Como funciona
A estratégia combina uma média móvel simples de curto e longo período (SMA) com Bandas de Bollinger para identificar oportunidades de negociação.
O tamanho inicial da negociação é fixo, mas as ordens de segurança subsequentes são dimensionadas de acordo com a porcentagem definida pelo usuário.
Benefícios
Os principais benefícios da estratégia incluem:
O valor da transação deve ser calculado de acordo com o método de classificação do mercado. Parâmetros de entrada flexíveis para otimização Dimensão da posição da balança utilizando ordens de segurança Implementado como um bot de negociação 3Commas Riscos
Riscos potenciais a considerar:
Os sinais de ruptura são transmitidos tarde quando a volatilidade aumenta Aumento da exposição a partir de posições de pirâmide Stop loss pode ficar para trás em mercados em rápida evolução A estratégia visa capitalizar sobre a continuação da tendência.
/*backtest
start: 2023-01-01 00:00:00
end: 2023-09-09 00:00:00
period: 10m
basePeriod: 1m
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 thick red line plotted on the chart shows the average entry price of the current deal.
// strategy("3Commas Bollinger Strategy", overlay=true, default_qty_type=strategy.cash, default_qty_value=100, initial_capital=1000, currency="USD", commission_value=0.1)
// USER INPUTS
sma_short_val = input(title="Short MA Window", defval=20)
sma_long_val = input(title="Long MA Window", defval=100)
ubOffset = input(title="Upper Band Offset", defval=2.5, step=0.5)
lbOffset = input(title="Lower Band Offset", defval=2.5, step=0.5)
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
initial_deviation_input = input(title="Initial SO Deviation (%)", minval=0, step=0.01, defval=0.8) * 0.01
volume_scale = input(title="Safety Order Vol Step (%)", minval=0.00, step=0.01, defval=1.55)
plotlines = input(title="Enable/Disable visual lines", type=input.bool, defval=true)
// 3Commas Bot settinsg
bot_id = input(title="3Commas Bot ID", defval="")
email_token = input(title="Bot Email Token", defval="")
bot_pair = input(title="3Commas Bot Trading Pair", defval="")
// 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-5)
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 = crossunder(close, lowerBand) // Buy when close crossing under lower band
safety = initial_deviation and (1-(close/strategy.position_avg_price))/.01 > strategy.opentrades * 1.55 and strategy.opentrades <= 6 // 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 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
//goodSell = crossover(high, upperBand)
goodSell = false
// 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 != ""
enter_msg := '{"message_type": "bot", "bot_id": ' + bot_id + ', "email_token": "' + email_token + '", "delay_seconds": 0, "pair": "' + bot_pair + '"}'
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"}'
// Strategy Actions
if inDateRange and goodBuy
strategy.entry("Good Buy", strategy.long, when = strategy.opentrades <= 0, alert_message=enter_msg)
if inDateRange and safety
strategy.order("Good Buy", strategy.long, strategy.position_size*volume_scale, when = strategy.opentrades > 0, comment = "safety order")
if inDateRange and goodSell
strategy.close_all(comment="Good sell point")
if inDateRange and stoploss
strategy.close_all(comment="Stoploss")
if inDateRange and takeprofit
strategy.close_all(comment="TP Target")