Statistical Dual Standard Deviation VWAP Breakout Trading Strategy

Pine ScriptBreakout Mean reversion Trend following VWAP

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

Jump to code View in vault Original on FMZ

Overview

This strategy is a trend breakout system based on VWAP (Volume Weighted Average Price) and standard deviation channels. It constructs a dynamic price range by calculating VWAP and standard deviation bands to capture upward breakout opportunities. The strategy mainly relies on standard deviation band breakthrough signals for trading, with profit targets and order intervals to control risk.

Strategy Principles

Core Indicator Calculation:

Calculate VWAP using intraday HL2 prices and volume
Compute standard deviation based on price volatility
Set 1.28 times standard deviation upper and lower bands

Trading Logic:

Entry condition: price crosses below lower band then rises above it
Exit condition: reaches preset profit target
Minimum order interval to avoid frequent trading

Strategy Advantages

Statistical Foundation

VWAP-based price center reference
Volatility measurement using standard deviation
Dynamic trading range adjustment

Risk Control

Fixed profit target setting
Trading frequency control
Long-only strategy reduces risk

Strategy Risks

Market Risks

False breakouts during high volatility
Difficulty in accurately timing trend reversals
Increased losses in downtrend markets

Parameter Risks

Sensitivity to standard deviation multiplier settings
Profit target optimization needed
Trading interval affects performance

Optimization Directions

Signal Optimization

Add trend filter
Incorporate volume change confirmation
Include additional technical indicators

Risk Management Optimization

Dynamic stop-loss placement
Position sizing based on volatility
Enhanced order management system

Summary

This is a quantitative trading strategy combining statistical principles and technical analysis. Through the combination of VWAP and standard deviation bands, it builds a relatively reliable trading system. The core advantages lie in its scientific statistical foundation and comprehensive risk control mechanisms, but continuous optimization of parameters and trading logic is still needed in practical applications.

Source Pine Script

/*backtest
start: 2019-12-23 08:00:00
end: 2025-01-04 08:00:00
period: 1d
basePeriod: 1d
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

//@version=5 
strategy("VWAP Stdev Bands Strategy (Long Only)", overlay=true)

// Standard Deviation Inputs
devUp1 = input.float(1.28, title="Stdev above (1)")
devDn1 = input.float(1.28, title="Stdev below (1)")

// Show Options
showPrevVWAP = input(false, title="Show previous VWAP close?")
profitTarget = input.float(2, title="Profit Target ($)", minval=0) // Profit target for closing orders
gapMinutes = input.int(15, title="Gap before new order (minutes)", minval=0) // Gap for placing new orders

// VWAP Calculation
var float vwapsum = na
var float volumesum = na
var float v2sum = na
var float prevwap = na // Track the previous VWAP
var float lastEntryPrice = na // Track the last entry price
var int lastEntryTime = na // Track the time of the last entry

start = request.security(syminfo.tickerid, "D", time)
newSession = ta.change(start)

vwapsum := newSession ? hl2 * volume : vwapsum[1] + hl2 * volume
volumesum := newSession ? volume : volumesum[1] + volume
v2sum := newSession ? volume * hl2 * hl2 : v2sum[1] + volume * hl2 * hl2

myvwap = vwapsum / volumesum
dev = math.sqrt(math.max(v2sum / volumesum - myvwap * myvwap, 0))

// Calculate Upper and Lower Bands
lowerBand1 = myvwap - devDn1 * dev
upperBand1 = myvwap + devUp1 * dev

// Plot VWAP and Bands with specified colors
plot(myvwap, style=plot.style_line, title="VWAP", color=color.green, linewidth=1)
plot(upperBand1, style=plot.style_line, title="VWAP Upper (1)", color=color.blue, linewidth=1)
plot(lowerBand1, style=plot.style_line, title="VWAP Lower (1)", color=color.red, linewidth=1)

// Trading Logic (Long Only)
longCondition = close < lowerBand1 and close[1] >= lowerBand1 // Price crosses below the lower band

// Get the current time in minutes
currentTime = timestamp("GMT-0", year(timenow), month(timenow), dayofmonth(timenow), hour(timenow), minute(timenow))

// Check if it's time to place a new order based on gap
canPlaceNewOrder = na(lastEntryTime) or (currentTime - lastEntryTime) >= gapMinutes * 60 * 1000

// Close condition based on profit target
if (strategy.position_size > 0)
    if (close - lastEntryPrice >= profitTarget)
        strategy.close("B")
        lastEntryTime := na // Reset last entry time after closing

// Execute Long Entry
if (longCondition and canPlaceNewOrder)
    strategy.entry("B", strategy.long)
    lastEntryPrice := close // Store the entry price
    lastEntryTime := currentTime // Update the last entry time

    // Add label for the entry
    label.new(bar_index, close, "B", style=label.style_label_down, color=color.green, textcolor=color.white, size=size.small)

// Optional: Plot previous VWAP for reference
prevwap := newSession ? myvwap[1] : prevwap[1]
plot(showPrevVWAP ? prevwap : na, style=plot.style_circles, color=close > prevwap ? color.green : color.red)

Published by ChaoZhang on the FMZ strategy square · last modified 2025-01-06. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.

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