Dual RSI Combined with Bollinger Band for Trend Following

Pine ScriptTrend following Machine learning Breakout RSI SMA Bollinger Bands

Author: ChaoZhang
Complexity: Intermediate · 75 lines
Parameters: 10
Backtest bar: 2m · intraday
Tested on: BTC/USDT · futures

Jump to code View in vault Original on FMZ

Overview

This strategy uses dual RSI indicators to identify overbought and oversold conditions, combined with Bollinger Band breakouts to generate trading signals. It belongs to the trend-following strategy category. The goal is to improve signal reliability through combining multiple indicators, and profit from obvious trends.

Principle Analysis

The strategy employs two RSI with different timeframes to judge short-term and long-term overbought/oversold status. Trading signals are only generated when both RSIs reach the threshold values simultaneously. This avoids false signals from a single RSI.

Bollinger Bands are also used to identify price breakouts. Only when RSI conditions are met and price breaks Boll Band upper/lower band will a trade signal be generated. The breakout confirmation helps avoid signals in non-trending markets.

Finally, fast and slow MAs are checked for trend direction. Trades are only opened when the breakout aligns with RSI signal direction.

Advantage Analysis

The combined use of multiple indicators helps filter out false signals, only trading obvious trends. The fast/slow MAs also facilitate trend following. The simple strategy is suitable for profiting from short-term trends.

Risk Analysis

The main risk is failing to promptly identify trend reversals. Sharp V-shaped reversals may lead to significant losses without timely stop loss. Parameter tuning could also impact performance.

Optimization Suggestions

Add stop loss strategies to exit quickly on reversals.
Incorporate other filters like volume to avoid false breakouts.
Optimize parameters to find best combination.
Add machine learning models to better identify market regimes.
Enhance risk management including position sizing, loss control.

Conclusion

This strategy combines dual RSI and Bollinger Bands to profit from short-term trends. While simple and straightforward, limitations exist like delayed reversal signals. Adding stop loss, signal filtering, parameter optimization can further enhance its robustness and profitability.

Parameters

Name	Default	What it controls
v_input_1	10	RSI
v_input_2	65	OSold
v_input_3	35	OBought
v_input_4	6	RSI2
v_input_5	65	OSold2
v_input_6	35	OBought2
v_input_7	20	Bollinger
v_input_8	1.7	Desv
v_input_9	3	Media corta
v_input_10	10	Media larga

Source Pine Script

/*backtest
start: 2023-09-11 00:00:00
end: 2023-09-12 04:00:00
period: 2m
basePeriod: 1m
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

//@version=2

strategy(title = "Madrugada strat copy", overlay = true, pyramiding = 0, default_qty_type = strategy.percent_of_equity, default_qty_value = 10, currency = currency.USD)
 
// === GENERAL INPUTS ===
// RSI 1
RSIlength = input(10,title="RSI") 
RSIoverSold = input(65,title="OSold")
RSIoverBought = input(35,title="OBought")
price = close
vrsi = rsi(price, RSIlength)
// RSI 2
RSIlength2 = input(6,title="RSI2") 
RSIoverSold2 = input(65,title="OSold2")
RSIoverBought2 = input(35,title="OBought2")
price2 = close
vrsi2 = rsi(price2, RSIlength2)

//Bollinger Bands
source = close
Bollinger = input(20, minval=1), Desv = input(1.7, minval=0.001, maxval=50)
basis = sma(source, Bollinger)
dev = Desv * stdev(source, Bollinger)
upper = basis + dev
lower = basis - dev
plot(basis, color=red, title="BB ma")
p1 = plot(upper, color=blue, title="BBajo")
p2 = plot(lower, color=blue, title="BAlto")
fill(p1, p2)

//Media movil
short = input(3, minval=1, title="Media corta")
long = input(10, minval=1, title="Media larga")
src = close
plot(sma(src, short), color=#00FF00, transp=0, linewidth=1, title="Media rapida")
plot(sma(src, long), color=white, transp=0, linewidth=2, title="Media lenta")


// === STRATEGY - LONG POSITION EXECUTION ===
enterLong() => vrsi < 30 and  vrsi2 < 27 and cross(lower, price)
exitLong() => short < long
strategy.entry(id = "Long", long = true, when = enterLong()) // use function or simple condition to decide when to get in
// === STRATEGY - SHORT POSITION EXECUTION ===
enterShort() => vrsi > 70 and vrsi2 > 70 and cross(upper, price)
strategy.entry(id = "Short", long = false, when = enterShort())


// Definición señales de compra
buy_signals = vrsi < 30 and  vrsi2 < 27 and cross(lower, price)

// Definición señales de venta
sell_signals = vrsi > 70 and vrsi2 > 70 and cross(upper, price)

// Dibuja las señales de compra venta en franjas de color
b_color = (sell_signals) ? color(red,65) : (buy_signals) ? color(green,65) : na
bgcolor(b_color)

// Dibuja las señales de compra venta coloreando las velas
barcolor(buy_signals ? white : sell_signals ? white : na)

plot(vrsi, color=white, linewidth=1)
plot(vrsi, color=white, linewidth=2)

// Crea alarmas usables desde el desplegable para poder enviar mails a haas
alertcondition(buy_signals, title='Buy-Signal', message='compra')
alertcondition(sell_signals, title='Sell-Signal', message='vende')

Published by ChaoZhang on the FMZ strategy square · last modified 2023-09-19. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.

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