Estrategia de negociación de la balanza de oro de múltiples indicadores

El autor:¿ Qué pasa?, Fecha: 2023-09-11 15:18:08
Las etiquetas:

Esta estrategia de negociación combina múltiples indicadores, incluidos el RSI, el estocástico, las bandas de Bollinger y SuperTrend, para generar señales comerciales.

Específicamente, considera que el RSI por encima de 50 y el valor estocástico K por encima de D son señales alcistas.

Por el contrario, el RSI por debajo de 50 y el Stochastic K por debajo de D dan señales bajistas.

La combinación de múltiples indicadores sirve como un filtro eficaz para mejorar la fiabilidad de la señal.

Sin embargo, la combinación de indicadores también introduce un retraso, potencialmente faltando entradas óptimas.


/*backtest
start: 2023-01-01 00:00:00
end: 2023-03-10 00:00:00
period: 45m
basePeriod: 5m
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

// This source code is subject to the terms of the Mozilla Public License 2.0 at https://mozilla.org/MPL/2.0/
// © rajm14

//@version=5
strategy(title = "Golden Swing Strategy - Souradeep Dey", shorttitle = "GSS", overlay = true, process_orders_on_close = true, default_qty_type = strategy.cash, default_qty_value=100000, currency = currency.USD)

// Indicator - RSI - 20
rsiSrc = input(defval = close, title = "RSI Source")
rsiLen = input.int(defval = 20, title = "RSI Length", minval = 0, maxval = 200, step = 1)
rsi = ta.rsi(rsiSrc, rsiLen)
//plot(rsi)

// Indicator - Stochastic (55,34,21)
kLength = input.int(defval = 55, title="Stoch %K Length", minval=1)
kSmooth = input.int(defval = 34, title="Stoch %K Smoothing", minval=1)
dLength = input.int(defval = 21, title="Stoch %D Smoothing", minval=1)
kLine = ta.sma(ta.stoch(close, high, low, kLength), kSmooth)
dLine = ta.sma(kLine, dLength)
// plot(kLine, color=color.red)
// plot(dLine, color=color.green)

// Indicator - ATR(5)
atrLength = input(5, "ATR Length")
atr = ta.atr(5)
// plot(atr)

// Indicator - SuperTrend(10,2)
atrPeriod = input(10, "SuperTrend ATR Length")
stSrc = hl2
stfactor = input.float(2.0, "SuperTrend Multiplier", step = 0.1)
stAtr = ta.atr(atrPeriod)
[supertrend, direction] = ta.supertrend(stfactor, atrPeriod)
bodyMiddle = (open + close) / 2
upTrend = direction < 0 ? supertrend : na
downTrend = direction < 0? na : supertrend
// plot(bodyMiddle, display=display.none)
// plot(upTrend)
// plot(downTrend)


// Indicator - Bollinger Bands (20,2)
bblength = input.int(defval = 20, title = "BB Length")
bbsource = input(defval = close, title = "BB Source")
bbStdDev = input.float(defval = 2.0, title = "BB Std Dev", step = 0.1)
bbmultiplier = bbStdDev * ta.stdev(bbsource, bblength)
bbMband = ta.sma(bbsource, bblength)
bbUband = bbMband + bbmultiplier
bbLband = bbMband - bbmultiplier
// plot (bbUband, color = color.red, linewidth = 2)
// plot (bbMband, color = color.black, linewidth = 2)
// plot (bbLband, color = color.green, linewidth = 2)

// Trade Entry

LongEntry = rsi >= 50 and kLine > dLine and low < supertrend and direction < 0 and supertrend < bbMband
ShortEntry = rsi <= 50 and kLine < dLine and high > supertrend and direction > 0 and supertrend > bbMband
plotshape(LongEntry, style = shape.triangleup,  text = "Long", location = location.belowbar, size = size.large, color = color.green)
plotshape(ShortEntry, style = shape.triangledown,  text = "Short", location = location.abovebar, size = size.large, color = color.red)

//Trade execution
if LongEntry
    strategy.entry(id = "Buy", direction = strategy.long, limit = close * .5 * atr)

closelong = close >= strategy.position_avg_price * 2.2 * atr
stoplong = close <=  strategy.position_avg_price * 1.1 * atr

if closelong
    strategy.close(id = "Buy")
    
if stoplong
    strategy.close(id = "Buy")
    
if ShortEntry
    strategy.entry(id = "Sell", direction = strategy.long, limit = close * .5 * atr)

closeshort = close <= strategy.position_avg_price * 2.2 * atr
stopshort = close >=  strategy.position_avg_price * 1.1 * atr

if closeshort
    strategy.close(id = "Sell")
    
if stopshort
    strategy.close(id = "Sell")



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