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Strategy vault / Mean reversion

RSI Moving Average Trailing Stop Strategy

This strategy combines RSI and moving averages for trend bias and adds trailing stops for risk management. It aims to follow trends with adaptive exits. Strategy Logic: 1. Calculate RSI to judge overbought/oversold…

Pine ScriptMean reversionTrend followingRSISMA
Author
ChaoZhang
Complexity
Starter · 69 lines
Parameters
4
Backtest bar
4d · position
Tested on
BTC/USDT · futures
Jump to codeView in vaultOriginal on FMZ

This strategy combines RSI and moving averages for trend bias and adds trailing stops for risk management. It aims to follow trends with adaptive exits.

Strategy Logic:

  1. Calculate RSI to judge overbought/oversold levels. RSI above 50 signals bullishness.

  2. Compute fast and slow moving averages, golden cross signals bull trend.

  3. Consistent RSI rise also signals long entry.

  4. After entry, set trailing stop loss and take profit lines.

  5. Stop loss trail below price, take profit trail above.

  6. Exit when price hits stop or take profit.

Advantages:

  1. RSI avoids chasing tops and bottoms.

  2. Moving averages identify trend direction. Combination improves accuracy.

  3. Trailing stops/profits adjust dynamically to price.

Risks:

  1. RSI and MAs prone to false signals in ranging markets.

  2. Trailing stop width requires prudent calibration, too wide or too narrow problematic.

  3. Unable to limit loss size, risks large losing trades.

In summary, this strategy combines RSI and MAs then uses trailing stops for risk management. With robust optimization and risk controls, it can achieve good results.

Parameters

NameDefaultWhat it controls
v_input_1trueShow Date Range
v_input_214length
v_input_float_12Trail Long Loss (%)
v_input_float_2trueTrail Short Loss (%)

Source Pine Script

/*backtest
start: 2022-09-06 00:00:00
end: 2023-09-12 00:00:00
period: 4d
basePeriod: 1d
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

//@version=5
strategy("RSI and MA Strategy with Trailing Stop Loss and Take Profit",
         overlay=true,
         initial_capital=1000,
         process_orders_on_close=true,
         default_qty_type=strategy.percent_of_equity,
         default_qty_value=100,
         commission_type=strategy.commission.percent,
         commission_value=0.1)

showDate = input(defval=true, title='Show Date Range')
timePeriod = time >= timestamp(syminfo.timezone, 2022, 1, 1, 0, 0)
notInTrade = strategy.position_size <= 0

//==================================Buy Conditions============================================

//RSI
length = input(14)
rsi = ta.rsi(close, length)
buyCondition1 = rsi > 50

//MA
SMA9 = ta.sma(close, 9)
SMA50 = ta.sma(close, 50)
SMA100 = ta.sma(close, 100)
plot(SMA9, color = color.green)
plot(SMA50, color = color.orange)
plot(SMA100, color = color.blue)
buyCondition2 = SMA9 > SMA50//ta.crossover(SMA9, SMA100)

//RSI Increase
increase = 5
buyCondition3 = (rsi > rsi[1] + increase)


if (buyCondition1 and buyCondition2 and buyCondition3 and timePeriod) //and buyCondition
    strategy.entry("Long", strategy.long)

//==================================Sell Conditions============================================

//Trailing Stop Loss and Take Profit
longTrailPerc = input.float(title='Trail Long Loss (%)', minval=0.0, step=0.1, defval=2) * 0.01
shortTrailPerc = input.float(title='Trail Short Loss (%)', minval=0.0, step=0.1, defval=1) * 0.01

longStopPrice = 0.0
shortStopPrice = 0.0

longStopPrice := if strategy.position_size > 0
    stopValue = close * (1 - longTrailPerc)
    math.max(stopValue, longStopPrice[1])
else
    0

shortStopPrice := if strategy.position_size < 0
    stopValue = close * (1 + shortTrailPerc)
    math.min(stopValue, shortStopPrice[1])
else
    999999


strategy.exit(id="Exit", stop = longStopPrice, limit = shortStopPrice)

Published by ChaoZhang on the FMZ strategy square · last modified 2023-09-13. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.

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