ChaoZhang
概述
双轨跟踪反转策略是一个结合布林带,Keltner通道以及动量指标的反转交易策略。该策略通过布林带和Keltner通道的综合判断,识别价格进入压缩区域的时机;同时结合动量指标判断价格的反转信号,形成交易入场和出场信号。
策略原理
计算布林带中的中轨、上轨、下轨
- 中轨采用close的SMA
- 上下轨是中轨加减一个可调整的倍数的标准差
计算Keltner通道中的中轨、上轨、下轨
- 中轨采用close的SMA
- 上下轨是中轨加减一个可调整的倍数的ATR
判断布林带是否位于Keltner通道内侧
- 当布林带上轨低于Keltner上轨,布林带下轨高于Keltner下轨时,认为处于压缩
- 反之,非压缩
计算close与布林带、Keltner通道中点的线性回归斜率val
- val > 0 表示close在上升,val < 0 表示close在下降
计算close的变化率ROC和其EMA
- 判断变化率是否达到可调整的阈值
- 如果超过阈值,认为处于趋势中
在压缩时,当val > 0且变化率达到阈值时做多
- 反之做空
设置止损、止盈条件
策略优势
结合双轨系统判断反转时点,提高准确率
增加线性回归和变化率判断,避免反转假信号
可调整的参数设置灵活,可针对不同品种进行优化
采用止损止盈策略,可以有效控制单次交易风险
回测数据充足,可验证策略有效性
策略风险及解决方案
双轨压缩不一定产生有效反转
- 优化参数,严格双轨压缩条件
假突破产生错误信号
- 增加线性回归判定,确定趋势方向
止损设置过于宽松,单次亏损过大
- 优化止损点,严格控制单次亏损
测试周期 Datenichinhalt
- 增加更多回测周期,验证长期有效性
策略优化方向
优化参数设置,适应更多品种
增加机器学习判断支撑阻力关键点
结合交易量变化提高突破真实性
增加跨时间段分析,判断趋势持续性
优化止损止盈策略,实现动态追踪
总结
双轨跟踪反转策略总体来说是一个利用布林带Keltner通道等指标进行的反转策略。该策略通过参数优化,可以适应不同品种,在一定程度上识别突破的真实性。但反转交易本身仍存在一定的风险,需要进一步结合机器学习等技术来提升判断准确性,从而获得更稳定的超额收益。
策略源码
/*backtest
start: 2023-10-02 00:00:00
end: 2023-11-01 00:00:00
period: 1h
basePeriod: 15m
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/
//@version=4
// Credit for the initial Squeeze Momentum code to LazyBear, rate of change code is from Kiasaki
strategy("Squeeze X BF 🚀", overlay=false, initial_capital=10000, default_qty_type=strategy.percent_of_equity, default_qty_value=100, commission_type=strategy.commission.percent, commission_value=0.0)
/////////////// Time Frame ///////////////
testStartYear = input(2012, "Backtest Start Year")
testStartMonth = input(1, "Backtest Start Month")
testStartDay = input(1, "Backtest Start Day")
testPeriodStart = timestamp(testStartYear,testStartMonth,testStartDay, 0, 0)
testStopYear = input(2019, "Backtest Stop Year")
testStopMonth = input(12, "Backtest Stop Month")
testStopDay = input(31, "Backtest Stop Day")
testPeriodStop = timestamp(testStopYear,testStopMonth,testStopDay, 0, 0)
testPeriod() => true
/////////////// Squeeeeze ///////////////
length = input(20, title="BB Length")
mult = input(2.0,title="BB MultFactor")
lengthKC=input(22, title="KC Length")
multKC = input(1.5, title="KC MultFactor")
useTrueRange = input(true, title="Use TrueRange (KC)")
// Calculate BB
source = close
basis = sma(source, length)
dev = mult * stdev(source, length)
upperBB = basis + dev
lowerBB = basis - dev
// Calculate KC
ma = sma(source, lengthKC)
range = useTrueRange ? tr : (high - low)
rangema = sma(range, lengthKC)
upperKC = ma + rangema * multKC
lowerKC = ma - rangema * multKC
sqzOn = (lowerBB > lowerKC) and (upperBB < upperKC)
sqzOff = (lowerBB < lowerKC) and (upperBB > upperKC)
noSqz = (sqzOn == false) and (sqzOff == false)
val = linreg(source - avg(avg(highest(high, lengthKC), lowest(low, lengthKC)),sma(close,lengthKC)), lengthKC,0)
///////////// Rate Of Change /////////////
roclength = input(30, minval=1), pcntChange = input(7, minval=1)
roc = 100 * (source - source[roclength]) / source[roclength]
emaroc = ema(roc, roclength / 2)
isMoving() => emaroc > (pcntChange / 2) or emaroc < (0 - (pcntChange / 2))
/////////////// Strategy ///////////////
long = val > 0 and isMoving()
short = val < 0 and isMoving()
last_long = 0.0
last_short = 0.0
last_long := long ? time : nz(last_long[1])
last_short := short ? time : nz(last_short[1])
long_signal = crossover(last_long, last_short)
short_signal = crossover(last_short, last_long)
last_open_long_signal = 0.0
last_open_short_signal = 0.0
last_open_long_signal := long_signal ? open : nz(last_open_long_signal[1])
last_open_short_signal := short_signal ? open : nz(last_open_short_signal[1])
last_long_signal = 0.0
last_short_signal = 0.0
last_long_signal := long_signal ? time : nz(last_long_signal[1])
last_short_signal := short_signal ? time : nz(last_short_signal[1])
in_long_signal = last_long_signal > last_short_signal
in_short_signal = last_short_signal > last_long_signal
last_high = 0.0
last_low = 0.0
last_high := not in_long_signal ? na : in_long_signal and (na(last_high[1]) or high > nz(last_high[1])) ? high : nz(last_high[1])
last_low := not in_short_signal ? na : in_short_signal and (na(last_low[1]) or low < nz(last_low[1])) ? low : nz(last_low[1])
sl_inp = input(100.0, title='Stop Loss %') / 100
tp_inp = input(5000.0, title='Take Profit %') / 100
take_level_l = strategy.position_avg_price * (1 + tp_inp)
take_level_s = strategy.position_avg_price * (1 - tp_inp)
since_longEntry = barssince(last_open_long_signal != last_open_long_signal[1])
since_shortEntry = barssince(last_open_short_signal != last_open_short_signal[1])
slLong = in_long_signal ? strategy.position_avg_price * (1 - sl_inp) : na
slShort = strategy.position_avg_price * (1 + sl_inp)
long_sl = in_long_signal ? slLong : na
short_sl = in_short_signal ? slShort : na
/////////////// Execution ///////////////
if testPeriod()
strategy.entry("Long", strategy.long, when=long)
strategy.entry("Short", strategy.short, when=short)
strategy.exit("Long Ex", "Long", stop=long_sl, limit=take_level_l, when=since_longEntry > 0)
strategy.exit("Short Ex", "Short", stop=short_sl, limit=take_level_s, when=since_shortEntry > 0)
/////////////// Plotting ///////////////
bcolor = iff(val > 0, iff(val > nz(val[1]), color.lime, color.green), iff(val < nz(val[1]), color.red, color.maroon))
plot(val, color=bcolor, linewidth=4)
bgcolor(not isMoving() ? color.white : long ? color.lime : short ? color.red : na, transp=70)
bgcolor(long_signal ? color.lime : short_signal ? color.red : na, transp=50)
hline(0, color = color.white)