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动态价格通道止损追踪策略Dynamic-Price-Channel-with-Stop-Loss-Tracking-Strategy.md

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Name

动态价格通道止损追踪策略Dynamic-Price-Channel-with-Stop-Loss-Tracking-Strategy

Author

ChaoZhang

Strategy Description

IMG [trans]

概述

本策略基于Donchian价格通道指标开发。该指标通过计算一定周期内的最高价和最低价,形成价格通道。策略利用价格通道实现双向交易,并设定止损和止盈价格。止损价格固定为价格通道中线,止盈价格设定为价格通道上下限之外的一定百分比。策略还实现了止盈和止损的追踪。

策略原理

首先,策略根据参数pclen计算价格通道的上限h和下限l。中线center为价格通道上下限的平均值。然后根据长仓和空仓的止盈参数tp,计算出止盈价格tpl和tps。止损价格固定为价格通道中线center。当价格突破价格通道时,根据风险大小risklong和riskshort计算出不同方向的交易仓位。策略会在价格重新进入通道时平仓。此外,还设置了时间过滤,只在指定的日期区间内交易。

具体交易逻辑为:

多仓开仓信号:价格大于通道上限h且回落到通道内时开多仓 多仓平仓信号:价格低于通道中线center(止损)或高于止盈价格tpl(止盈)时平多仓

空仓开仓信号:价格小于通道下限l且回落到通道内时开空仓 空仓平仓信号:价格高于通道中线center(止损)或低于止盈价格tps(止盈)时平空仓

优势分析

本策略具有以下优势:

  1. 双向交易,可以捕捉价格趋势的反转
  2. 利用价格通道判断趋势方向,避免假突破
  3. 设定止盈止损,控制风险
  4. 计算仓位规模关联风险大小,实现风险可控
  5. 实现止盈和止损的追踪,可以锁定更多利润

风险分析

本策略也存在一定的风险:

  1. 价格通道参数设置不当可能导致交易频率过高或错过交易机会
  2. 止损价格过宽容可能增加风险敞口
  3. 追踪止盈在高波动时期可能提前触发

可以通过调整参数以及人工监控的方式降低和控制这些风险。

优化方向

本策略还可以从以下几个方面进行优化:

  1. 增加更多指标判断过滤,避免在震荡行情中频繁开平仓
  2. 可以测试不同的止盈止损算法,如ATR止损等
  3. 扩展为跨时间周期交易系统,利用更高级时间周期确定趋势方向
  4. 增加仓位管理模块,根据资金使用比例调整仓位
  5. 结合机器学习模型判断价格突破的成功率,避免假突破

总结

本策略总体来说是一个利用价格通道指标实现双向交易的有效方法。设置了止盈止损和仓位控制模块,可以很好地控制风险。通过一定的优化和调整,可以成为一个强大的量化交易策略。

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Overview

This strategy is developed based on the Donchian price channel indicator. The indicator forms a price channel by calculating the highest and lowest prices over a certain period. The strategy utilizes the price channel to implement two-way trading and sets stop loss and take profit prices. The stop loss price is fixed to the middle line of the price channel, and the take profit price is set to a certain percentage beyond the upper and lower limits of the price channel. The strategy also implements tracking of stop loss and take profit.

Strategy Principle

Firstly, the strategy calculates the upper limit h and lower limit l of the price channel based on the parameter pclen. The middle line center is the average of the upper and lower limits of the price channel. Then, take profit prices tpl and tps are calculated according to the take profit parameters tp for long and short positions. The stop loss price is fixed to the middle line center of the price channel. When the price breaks through the price channel, trading positions of different directions are calculated according to the risk sizes risklong and riskshort. The strategy will close positions when the price re-enters the channel. In addition, time filtering is set to only trade within the specified date range.

