ChaoZhang
概述
该策略主要利用均线交叉原理,结合RSI指标反转信号,以及自定义的双线追踪算法实现均线交叉追踪交易。策略追踪两个不同周期的均线交叉,一个快速均线追踪短期趋势,另一个慢速均线追踪长期趋势。当快速均线向上穿过慢速均线时,表示短期趋势向上,可以买入;当快速均线向下穿过慢速均线时,表示短期趋势结束,应该平仓。
策略原理
计算两组不同参数的VWAP均线,分别代表长期趋势和短期趋势
- 慢速天幕线和基准线计算长期趋势
- 快速天幕线和基准线计算短期趋势
分别取两组天幕线和基准线的平均值作为慢速均线和快速均线
计算布林带指标判断盘整和突破
- 中线为快速均线和慢速均线的平均值
- 布林带上下轨用于判断突破
计算TSV指标判断交易量能量
- TSV大于0表示上涨力量大于下跌力量
- TSV大于其EMA表示力量增强
计算RSI指标判断超买超卖
- RSI低于30时为超卖区间,可以买入
- RSI高于70时为超买区间,应该卖出
入场条件:
- 快速均线上穿慢速均线
- 关闭价上穿布林带上轨
- TSV大于0且大于其EMA
- RSI低于30
出场条件:
- 快速均线下穿慢速均线
- RSI高于70
优势分析
使用双均线系统,可以同时捕捉长短期趋势
RSI指标避免买入超买区域,卖出超卖区域
TSV指标确保有足够的交易量支撑趋势
利用布林带判断关键的突破点
多种指标组合,可以有效过滤假突破
风险分析
均线系统容易产生错误信号,需要辅助指标过滤
RSI指标参数需要优化,否则可能错过买卖点
TSV指标对参数也很敏感,需要仔细测试
突破布林带上轨有可能是假突破,需要验证
多指标组合,参数优化难度大,容易过度优化
训练和测试数据不充分可能导致曲线拟合
优化方向
测试更多周期参数,寻找最佳参数组合
尝试其他指标如MACD、KD替代或结合RSI
参数优化要充分利用walk forward分析
增加止损策略,以控制单笔损失
考虑加入机器学习模型辅助信号判断
针对不同市场调整参数,不要过度依赖单一参数组合
总结
本策略通过双均线系统捕捉长短期趋势,同时使用RSI、TSV、布林带等多种指标过滤信号。策略优势是可以顺势而为,捕捉长期上升浪潮。但也存在一定的假信号风险,需要进一步优化参数并控制止损来降低风险。总体来说,该策略结合趋势跟踪和反转指标,在长线上升市场中效果较好,但需要针对不同市场做getParameter调整。
策略源码
/*backtest
start: 2022-10-23 00:00:00
end: 2023-10-29 00:00:00
period: 1d
basePeriod: 1h
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/
// @version=4
// Credits
// "Vwap with period" code which used in this strategy to calculate the leadLine was written by "neolao" active on https://tr.tradingview.com/u/neolao/
// "TSV" code which used in this strategy was written by "liw0" active on https://www.tradingview.com/u/liw0. The code is corrected by "vitelot" December 2018.
// "Vidya" code which used in this strategy was written by "everget" active on https://tr.tradingview.com/u/everget/
strategy("HYE Combo Market [Strategy] (Vwap Mean Reversion + Trend Hunter)", overlay = true, initial_capital = 1000, default_qty_value = 100, default_qty_type = strategy.percent_of_equity, commission_value = 0.025)
//Strategy inputs
source = input(title = "Source", defval = close, group = "Mean Reversion Strategy Inputs")
smallcumulativePeriod = input(title = "Small VWAP", defval = 8, group = "Mean Reversion Strategy Inputs")
bigcumulativePeriod = input(title = "Big VWAP", defval = 10, group = "Mean Reversion Strategy Inputs")
meancumulativePeriod = input(title = "Mean VWAP", defval = 50, group = "Mean Reversion Strategy Inputs")
percentBelowToBuy = input(title = "Percent below to buy %", defval = 2, group = "Mean Reversion Strategy Inputs")
rsiPeriod = input(title = "Rsi Period", defval = 2, group = "Mean Reversion Strategy Inputs")
rsiEmaPeriod = input(title = "Rsi Ema Period", defval = 5, group = "Mean Reversion Strategy Inputs")
rsiLevelforBuy = input(title = "Maximum Rsi Level for Buy", defval = 30, group = "Mean Reversion Strategy Inputs")
slowtenkansenPeriod = input(9, minval=1, title="Slow Tenkan Sen VWAP Line Length", group = "Trend Hunter Strategy Inputs")
slowkijunsenPeriod = input(13, minval=1, title="Slow Kijun Sen VWAP Line Length", group = "Trend Hunter Strategy Inputs")
fasttenkansenPeriod = input(3, minval=1, title="Fast Tenkan Sen VWAP Line Length", group = "Trend Hunter Strategy Inputs")
fastkijunsenPeriod = input(7, minval=1, title="Fast Kijun Sen VWAP Line Length", group = "Trend Hunter Strategy Inputs")
BBlength = input(20, minval=1, title= "Bollinger Band Length", group = "Trend Hunter Strategy Inputs")
BBmult = input(2.0, minval=0.001, maxval=50, title="Bollinger Band StdDev", group = "Trend Hunter Strategy Inputs")
