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Oscilación de impulso cruzando bandas de Bollinger con estrategia de media móvil

El autor:¿ Qué pasa?, Fecha: 2023-12-19 11:34:46
Las etiquetas:

Resumen general

Esta es una estrategia de negociación cuantitativa basada en bandas de Bollinger e indicadores MACD. Combina dos indicadores técnicos principales para identificar oportunidades de negociación, con el objetivo de lograr una mayor tasa de ganancia en los mercados de tendencia.

La estrategia establecerá una posición larga cuando el precio rompe la banda inferior de las bandas de Bollinger para seguir la tendencia, y una posición cerrada cuando el precio rompe la banda superior.

Estrategia lógica

La estrategia consiste principalmente en bandas de Bollinger y indicadores MACD.

Las bandas de Bollinger calculan las bandas superiores e inferiores basadas en la desviación estándar de los precios. La ruptura ascendente de la banda superior señala la condición de sobrecompra, mientras que la ruptura descendente de la banda inferior señala la condición de sobreventa.

El indicador MACD juzga el impulso y la dirección de los precios. El cruce de la media móvil a corto plazo por encima de la media móvil a largo plazo es una señal de compra, mientras que el cruce por debajo es una señal de venta.

Además, el indicador RSI puede ayudar a identificar los niveles de sobrecompra / sobreventa.

Ventajas de la estrategia

La estrategia combina las bandas de Bollinger, el MACD y los indicadores RSI, que pueden determinar eficazmente la tendencia y la volatilidad de los precios.

Las bandas de Bollinger capturan la tendencia que sigue cuando el precio rompe las bandas
El MACD filtra las señales falsas de las bandas de Bollinger al juzgar el impulso
El RSI evita comprar en el pico al identificar los niveles de sobrecompra/sobreventa
Se puede lograr una mayor tasa de ganancia mediante la optimización de parámetros

Riesgos de la estrategia

También hay algunos riesgos a tener en cuenta:

Riesgo elevado de stop loss cuando los precios fluctúan violentamente
La rentabilidad disminuye con ajustes incorrectos de parámetros
El MACD puede juzgar erróneamente cuando la tendencia se invierte

Contramedidas:

El porcentaje de pérdida de parada puede aflojarse adecuadamente
Se requiere una extensa prueba posterior para encontrar los parámetros óptimos
Se pueden utilizar más indicadores para predecir la reversión de tendencia

Direcciones para la optimización

Las principales direcciones para optimizar la estrategia incluyen:

Optimizar los parámetros de las bandas de Bollinger para más regímenes de mercado
Aumentar los indicadores para mejorar la robustez
Utilice el aprendizaje automático para optimizar automáticamente los parámetros
Rendimiento de la estrategia de ensayo en datos de alta frecuencia
Añadir módulo de gestión de riesgos al límite de pérdida por operación

Conclusión

En general, esta es una tendencia típica después de la estrategia. Al combinar múltiples indicadores técnicos, mejora la robustez y puede lograr una tasa de ganancia decente cuando las señales son precisas. Sin embargo, los riesgos deben monitorearse. Se pueden hacer mejoras adicionales a través de la optimización y el ajuste continuos.

/*backtest
start: 2022-12-12 00:00:00
end: 2023-12-18 00:00:00
period: 1d
basePeriod: 1h
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

//@version=4
// This source code is subject to the terms of the Mozilla Public License 2.0 at https://mozilla.org/MPL/2.0/
// © tedwardd

// This strategy is intended to help users of the 3commas.io platform backtest bot performance based on a Bollinger Strategy.
// It can also be used to signal a bot to open a deal by providing the Bot ID, email token and trading pair in the strategy settings screen.
// As currently written, this strategy uses a basic Bollinger Band strategy, recommening a deal start when the closing price crosses under the lower band.
// The thick red line plotted on the chart shows the average entry price of the current deal.

strategy("[v1.3laoowai]BNB_USDT_3m_3Commas_Bollinger_Strategy_by_tedwardd", overlay=true, default_qty_type=strategy.cash, default_qty_value=1000, initial_capital=900, currency="USD", commission_value=0.1)

