Trend Following Strategy Based on Dynamic Moving Average

This strategy is based on the dynamic moving average indicator to track the price trend in real time and generate trading signals when the moving average is broken through. The advantage of this strategy lies in its…

Pine ScriptTrend following Machine learning Breakout EMA SMA

Author: ChaoZhang
Complexity: Intermediate · 72 lines
Parameters: 8
Backtest bar: 1h · intraday
Tested on: BTC/USDT · futures

Jump to code View in vault Original on FMZ

Overview

Strategy Logic

This strategy utilizes dynamic moving average indicators including ALMA, EMA, SMA and more. The principle is to go long when the price breaks above the moving average and go short when it breaks below. That is, the moving average serves as a barometer for the price trend, and signals can be generated when a trend reversal occurs.

Specifically, the strategy uses moving averages formed by high and low prices. The low price MA serves as the signal line for long signals, while the high price MA serves as the line for shorts. When the closing price rises above the low price MA, go long. When the close drops below the high price MA, go short.

By judging the price trend with MA and combining with the breakout principle to generate signals, a simple and practical trend following strategy is formed.

Advantages

Simple parameter settings with MA indicator, easy to operate
Clear signal rules without false signals
Flexible MA types to adapt to market changes
Adjustable MA periods suit different trend cycles
Multi-timeframe signal validation improves reliability

Risks and Solutions

MA lag may miss some opportunities
- Shorten MA period or use EMA
Large swing risks in short term
- Widen stop loss room for flexibility
Long holding risks, unable to lock profit in time
- Combine other indicators, avoid chasing highs and killing lows

Optimization Directions

Adjust MA type and parameters based on symbol characteristics
Add auxiliary indicators to improve strategy
Add stop loss and take profit mechanisms
Evaluate signal reliability across timeframes
Utilize machine learning to find better parameters

Conclusion

This strategy judges the trend direction with MA and generates signals based on the breakout principles. It is simple to use and suitable for medium-to-long-term holding. The parameters can also be adjusted to adapt to market changes. Risks from short-term fluctuations and long holding need to be managed with stop loss/profit taking. There is room for improvement by incorporating more indicators and finding optimal parameters through machine learning.

Parameters

Name	Default	What it controls
v_input_1	0	MA Type: ALMA \| EMA \| WMA \| HMA \| VWMA \| RMA \| SMA
v_input_2	55	MA Length
v_input_3_ohlc4	0	Closing Source: ohlc4 \| high \| low \| open \| hl2 \| hlc3 \| hlcc4 \| close
v_input_4	0.85	Offset (alma only)
v_input_5	10	Sigma (alma only)
v_input_6	true	Use Current Resolution
v_input_7	1440	Timeframe
v_input_8	false	Show Signals ?

Source Pine Script

/*backtest
start: 2023-12-02 00:00:00
end: 2024-01-01 00:00:00
period: 1h
basePeriod: 15m
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

//@version=4
strategy(title="Baseline Strategy - evo", shorttitle="Baseline", overlay=true)

//INPUTS
mat =               input("ALMA", "MA Type", options=["SMA", "EMA", "WMA", "HMA", "VWMA", "RMA", "ALMA"])
baseline =          input(55, title="MA Length")
src =               input(ohlc4, title="Closing Source")

offset =            input(0.85, step=0.05, title="Offset (alma only)")
sigma =             input(10, title="Sigma (alma only)")

useCurrentRes =     input(true, title="Use Current Resolution")
resCustom =         input("1440", title="Timeframe")

showsignals =       input(false, title="Show Signals ?")

//BASELINE
baselinehigh = 

 mat=="SMA" ? sma(high,baseline) : 
 mat=="EMA" ? ema(high,baseline) : 
 mat=="WMA" ? wma(high,baseline) : 
 mat=="HMA" ? wma(2*wma(high, baseline/2)-wma(high, baseline), round(sqrt(baseline))) : 
 mat=="VWMA" ? vwma(high,baseline) : 
 mat=="RMA" ? rma(high,baseline) :
 mat=="ALMA" ? alma(high, baseline, offset, sigma) : na

baselinelow = 

 mat=="SMA" ? sma(low,baseline) : 
 mat=="EMA" ? ema(low,baseline) : 
 mat=="WMA" ? wma(low,baseline) : 
 mat=="HMA" ? wma(2*wma(low, baseline/2)-wma(low, baseline), round(sqrt(baseline))) : 
 mat=="VWMA" ? vwma(low,baseline) : 
 mat=="RMA" ? rma(low,baseline) : 
 mat=="ALMA" ? alma(low, baseline, offset, sigma) : na

//RESOLUTION
res =               useCurrentRes ? timeframe.period : resCustom

mtfhigh =           security(syminfo.tickerid, res, baselinehigh)
mtflow =            security(syminfo.tickerid, res, baselinelow)

//PLOTS
plot(mtfhigh, color=color.navy, linewidth=2, transp=0, title="Baseline High")
plot(mtflow, color=color.navy, linewidth=2, transp=0, title="Baseline Low")

long =              src > mtfhigh
short =             src < mtflow

barcolor(long ? #ffe0b2 : short ? #2a2e39 : not long and not short ? #b09e82 : na, title="BaseLine BarColor")

signal = 0
signal := long ? 1 : short ? 2 : nz(signal[1])

plotshape(showsignals ? (signal != signal[1] and long ? mtflow : na) : na, title="Long", location=location.absolute, size=size.small, style=shape.labelup, text="Long", textcolor=color.black, transp=40, color=#00ff00)
plotshape(showsignals ? (signal != signal[1] and short ? mtfhigh : na) : na, title="Short", location=location.absolute, size=size.small, style=shape.labeldown, text="Short", textcolor=color.white, transp=40, color=#ff0000)

alertcondition(signal != signal[1], title="Trend Change !", message="Trend Change !")

if (long)
    strategy.entry("Long", strategy.long)
if (short)
    strategy.entry("Short", strategy.short)

Published by ChaoZhang on the FMZ strategy square · last modified 2024-01-02. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.

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