The specific trading logic is:

Long entry signal: open long when price is greater than the channel upper limit h and falls back into the channel

Long exit signal: close long when price is lower than the channel middle line center (stop loss) or higher than take profit price tpl (take profit)

Short entry signal: open short when price is less than the channel lower limit l and falls back into the channel

Short exit signal: close short when price is higher than the channel middle line center (stop loss) or lower than take profit price tps (take profit)

Advantage Analysis

The advantages of this strategy are:

  1. Two-way trading can capture reversals of price trends
  2. Use price channel to determine trend direction and avoid false breakouts
  3. Set stop loss and take profit to control risks
  4. Calculate position size associated with risk size to achieve controllable risks
  5. Implement tracking of stop loss and take profit to lock in more profits

Risk Analysis

There are also some risks in this strategy:

  1. Improper parameter settings of price channel may lead to too high trading frequency or missing trading opportunities
  2. Stop loss price set too wide may increase risk exposure
  3. Tracking take profit may trigger prematurely in high volatility periods

These risks can be reduced and controlled by adjusting parameters and manual monitoring.

Optimization Directions

This strategy can also be optimized in the following aspects:

  1. Add more indicator filters to avoid frequent opening and closing in range-bound markets
  2. Different stop loss and take profit algorithms can be tested, such as ATR stop loss
  3. Expand to a cross-timeframe trading system using higher timeframe to determine trend direction
  4. Add position sizing module to adjust positions based on capital utilization ratio
  5. Incorporate machine learning models to judge the success rate of price breakouts to avoid false breakouts

Conclusion

In conclusion, this is an effective strategy to implement two-way trading using price channel indicators. With proper stop loss, take profit, and position sizing control modules, risks can be well controlled. With some optimizations and adjustments, it can become a powerful quantitative trading strategy.

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Strategy Arguments

Argument Default Description
v_input_1 true Long
v_input_2 true Short
v_input_3 20 Take-profit, %
v_input_4 0 Take-profit type: 2. Fix
v_input_5 0 Take-profit type: 2. Center
v_input_6 5 Risk size for long, %
v_input_7 5 Risk size for short, %
v_input_8 50 Price Channel Length
v_input_9 true Show lines
v_input_10 false Show Background
v_input_11 true Show Offset
v_input_12 true Show label
v_input_13 1900 From Year
v_input_14 2100 To Year
v_input_15 true From Month
v_input_16 12 To Month
v_input_17 true From day
v_input_18 31 To day

Source (PineScript)

/*backtest
start: 2023-01-31 00:00:00
end: 2024-01-31 00:00:00
period: 1d
basePeriod: 1h
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

//Noro
//2020

//@version=4
strategy(title = "Noro's RiskDonchian Strategy", shorttitle = "RiskDonchian str", overlay = true, default_qty_type = strategy.percent_of_equity, initial_capital = 100, default_qty_value = 100, commission_value = 0.1)

//Settings
needlong = input(true, defval = true, title = "Long")
needshort = input(true, defval = true, title = "Short")
tp = input(defval = 20.0, minval = 1, title = "Take-profit, %")
tptype = input(defval = "2. Fix", options = ["1. None", "2. Fix", "3. Trailing"], title = "Take-profit type")
sltype = input(defval = "2. Center", options = ["1. None", "2. Center"], title = "Take-profit type")
risklong  = input(5.0, minval = 0.0, maxval = 99.9, title = "Risk size for long, %")
riskshort = input(5.0, minval = 0.0, maxval = 99.9, title = "Risk size for short, %")
pclen = input(50, minval = 1, title = "Price Channel Length")
showll = input(true, defval = true, title = "Show lines")
showbg = input(false, defval = false, title = "Show Background")
showof = input(true, defval = true, title = "Show Offset")
showlabel = input(true, defval = true, title = "Show label")
fromyear = input(1900, defval = 1900, minval = 1900, maxval = 2100, title = "From Year")
toyear = input(2100, defval = 2100, minval = 1900, maxval = 2100, title = "To Year")
frommonth = input(01, defval = 01, minval = 01, maxval = 12, title = "From Month")
tomonth = input(12, defval = 12, minval = 01, maxval = 12, title = "To Month")
fromday = input(01, defval = 01, minval = 01, maxval = 31, title = "From day")
today = input(31, defval = 31, minval = 01, maxval = 31, title = "To day")

