モメンタム緩和指標と123パターン戦略

DMI = RSI(DTime)

其中:
DTime = 14 / X日收盘价标准差的10日均值

/*backtest
start: 2024-01-17 00:00:00
end: 2024-01-24 00:00:00
period: 1m
basePeriod: 1m
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

//@version=4
////////////////////////////////////////////////////////////
//  Copyright by HPotter v1.0 18/03/2020
// 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
// This indicator plots Dynamic Momentum Index indicator. The Dynamic Momentum 
// Index (DMI) was developed by Tushar Chande and Stanley Kroll. The indicator 
// is covered in detail in their book The New Technical Trader.
// The DMI is identical to Welles Wilder`s Relative Strength Index except the 
// number of periods is variable rather than fixed. The variability of the time 
// periods used in the DMI is controlled by the recent volatility of prices. 
// The more volatile the prices, the more sensitive the DMI is to price changes. 
// In other words, the DMI will use more time periods during quiet markets, and 
// less during active markets. The maximum time periods the DMI can reach is 30 
// and the minimum is 3. This calculation method is similar to the Variable 
// Moving Average, also developed by Tushar Chande.
// The advantage of using a variable length time period when calculating the RSI 
// is that it overcomes the negative effects of smoothing, which often obscure short-term moves.
// The volatility index used in controlling the time periods in the DMI is based 
// on a calculation using a five period standard deviation and a ten period average 
// of the standard deviation.
//
// 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

DMI(RSILen, BuyZone,SellZone,UpLimit,LoLimit) =>
    pos = 0
    xStdDev = stdev(close, 5) 
    xSMAStdDev = sma(xStdDev, 10)
    DTime = round(14 / xSMAStdDev - 0.5)
    xDMI = iff(DTime > UpLimit, UpLimit,
             iff(DTime < LoLimit, LoLimit, DTime))
    xRSI = rsi(xDMI, RSILen)
    pos := iff(xRSI > BuyZone, 1,
             iff(xRSI < SellZone, -1, nz(pos[1], 0))) 
    pos

strategy(title="Combo Backtest 123 Reversal & Dynamic Momentum Index", shorttitle="Combo", overlay = true)
Length = input(14, minval=1)
KSmoothing = input(1, minval=1)
DLength = input(3, minval=1)
Level = input(50, minval=1)
//-------------------------
RSILen = input(14, minval=1)
BuyZone = input(30, minval=1)
SellZone = input(70, minval=1)
UpLimit = input(30, minval=1)
LoLimit = input(5, minval=1)
reverse = input(false, title="Trade reverse")
posReversal123 = Reversal123(Length, KSmoothing, DLength, Level)
posDMI = DMI(RSILen, BuyZone,SellZone,UpLimit,LoLimit)
pos = iff(posReversal123 == 1 and posDMI == 1 , 1,
	   iff(posReversal123 == -1 and posDMI == -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 )