// 3Commas Bot settinsg
bot_type                = input(title="Simple bot", defval="simple", options=["simple", "composite"])
bot_id                  = input(title="3Commas Bot ID", defval="")
email_token             = input(title="Bot Email Token", defval="")
base_order_size         = input(title="Base order size",minval=10, step=1, defval=10)
safety_order_size       = input(title="Safety order size", minval=15, step=1, defval=400)
volume_scale            = input(title="Safety Order Vol Scale (%)", minval=0.00, step=0.01, defval=1.83)
safety_step             = input(title="Safety Order Step Scale (%)", minval=0.00, step=0.1, defval=1.55)
safety_max              = input(title="Max Number of Safety Orders", minval=0, step=1, defval=2)
initial_deviation_input = input(title="Initial SO Deviation (%)", minval=0, step=0.01, defval=1.54) * 0.01
stoploss_input          = input(title="Long Stop Loss (%)", minval=0, step=1, defval=15) * 0.01
takeprofit_input        = input(title="Long Take Profit (%)", minval=0, step=1, defval=1.4) * 0.01

// USER INPUTS
sma_short_val           = input(title="Short MA Window", defval=21)
sma_long_val            = input(title="Long MA Window", defval=100)
ubOffset                = input(title="Upper Band Offset", defval=2.2, step=0.5)
lbOffset                = input(title="Lower Band Offset", defval=2.40, step=0.5)
cross                   = input(title="Entrry at Cross Over/Under Lower", defval="under", options=["over", "under"])

// Backtesting Date Ranges
startDate  = input(title="Start Date", defval=1, minval=1, maxval=31)
startMonth = input(title="Start Month", defval=1, minval=1, maxval=12)
startYear  = input(title="Start Year", defval=2016, minval=1800, maxval=2100)
endDate    = input(title="End Date", defval=31, minval=1, maxval=31)
endMonth   = input(title="End Month", defval=12, minval=1, maxval=12)
endYear    = input(title="End Year", defval=2022, minval=1800, maxval=2100)

// VARS
short_sma        = sma(close, sma_short_val)
long_sma         = sma(close, sma_long_val)
stdDev           = stdev(close, sma_short_val)
upperBand        = short_sma + (stdDev * ubOffset)
lowerBand        = short_sma - (stdDev * lbOffset)
stoploss_value   = strategy.position_avg_price * (1 - stoploss_input)
takeprofit_value = strategy.position_avg_price * (1 + takeprofit_input)
initial_dev_val  = strategy.position_avg_price * (1 - initial_deviation_input)
inDateRange      = true

initial_deviation = close < initial_dev_val

// Market Conditions
goodBuy    = cross=="over"?crossover(close, lowerBand):crossunder(close, lowerBand) // Buy when close crossing lower band
safety     = initial_deviation and (1-(close/strategy.position_avg_price))/.01 > strategy.opentrades-1 * safety_step and strategy.opentrades <= safety_max // SO when price deviates below SO threshold %
stoploss   = close <= stoploss_value // Stoploss condition - true if closing price for current bar drops below stoploss %
takeprofit = close >= takeprofit_value // Take profit condition - true if closing price for current bar is >= take profit percentage
goodSell = crossover(high, upperBand)

// goodSell is currently unused for any practical purpose. If you wish to try it, switch these two values. 
// Doing so will make sell suggestions at high crossover upper bollinger but it does not trigger the bot to sell as written but may affect backtest results

// Plot some lines
plot(short_sma, color=color.green)
plot(upperBand)
plot(lowerBand, color=color.yellow)
plot(strategy.position_avg_price, color=color.red, linewidth=3)


// Webhook message. Defaults to string. To signal 3c bot, fill in bot_id and email_token in user settings
var enter_msg = "Enter Position"
var exit_msg  = "Exit Position"
var close_all = "Exit Position"
if bot_id != "" and email_token != ""
    if bot_type == "composite"
        enter_msg := '{"message_type": "bot", "bot_id": ' + bot_id + ', "email_token": "' + email_token + '", "delay_seconds": 0, "pair": "' + syminfo.currency + "_" + syminfo.basecurrency + '"}'
    else
        enter_msg := '{"message_type": "bot", "bot_id": ' + bot_id + ',  "email_token": "' + email_token + '", "delay_seconds": 0}'
    if bot_type == "composite"
        exit_msg := '{"message_type": "bot", "bot_id": ' + bot_id + ', "email_token": "' + email_token + '", "delay_seconds": 0, "pair": "' + syminfo.currency + "_" + syminfo.basecurrency + '", "action": "close_at_market_price"}'
    else
        exit_msg := '{"message_type": "bot", "bot_id": ' + bot_id + ', "email_token": "' + email_token + '", "delay_seconds": 0, "action": "close_at_market_price"}'
    close_all := '{"message_type": "bot", "bot_id": ' + bot_id + ', "email_token": "' + email_token + '", "delay_seconds": 0, "action": "close_at_market_price_all"}'

actual_safety_size = float(safety_order_size) // Set safety order size to starting safety
if strategy.opentrades > 1 // If we have more than two open trades we need to start scaling the safety size by the volume_scale
    actual_safety_size := (strategy.position_size - base_order_size) * volume_scale // Remove base order from total position size and scale it for next safety order

