ChaoZhang
概述
本策略综合运用了股票量价反转因子和动量因子,构建了一个双因子模型,以期捕捉市场短期反转和中长期persistence的机会。策略首先利用123形态判断近期价格反转信号,然后结合Laguerre RSI指标判断中长线趋势,最终实现双因子信号的有效结合。
策略原理
该策略由两部分组成:
123形态反转因子
该部分通过判断前两天的收盘价变化,发现价格短期反转信号。具体来说,如果前一天的收盘价低于前两天,且今天的收盘价高于前一天,那么可以判断为价格反转上涨的信号。Stoch指标用于辅助判断。
基于拉格尔滤波器的RSI因子
该部分构建了一种更灵敏的RSI指标。传统RSI指标对价格变化的敏感性较低,而拉格尔滤波器可以用更少的历史数据构建指标,从而提高对价格变化的敏感性。新的RSI指标用于判断中长线趋势。
最终,策略会结合两者的信号,在短期反转的同时,确保大趋势不会反转,从而捕捉反弹机会。
策略优势
该策略最大的优势在于成功结合了反转因子和趋势因子。反转因子能够捕捉短期调整后的价格反弹机会,而趋势因子则确保做多/做空的大方向不会发生改变。相比单一的反转或动量模型,该双因子模型能够在降低假信号的前提下,提高做多做空准确性。
此外,拉格尔RSI指标的加入也增加了模型对价格变化的敏感性,这对高频交易尤其重要。
风险分析
该策略面临的主要风险在于双因子信号可能发生分歧。尤其是在市场震荡调整期间,短期价格频繁反转的同时,中长线趋势也可能发生改变。这时,两种信号极有可能出现错误组合或者延迟。这将导致策略生成错误信号,进而错过最佳入场时机或者造成不必要的损失。
此外,参数选择不当也会导致策略表现不佳。反转因子和趋势因子对应的技术指标参数需要分别调优和测试,不当的参数组合也可能使策略效果大打折扣。
优化方向
该策略下一步优化的方向主要集中在信号过滤和参数选择上。可以考虑加入更多过滤条件,在双因子信号发生分歧时发挥作用,确保只在高确定性场景下开仓。这可以大幅减少错信号率。
在参数选择上,可以尝试机器学习和科学实验的方法,对各个参数组合进行系统测试,找到最优参数。这需要较高的计算能力支持,但可以显著提高策略稳定性。
总结
本策略成功地融合了反转因子和趋势因子,通过双因子模型捕捉短期反弹和中长期persistence机会。加入的拉格尔RSI滤波器也提高了模型对价格变化的敏感性。下一步工作将集中于信号过滤和参数优化上,以进一步增强策略效果。
/*backtest
start: 2024-01-10 00:00:00
end: 2024-01-17 00:00:00
period: 5m
basePeriod: 1m
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/
//@version=4
////////////////////////////////////////////////////////////
// Copyright by HPotter v1.0 21/01/2021
// 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
// This is RSI indicator which is more sesitive to price changes.
// It is based upon a modern math tool - Laguerre transform filter.
// With help of Laguerre filter one becomes able to create superior
// indicators using very short data lengths as well. The use of shorter
// data lengths means you can make the indicators more responsive to
// changes in the price.
//
// 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
LB_RSI(gamma,BuyBand,SellBand) =>
pos = 0.0
xL0 = 0.0
xL1 = 0.0
xL2 = 0.0
xL3 = 0.0
xL0 := (1-gamma) * close + gamma * nz(xL0[1], 1)
xL1 := - gamma * xL0 + nz(xL0[1], 1) + gamma * nz(xL1[1], 1)
xL2 := - gamma * xL1 + nz(xL1[1], 1) + gamma * nz(xL2[1], 1)
xL3 := - gamma * xL2 + nz(xL2[1], 1) + gamma * nz(xL3[1], 1)
CU = (xL0 >= xL1 ? xL0 - xL1 : 0) + (xL1 >= xL2 ? xL1 - xL2 : 0) + (xL2 >= xL3 ? xL2 - xL3 : 0)
CD = (xL0 >= xL1 ? 0 : xL1 - xL0) + (xL1 >= xL2 ? 0 : xL2 - xL1) + (xL2 >= xL3 ? 0 : xL3 - xL2)
nRes = iff(CU + CD != 0, CU / (CU + CD), 0)
pos := iff(nRes > BuyBand, 1,
iff(nRes < SellBand, -1, nz(pos[1], 0)))
pos
strategy(title="Combo Backtest 123 Reversal & Laguerre-based RSI", shorttitle="Combo", overlay = true)
Length = input(14, minval=1)
KSmoothing = input(1, minval=1)
DLength = input(3, minval=1)
Level = input(50, minval=1)
//-------------------------
gamma = input(0.5, minval=-0.1, maxval = 0.9)
BuyBand = input(0.8, step = 0.01)
SellBand = input(0.2, step = 0.01)
reverse = input(false, title="Trade reverse")
posReversal123 = Reversal123(Length, KSmoothing, DLength, Level)
posLB_RSI = LB_RSI(gamma,BuyBand,SellBand)
pos = iff(posReversal123 == 1 and posLB_RSI == 1 , 1,
iff(posReversal123 == -1 and posLB_RSI == -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 )