ChaoZhang
概述
该策略运用多时间框架动态回溯机制,通过比较不同时间周期的最高价和最低价,判断价格趋势,实现低风险套利。
策略原理
该策略通过调用自定义函数f_get_htfHighLow,获取不同时间周期的最高价nhigh和最低价nlow。具体来说,根据用户设定的时间周期resolution、时间周期乘数HTFMultiplier、回溯参数lookahead与gaps,以及偏移量offset,调用security函数获取不同时间周期的最高价和最低价。
例如,offset为0时,获得当前K线的最高价和最低价;offset为1时,获得上一K线的最高价和最低价。通过比较两K线之间价格的变化,判断趋势方向。
如果最高价上涨且最低价上涨,则判断为看涨趋势;如果最高价下跌且最低价下跌,则判断为看跌趋势。根据趋势方向进行 longing或shorting,实现套利交易。
策略优势
- 运用多时间框架分析,提高判断准确性
- 应用动态回溯机制,避免repainting
- 灵活设置不同参数组合,适应市场变化
- 仅在趋势明确时开仓,有效控制风险
策略风险
- 多时间框架判断可能存在误判风险
- 回溯参数设置不当可能导致repainting
- 交易频率可能过高,增加交易成本和滑点风险
解决方法: 1. 优化时间周期参数,提高判断准确性 2. 严格测试回溯参数,避免repainting 3. 适当调整开仓条件,控制交易频率
策略优化方向
- 增加机器学习模块,利用AI判断趋势
- 结合股价波动率,动态调整仓位
- 加入止损机制,有效控制亏损风险
总结
该策略整体思路清晰,利用多时间框架动态回溯判断股价趋势,最大程度减少人为判断错误,是一种典型的程序化交易策略。通过参数优化与功能扩展,可进一步增强策略稳定性与盈利空间,值得深入研究与跟踪。
策略源码
/*backtest
start: 2022-11-14 00:00:00
end: 2023-11-20 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/
// © HeWhoMustNotBeNamed
//@version=4
strategy("HTF High/Low Repaint Strategy", overlay=true, initial_capital = 20000, default_qty_type = strategy.percent_of_equity, default_qty_value = 100, commission_type = strategy.commission.percent, pyramiding = 1, commission_value = 0.01)
i_startTime = input(defval = timestamp("01 Jan 2010 00:00 +0000"), title = "Start Time", type = input.time)
i_endTime = input(defval = timestamp("01 Jan 2099 00:00 +0000"), title = "End Time", type = input.time)
inDateRange = true
resolution = input("3M", type=input.resolution)
HTFMultiplier = input(22, minval=1, step=1)
offset = input(0, minval=0, step=1)
lookahead = input(true)
gaps = false
f_secureSecurity_on_on(_symbol, _res, _src, _offset) => security(_symbol, _res, _src[_offset], lookahead = barmerge.lookahead_on, gaps=barmerge.gaps_on)
f_secureSecurity_on_off(_symbol, _res, _src, _offset) => security(_symbol, _res, _src[_offset], lookahead = barmerge.lookahead_on, gaps=barmerge.gaps_off)
f_secureSecurity_off_on(_symbol, _res, _src, _offset) => security(_symbol, _res, _src[_offset], lookahead = barmerge.lookahead_off, gaps=barmerge.gaps_on)
f_secureSecurity_off_off(_symbol, _res, _src, _offset) => security(_symbol, _res, _src[_offset], lookahead = barmerge.lookahead_off, gaps=barmerge.gaps_off)
f_multiple_resolution(HTFMultiplier) =>
target_Res_In_Min = timeframe.multiplier * HTFMultiplier * (
timeframe.isseconds ? 1. / 60. :
timeframe.isminutes ? 1. :
timeframe.isdaily ? 1440. :
timeframe.isweekly ? 7. * 24. * 60. :
timeframe.ismonthly ? 30.417 * 24. * 60. : na)
target_Res_In_Min <= 0.0417 ? "1S" :
target_Res_In_Min <= 0.167 ? "5S" :
target_Res_In_Min <= 0.376 ? "15S" :
target_Res_In_Min <= 0.751 ? "30S" :
target_Res_In_Min <= 1440 ? tostring(round(target_Res_In_Min)) :
tostring(round(min(target_Res_In_Min / 1440, 365))) + "D"
f_get_htfHighLow(resolution, HTFMultiplier, lookahead, gaps, offset)=>
derivedResolution = resolution == ""?f_multiple_resolution(HTFMultiplier):resolution
nhigh_on_on = f_secureSecurity_on_on(syminfo.tickerid, derivedResolution, high, offset)
nlow_on_on = f_secureSecurity_on_on(syminfo.tickerid, derivedResolution, low, offset)
nhigh_on_off = f_secureSecurity_on_off(syminfo.tickerid, derivedResolution, high, offset)
nlow_on_off = f_secureSecurity_on_off(syminfo.tickerid, derivedResolution, low, offset)
nhigh_off_on = f_secureSecurity_off_on(syminfo.tickerid, derivedResolution, high, offset)
nlow_off_on = f_secureSecurity_off_on(syminfo.tickerid, derivedResolution, low, offset)
nhigh_off_off = f_secureSecurity_off_off(syminfo.tickerid, derivedResolution, high, offset)
nlow_off_off = f_secureSecurity_off_off(syminfo.tickerid, derivedResolution, low, offset)
nhigh = lookahead and gaps ? nhigh_on_on :
lookahead and not gaps ? nhigh_on_off :
not lookahead and gaps ? nhigh_off_on :
not lookahead and not gaps ? nhigh_off_off : na
nlow = lookahead and gaps ? nlow_on_on :
lookahead and not gaps ? nlow_on_off :
not lookahead and gaps ? nlow_off_on :
not lookahead and not gaps ? nlow_off_off : na
[nhigh, nlow]
[nhigh, nlow] = f_get_htfHighLow(resolution, HTFMultiplier, lookahead, gaps, offset)
[nhighlast, nlowlast] = f_get_htfHighLow(resolution, HTFMultiplier, lookahead, gaps, offset+1)
plot(nhigh , title="HTF High",style=plot.style_circles, color=color.green, linewidth=1)
plot(nlow , title="HTF Low",style=plot.style_circles, color=color.red, linewidth=1)
buyCondition = nhigh > nhighlast and nlow > nlowlast
sellCondition = nhigh < nhighlast and nlow < nlowlast
strategy.entry("Buy", strategy.long, when= buyCondition and inDateRange, oca_name="oca_buy")
strategy.entry("Sell", strategy.short, when= sellCondition and inDateRange, oca_name="oca_sell")
更多内容