tsvlength = input(20, minval=1, title="TSV Length", group = "Trend Hunter Strategy Inputs")
tsvemaperiod = input(7, minval=1, title="TSV Ema Length", group = "Trend Hunter Strategy Inputs")
length = input(title="Vidya Length", type=input.integer, defval=20, group = "Trend Hunter Strategy Inputs")
src = input(title="Vidya Source", type=input.source, defval= hl2 , group = "Trend Hunter Strategy Inputs")
// Vidya Calculation
getCMO(src, length) =>
mom = change(src)
upSum = sum(max(mom, 0), length)
downSum = sum(-min(mom, 0), length)
out = (upSum - downSum) / (upSum + downSum)
out
cmo = abs(getCMO(src, length))
alpha = 2 / (length + 1)
vidya = 0.0
vidya := src * alpha * cmo + nz(vidya[1]) * (1 - alpha * cmo)
// Make input options that configure backtest date range
startDate = input(title="Start Date", type=input.integer,
defval=1, minval=1, maxval=31, group = "Strategy Date Range")
startMonth = input(title="Start Month", type=input.integer,
defval=1, minval=1, maxval=12, group = "Strategy Date Range")
startYear = input(title="Start Year", type=input.integer,
defval=2000, minval=1800, maxval=2100, group = "Strategy Date Range")
endDate = input(title="End Date", type=input.integer,
defval=31, minval=1, maxval=31, group = "Strategy Date Range")
endMonth = input(title="End Month", type=input.integer,
defval=12, minval=1, maxval=12, group = "Strategy Date Range")
endYear = input(title="End Year", type=input.integer,
defval=2021, minval=1800, maxval=2100, group = "Strategy Date Range")
inDateRange = true
// Mean Reversion Strategy Calculation
typicalPriceS = (high + low + close) / 3
typicalPriceVolumeS = typicalPriceS * volume
cumulativeTypicalPriceVolumeS = sum(typicalPriceVolumeS, smallcumulativePeriod)
cumulativeVolumeS = sum(volume, smallcumulativePeriod)
smallvwapValue = cumulativeTypicalPriceVolumeS / cumulativeVolumeS
typicalPriceB = (high + low + close) / 3
typicalPriceVolumeB = typicalPriceB * volume
cumulativeTypicalPriceVolumeB = sum(typicalPriceVolumeB, bigcumulativePeriod)
cumulativeVolumeB = sum(volume, bigcumulativePeriod)
bigvwapValue = cumulativeTypicalPriceVolumeB / cumulativeVolumeB
typicalPriceM = (high + low + close) / 3
typicalPriceVolumeM = typicalPriceM * volume
cumulativeTypicalPriceVolumeM = sum(typicalPriceVolumeM, meancumulativePeriod)
cumulativeVolumeM = sum(volume, meancumulativePeriod)
meanvwapValue = cumulativeTypicalPriceVolumeM / cumulativeVolumeM
rsiValue = rsi(source, rsiPeriod)
rsiEMA = ema(rsiValue, rsiEmaPeriod)
buyMA = ((100 - percentBelowToBuy) / 100) * bigvwapValue[0]
inTrade = strategy.position_size > 0
notInTrade = strategy.position_size <= 0
if(crossunder(smallvwapValue, buyMA) and rsiEMA < rsiLevelforBuy and close < meanvwapValue and inDateRange and notInTrade)
strategy.entry("BUY-M", strategy.long)
if(close > meanvwapValue or not inDateRange)
strategy.close("BUY-M")
// Trend Hunter Strategy Calculation
// Slow Tenkan Sen Calculation
typicalPriceTS = (high + low + close) / 3
typicalPriceVolumeTS = typicalPriceTS * volume
cumulativeTypicalPriceVolumeTS = sum(typicalPriceVolumeTS, slowtenkansenPeriod)
cumulativeVolumeTS = sum(volume, slowtenkansenPeriod)
slowtenkansenvwapValue = cumulativeTypicalPriceVolumeTS / cumulativeVolumeTS
// Slow Kijun Sen Calculation
typicalPriceKS = (high + low + close) / 3
typicalPriceVolumeKS = typicalPriceKS * volume
