Momentum Moving Average Crossover Quant Strategy

Author: ChaoZhang, Date: 2024-01-26 11:39:26



This strategy combines the moving average and trading volume indicators to design the long and short entry and exit rules, forming a complete quantitative trading strategy.

Strategy Principle

Key Indicators

  1. Moving Averages: Fast MA (Blue Line) and Slow MA (Red Line)
  2. Volume: 24-hour Volume (Purple) and 7-day Average Volume (Orange)

Strategy Conditions

Long Entry Conditions:

  1. Fast MA crosses above Slow MA
  2. 24-hour Volume below 50% of 7-day Average Volume

Short Entry Conditions:

Fast MA crosses below Slow MA

Entries and Exits

Long Entry: Go long when long conditions are met

Short Entry: Go short when short conditions are met

Take Profit and Stop Loss: Displayed take profit and stop loss levels for long position

Advantage Analysis

  1. Combining price and volume avoid false breakout
  2. Clear entry and exit rules
  3. Take profit and stop loss to control risk

Risk Analysis

  1. Frequent trading with moving average strategy
  2. Unreliable volume data quality
  3. Overoptimization in parameter tuning


  1. Adjust MA parameters to reduce trading frequency
  2. Verify signals with more data sources
  3. Strict backtesting to prevent overoptimization

Optimization Directions

  1. Add other indicators to filter signals
  2. Dynamic take profit and stop loss
  3. Multiple timeframe analysis to improve stability


This strategy integrates MA and volume indicators to design a complete quant strategy with clear entry conditions, take profit/stop loss, easy to operate. Need to prevent frequent trading issue, monitor volume data quality and overoptimization. NEXT steps are multivariate optimization, dynamic TP/SL and multiple timeframe analysis.

start: 2023-01-25 00:00:00
end: 2024-01-25 00:00:00
period: 1h
basePeriod: 15m
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]

strategy("MA and Volume Strategy", overlay=true)

// Input parameters
fastLength = input(9, title="Fast MA Length")
slowLength = input(21, title="Slow MA Length")
volumePercentageThreshold = input(50, title="Volume Percentage Threshold")

// Calculate moving averages
fastMA = ta.sma(close, fastLength)
slowMA = ta.sma(close, slowLength)

// Calculate 24-hour volume and weekly volume average
dailyVolume =, "D", volume)
weeklyVolumeAvg = ta.sma(, "W", volume), 7)

// Strategy conditions
longCondition = ta.crossover(fastMA, slowMA) and dailyVolume < (weeklyVolumeAvg * volumePercentageThreshold / 100)
shortCondition = ta.crossunder(fastMA, slowMA)

// Set take profit and stop loss levels
takeProfitLong = close * 1.50
stopLossLong = close * 0.90

// Strategy orders
strategy.entry("Long", strategy.long, when=longCondition)
strategy.entry("Short", strategy.short, when=shortCondition)

// Plot moving averages
plot(fastMA,, title="Fast MA")
plot(slowMA,, title="Slow MA")

// Plot 24-hour volume and weekly volume average
plot(dailyVolume, color=color.purple, title="24-Hour Volume", transp=0)
plot(weeklyVolumeAvg,, title="Weekly Volume Average")

// Plot entry signals
plotshape(series=longCondition, title="Buy Signal",, style=shape.triangleup, size=size.small)
plotshape(series=shortCondition, title="Sell Signal",, style=shape.triangledown, size=size.small)

// Plot take profit and stop loss levels only when a valid trade is active
plotshape(series=longCondition, title="Take Profit Long",, style=shape.triangleup, size=size.small)
plotshape(series=longCondition, title="Stop Loss Long",, style=shape.triangledown, size=size.small)