Triple Moving Average Quantitative Trading Strategy

Pine ScriptBreakout Trend following MACD EMA SMA Bollinger Bands

Author: ChaoZhang
Complexity: Intermediate · 117 lines
Parameters: 13
Backtest bar: 1d · swing
Tested on: BTC/USDT · futures

Jump to code View in vault Original on FMZ

This strategy generates trading signals by calculating three moving averages of different periods and combining price breakthroughs. It belongs to a typical trend-following strategy. The strategy aims to follow medium-term trends in the market and can be adapted to different products and trading environments by dynamically adjusting parameters.

Principle

The strategy contains three moving averages: MA1, MA2 and MA3. MA1 and MA2 form a trading channel, and their crossover generates trading signals; MA3 is used to filter signals.

When the fast moving average MA1 crosses above the medium-term moving average MA2, it indicates the strengthening of the short-term trend. At this time, if the price is above the long-term moving average MA3, a long signal is generated; conversely, if MA1 crosses below MA2 and the price is below MA3, a short signal is generated.

The role of MA3 is to filter out short-term market noise and only generate signals after determining that the trend has entered the medium and long term stage. By dynamically adjusting the parameters of the three moving averages, the strategy can find the optimal parameter combination in different markets.

Advantages

Capture trends of different cycles through multiple moving averages
MA3 filters signals to avoid whipsaws
Customizable moving average types and parameters, high adaptability
Visualize crosses to identify signal points

Risks

Moving averages may lag when major trend reverses
Potentially high trading frequency, increasing trading costs and slippage risks
Improper parameters may cause overtrading or lagging signals

Can optimize MA periods for different products; optimize stop loss to control single loss; combine other technical indicators to confirm signal validity and reduce false signals.

Optimization Directions

Add other indicators to determine trends, e.g. MACD, Bollinger Bands, etc.
Add stop loss/take profit strategies
Dynamically adjust parameters to find optimal combinations
Parameter optimization for different products
Consider trading costs, optimize trade frequency

Summary

This strategy generates trading signals by calculating three moving averages and observing their crosses. Using the idea of combining fast, medium and slow lines to determine trends, it is a typical trend-following strategy. The strategy can be adapted to different products through parameter optimization, but risks whipsaws and missing turnings. Future improvements could introduce other technical indicators to judge signal validity, develop dynamic parameter optimization mechanisms, etc. to make the strategy more flexible.

Parameters

Name	Default	What it controls
v_input_1	13	MA1 Period
v_input_2	0	MA1 Type: SMA \| RMA \| EMA \| WMA \| HMA \| DEMA \| TEMA
v_input_3_close	0	MA1 Source: close \| high \| low \| open \| hl2 \| hlc3 \| hlcc4 \| ohlc4
v_input_4	true	MA1 Visible
v_input_5	50	MA2 Period
v_input_6	0	MA2 Type: SMA \| RMA \| EMA \| WMA \| HMA \| DEMA \| TEMA
v_input_7_close	0	MA2 Source: close \| high \| low \| open \| hl2 \| hlc3 \| hlcc4 \| ohlc4
v_input_8	true	MA2 Visible
v_input_9	200	MA3 Period
v_input_10	0	MA3 Type: SMA \| RMA \| EMA \| WMA \| HMA \| DEMA \| TEMA
v_input_11_close	0	MA3 Source: close \| high \| low \| open \| hl2 \| hlc3 \| hlcc4 \| ohlc4
v_input_12	true	MA3 Visible
v_input_13	true	Show Crosses

Source Pine Script

/*backtest
start: 2023-01-16 00:00:00
end: 2024-01-22 00:00:00
period: 1d
basePeriod: 1h
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

// This source code is subject to the terms of the Mozilla Public License 2.0 at https://mozilla.org/MPL/2.0/
// © Meesemoo

