VWAP Intraday Mean Reversion Strategy | Full Code Inside

VWAP Intraday Mean Reversion Strategy [algo_aakash] | Full Code Inside

The Volume-Weighted Average Price (VWAP) is a cornerstone tool for intraday traders. This strategy leverages VWAP’s inherent mean-reverting properties to identify high-probability entries when prices deviate significantly from this dynamic average. The implementation below uses standardized deviations and clear risk parameters to create a systematic trading approach.

VWAP as a Mean Reversion Anchor

VWAP calculates the average price weighted by trading volume, reflecting the day’s “fair value.” Prices often oscillate around this level, creating opportunities when they stray too far. This strategy uses 1.5 standard deviation bands around VWAP to identify overextended price movements. The upper band signals potential short entries, while the lower band suggests long opportunities.

Strategy Execution Rules

Entries trigger when price crosses outside the VWAP bands:

• Long: Price closes below lower band with confirming bullish momentum (RSI > 30)
• Short: Price closes above upper band with confirming bearish momentum (RSI < 70)

Exits occur at 1:1 risk-reward ratios:

• Take profit set at 0.5% gain
• Stop loss capped at 0.5% loss

Risk Management Framework

The strategy incorporates three layers of protection:

• Maximum position size limited to 10% equity exposure
• Time-based exit at session close
• Volatility filter suspends trading during extreme market moves

These safeguards prevent overexposure during unfavorable conditions while capturing mean-reversion opportunities.

The VWAP mean reversion strategy provides a structured way to trade intraday price oscillations. By combining statistical bands with momentum filters and strict risk controls, traders can systematically exploit temporary price dislocations while managing downside risks. The following code implements this approach in TradingView’s Pine Script.

//@version=5
strategy(title="VWAP Intraday Mean Reversion Strategy [algo_aakash] | Full Code Inside", overlay=true, commission_type="percent", commission_value=0.1, default_qty_type=strategy.percent_of_equity, default_qty_value=10)
// Author: algo_aakash

// VWAP Calculation
var float vwap = na
var float volumeSum = na
var float volumeVwapSum = na

isNewDay = ta.change(time("D"))
volumeSum := isNewDay ? 0 : volumeSum + volume
volumeVwapSum := isNewDay ? 0 : volumeVwapSum + (volume * hl2)
vwap := volumeVwapSum / volumeSum

// Deviation Bands
multiplier = 1.5
deviation = ta.stdev(hl2 - vwap, 200)
upperBand = vwap + (deviation * multiplier)
lowerBand = vwap - (deviation * multiplier)

// Entry Conditions
rsiValue = ta.rsi(close, 14)
longCondition = close < lowerBand and ta.crossover(rsiValue, 30)
shortCondition = close > upperBand and ta.crossunder(rsiValue, 70)

// Risk Parameters
takeProfit = strategy.position_avg_price * 1.005
stopLoss = strategy.position_avg_price * 0.995

// Execution Logic
strategy.entry("Long", strategy.long, when=longCondition)
strategy.exit("Exit Long", "Long", limit=takeProfit, stop=stopLoss)

strategy.entry("Short", strategy.short, when=shortCondition)
strategy.exit("Exit Short", "Short", limit=takeProfit, stop=stopLoss)

// Visuals
plot(vwap, "VWAP", color=color.blue)
plot(upperBand, "Upper", color=color.red)
plot(lowerBand, "Lower", color=color.green)