//Price Channel
h = highest(high, pclen)
l = lowest(low, pclen)
center = (h + l) / 2

//Take-profit
tpl = 0.0
tpl := tptype == "2. Fix" and strategy.position_size > 0 ? tpl[1] : h * (100 + tp) / 100

//Stop-loss
tps = 0.0
tps := tptype == "2. Fix" and strategy.position_size < 0 ? tps[1] : l * (100 - tp) / 100

//Lines
tplcol = showll and needlong and tptype != "1. None" ? color.lime : na
pclcol = showll and needlong ? color.blue : na
sllcol = showll and needlong and sltype != "1. None" ? color.red : na
tpscol = showll and needshort and tptype != "1. None" ? color.lime : na
pcscol = showll and needshort ? color.blue : na
slscol = showll and needshort and sltype != "1. None" ? color.red : na
offset = showof ? 1 : 0
plot(tpl, offset = offset, color = tplcol, title = "TP Long")
plot(h, offset = offset, color = pclcol, title = "Channel High")
plot(center, offset = offset, color = sllcol, title = "SL Long")
plot(center, offset = offset, color = slscol, title = "SL Short")
plot(l, offset = offset, color = pcscol, title = "Channel Low")
plot(tps, offset = offset, color = tpscol, title = "TP Short")

//Background
size = strategy.position_size
bgcol = showbg == false ? na : size > 0 ? color.lime : size < 0 ? color.red : na
bgcolor(bgcol, transp = 70)

//Lot size
risksizelong = -1 * risklong
risklonga = ((center / h) - 1) * 100
coeflong = abs(risksizelong / risklonga)
lotlong = (strategy.equity / close) * coeflong
risksizeshort = -1 * riskshort
riskshorta = ((center / l) - 1) * 100
coefshort = abs(risksizeshort / riskshorta)
lotshort = (strategy.equity / close) * coefshort

//Trading
truetime = time > timestamp(fromyear, frommonth, fromday, 00, 00) and time < timestamp(toyear, tomonth, today, 23, 59)
mo = 0
mo := strategy.position_size != 0 ? 0 : high >= center[1] and low <= center[1] ? 1 : mo[1]

if h > 0
    longlimit = tptype == "1. None" ? na : tpl
    longstop = sltype == "1. None" ? na : center
    strategy.entry("Long", strategy.long, lotlong, stop = h, when = strategy.position_size <= 0 and needlong and truetime and mo)
    strategy.exit("TP Long", "Long", limit = longlimit, stop = longstop)
    shortlimit = tptype == "1. None" ? na : tps
    shortstop = sltype == "1. None" ? na : center
    strategy.entry("Short", strategy.short, lotshort, stop = l, when = strategy.position_size >= 0 and needshort and truetime and mo)
    strategy.exit("Exit Short", "Short", limit = shortlimit, stop = shortstop)
if time > timestamp(toyear, tomonth, today, 23, 59)
    strategy.close_all()
    strategy.cancel("Long")
    strategy.cancel("Short")
    
if showlabel

    //Drawdown
    max = 0.0
    max := max(strategy.equity, nz(max[1]))
    dd = (strategy.equity / max - 1) * 100
    min = 100.0
    min := min(dd, nz(min[1]))
    
    //Label
    min := round(min * 100) / 100
    labeltext = "Drawdown: " + tostring(min) + "%"
    var label la = na
    label.delete(la)
    tc = min > -100 ? color.white : color.red
    osx = timenow + round(change(time)*10)
    osy = highest(100)

Detail

https://www.fmz.com/strategy/440687

Last Modified

2024-02-01 10:52:33