//@version=4
strategy("Custom MA Strategy Tester", overlay = true)
MA1Period = input(13, title="MA1 Period")
MA1Type = input(title="MA1 Type", defval="SMA", options=["RMA", "SMA", "EMA", "WMA", "HMA", "DEMA", "TEMA"])
MA1Source = input(title="MA1 Source", type=input.source, defval=close)
MA1Visible = input(title="MA1 Visible", type=input.bool, defval=true)
MA2Period = input(50, title="MA2 Period")
MA2Type = input(title="MA2 Type", defval="SMA", options=["RMA", "SMA", "EMA", "WMA", "HMA", "DEMA", "TEMA"])
MA2Source = input(title="MA2 Source", type=input.source, defval=close)
MA2Visible = input(title="MA2 Visible", type=input.bool, defval=true) 
MA3Period = input(200, title="MA3 Period")
MA3Type = input(title="MA3 Type", defval="SMA", options=["RMA", "SMA", "EMA", "WMA", "HMA", "DEMA", "TEMA"])
MA3Source = input(title="MA3 Source", type=input.source, defval=close)
MA3Visible = input(title="MA3 Visible", type=input.bool, defval=true)
ShowCrosses = input(title="Show Crosses", type=input.bool, defval=true)

MA1 = if MA1Type == "SMA"
    sma(MA1Source, MA1Period)
else
    if MA1Type == "EMA"
        ema(MA1Source, MA1Period)
    else
        if MA1Type == "WMA"
            wma(MA1Source, MA1Period)
        else
            if MA1Type == "RMA"
                rma(MA1Source, MA1Period)
            else
                if MA1Type == "HMA"
                    wma(2*wma(MA1Source, MA1Period/2)-wma(MA1Source, MA1Period), round(sqrt(MA1Period)))
                else
                    if MA1Type == "DEMA"
                        e = ema(MA1Source, MA1Period)
                        2 * e - ema(e, MA1Period)
                    else
                        if MA1Type == "TEMA"
                            e = ema(MA1Source, MA1Period)
                            3 * (e - ema(e, MA1Period)) + ema(ema(e, MA1Period), MA1Period)

                    
MA2 = if MA2Type == "SMA"
    sma(MA2Source, MA2Period)
else
    if MA2Type == "EMA"
        ema(MA2Source, MA2Period)
    else
        if MA2Type == "WMA"
            wma(MA2Source, MA2Period)
        else
            if MA2Type == "RMA"
                rma(MA2Source, MA2Period)
            else
                if MA2Type == "HMA"
                    wma(2*wma(MA2Source, MA2Period/2)-wma(MA2Source, MA2Period), round(sqrt(MA2Period)))
                else
                    if MA2Type == "DEMA"
                        e = ema(MA2Source, MA2Period)
                        2 * e - ema(e, MA2Period)
                    else
                        if MA2Type == "TEMA"
                            e = ema(MA2Source, MA2Period)
                            3 * (e - ema(e, MA2Period)) + ema(ema(e, MA2Period), MA2Period)
                    
MA3 = if MA3Type == "SMA"
    sma(MA3Source, MA3Period)
else
    if MA3Type == "EMA"
        ema(MA3Source, MA3Period)
    else
        if MA3Type == "WMA"
            wma(MA3Source, MA3Period)
        else
            if MA3Type == "RMA"
                rma(MA3Source, MA3Period)
            else
                if MA3Type == "HMA"
                    wma(2*wma(MA3Source, MA3Period/2)-wma(MA3Source, MA3Period), round(sqrt(MA3Period)))
                else
                    if MA3Type == "DEMA"
                        e = ema(MA3Source, MA3Period)
                        2 * e - ema(e, MA3Period)
                    else
                        if MA3Type == "TEMA"
                            e = ema(MA3Source, MA3Period)
                            3 * (e - ema(e, MA3Period)) + ema(ema(e, MA3Period), MA3Period)
                    


p1 = plot(MA1Visible ? MA1 : na, color=color.green, linewidth=1)
p2 = plot(MA2Visible ? MA2 : na, color=color.yellow, linewidth=1)
p3 = plot(MA3Visible ? MA3 : na, color=color.red, linewidth=2)

fill(p1, p2, color.silver, transp=80, title="Fill")


start = timestamp(2019, 1, 1, 1, 0)
end = timestamp(2025, 1, 1, 1, 0)

if time >= start and time <= end
    longCondition = crossover(MA1, MA2) and close > MA3
    if (longCondition)
        strategy.entry("Long", strategy.long)
        
    shortCondition = crossunder(MA1, MA2) and close < MA3
    if (shortCondition)
        strategy.entry("Short", strategy.short)

Published by ChaoZhang on the FMZ strategy square · last modified 2024-01-23. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.

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