// Momentum Strategy (BTC/USDT; 1h) - MACD (with source code) by Drun30

//@version=4
// Getting inputs
fast_length = input(title="Fast Length", type=input.integer, defval=23,group="MACD")
slow_length = input(title="Slow Length", type=input.integer, defval=16,group="MACD")
src = input(title="Source", type=input.source, defval=open,group="MACD")

signal_length = input(title="Signal Smoothing", type=input.integer, minval = 1, maxval = 50, defval = 9,group="MACD")
sma_source1 = input(title="Simple MA FAST (Oscillator)", defval="EMA", options=["HMA","DHMA","THMA","FHMA","WMA","DWMA","TWMA","FWMA","SMA","DSMA","TSMA","FSMA","EMA","DEMA","TEMA","FEMA","RMA","DRMA","TRMA","FRMA"],group="MACD")
sma_source2 = input(title="Simple MA SLOW (Oscillator)", defval="EMA", options=["HMA","DHMA","THMA","FHMA","WMA","DWMA","TWMA","FWMA","SMA","DSMA","TSMA","FSMA","EMA","DEMA","TEMA","FEMA","RMA","DRMA","TRMA","FRMA"],group="MACD")

sma_signal = input(title="Simple MA(Signal Line)",defval="EMA", options=["HMA","DHMA","THMA","FHMA","WMA","DWMA","TWMA","FWMA","SMA","DSMA","TSMA","FSMA","EMA","DEMA","TEMA","FEMA","RMA","DRMA","TRMA","FRMA"],group="MACD")
// Calculating
ma(source,length,type)=>
    type=="FEMA"?4*ema(source,length)-ema(ema(ema(ema(source,length),length),length),length):type=="FSMA"?4*sma(source,length)-sma(sma(sma(sma(source,length),length),length),length):type=="FWMA"?4*wma(source,length)-wma(wma(wma(wma(source,length),length),length),length):type=="FRMA"?4*rma(source,length)-rma(rma(rma(rma(source,length),length),length),length):type=="TEMA"?3*ema(source,length)-ema(ema(ema(source,length),length),length):type=="TSMA"?3*sma(source,length)-sma(sma(sma(source,length),length),length):type=="TWMA"?3*wma(source,length)-wma(wma(wma(source,length),length),length):type=="TRMA"?3*rma(source,length)-rma(rma(rma(source,length),length),length):type=="EMA"?ema(source,length):type=="SMA"?sma(source,length):type=="WMA"?wma(source,length):type=="RMA"?rma(source,length):type=="DEMA"?2*ema(source,length)-ema(ema(source,length),length):type=="DSMA"?2*sma(source,length)-sma(sma(source,length),length):type=="DWMA"?2*wma(source,length)-wma(wma(source,length),length):type=="DRMA"?2*rma(source,length)-rma(rma(source,length),length):type=="HMA"?hma(source,length):type=="DHMA"?2*hma(source,length)-hma(hma(source,length),length):type=="THMA"?3*hma(source,length)-hma(hma(hma(source,length),length),length):type=="FHMA"?4*hma(source,length)-hma(hma(hma(hma(source,length),length),length),length):ema(source,length)
fast_ma = ma(src,fast_length,sma_source1)  
slow_ma = ma(src,slow_length,sma_source2)
macd = fast_ma - slow_ma //Differenza tra la media mobile veloce e quella lenta 
signal = ma(macd,signal_length,sma_signal) //usa o la SMA oppure la EMA sulla differenza tra la media mobile veloce e lenta
hist = macd - signal //Differenza tra la differenza precedente e la media mobile della differenza

