The moving average crossover strategy is a very common quantitative trading strategy. It uses the golden cross and death cross of moving averages to determine trends and profit. When the short-term moving average crosses above the long-term moving average, it signals an uptrend, and a long position can be taken. When the short-term moving average crosses below the long-term moving average, it signals a downtrend, and a short position can be taken.
This strategy is based on the golden cross and death cross of moving averages to determine entry and exit points. The code uses two boolean input parameters upOrDown and longOrShort to determine long or short; percentInput to set the threshold percentage of price change; closePositionDays to set the number of days to hold the position.
The core logic is: calculate the increase/decrease of today relative to yesterday. If it reaches the input threshold percentage, a trading signal is triggered. If it’s a long signal, when today’s price increases more than threshold relative to yesterday, go long. If it’s a short signal, when today’s price decreases more than threshold relative to yesterday, go short.
After going long/short, the entry day and next 4 days will be marked with colors on the chart. The position will be closed automatically after 4 days.
Risk management:
The moving average crossover strategy is a very simple and practical quantitative trading strategy. By judging the relationship between short-term and long-term trends, it profits from the trending nature of asset prices. This strategy is easy to implement with clear logic, and forms the foundation of many quantitative trading strategies. We can obtain better performance through parameter tuning and optimizations. But we also need to manage risks and avoid misuse.
/*backtest
start: 2023-01-01 00:00:00
end: 2023-10-11 00:00:00
period: 1d
basePeriod: 1h
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/
//@version=3
// Created by Leon Ross
strategy(title = "DaysAfterCertainPercentChangev1", shorttitle = "DACPCv1", overlay = true,
pyramiding = 0, default_qty_type = strategy.percent_of_equity, default_qty_value = 100,
calc_on_every_tick=true, initial_capital=100000)
//Inputs
longOrShort = input(title="Long=Checked Short=Unchecked", type=bool, defval=true) //long=true, down=false
upOrDown = input(title="Direction of Today vs. Previous day: Up=Checked Down=Unchecked", type=bool, defval=true) //up=true, down=false: this is the direction of days vs previous day
percentInput = input(title="Percent", type=float, defval=4.5)
closePositionDays = input(title="How Many Days to Close Position", defval=4)
//Conditions
//percentUpValue = (close / close[1]) - 1
//percentUp = percentUpValue >= (percentInput/100.0)
//upConditions = percentUp
//percentDownValue = 1- (close / close[1])
//percentDown = percentDownValue >= (percentInput/100.0)
//downConditions = percentDown
upValue = (close / close[1]) - 1
downValue = 1 - (close / close[1])
allConditions = if(upOrDown)
upValue >= (percentInput/100.0)
else
downValue >= (percentInput/100.0)
//Plots
bgcolor(allConditions ? (upOrDown ? green : red) : na, transp=70)
bgcolor(allConditions ? silver : na, transp=70, offset=1)
bgcolor(allConditions ? silver : na, transp=70, offset=2)
bgcolor(allConditions ? silver : na, transp=70, offset=3)
bgcolor(allConditions ? silver : na, transp=70, offset=4)
//bgcolor(downConditions == 1 ? red : na, transp=70)
//bgcolor(downConditions == 1 ? silver : na, transp=70, offset=1)
//bgcolor(downConditions == 1 ? silver : na, transp=70, offset=2)
//bgcolor(downConditions == 1 ? silver : na, transp=70, offset=3)
//bgcolor(downConditions == 1 ? silver : na, transp=70, offset=4)
//Entires
if(longOrShort)
strategy.entry(id = "Long", long = true, when = allConditions)
else
strategy.entry(id = "Short", long = false, when = allConditions)
//Exits
if (barssince(allConditions) == closePositionDays)
if(longOrShort)
strategy.close("Long")
else
strategy.close("Short")