Dual Moving Average Strategy 442377

Pine ScriptBreakout Mean reversion Trend following RSI SMA

Author: ChaoZhang
Complexity: Intermediate · 59 lines
Parameters: 12
Backtest bar: 1h · intraday
Tested on: BTC/USDT · futures

Jump to code View in vault Original on FMZ

Overview

This strategy uses dual moving averages to form a channel and capture trend direction. Trading signals are generated when price breaks through the channel. RSI indicator is also incorporated to filter false breakouts. It trades only during London session with max 5 trades per day and max 2% daily loss.

Strategy Logic

The strategy employs two moving averages of length 5, one calculated from highest price and the other from lowest price, to form a price channel. Long signal triggers when close price breaks above the upper band, and short signal below the lower band.

To avoid false breakout, RSI indicator is added to gauge overbought/oversold levels. Go long only if RSI is above 80, and go short only if RSI is below 20.

Also, the strategy trades only during London session (3am - 11am), with max 5 orders per day and max 2% loss of equity per day.

Advantage Analysis

Catch the trend

The dual MA channel can effectively detect price trend direction. Breaking upper band catches the upside trend, while breaking lower band catches the downside trend.

Reduce false breakout

Using RSI overbought/oversold filter reduces some false breakout signals caused by price fluctuation.

Effective risk control

Trading only during major session and having max orders per day limit trading frequency. Max 2% daily loss also defines risk tolerance.

Risk Analysis

False breakout with volatility

Significant price swing can cause some false breakout signals, leading to unnecessary losses. Parameters can be optimized and more filters added to reduce such risk.

Fixed SL/TP risk

Using fixed pips for SL/TP risks being stopped out/missing profit in volatile market. Consider percentage-based or dynamic SL/TP instead.

Limited trading session risk

Opening positions only during fixed sessions runs the risk of missing potential trades in other hours. Consider expanding session or adjust dynamically based on real-time situation.

Optimization Directions

Parameter tuning

Optimize parameters like MA length, RSI figures, fixed SL/TP pips etc to find best combination.

Additional filters

Add more indicators or conditions to verify signals, e.g. higher volume, reduced BB width etc, to avoid false breakouts.

Dynamic SL/TP

Use percentage-based or dynamic stop loss/take profit instead of fixed pips to better handle one-sided market moves.

Manual review

Manually review signals, or only enter on confirmed breakout to prevent being trapped.

Conclusion

The strategy is fairly simple and practical overall, using dual MA channel to determine trend and RSI to filter false breakouts. Risk management via trading hours and loss limit also defines risk tolerance. Still large room for improvements, e.g. parameter tuning, better SL/TP mechanism etc.

Parameters

Name	Default	What it controls
v_input_1	5	Length
v_input_2_high	0	Source: high \| close \| low \| open \| hl2 \| hlc3 \| hlcc4 \| ohlc4
v_input_3	false	Offset
v_input_4	5	Length
v_input_5_low	0	Source: low \| high \| close \| open \| hl2 \| hlc3 \| hlcc4 \| ohlc4
v_input_6	false	Offset
v_input_7	5	length
v_input_8	10	overSold
v_input_9	80	overBought
v_input_10_close	0	Source RSI: close \| high \| low \| open \| hl2 \| hlc3 \| hlcc4 \| ohlc4
v_input_11	150	tp
v_input_12	80	sl

Source Pine Script

/*backtest
start: 2024-01-01 00:00:00
end: 2024-01-16 23:59:59
period: 1h
basePeriod: 15m
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/
// © SoftKill21
//@version=4
strategy(title="Moving Average", shorttitle="MA", overlay=true)
timeinrange(res, sess) => time(res, sess) != 0
len = input(5, minval=1, title="Length")
src = input(high, title="Source")
offset = input(title="Offset", type=input.integer, defval=0, minval=-500, maxval=500)
out = sma(src, len)
plot(out, color=color.white, title="MA", offset=offset)

len2 = input(5, minval=1, title="Length")
src2 = input(low, title="Source")
offset2 = input(title="Offset", type=input.integer, defval=0, minval=-500, maxval=500)
out2 = sma(src2, len2)
plot(out2, color=color.white, title="MA", offset=offset2)

length = input( 5 )
overSold = input( 10 )
overBought = input( 80 )
price = input(close, title="Source RSI")

vrsi = rsi(price, length)

longcond= close > out and close > out2 and vrsi > overBought
shortcont = close < out and close < out2 and vrsi < overSold
tp=input(150,title="tp")
sl=input(80,title="sl")


strategy.entry("long",1,when=longcond)
//strategy.close("long",when= close < out2)
strategy.exit("long_exit","long",profit=tp,loss=sl)

strategy.entry("short",1,when=shortcont)
//strategy.close("short",when=close >out)
strategy.exit("short_exit","short",profit=tp,loss=sl)

// maxOrder = input(6, title="max trades per day")
// maxRisk = input(2,type=input.float, title="maxrisk per day")
// strategy.risk.max_intraday_filled_orders(maxOrder)

// strategy.risk.max_intraday_loss(maxRisk, strategy.percent_of_equity)


// strategy.close_all(when =not timeinrange(timeframe.period, "0300-1100"))

Published by ChaoZhang on the FMZ strategy square · last modified 2024-02-21. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.

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