when price breaks resistance (upward >1%) or bounces from support (false breakdown recovery).
Volume Filter: Calculates volume SMA (volSmaLength periods). A valid signal requires current volume exceeding SMA by volMultiplier (default 1.5x).
Long/Short Logic:
- Long Condition: Price breaks resistance (close > resZone*1.01) with high volume, or shows false breakdown near support (±1% range) with volume confirmation.
- Short Condition: Price breaks support (close < supZone*0.99) with high volume, or shows false breakout near resistance (±1% range) with volume confirmation.
Risk Management: Fixed 2% stop loss and adjustable take profit (default 3%) via strategy.exit().

Advantages

Multi-Factor Validation: Combines price structure (S/R), volume, and market behavior (false breaks), significantly reducing false signals.
Dynamic Adaptation: Auto-updates S/R levels to adapt to market changes.
Strict Risk Control: Fixed stop loss prevents excessive losses; adjustable take profit suits varying market conditions.
High Visibility: Real-time S/R plotting and clear signal labels.
Alert Integration: Compatible with automated trading systems.

Risks

Range-Bound Risk: Frequent false breakouts in choppy markets. Solution: Add trend filters like ADX or EMA.
Parameter Sensitivity: pivotLen and volMultiplier require market-specific tuning. Solution: Parameter optimization and Walk-Forward testing.
Volume Lag: Abnormal volume may follow price moves. Solution: Incorporate order book data or reduce volSmaLength.
Gap Risk: Opening gaps may skip stop levels. Solution: Use limit orders or avoid high-volatility sessions.

Optimization Directions

Trend Filtering: Add ADX>25 or 200EMA direction filters to avoid counter-trend trades.
Dynamic Parameters: Auto-adjust pivotLen and volMultiplier based on volatility (e.g., ATR).
Scaled Take Profit: Implement two-tier exits (e.g., close 50% at 2%, trail remainder).
Machine Learning: Train models to optimize volMultiplier and tpPerc historically.
Multi-Timeframe Confirmation: Validate signals with higher timeframe S/R levels.

Conclusion

This strategy establishes a high-probability framework through triple validation (price position, volume, price action), ideal for capturing early trend phases. Its transparency and controlled risk are key strengths, though range-bound performance requires caution. Future enhancements should focus on parameter self-adaptation and trend filtering for greater robustness.

Source Pine Script

/*backtest
start: 2024-04-24 00:00:00
end: 2024-12-31 00:00:00
period: 1d
basePeriod: 1d
exchanges: [{"eid":"Futures_Binance","currency":"DOGE_USDT"}]
*/

//@version=5
strategy("S/R Breakout/Reversal + Volume + Alerts", overlay=true, default_qty_type=strategy.percent_of_equity, default_qty_value=100)

// === INPUTS ===
pivotLen       = input.int(10, "Pivot Lookback for S/R")
volSmaLength   = input.int(20, "Volume SMA Length")
volMultiplier  = input.float(1.5, "Volume Multiplier")
tpPerc         = input.float(3.0, "Take Profit %", step=0.1)
slPerc         = 2.0  // Stop Loss fixed at 2%

// === S/R ZONES ===
pivotHigh = ta.pivothigh(high, pivotLen, pivotLen)
pivotLow  = ta.pivotlow(low, pivotLen, pivotLen)

var float resZone = na
var float supZone = na
if not na(pivotHigh)
    resZone := pivotHigh
if not na(pivotLow)
    supZone := pivotLow

plot(supZone, title="Support", color=color.green, linewidth=2, style=plot.style_linebr)
plot(resZone, title="Resistance", color=color.red,   linewidth=2, style=plot.style_linebr)

// === VOLUME FILTER ===
volSma     = ta.sma(volume, volSmaLength)
highVolume = volume > volSma * volMultiplier

// === LONG LOGIC ===
priceAboveRes     = close > resZone * 1.01
nearSupport       = close >= supZone * 0.99 and close <= supZone * 1.01
rejectSupport     = low <= supZone and close > supZone
longBreakoutCond  = priceAboveRes and highVolume
longReversalCond  = nearSupport and rejectSupport and highVolume
longCondition     = longBreakoutCond or longReversalCond

// === SHORT LOGIC ===
priceBelowSup     = close < supZone * 0.99
nearResistance    = close >= resZone * 0.99 and close <= resZone * 1.01
rejectResistance  = high >= resZone and close < resZone
shortBreakoutCond = priceBelowSup and highVolume
shortReversalCond = nearResistance and rejectResistance and highVolume
shortCondition    = shortBreakoutCond or shortReversalCond

// === ENTRIES WITH LABELS ===
if (longCondition)
    strategy.entry("Long", strategy.long)
    label.new(bar_index, low * 0.995, "BUY", style=label.style_label_up, color=color.green, textcolor=color.white)

if (shortCondition)
    strategy.entry("Short", strategy.short)
    label.new(bar_index, high * 1.005, "SELL", style=label.style_label_down, color=color.red, textcolor=color.white)

// === TP/SL ===
longTP  = close * (1 + tpPerc / 100)
longSL  = close * (1 - slPerc / 100)
shortTP = close * (1 - tpPerc / 100)
shortSL = close * (1 + slPerc / 100)

strategy.exit("Long TP/SL",  from_entry="Long",  limit=longTP,  stop=longSL)
strategy.exit("Short TP/SL", from_entry="Short", limit=shortTP, stop=shortSL)

// === ALERT CONDITIONS ===
alertcondition(longCondition,  title="Buy Alert",  message="? BUY signal: S/R + Volume breakout/reversal")
alertcondition(shortCondition, title="Sell Alert", message="? SELL signal: S/R + Volume breakout/reversal")

Published by ianzeng123 on the FMZ strategy square · last modified 2025-04-24. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.

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