This strategy implements reversal trading by tracking missed overbought and oversold signals from the RSI indicator. Buy signals are generated when RSI drops from overbought levels, and sell signals when RSI bounces from oversold levels, aiming to capture reversal opportunities.
RSI indicator identifies overbought/oversold levels. Overbought when RSI crosses above the overbought threshold, oversold when crossing below the oversold threshold.
overbought = rsi > uplimit
oversold = rsi < dnlimit
If RSI was overbought last bar and exits overbought this bar, a buy signal up1 is triggered. If RSI was oversold last bar and exits oversold this bar, a sell signal dn1 is generated.
up1 = bar == -1 and strategy.position_size == 0 and overbought[1] and overbought == false
dn1 = bar == 1 and strategy.position_size == 0 and oversold[1] and oversold == false
If the bar direction aligns with position direction, and bar body exceeds half of its 10-period average, an exit signal is triggered.
exit = (((strategy.position_size > 0 and bar == 1) or
(strategy.position_size < 0 and bar == -1)) and
body > abody / 2)
Track missed RSI reversal signals, avoiding the need to timely catch overbought/oversold points.
Leverage RSI’s reversal property to capture turning points.
Incorporate bar direction and size into exit logic to avoid further tracking after pullbacks.
Risk of false signals from RSI
Prices may already have pulled back significantly when tracking signal, increasing loss risk
Risk of premature exits before full profitable reversal
Optimize parameters like overbought/oversold levels, lookback period etc based on different markets
Adjust position sizing, like lowering size when tracking signals
Improve entry timing, adding filters beyond tracking signals
Enhance exits to increase profitability, like trailing profit stops
Optimize stops to reduce losses, like trailing stops or cone stops
This strategy implements reversal trading by tracking RSI overbought/oversold signals. It has the advantage of catching reversal signals but also has risks of false signals and losses. Further optimizations can improve the strategy’s stability and profitability.
/*backtest
start: 2023-09-20 00:00:00
end: 2023-09-27 00:00:00
period: 15m
basePeriod: 5m
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/
//Noro
//2018
//@version=2
strategy(title = "Noro's Anti RSI Strategy v1.0", shorttitle = "Anti RSI str 1.0", overlay = true, default_qty_type = strategy.percent_of_equity, default_qty_value = 100, pyramiding = 0)
//Settings
needlong = input(true, defval = true, title = "Long")
needshort = input(true, defval = true, title = "Short")
usemar = input(false, defval = false, title = "Use Martingale")
capital = input(100, defval = 100, minval = 1, maxval = 10000, title = "Capital, %")
rsiperiod1 = input(14, defval = 14, minval = 2, maxval = 50, title = "RSI Period")
rsilimit1 = input(25, defval = 25, minval = 1, maxval = 100, title = "RSI limit")
showarr = input(false, defval = false, title = "Show Arrows")
fromyear = input(1900, defval = 1900, 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")
//RSI
uprsi1 = rma(max(change(close), 0), rsiperiod1)
dnrsi1 = rma(-min(change(close), 0), rsiperiod1)
rsi = dnrsi1 == 0 ? 100 : uprsi1 == 0 ? 0 : 100 - (100 / (1 + uprsi1 / dnrsi1))
uplimit = 100 - rsilimit1
dnlimit = rsilimit1
//Body
body = abs(close - open)
abody = sma(body, 10)
//Signals
bar = close > open ? 1 : close < open ? -1 : 0
overbought = rsi > uplimit
oversold = rsi < dnlimit
up1 = bar == -1 and strategy.position_size == 0 and overbought[1] and overbought == false
dn1 = bar == 1 and strategy.position_size == 0 and oversold[1] and oversold == false
up2 = bar == -1 and strategy.position_size > 0 and overbought == false
dn2 = bar == 1 and strategy.position_size < 0 and oversold == false
norma = overbought == false and oversold == false
exit = (((strategy.position_size > 0 and bar == 1) or (strategy.position_size < 0 and bar == -1)) and body > abody / 2)
//Arrows
col = exit ? black : up1 or dn1 or up2 or dn2 ? blue : na
needup = up1 or up2
needdn = dn1 or dn2
needexitup = exit and strategy.position_size < 0
needexitdn = exit and strategy.position_size > 0
plotarrow(showarr and needup ? 1 : na, colorup = blue, colordown = blue, transp = 0)
plotarrow(showarr and needdn ? -1 : na, colorup = blue, colordown = blue, transp = 0)
plotarrow(showarr and needexitup ? 1 : na, colorup = black, colordown = black, transp = 0)
plotarrow(showarr and needexitdn ? -1 : na, colorup = black, colordown = black, transp = 0)
//Trading
profit = exit ? ((strategy.position_size > 0 and close > strategy.position_avg_price) or (strategy.position_size < 0 and close < strategy.position_avg_price)) ? 1 : -1 : profit[1]
mult = usemar ? exit ? profit == -1 ? mult[1] * 2 : 1 : mult[1] : 1
lot = strategy.position_size == 0 ? strategy.equity / close * capital / 100 * mult : lot[1]
if up1 or up2
if strategy.position_size < 0
strategy.close_all()
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 dn1 or dn2
if strategy.position_size > 0
strategy.close_all()
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()