use_stress=input(true,title="Use stress on recent bars",group="Stress")
recent_stress=input(0.41,title="Stress on recent bars",group="Stress",step=0.01,minval=0.01,maxval=0.99)
level=input(6,title="Level of stress",group="Stress")
if use_stress 
    macd:=macd*(1/(1-recent_stress))
    if not na(macd[1])
        macd:=pow((macd*(recent_stress)),level)+(1-recent_stress*macd[1])

use_ma= input(true,title="Use moving average (MACD)?",group="Moving Average")
if use_ma
    macd:=ma(macd,input(36,title="Length",group="Moving Average"),input(title="Type MA",defval="THMA", options=["HMA","DHMA","THMA","FHMA","WMA","DWMA","TWMA","FWMA","SMA","DSMA","TSMA","FSMA","EMA","DEMA","TEMA","FEMA","RMA","DRMA","TRMA","FRMA"],group="Moving Average"))

use_linreg= input(true,title="Use linear regression (MACD)?",group="Linear Regression")
if use_linreg
    macd:=linreg(macd,input(10,title="Length",group="Linear Regression"),input(1,title="Offset",group="Linear Regression"))

//macd == linea blu (differenza tra media mobile veloce e media mobile lenta)
//signal == linea arancione (media mobile dell'macd)
//hist == istogramma (differenza tra macd e media mobile)

on_cross = input(false,title="Use cross macd and signal",group="Condition entry/exit")
on_minmax = input(true,title="Use min/max macd",group="Condition entry/exit")


aperturaLong = change(macd)>0//crossover(macd,signal)
aperturashort=not (change(macd)>0)//crossunder(macd,signal)

if on_cross
    on_minmax:=false
    aperturaLong := crossover(macd,signal)
    aperturashort := crossunder(macd,signal)
if on_minmax
    on_cross:=false
    aperturaLong := change(macd)>0//crossover(macd,signal)
    aperturashort:=change(macd)<0//crossunder(macd,signal)

rsiFilter = input(false,title="Use RSI filter?",group="RSI")
rsiTP = input(true,title="Use RSI Take Profit?",group="RSI")

len=input(22,title="RSI period",group="RSI")
srcr=input(close,title="RSI source",group="RSI")
rsi=rsi(srcr,len)
ovb=input(90,title="Overbought height",group="RSI") 
ovs=input(45,title="Oversold height",group="RSI")
okLong=rsi<ovb and change(macd)>0 and change(macd)[1]<=0
okShort=rsi>ovs and change(macd)<0 and change(macd)[1]>=0
if not rsiFilter
    okLong:=true
    okShort:=true
    
usiLong=input(true,title="Use long?")
usiShort=input(true,title="Use short?")

chiusuraShort=rsi<ovs or (aperturaLong)
chiusuraLong=rsi>ovb or (aperturashort)
if rsiTP
    aperturaLong := change(macd)>0 and change(macd)[1]<=0 and rsi<ovb//crossover(macd,signal)
    aperturashort:=change(macd)<0 and change(macd)[1]>=0 and rsi>ovs//crossunder(macd,signal)

if not rsiTP
    chiusuraShort:=okLong and aperturaLong
    chiusuraLong:=okShort and aperturashort
    
//if chiusuraShort 
//    strategy.close("SHORTISSIMO")
//if usiLong and strategy.position_size<=0 and okLong and aperturaLong
//    strategy.entry("LONGHISSIMO",true)
//if chiusuraLong 
//    strategy.close("LONGHISSIMO")
//if usiShort and strategy.position_size>=0 and okShort and aperturashort
//    strategy.entry("SHORTISSIMO",false)

// Strategy Actions
//Buy
if inDateRange and goodBuy
    strategy.entry("Good Buy", strategy.long, base_order_size, when = strategy.opentrades <= 0, alert_message=enter_msg)
if inDateRange and safety
    strategy.order("Good Buy", strategy.long, actual_safety_size, when = strategy.opentrades > 0, comment = "safety order", alert_message=enter_msg)

// Sell
if inDateRange and goodSell
    strategy.close_all(comment="Good sell point", alert_message=exit_msg)
if inDateRange and stoploss
    strategy.close_all(comment="Stoploss", alert_message=exit_msg)
//if inDateRange and takeprofit
//    strategy.close_all(comment="TP Target", alert_message=exit_msg)
if usiShort and strategy.position_size>=0 and okShort and aperturashort
    strategy.close_all(comment="SHORTISSIMO", alert_message=exit_msg)
//if chiusuraShort
//    strategy.close_all(comment="SHORTISSIMO1")

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