cumulativeTypicalPriceVolumeKS = sum(typicalPriceVolumeKS, slowkijunsenPeriod)
cumulativeVolumeKS = sum(volume, slowkijunsenPeriod)
slowkijunsenvwapValue = cumulativeTypicalPriceVolumeKS / cumulativeVolumeKS
// Fast Tenkan Sen Calculation
typicalPriceTF = (high + low + close) / 3
typicalPriceVolumeTF = typicalPriceTF * volume
cumulativeTypicalPriceVolumeTF = sum(typicalPriceVolumeTF, fasttenkansenPeriod)
cumulativeVolumeTF = sum(volume, fasttenkansenPeriod)
fasttenkansenvwapValue = cumulativeTypicalPriceVolumeTF / cumulativeVolumeTF
// Fast Kijun Sen Calculation
typicalPriceKF = (high + low + close) / 3
typicalPriceVolumeKF = typicalPriceKS * volume
cumulativeTypicalPriceVolumeKF = sum(typicalPriceVolumeKF, fastkijunsenPeriod)
cumulativeVolumeKF = sum(volume, fastkijunsenPeriod)
fastkijunsenvwapValue = cumulativeTypicalPriceVolumeKF / cumulativeVolumeKF
// Slow LeadLine Calculation
lowesttenkansen_s = lowest(slowtenkansenvwapValue, slowtenkansenPeriod)
highesttenkansen_s = highest(slowtenkansenvwapValue, slowtenkansenPeriod)
lowestkijunsen_s = lowest(slowkijunsenvwapValue, slowkijunsenPeriod)
highestkijunsen_s = highest(slowkijunsenvwapValue, slowkijunsenPeriod)
slowtenkansen = avg(lowesttenkansen_s, highesttenkansen_s)
slowkijunsen = avg(lowestkijunsen_s, highestkijunsen_s)
slowleadLine = avg(slowtenkansen, slowkijunsen)
// Fast LeadLine Calculation
lowesttenkansen_f = lowest(fasttenkansenvwapValue, fasttenkansenPeriod)
highesttenkansen_f = highest(fasttenkansenvwapValue, fasttenkansenPeriod)
lowestkijunsen_f = lowest(fastkijunsenvwapValue, fastkijunsenPeriod)
highestkijunsen_f = highest(fastkijunsenvwapValue, fastkijunsenPeriod)
fasttenkansen = avg(lowesttenkansen_f, highesttenkansen_f)
fastkijunsen = avg(lowestkijunsen_f, highestkijunsen_f)
fastleadLine = avg(fasttenkansen, fastkijunsen)
// BBleadLine Calculation
BBleadLine = avg(fastleadLine, slowleadLine)
// Bollinger Band Calculation
basis = sma(BBleadLine, BBlength)
dev = BBmult * stdev(BBleadLine, BBlength)
upper = basis + dev
lower = basis - dev
// TSV Calculation
tsv = sum(close>close[1]?volume*(close-close[1]):close<close[1]?volume*(close-close[1]):0,tsvlength)
tsvema = ema(tsv, tsvemaperiod)
// Rules for Entry & Exit
if(fastleadLine > fastleadLine[1] and slowleadLine > slowleadLine[1] and tsv > 0 and tsv > tsvema and close > upper and close > vidya and inDateRange and notInTrade)
strategy.entry("BUY-T", strategy.long)
if((fastleadLine < fastleadLine[1] and slowleadLine < slowleadLine[1]) or not inDateRange)
strategy.close("BUY-T")
// Plots
plot(meanvwapValue, title="MEAN VWAP", linewidth=2, color=color.yellow)
//plot(vidya, title="VIDYA", linewidth=2, color=color.green)
//colorsettingS = input(title="Solid Color Slow Leadline", defval=false, type=input.bool)
//plot(slowleadLine, title = "Slow LeadLine", color = colorsettingS ? color.aqua : slowleadLine > slowleadLine[1] ? color.green : color.red, linewidth=3)
//colorsettingF = input(title="Solid Color Fast Leadline", defval=false, type=input.bool)
//plot(fastleadLine, title = "Fast LeadLine", color = colorsettingF ? color.orange : fastleadLine > fastleadLine[1] ? color.green : color.red, linewidth=3)
//p1 = plot(upper, "Upper BB", color=#2962FF)
//p2 = plot(lower, "Lower BB", color=#2962FF)
//fill(p1, p2, title = "Background", color=color.blue)
//plot(smallvwapValue, color=#13C425, linewidth=2)
//plot(bigvwapValue, color=#CA1435, linewidth=2)