Dynamic RSI Trading Strategy

Pine ScriptMachine learning Breakout Mean reversion RSI

Author: ChaoZhang
Complexity: Starter · 58 lines
Parameters: 3
Backtest bar: 4h · intraday
Tested on: BTC/USDT · futures

Jump to code View in vault Original on FMZ

Overview

This strategy builds a trading system using RSI indicator to determine overbought and oversold levels, together with dynamic trailing stop loss and profit target exit. It goes short when RSI crosses above overbought level and goes long when RSI crosses below oversold level. Trailing stop loss and profit target exit are used to close positions.

Strategy Logic

This strategy uses 14-period RSI indicator to judge market technical patterns. RSI reflects the ratio of rising and falling power over a period of time, to tell if the market is overbought or oversold. The RSI length here is 14. When RSI crosses above 70, the market is considered overbought, and we go short. When RSI crosses below 30, the market is considered oversold, and we go long.

In addition, this strategy uses dynamic trailing stop loss mechanism. When holding long position, trailing stop price is set at 97% of closing price. When holding short position, trailing stop price is 103% of closing price. This locks in most profits while avoiding being stopped out by market noise.

Finally, this strategy uses profit target exit. When position profit reaches 20%, it will be closed. This locks in some profits and avoids profit retracement.

Advantage Analysis

The advantages of this strategy include:

Using RSI indicator to determine overbought/oversold market effectively
Adopting dynamic trailing stop loss to control risk
Setting proper profit target to lock in profits
Clear logic and few parameters, easy to implement for live trading
Easy to optimize parameters like RSI length, overbought/oversold levels, stop loss percentage etc.

Risk Analysis

Some risks of this strategy to note:

Potential false signals from RSI, causing unnecessary losses
Probability of stop loss being hit, enlarging losses
Profit target set too low, unable to hold position long enough to earn adequate profits

To cope with these risks, optimizing RSI parameters, adjusting stop loss percentage, relaxing profit target requirements reasonably can help.

Optimization Directions

Some directions to optimize the strategy:

Optimize RSI parameters and overbought/oversold judge standards to reduce false signals
Add other indicator filters to avoid erroneous signals caused by single RSI
Dynamically optimize profit target according to market conditions
Incorporate trading volume indicators to avoid low volume false breakouts
Introduce machine learning algorithms to auto-tune parameters

Summary

The strategy has clear logic of using RSI to determine overbought/oversold market, with dynamic stops and profit taking. Its pros are easy understanding and implementation, good risk control, and high extensibility. Next step is to enhance signal quality, auto-tune parameters etc to make strategy more intelligent.

Parameters

Name	Default	What it controls
v_input_1	14	RSI Length
v_input_2	3	Trailing Stop Percentage (%)
v_input_3	20	Profit Target Percentage (%)

Source Pine Script

/*backtest
start: 2024-01-04 00:00:00
end: 2024-02-03 00:00:00
period: 4h
basePeriod: 15m
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

//@version=5
strategy("Modified RSI-Based Trading Strategy", overlay=true)

// RSI settings
rsiLength = input(14, title="RSI Length")
overboughtLevel = 70
oversoldLevel = 30

// User-defined parameters
trailingStopPercentage = input(3, title="Trailing Stop Percentage (%)")
profitTargetPercentage = input(20, title="Profit Target Percentage (%)")

rsiValue = ta.rsi(close, rsiLength)

var float trailingStopLevel = na
var float profitTargetLevel = na

// Entry criteria
enterLong = ta.crossover(rsiValue, oversoldLevel)
enterShort = ta.crossunder(rsiValue, overboughtLevel)

// Exit criteria
exitLong = ta.crossover(rsiValue, overboughtLevel)
exitShort = ta.crossunder(rsiValue, oversoldLevel)

// Trailing stop calculation
if (strategy.position_size > 0)
    trailingStopLevel := close * (1 - trailingStopPercentage / 100)

if (strategy.position_size < 0)
    trailingStopLevel := close * (1 + trailingStopPercentage / 100)

// Execute the strategy
if (enterLong)
    strategy.entry("Buy", strategy.long)

if (exitLong or ta.crossover(close, trailingStopLevel) or ta.change(close) > profitTargetPercentage / 100)
    strategy.close("Buy")

if (enterShort)
    strategy.entry("Sell", strategy.short)

if (exitShort or ta.crossunder(close, trailingStopLevel) or ta.change(close) < -profitTargetPercentage / 100)
    strategy.close("Sell")

// Plot RSI and overbought/oversold levels
plot(rsiValue, title="RSI", color=color.blue)
hline(overboughtLevel, "Overbought", color=color.red, linestyle=hline.style_dashed)
hline(oversoldLevel, "Oversold", color=color.green, linestyle=hline.style_dashed)

Published by ChaoZhang on the FMZ strategy square · last modified 2024-02-04. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.

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