本策略名称为“123反转与费希尔变换指标组合策略”。该策略集成应用123反转形态判定和费希尔变换指标,在两者发出共同信号时进行买入或卖出。
123反转形态指价格连续三日形成高低缺口,第三日收盘反转前两日趋势的形态。根据统计,123反转的交易获利率较高。
费希尔变换指标对价格作正态化处理,当变换曲线出现突破极值点时,可以有效识别价格反转点。
交易逻辑如下:
123反转形态显示买入信号或卖出信号。
费希尔变换曲线显示买入或卖出信号。
当两者发出同向信号时,进行相应的买入或卖出交易。
当两者发出反向信号时,保持空仓。
该策略的优势在于指标组合可以提高对价格反转时点的判断准确性。但参数优化仍然关键,需要严格的资金管理。
总体来看,指标集成应用可以形成更全面的分析角度。但交易者仍需保持足够的灵活性,根据市场情况进行策略调整。
/*backtest
start: 2023-08-13 00:00:00
end: 2023-09-12 00:00:00
period: 4h
basePeriod: 15m
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/
//@version=4
////////////////////////////////////////////////////////////
// Copyright by HPotter v1.0 28/08/2020
// 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
// Market prices do not have a Gaussian probability density function
// as many traders think. Their probability curve is not bell-shaped.
// But trader can create a nearly Gaussian PDF for prices by normalizing
// them or creating a normalized indicator such as the relative strength
// index and applying the Fisher transform. Such a transformed output
// creates the peak swings as relatively rare events.
// Fisher transform formula is: y = 0.5 * ln ((1+x)/(1-x))
// The sharp turning points of these peak swings clearly and unambiguously
// identify price reversals in a timely manner.
//
// 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
FTI(Length) =>
pos = 0
nValue1 =0.0
nFish = 0.0
xHL2 = hl2
xMaxH = highest(xHL2, Length)
xMinL = lowest(xHL2,Length)
nValue1 := 0.33 * 2 * ((xHL2 - xMinL) / (xMaxH - xMinL) - 0.5) + 0.67 * nz(nValue1[1])
nValue2 = iff(nValue1 > .99, .999,
iff(nValue1 < -.99, -.999, nValue1))
nFish := 0.5 * log((1 + nValue2) / (1 - nValue2)) + 0.5 * nz(nFish[1])
pos := iff(nFish > nz(nFish[1]), 1,
iff(nFish < nz(nFish[1]), -1, nz(pos[1], 0)))
pos
strategy(title="Combo Backtest 123 Reversal & Fisher Transform Indicator", shorttitle="Combo", overlay = true)
Length = input(15, minval=1)
KSmoothing = input(1, minval=1)
DLength = input(3, minval=1)
Level = input(50, minval=1)
//-------------------------
LengthFTI = input(10, minval=1)
reverse = input(false, title="Trade reverse")
posReversal123 = Reversal123(Length, KSmoothing, DLength, Level)
posFTI = FTI(LengthFTI)
pos = iff(posReversal123 == 1 and posFTI == 1 , 1,
iff(posReversal123 == -1 and posFTI == -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 )