Moving Average Crossover Strategy 430064

Author: ChaoZhang
Complexity: Intermediate · 74 lines
Parameters: 8
Backtest bar: 2h · intraday
Tested on: BTC/USDT · futures

Jump to code View in vault Original on FMZ

Overview

This strategy is based on the moving average crossover principle. It goes long when the short-term moving average crosses above the long-term moving average from below, and goes short when the short-term moving average crosses below the long-term moving average from above. It's a typical trend following strategy.

Strategy Logic

The strategy mainly calculates the short-term and long-term simple moving averages, and determines the trend direction based on their crossover.

Specifically, it first calculates the short-term moving average xMA and the long-term moving average, where the short-term period is Len, and the long-term period is 2*Len.

Then it checks if the short-term MA crosses above the long-term MA, and generates a long signal if the crossover happens. It also checks if the short-term MA crosses below the long-term MA, and generates a short signal if the crossover happens.

Upon receiving a long signal, it opens a long position at market price if there is no position. Upon receiving a short signal, it opens a short position at market price if there is no position.

In addition, stop loss and take profit points are configured. For long trades, the stop loss is set at entry price - stop loss percentage * entry price, and take profit at entry price + take profit percentage * entry price. For short trades, the stop loss is set at entry price + stop loss percentage * entry price, and take profit at entry price - take profit percentage * entry price.

Finally, the moving averages are plotted for visualization to assist with trend determination.

Advantages

Simple and easy to understand, suitable for beginners.
Can effectively track market trends based on moving average crossovers.
Risks are controlled by configuring stop loss and take profit.
Visualization of moving averages intuitively reflects trend changes.

Risks

Moving averages have lagging effects, which may cause missing the best entry points.
Improper stop loss configuration may result in stops being too wide or too tight.
Prices whipsawing may generate false signals.
Optimizing solely based on the moving average periods may lead to overfitting.

These risks can be reduced by using looser stops, optimizing moving average period combinations, adding filter indicators etc.

Optimization Directions

Add other indicators like MACD, KDJ for filtering to avoid false signals.
Optimize combinations of short and long moving average periods to find optimum parameters.
Test different stop loss/take profit strategies like trailing stops.
Add position sizing to optimize capital utilization.

Summary

The strategy has a clear and simple logic, can track trends effectively based on moving average crossovers, and has controllable risks. It is suitable for beginners to learn from. But relying solely on moving averages may generate false signals. There is still much room for optimizating it in various aspects to make it more robust.

Parameters

Name	Default	What it controls
v_input_2	13	Len
v_input_float_3	7	Take Profit %
v_input_float_4	7	Stop Loss %
v_input_1		(?entry)Signal Token
v_input_string_1	0	Order Type: market \| limit
v_input_float_1	false	Order Price Offset
v_input_string_2	0	Investment Type: percentage_balance \| contract \| margin \| percentage_investment
v_input_float_2	100	Amount

Source Pine Script

/*backtest
start: 2023-09-23 00:00:00
end: 2023-10-23 00:00:00
period: 2h
basePeriod: 15m
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

//@version=5
//@strategy_alert_message {{strategy.order.alert_message}} 
////////////////////////////////////////////////////////////
//  Copyright by HPotter v2.0 19/09/2023
// MA Crossover Bot for OKX Exchange
////////////////////////////////////////////////////////////
var ALERTGRP_CRED = "entry"
signalToken = input("", "Signal Token", inline = "11", group = ALERTGRP_CRED)
OrderType = input.string("market", "Order Type", options = ["market", "limit"], inline = "21", group = ALERTGRP_CRED)
OrderPriceOffset = input.float(0, "Order Price Offset", minval = 0, maxval = 100, step = 0.01, inline = "21", group = ALERTGRP_CRED)
InvestmentType = input.string("percentage_balance", "Investment Type", options = ["margin", "contract", "percentage_balance", "percentage_investment"], inline = "31", group = ALERTGRP_CRED)
Amount = input.float(100, "Amount", minval = 0.01, inline = "31", group = ALERTGRP_CRED)

getAlertMsg(action, instrument, signalToken, orderType, orderPriceOffset, investmentType, amount) =>
    str = '{'
    str := str + '"action": "' + action + '", '
    str := str + '"instrument": "' + instrument + '", '
    str := str + '"signalToken": "' + signalToken + '", '
    //str := str + '"timestamp": "' + str.format_time(timenow, "yyyy-MM-dd'T'HH:mm:ssZ", "UTC+0") + '", '
    str := str + '"timestamp": "' + '{{timenow}}' + '", '
    str := str + '"orderType": "' + orderType + '", '
    str := str + '"orderPriceOffset": "' + str.tostring(orderPriceOffset) + '", '
    str := str + '"investmentType": "' + investmentType + '", '
    str := str + '"amount": "' + str.tostring(amount) + '"'
    str := str + '}'
    str

getOrderAlertMsgExit(action, instrument, signalToken) =>
    str = '{'
    str := str + '"action": "' + action + '", '
    str := str + '"instrument": "' + instrument + '", '
    str := str + '"signalToken": "' + signalToken + '", '
    str := str + '"timestamp": "' + '{{timenow}}' + '", '
    str := str + '}'
    str

strategy(title='OKX: MA Crossover', overlay=true)
Len = input(13)
Profit = input.float(7, title='Take Profit %', minval=0.01) / 100
Stop =  input.float(7, title='Stop Loss %', minval=0.01) / 100
xMA = ta.sma(close, Len)
//Robot State
isLong = strategy.position_size > 0 
isShort = strategy.position_size < 0 
isFlat = strategy.position_size == 0 
//Current Signal
doLong = low < xMA[1] ? true : false
doShort =   high > xMA[1] ? true:  false
//Backtest Start Date
tm =  timestamp(2022, 01, 01, 09, 30)
//Entry and exit orders
if  doLong[2] == false and isLong == false and doLong and time > tm
    strategy.cancel_all()
    buyAlertMsgExit = getOrderAlertMsgExit(action = 'EXIT_LONG', instrument = syminfo.ticker, signalToken = signalToken)
    buyAlertMsg = getAlertMsg(action = 'ENTER_LONG', instrument = syminfo.ticker, signalToken = signalToken, orderType =  OrderType, orderPriceOffset =  OrderPriceOffset, investmentType =  InvestmentType, amount = Amount)
    strategy.entry('Long', strategy.long, limit = close, comment='Long', alert_message =buyAlertMsg)
    strategy.exit("ExitLong", 'Long', stop=close - close * Stop  , limit = close + close * Profit , qty_percent = 100, alert_message = buyAlertMsgExit)  
if doShort[2] == false and isShort == false and doShort and time > tm
    strategy.cancel_all()
    sellAlertMsgExit = getOrderAlertMsgExit(action = 'EXIT_SHORT', instrument = syminfo.ticker, signalToken = signalToken)
    sellAlertMsg = getAlertMsg(action = 'ENTER_SHORT', instrument = syminfo.ticker, signalToken = signalToken, orderType =  OrderType, orderPriceOffset =  OrderPriceOffset, investmentType =  InvestmentType, amount = Amount)
    strategy.entry('Short', strategy.short, limit=close, comment='Short', alert_message = sellAlertMsg)
    strategy.exit("ExitShort", 'Short', stop=close + close * Stop  , limit = close - close * Profit  , qty_percent = 100, alert_message = sellAlertMsgExit)  
//Visual
barcolor(isShort  ? color.red : isLong ? color.green : color.blue)
plot(xMA, color=color.new(color.red, 0), title='MA')

Published by ChaoZhang on the FMZ strategy square · last modified 2023-10-24. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.

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