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基于布林带通道的突破回归策略Bollinger-Bands-Channel-Breakout-Mean-Reversion-Strategy.md

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Name

基于布林带通道的突破回归策略Bollinger-Bands-Channel-Breakout-Mean-Reversion-Strategy

Author

ChaoZhang

Strategy Description

IMG [trans]

概述

该策略是基于布林带通道的回归突破策略。当价格跌破布林带通道下轨时,进行长仓入场。止损价格设为入场突破点的最低价。止盈目标为布林带上轨。

策略原理

该策略使用20周期的布林带通道。布林带通道由中轨、上轨和下轨组成。中轨为20周期的简单移动平均线,上轨由中轨加上标准差的2倍构成,下轨由中轨减去标准差的2倍构成。

当价格跌破下轨时,表明价格进入了超卖状态,这时进行长仓入场。入场后,止损价格设为入场时那根K线的最低价,止盈目标为布林带上轨。这样,策略就是追逐价格从超卖状态回归均线的过程,实现盈利。

策略优势分析

该策略具有以下优势:

  1. 利用布林带通道判断市场超买超卖状态,具有一定的时效性
  2. 回归交易策略,避免docname追高杀跌
  3. 止盈止损点设置合理,有利于风险控制

风险分析

该策略也存在一些风险:

  1. 布林带并不能完美判断价格趋势,价格突破下轨不一定会反弹
  2. 大盘持续下跌时, Floating P/L 可能首先触发止损
  3. 止盈点靠近上轨,存在止盈成本过高风险

策略优化方向

该策略可以从以下几个方面进行优化:

  1. 优化布林带参数,寻找最佳参数组合
  2. 添加其他指标过滤信号,提高入场准确率
  3. 优化止盈止损策略,提高盈亏比

总结

该策略整体思路清晰,具有一定的操作性。但其利用布林带判断超买超卖的时效性并不高,无法完美判断价格趋势。此外,止盈止损机制也有待优化。后续可从选择更准确指标、优化参数以及改进止盈止损机制等方面进行优化,提升策略profitability。

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Overview

This is a mean reversion breakout strategy based on the Bollinger Bands channel. It goes long when the price breaks below the lower band of the Bollinger Bands. The stop loss is set at the low of the breakout bar. The profit target is the upper band of the Bollinger Bands.

Strategy Logic

The strategy uses a 20-period Bollinger Bands channel, which consists of a middle band, an upper band and a lower band. The middle band is a 20-period simple moving average. The upper band is the middle band plus 2 standard deviations. The lower band is the middle band minus 2 standard deviations.

When the price breaks below the lower band, it indicates the price has entered an oversold status. The strategy will go long at this point. After entering the position, the stop loss is set at the low of the entry bar, and the profit target is the upper band. Thus the strategy aims to capture the reversion process from oversold to the mean, in order to make profits.

Advantage Analysis

The advantages of this strategy are:

  1. Use Bollinger Bands to judge overbought/oversold status, which has some timeliness
  2. Reversion trading strategy, avoiding chasing highs and killing lows
  3. Reasonable stop loss and take profit setting for better risk control

Risk Analysis

The risks of this strategy include:

  1. Bollinger Bands cannot perfectly determine price trends, breakouts may fail
  2. Continous market crash may hit stop loss
  3. Take profit near upper band has the risk of high cost

Optimization Directions

The strategy can be improved from the following aspects:

  1. Optimize parameters of Bollinger Bands to find the best combination
  2. Add filter indicators to improve entry accuracy
  3. Optimize stop loss and take profit for higher profitability

Conclusion

The strategy has clear logic and is tradable to some extent. However, its effectiveness in judging overbought/oversold with Bollinger Bands is limited, and it cannot perfectly determine the trend. Also, the stop loss and take profit mechanism needs improvement. Going forwards, it can be optimized by choosing more accurate indicators, tuning parameters, and enhancing the exit logic to improve profitability.

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Strategy Arguments

Argument Default Description
v_input_int_1 20 Bollinger Bands Length
v_input_float_1 2 Multiplier
v_input_3_close 0 Source: close
v_input_bool_1 true (?Backtest Time Period)Filter Date Range of Backtest
v_input_1 timestamp(1 Jan 1997) Start Date
v_input_2 timestamp(1 Sept 2023) End Date

Source (PineScript)

/*backtest
start: 2023-01-15 00:00:00
end: 2024-01-21 00:00:00
period: 1d
basePeriod: 1h
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/
// © Ronsword
//@version=5

strategy("bb 2ND target", overlay=true)
 
// STEP 1. Create inputs that configure the backtest's date range
useDateFilter = input.bool(true, title="Filter Date Range of Backtest",
     group="Backtest Time Period")
backtestStartDate = input(timestamp("1 Jan 1997"), 
     title="Start Date", group="Backtest Time Period",
     tooltip="This start date is in the time zone of the exchange " + 
     "where the chart's instrument trades. It doesn't use the time " + 
     "zone of the chart or of your computer.")
backtestEndDate = input(timestamp("1 Sept 2023"),
     title="End Date", group="Backtest Time Period",
     tooltip="This end date is in the time zone of the exchange " + 
     "where the chart's instrument trades. It doesn't use the time " + 
     "zone of the chart or of your computer.")

// STEP 2. See if the current bar falls inside the date range
inTradeWindow = true

// Bollinger Bands inputs
length = input.int(20, title="Bollinger Bands Length")
mult = input.float(2.0, title="Multiplier")
src = input(close, title="Source")
basis = ta.sma(src, length)
dev = mult * ta.stdev(src, length)
upper = basis + dev
lower = basis - dev

// EMA Settings
ema20 = ta.ema(close, 20)
plot(ema20, color=color.blue, title="20 EMA")

// Entry condition
longEntryCondition = ta.crossover(close, lower)

// Define stop loss level as the low of the entry bar
var float stopLossPrice = na
if longEntryCondition
    stopLossPrice := low

// Top Bollinger Band itself is set as the target
topBandTarget = upper

// Enter long position when conditions are met
if inTradeWindow and longEntryCondition
    strategy.entry("Long", strategy.long, qty=1)

// Set profit targets
strategy.exit("ProfitTarget2", from_entry="Long", limit=topBandTarget)

// Set stop loss
strategy.exit("StopLoss", stop=stopLossPrice)

// Plot Bollinger Bands with the same gray color
plot(upper, color=color.gray, title="Upper Bollinger Band")
plot(lower, color=color.gray, title="Lower Bollinger Band")

Detail

https://www.fmz.com/strategy/439608

Last Modified

2024-01-22 10:47:45