基于趋势追踪均线战略

Author: ChaoZhang, Date: 2024-02-29 14:00:35
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基于趋势追踪均线战略

概述

该策略通过计算通道均线,在价格突破通道均线时建立多头或空头头寸,追踪股票价格趋势,属于趋势追踪类策略。

策略原理

该策略首先计算20日高点平均值作为通道上轨,20日低点平均值作为通道下轨,并计算通道中线。通道中线代表近期价格平均趋势。当价格上穿通道中线时,建立多头头寸;当价格下穿通道中线时,建立空头头寸。追踪价格趋势,直到价格重新回落到通道区间反向时,平仓头寸。

优势分析

利用通道追踪价格趋势,避免资金被横盘市锁定;
通过通道上下轨判断买卖点位,入场容易控制;
通道范围过滤掉部分噪音,加大获利概率;
可配置通道参数,调整策略的灵敏度;

风险分析

大幅突破通道中线过后可能出现回调测试中线的情况,此时会被套;
震荡类型股票不适合该策略,容易出现高频交易套利;
参数设置不当也可能影响策略效果;

优化方向

优化通道周期参数,测试不同参数对策略效果的影响;
增加止盈止损策略,控制单次亏损和全部亏损;
结合其他指标作为辅助判断,避免错误信号;
分阶段建仓,降低突破回调测试中线的被套概率;

总结

该策略整体来说较为简单直接,通过基本的价格通道来判断股票价格趋势,属于趋势追踪类型策略。优点是容易操作,充分利用价格趋势带来的投资机会,避免资金被锁定。缺点是参数设置不当可能影响效果,且存在一定回调测试的风险。通过合理优化,可以提高策略稳定性,增强实盘表现。

/*backtest
start: 2024-01-01 00:00:00
end: 2024-01-31 23:59:59
period: 4h
basePeriod: 15m
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

//@version=3
//future strategy
//strategy(title = "stub", default_qty_type = strategy.fixed, default_qty_value = 1,  overlay = true, commission_type=strategy.commission.cash_per_contract,commission_value=2)
//stock strategy
strategy(title = "dc", default_qty_type = strategy.percent_of_equity, default_qty_value = 20,  overlay = true, commission_type=strategy.commission.cash_per_contract,commission_value=.005)
//forex strategy
//strategy(title = "stub", default_qty_type = strategy.percent_of_equity, default_qty_value = 20,  overlay = true)
//crypto strategy
//strategy(title = "stub", default_qty_type = strategy.percent_of_equity, default_qty_value = 20,  overlay = true, commission_type=strategy.commission.percent,commission_value=.25,default_qty_value=20)


testStartYear = input(2000, "Backtest Start Year")
testStartMonth = input(1, "Backtest Start Month")
testStartDay = input(1, "Backtest Start Day")
testPeriodStart = timestamp(testStartYear,testStartMonth,testStartDay,0,0)

testEndYear = input(2019, "Backtest Start Year")
testEndMonth = input(3)
testEndDay = input(31, "Backtest Start Day")
testPeriodEnd = timestamp(testStartYear,testStartMonth,testStartDay,0,0)


testPeriod() =>
    true
    //time >= testPeriodStart  ? true : false

dcPeriod = 20

dcUpper = highest(close, dcPeriod)[1]
dcLower = lowest(close, dcPeriod)[1]
dcAverage = (dcUpper + dcLower) / 2

plot(dcLower, style=line, linewidth=3, color=red, offset=1)
plot(dcUpper, style=line, linewidth=3, color=aqua, offset=1)

plot(dcAverage, color=black, style=line, linewidth=3, title="Mid-Line Average")

strategy.entry("simpleBuy", strategy.long, when=close > dcAverage)
strategy.close("simpleBuy",when=close < dcLower)
    
strategy.entry("simpleSell", strategy.short,when=close < dcAverage)
strategy.close("simpleSell",when=close > dcAverage)

更多内容

2019 - FMZ - 发明者量化