ChaoZhang
概述
该策略是一个多因子组合策略,结合使用反转因子和动量因子,目的是发掘市场中的反转机会。策略首先使用久负反转因子识别盘整下跌后的反转机会,然后利用动量指标进行二次筛选,过滤掉大趋势下的反转假信号,从而锁定短线反转套利机会。
策略原理
该策略由两部分组成:
123反转因子
该部分运用日内反转思想,判断前一日收盘价与前二日收盘价的关系,配合慢速K线识别反转机会。具体逻辑是:
买入信号:连续两日收盘价下跌后当日收盘价上涨,且九日慢速K线低于50,则产生买入信号;
卖出信号:连续两日收盘价上涨后当日收盘价下跌,且九日快速K线高于50,则产生卖出信号。
埃尔格迪克动量震荡指标(ETSI)
该部分利用三EMA平滑价格动量的方法构建动量指标。指标公式如下:
xPrice1 = close - close[1] xPrice2 = abs(close - close[1]) xSMA_R = EMA(EMA(EMA(xPrice1,r), s), u) xSMA_aR = EMA(EMA(EMA(xPrice2, r), s), u) xTSI = xSMA_R / xSMA_aR * 100 xEMA_TSI = EMA(xTSI, N)其中,xSMA_R是价格动量的EMA平滑值,xSMA_aR是价格波动幅度的EMA平滑值,xTSI是两者的比值构成的动量指标,xEMA_TSI是xTSI的再次EMA平滑。该指标判断xTSI和xEMA_TSI的关系,作为交易信号方向。
最后,策略将两部分信号进行AND运算,只有当两部分因子同向发出信号时,才产生实际的交易指令。
策略优势
该策略最大的优势在于多因子设计,可以过滤假信号,发掘高质量交易机会。具体来说,主要有以下三点:
123反转因子可以识别盘整下跌后的短期反弹点位。
埃尔格迪克动量指标可以有效判断大趋势方向,避免反转信号发生在大趋势下,从而过滤假信号。
两部分信号采用AND运算,可以提高信号质量,增强策略稳定性。
策略风险
尽管策略采用多因子设计以控制风险,但仍存在以下主要风险:
反转信号可能发生在震荡趋势中,无法获利。
两因子之间参数设定存在主观性,可能过拟合特定品种。
反转后价格再次调头可能增加亏损风险。
这些风险可以通过优化参数以适应更多品种,控制反转后持仓时间,实时监控指标关系变化等方式加以缓解。
策略优化
该策略主要可以从以下几个方面进行优化:
调整两因子的参数,寻找更匹配的数据样本。
增加止损策略,控制单笔损失。
针对趋势品种和震荡品种使用不同参数组合。
增加因子权重机制,让表现更好的因子拥有更大权重。
增加机器学习算法,实现参数的自动优化和更新。
总结
该策略成功地结合反转因子和动量指标,实现多因子优化设计。它可以有效识别短期反转机会,并利用动量指标对信号进行二次验证,从而提高策略胜率。虽然策略仍存在一定改进空间,但其核心思路为量化策略的设计提供了良好参考。
/*backtest
start: 2023-10-21 00:00:00
end: 2023-11-20 00:00:00
period: 1h
basePeriod: 15m
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/
//@version=4
////////////////////////////////////////////////////////////
// Copyright by HPotter v1.0 30/07/2020
// This is combo strategies for get a cumulative signal.
//
// First strategy
// This System was created from the Book "How I Tripled My Money In The
// Futures Market" by Ulf Jensen, Page 183. This is reverse type of strategies.
// The strategy buys at market, if close price is higher than the previous close
// during 2 days and the meaning of 9-days Stochastic Slow Oscillator is lower than 50.
// The strategy sells at market, if close price is lower than the previous close price
// during 2 days and the meaning of 9-days Stochastic Fast Oscillator is higher than 50.
//
// Second strategy
// r - Length of first EMA smoothing of 1 day momentum 4
// s - Length of second EMA smoothing of 1 day smoothing 8
// u- Length of third EMA smoothing of 1 day momentum 6
// Length of EMA signal line 3
// Source of Ergotic TSI Close
//
// This is one of the techniques described by William Blau in his book "Momentum,
// Direction and Divergence" (1995). If you like to learn more, we advise you to
// read this book. His book focuses on three key aspects of trading: momentum,
// direction and divergence. Blau, who was an electrical engineer before becoming
// a trader, thoroughly examines the relationship between price and momentum in
// step-by-step examples. From this grounding, he then looks at the deficiencies
// in other oscillators and introduces some innovative techniques, including a
// fresh twist on Stochastics. On directional issues, he analyzes the intricacies
// of ADX and offers a unique approach to help define trending and non-trending periods.
//
// WARNING:
// - For purpose educate only
// - This script to change bars colors.
////////////////////////////////////////////////////////////
Reversal123(Length, KSmoothing, DLength, Level) =>
vFast = sma(stoch(close, high, low, Length), KSmoothing)
vSlow = sma(vFast, DLength)
pos = 0.0
pos := iff(close[2] < close[1] and close > close[1] and vFast < vSlow and vFast > Level, 1,
iff(close[2] > close[1] and close < close[1] and vFast > vSlow and vFast < Level, -1, nz(pos[1], 0)))
pos
ETSI(r,s,u,SmthLen) =>
pos = 0
xPrice = close
xPrice1 = xPrice - xPrice[1]
xPrice2 = abs(xPrice - xPrice[1])
xSMA_R = ema(ema(ema(xPrice1,r), s),u)
xSMA_aR = ema(ema(ema(xPrice2, r), s),u)
Val1 = 100 * xSMA_R
Val2 = xSMA_aR
xTSI = iff (Val2 != 0, Val1 / Val2, 0)
xEMA_TSI = ema(xTSI, SmthLen)
pos:= iff(xTSI > xEMA_TSI, 1,
iff(xTSI < xEMA_TSI, -1, nz(pos[1], 0)))
pos
strategy(title="Combo Backtest 123 Reversal & Ergodic TSI", shorttitle="Combo", overlay = true)
Length = input(14, minval=1)
KSmoothing = input(1, minval=1)
DLength = input(3, minval=1)
Level = input(50, minval=1)
//-------------------------
r = input(4, minval=1)
s = input(8, minval=1)
u = input(6, minval=1)
SmthLen = input(3, minval=1)
reverse = input(false, title="Trade reverse")
posReversal123 = Reversal123(Length, KSmoothing, DLength, Level)
posETSI = ETSI(r,s,u,SmthLen)
pos = iff(posReversal123 == 1 and posETSI == 1 , 1,
iff(posReversal123 == -1 and posETSI == -1, -1, 0))
possig = iff(reverse and pos == 1, -1,
iff(reverse and pos == -1 , 1, pos))
if (possig == 1)
strategy.entry("Long", strategy.long)
if (possig == -1)
strategy.entry("Short", strategy.short)
if (possig == 0)
strategy.close_all()
barcolor(possig == -1 ? #b50404: possig == 1 ? #079605 : #0536b3 )