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Strategy vault / Mean reversion

Composite Entry Signal RSI Trading Strategy

This trading strategy combines RSI, rate of change ROC, and moving average MA to form an integrated mechanism for identifying entry signals. Specifically, it calculates a 3-period RSI, 2-period RSI change rate, and…

Pine ScriptMean reversionMomentumRSISMA
Author
ChaoZhang
Complexity
Starter · 54 lines
Parameters
0
Backtest bar
1d · swing
Tested on
BTC/USDT · futures
Jump to codeView in vaultOriginal on FMZ

This trading strategy combines RSI, rate of change ROC, and moving average MA to form an integrated mechanism for identifying entry signals.

Specifically, it calculates a 3-period RSI, 2-period RSI change rate, and 100-period price rate of change, taking the average of these 3 as the composite RSI indicator. Buy signals are generated when the composite RSI crosses above 40, and sell signals when it crosses above 70.

The advantage of this strategy is it synergizes the strengths of multiple indicators - RSI for overbought/oversold, RSI rate of change for momentum, and ROC for price rate of change. However, each indicator has lag, and combining them cannot fully avoid the risk of false signals.

In summary, this composite entry signal RSI strategy fuses the strengths of multiple indicators to improve judgment accuracy. But for practical application, attention is still needed on risk controls like parameter optimization and stop loss settings, in order to achieve long-term stability.

Source Pine Script

/*backtest
start: 2023-01-01 00:00:00
end: 2023-03-10 00:00:00
period: 1d
basePeriod: 1h
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

//@version=3
src = close, lenrsi = 3, lenupdown = 2, lenroc = 100, malengt = 2, low = 40, high = 70, a = 1, vlow = 20
updown(s) => 
    isEqual = s == s[1]
    isGrowing = s > s[1]
    ud = 0.0
    ud := isEqual ? 0 : isGrowing ? (nz(ud[1]) <= 0 ? 1 : nz(ud[1])+1) : (nz(ud[1]) >= 0 ? -1 : nz(ud[1])-1)
    ud
rsi = rsi(src, lenrsi)
updownrsi = rsi(updown(src), lenupdown)
percentrank = percentrank(roc(src, 1), lenroc)
crsi = avg(rsi, updownrsi, percentrank)
MA = sma(crsi, malengt)

band1 = 70
band0 = 40
band2 = 20

ColorMA = MA>=band0 ? lime : red

p1 = plot(MA, title="BuyNiggers", style=line, linewidth=4, color=ColorMA)

p2 = plot(low, title="idk", style=line, linewidth=2, color=blue)
p3 = plot(high, title="idk2", style=line, linewidth=2, color=orange)
p4 = plot(vlow, title="idk3", style=line, linewidth=1, color=red)

//@version=2
strategy("CMARSI")


if crossover(MA, band0)
    strategy.entry("buy", strategy.long, when=strategy.position_size <= 0)
    
if crossunder(MA, band1)
    strategy.exit("close", "buy")
    



plot(strategy.equity)

Published by ChaoZhang on the FMZ strategy square · last modified 2023-09-11. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.

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