Multi SMA Moving Average Crossover Strategy

Pine ScriptTrend following Breakout Multi-timeframe SMA

Author: ChaoZhang
Complexity: Starter · 64 lines
Parameters: 5
Backtest bar: 30m · intraday
Tested on: BTC/USDT · futures

Jump to code View in vault Original on FMZ

Overview

This strategy calculates the SMA moving averages of multiple timeframes and takes the average value to construct the moving average indicator. It generates buy signals when prices rise above the moving average and sell signals when prices fall below the moving average. This is a typical moving average crossover strategy.

Strategy Principle

Calculate 5 SMA moving averages of different periods (8-day, 21-day, 50-day, 100-day, 200-day)
Take the average of the 5 moving averages to get the final moving average indicator
Generate buy signals when closing prices rise above the moving average
Generate sell signals when closing prices fall below the moving average

By averaging the SMAs of multiple timeframes, this strategy can effectively smooth the curve and filter out false breakouts. Compared with a single moving average, it has higher stability.

Advantage Analysis

Using multiple timeframe moving averages can effectively filter market noise and identify trends
Smooth curve, avoid generating too many false signals
The strategy logic is simple and clear, easy to understand and implement, suitable for beginners to learn
Customizable moving average period combination to optimize indicator effect

Risk Analysis

The moving average system lags as a whole and cannot keep up with price changes in time
When breakout failure occurs, the stop loss point is far away, with greater risk of loss
Stop loss lines are frequently triggered in oscillating trends

These risks can be reduced by appropriately shortening some moving average periods and adding other indicators for confirmation.

Optimization Directions

Optimize the combinations of moving average periods to find the best parameters
Add indicators like trading volume to confirm breakout signals
Incorporate trend indicators to avoid false signals in oscillating markets
Develop automatic parameter optimization programs to dynamically find the optimal parameters

Summary

The overall idea of this strategy is clear. By integrating the moving averages of multiple timeframes, it can effectively identify trends and is a stable and practical strategy. However, we also need to pay attention to its lag and false signal risks. Through further optimizing parameter settings, adding confirmation indicators, etc., we can continuously improve this strategy to make it a powerful quantitative trading tool.

Parameters

Name	Default	What it controls
v_input_1	8	SMA 1
v_input_2	21	SMA 2
v_input_3	50	SMA 3
v_input_4	100	SMA 4
v_input_5	200	SMA 5

Source Pine Script

/*backtest
start: 2023-11-20 00:00:00
end: 2023-11-27 00:00:00
period: 30m
basePeriod: 15m
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

//@version=3
strategy("STRATEGY AVERAGE MULTI_SMA", overlay=true)


sma1 = sma(close,input(title="SMA 1", defval=8))

sma2 = sma(close,input(title="SMA 2", defval=21))

sma3 = sma(close,input(title="SMA 3", defval=50))

sma4 = sma(close,input(title="SMA 4", defval=100))

sma5 = sma(close,input(title="SMA 5", defval=200))


mediaSMA= (sma1+sma2+sma3+sma4+sma5)/5

//color mediaSMA

MediaUP = mediaSMA>mediaSMA[1]
colorUP = (MediaUP ? #3CFF35 : na)

MediaDOWN = mediaSMA<mediaSMA[1]
colorDOWN =(MediaDOWN ? #FF0F03 : na)

colorN =(not MediaUP and not MediaDOWN and mediaSMA==mediaSMA[1] ? white : na )

plot(mediaSMA,title="Avarege MULTI_SMA UP", color=colorUP, style=circles, linewidth=2, transp=0)
plot(mediaSMA,title="Avarege MULTI_SMA DOWN", color=colorDOWN, style=circles, linewidth=2, transp=0)
plot(mediaSMA,title="Avarege MULTI_SMA UP NEUTRAL", color=colorN, style=circles, linewidth=2, transp=0)


//plot(sma1,color=blue,linewidth=1, style=line,transp=0,title="SMA 1")
//plot(sma2,color=yellow,linewidth=1, style=line,transp=0,title="SMA 2")
//plot(sma3,color=green,linewidth=1, style=line,transp=0,title="SMA 3")
//plot(sma4,color=purple,linewidth=1, style=line,transp=0,title="SMA 4")
//plot(sma5,color=red,linewidth=1, style=line,transp=0,title="SMA 5")


// Strategy

//BUY
comprar=close>mediaSMA and mediaSMA>mediaSMA[1] 
fechar=close<mediaSMA and mediaSMA<mediaSMA[1]
 
strategy.entry("BUY",strategy.long,when=comprar)
strategy.entry("SELL",strategy.short, when=fechar)

//SELL
vender=close<mediaSMA and mediaSMA<mediaSMA[1] 
fechar2=close>mediaSMA and mediaSMA>mediaSMA[1]

strategy.entry("SELL",strategy.short, when=vender)
strategy.entry("BUY", strategy.long,when=fechar2)

Published by ChaoZhang on the FMZ strategy square · last modified 2023-11-28. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.

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