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RSI Trend Following Strategy

Author: ChaoZhang, Date: 2023-10-26 15:44:15
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Overview

This strategy designs a simple trend following trading system based on the RSI indicator, which can determine the market trend direction through RSI and implement automated long and short positions within a specific date range.

Strategy Logic

The strategy uses RSI indicator to determine market trend, and Bollinger Bands to confirm overbought and oversold zones.

Firstly, RSI value is calculated. The upper and lower bands of Bollinger Bands are calculated based on moving average and standard deviation of RSI. RSI fluctuates between 0-1, and Bollinger Bands identifies overbought and oversold zones through standard deviation. When RSI is higher than the upper band, it’s overbought zone, and when lower than the lower band, it’s oversold zone.

When RSI breaks through from the lower to the upper band, a buy signal is generated. When RSI breaks through from the upper to the lower band, a sell signal is generated, to follow the trend. After entering the market, no stop loss or take profit is set until positions are closed at the end of the specified date range.

The strategy simply and effectively uses RSI to determine trend direction, and Bollinger Bands to identify specific trading opportunities. By defining the date range, unnecessary risks can be avoided.

Advantage Analysis

  • Using RSI to determine trend direction is simple and effective
  • Combining Bollinger Bands to confirm trading signals avoids false breakouts
  • Defining trading date range helps avoid market risks
  • No stop loss or take profit, maximizes trend following
  • Flexible parameter adjustment, adapts to various market environments

Risks and Optimization

  • Market may have violent swings, leading to losses
  • No stop loss or take profit fails to effectively control risks
  • Improper parameter settings may cause overtrading or missing opportunities

Optimization Directions:

  • Add stop loss and take profit to control risks
  • Optimize parameter settings to improve win rate
  • Add other indicators to filter signals and avoid false breakouts
  • Dynamically adjust position sizing

Summary

In summary, this is a very simple and direct trend following strategy. Using RSI to determine trend, Bollinger Bands to filter signals, and defining trading date range, can effectively follow trends and control risks. But the strategy can be further optimized. While keeping it simple and effective, methods like stop loss, parameter optimization and signal filtering can be added to make it more suitable for live trading.

/*backtest
start: 2022-10-19 00:00:00
end: 2023-10-25 00:00:00
period: 1d
basePeriod: 1h
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

//Gidra
//2018

//@version=2
strategy(title = "Gidra's RSI or MFI Strategy v0.1", shorttitle = "Gidra's RSI or MFI v0.1", overlay = false, default_qty_type = strategy.percent_of_equity, default_qty_value = 100, pyramiding = 1)

//Settings
needlong = input(true, defval = true, title = "Long")
needshort = input(true, defval = true, title = "Short")
capital = input(100, defval = 100, minval = 1, maxval = 10000, title = "Lot, %")
src = input(close, title="source")
lengthRSI = input(14, title="RSI or MFI length")
// RSI %B
useRSI = input(true, title="use RSI or MFI")
fromyear = input(2018, defval = 2018, minval = 1900, maxval = 2100, title = "From Year")
toyear = input(2100, defval = 2100, minval = 1900, maxval = 2100, title = "To Year")
frommonth = input(01, defval = 01, minval = 01, maxval = 12, title = "From Month")
tomonth = input(12, defval = 12, minval = 01, maxval = 12, title = "To Month")
fromday = input(01, defval = 01, minval = 01, maxval = 31, title = "From Day")
today = input(31, defval = 31, minval = 01, maxval = 31, title = "To Day")

//MFI
upper = sum(volume * (change(src) <= 0 ? 0 : src), lengthRSI)
lower = sum(volume * (change(src) >= 0 ? 0 : src), lengthRSI)
mf = rsi(upper, lower)

//RSI
rsi = useRSI?rsi(src, lengthRSI): mf

// %B
length = input(50, minval=1, title="BB length")
mult = input(1.618, minval=0.001, maxval=50)
basis = sma(rsi, length)
dev = mult * stdev(rsi, length)
upperr = basis + dev
lowerr = basis - dev
bbr = (rsi - lowerr)/(upperr - lowerr)

plot(bbr, color=black, transp=0, linewidth=2)
// band1 = hline(1, color=white, linestyle=dashed)
// band0 = hline(0, color=white, linestyle=dashed)
// fill(band1, band0, color=teal)
hline(0.5, color=white)

//Signals
up = bbr >= 0 and bbr[1] < 0
dn = bbr <= 1 and bbr[1] > 1
//exit = ((bbr[1] < 0.5 and bbr >= 0.5) or (bbr[1] > 0.5 and bbr <= 0.5))

lot = strategy.position_size == 0 ? strategy.equity / close * capital / 100 : lot[1]

//Trading
if up
    strategy.entry("Long", strategy.long, needlong == false ? 0 : lot, when=(time > timestamp(fromyear, frommonth, fromday, 00, 00) and time < timestamp(toyear, tomonth, today, 23, 59)))

if dn
    strategy.entry("Short", strategy.short, needshort == false ? 0 : lot, when=(time > timestamp(fromyear, frommonth, fromday, 00, 00) and time < timestamp(toyear, tomonth, today, 23, 59)))
    
if time > timestamp(toyear, tomonth, today, 23, 59)// or exit
    strategy.close_all()
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