ChaoZhang
概述
该策略综合运用多种技术指标,对价格反转进行判断,属于多因子驱动的反转交易策略。它整合123形态与极化分形效率(PFE)指标,在两者给出一致信号时入场,可以有效过滤假信号,提高交易胜率。
策略原理
该策略主要由两部分组成:
123形态判断:当收盘价连续2日上涨后第3日回落,且 Stochastic快线低于慢线,产生买入信号;当收盘价连续2日下跌后第3日反弹,且 Stochastic快线高于慢线,产生卖出信号。
PFE指标判断:PFE高于预设上限时看空,PFE低于预设下限时看多。
仅当123形态与PFE指标产生一致信号时,才会入场。当两者不一致时,维持空仓。
123形态可识别潜在反转点。PFE判别趋势效率,避免追逐假突破。两者配合,可以提高判断准确率,达到多因子验证的效果。
策略优势
- 123形态与PFE指标互为验证,减少假信号
- PFE指标理论基础稳固,对价格效率有效判断
- 多因子驱动,提高判断准确率
- 结合反转形态与趋势指标,策略灵活
- 可自定义参数,适应市场变化
策略风险及应对
- 个别因子可能发出错误信号
- 因子设定需要不断优化和调整
- 持仓时间较短,受到频繁止损风险
应对方法:
- 增加验证因子,提高准确率
- 优化参数配置,提高 stableness
- 采用自动优化方法找到最佳参数
- 设置问候止损或移动止损
策略优化方向
该策略可以从以下几个方面进行优化:
- 增加基于Volatility的止损设置
- 采用机器学习等方法自动优化所有参数
- 在趋势较强时,降低反转交易频率
- 结合自适应指标针对市场波动性调整持仓
- 与其他策略组合,分散风险,提高整体收益率
总结
该策略融合多种因子判断价格反转点,既有理论依据,又易于实施。相比单一指标,多因子驱动提高判断准确率,是一种相对稳健的反转交易策略。通过参数优化、止损管理、组合等方法可以进一步增强策略效果。
策略源码
/*backtest
start: 2023-09-11 00:00:00
end: 2023-09-13 08:00:00
period: 1m
basePeriod: 1m
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/
//@version=4
////////////////////////////////////////////////////////////
// Copyright by HPotter v1.0 16/04/2021
// 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
// The Polarized Fractal Efficiency (PFE) indicator measures the efficiency
// of price movements by drawing on concepts from fractal geometry and chaos
// theory. The more linear and efficient the price movement, the shorter the
// distance the prices must travel between two points and thus the more efficient
// the price movement.
//
// 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
PFE(Length,LengthEMA,BuyBand,SellBand) =>
pos = 0.0
PFE = sqrt(pow(close - close[Length], 2) + 100)
C2C = sum(sqrt(pow((close - close[1]), 2) + 1), Length)
xFracEff = iff(close - close[Length] > 0, round((PFE / C2C) * 100) , round(-(PFE / C2C) * 100))
xEMA = ema(xFracEff, LengthEMA)
pos := iff(xEMA < SellBand, -1,
iff(xEMA > BuyBand, 1, nz(pos[1], 0)))
pos
strategy(title="Combo Backtest 123 Reversal & PFE (Polarized Fractal Efficiency)", shorttitle="Combo", overlay = true)
line1 = input(true, "---- 123 Reversal ----")
Length = input(14, minval=1)
KSmoothing = input(1, minval=1)
DLength = input(3, minval=1)
Level = input(50, minval=1)
//-------------------------
line2 = input(true, "---- PFE ----")
LengthPFE = input(9, minval=1)
LengthEMA = input(5, minval=1)
BuyBand = input(50, step = 0.1)
SellBand = input(-50, step = 0.1)
reverse = input(false, title="Trade reverse")
posReversal123 = Reversal123(Length, KSmoothing, DLength, Level)
posPFE = PFE(LengthPFE,LengthEMA,BuyBand,SellBand)
pos = iff(posReversal123 == 1 and posPFE == 1 , 1,
iff(posReversal123 == -1 and posPFE == -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 )