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Trend Following RSI Scalping Strategy

Author: ChaoZhang, Date: 2024-02-02 14:54:53
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Overview

According to technical analysis, an RSI above 70 should signal overbought conditions and thus a sell signal. Cryptocurrencies represent an entirely new asset class that is reshaping concepts of technical analysis. FOMO buying can be very powerful, and coins can remain in overbought territory long enough to provide excellent scalping opportunities on the upside.

Building a trend-following trading strategy based on the RSI, which is generally considered a contrarian indicator, may sound counterintuitive. However, over 200 backtests prove this is a very interesting long-term setup.

Strategy Logic

The strategy assumes each order to trade 30% of the available capital. A trading fee of 0.1% is taken into account, aligned with the base fee applied on Binance, the world’s largest cryptocurrency exchange.

  • Entry Signal: Go long when RSI goes above 70 and within backtest window
  • Exit Signal: Close long position when RSI drops below 55 or close goes above take profit

Advantage Analysis

  • Identify trends using RSI, avoiding missing signals in ranging markets
  • Fixed position sizing manages single trade risk
  • Suitable for mid-to-long term holds, avoiding shakeouts from short-term fluctuations

Risk Analysis

  • Ensure RSI parameters are set reasonably, otherwise overbought/oversold errors occur
  • Tracking take profit requires timely updates, otherwise profits are left on the table
  • Monitor risk from exceptional market volatility, adjust position sizing or stop losses if necessary

Optimization Directions

  • Consider combining other indicators like MACD to confirm trend
  • Test different RSI parameter settings
  • Introduce dynamic take profit based on market volatility

Conclusion

This strategy identifies overbought conditions with RSI to determine trend direction and takes progressive profits trailing the uptrend. Compared to traditional RSI contrarian usage, this strategy offers a new perspective. Rigorous backtesting shows promising results, but we need to monitor risks and optimize parameters. Overall, it provides a simple, practical trend following approach for quantitative trading.

/*backtest
start: 2024-01-02 00:00:00
end: 2024-02-01 00:00:00
period: 3h
basePeriod: 15m
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

//@version=1
strategy(shorttitle='Trend-following RSI Scalping Strategy (by Coinrule)',title='Trend-following RSI Strategy ', overlay=true, initial_capital = 1000, default_qty_type = strategy.percent_of_equity, default_qty_type = strategy.percent_of_equity, default_qty_value = 30, commission_type=strategy.commission.percent, commission_value=0.1)

//Backtest dates
fromMonth = input(defval = 1,  title = "From Month")     
fromDay   = input(defval = 10,    title = "From Day")       
fromYear  = input(defval = 2020, title = "From Year")       
thruMonth = input(defval = 1,    title = "Thru Month")     
thruDay   = input(defval = 1,    title = "Thru Day")     
thruYear  = input(defval = 2112, title = "Thru Year")       

showDate  = input(defval = true, title = "Show Date Range")

start     = timestamp(fromYear, fromMonth, fromDay, 00, 00)        // backtest start window
finish    = timestamp(thruYear, thruMonth, thruDay, 23, 59)        // backtest finish window
window()  => true


// RSI inputs and calculations
lengthRSI = input(14, title = 'RSI period', minval=1)
RSI = rsi(close, lengthRSI)

//Entry


strategy.entry(id="long", long = true, when = RSI > 70 and window()) 

//Exit

Take_profit= ((input (6))/100)
longTakeProfit = strategy.position_avg_price * (1 + Take_profit)

strategy.close("long", when = RSI < 55 or close > longTakeProfit and window())
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