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2. समतल चलती औसत रणनीति

समतल चलती औसत रणनीति

लेखक:चाओझांग, दिनांक: 2023-11-06 10:29:24
टैगः

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/*backtest
start: 2022-10-30 00:00:00
end: 2023-11-05 00:00:00
period: 1d
basePeriod: 1h
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

//@version=4
// Copyright (c) 2007-present Jurik Research and Consulting. All rights reserved.
// Copyright (c) 2018-present, Alex Orekhov (everget)
// Thanks to everget for code for more advanced moving averages
// Smooth Moving Average [STRATEGY] @PuppyTherapy script may be freely distributed under the MIT license.
strategy( title="Smooth Moving Average [STRATEGY] @PuppyTherapy", overlay=true )

// ---- CONSTANTS ----
lsmaOffset = 1
almaOffset = 0.85
almaSigma  = 6
phase = 2
power = 2

// ---- GLOBAL FUNCTIONS ----
kama(src, len)=>
    xvnoise = abs(src - src[1])
    nfastend = 0.666
    nslowend = 0.0645
    nsignal = abs(src - src[len])
    nnoise = sum(xvnoise, len)
    nefratio = iff(nnoise != 0, nsignal / nnoise, 0)
    nsmooth = pow(nefratio * (nfastend - nslowend) + nslowend, 2)
    nAMA = 0.0
    nAMA := nz(nAMA[1]) + nsmooth * (src - nz(nAMA[1]))

t3(src, len)=>
    xe1_1 = ema(src,    len)
    xe2_1 = ema(xe1_1,  len)
    xe3_1 = ema(xe2_1,  len)
    xe4_1 = ema(xe3_1,  len)
    xe5_1 = ema(xe4_1,  len)
    xe6_1 = ema(xe5_1,  len)
    b_1 = 0.7
    c1_1 = -b_1*b_1*b_1
    c2_1 = 3*b_1*b_1+3*b_1*b_1*b_1
    c3_1 = -6*b_1*b_1-3*b_1-3*b_1*b_1*b_1
    c4_1 = 1+3*b_1+b_1*b_1*b_1+3*b_1*b_1
    nT3Average_1 = c1_1 * xe6_1 + c2_1 * xe5_1 + c3_1 * xe4_1 + c4_1 * xe3_1
    
// The general form of the weights of the (2m + 1)-term Henderson Weighted Moving Average
getWeight(m, j) =>
    numerator = 315 * (pow(m + 1, 2) - pow(j, 2)) * (pow(m + 2, 2) - pow(j, 2)) * (pow(m + 3, 2) - pow(j, 2)) * (3 * pow(m + 2, 2) - 11 * pow(j, 2) - 16)
    denominator = 8 * (m + 2) * (pow(m + 2, 2) - 1) * (4 * pow(m + 2, 2) - 1) * (4 * pow(m + 2, 2) - 9) * (4 * pow(m + 2, 2) - 25)

    denominator != 0
         ? numerator / denominator
         : 0

hwma(src, termsNumber) =>
    sum = 0.0
    weightSum = 0.0
    
    termMult = (termsNumber - 1) / 2

    for i = 0 to termsNumber - 1
        weight = getWeight(termMult, i - termMult)
        sum := sum + nz(src[i]) * weight
        weightSum := weightSum + weight

    sum / weightSum

get_jurik(length, phase, power, src)=>
    phaseRatio = phase < -100 ? 0.5 : phase > 100 ? 2.5 : phase / 100 + 1.5
    beta = 0.45 * (length - 1) / (0.45 * (length - 1) + 2)
    alpha = pow(beta, power)
    jma = 0.0
    e0 = 0.0
    e0 := (1 - alpha) * src + alpha * nz(e0[1])
    e1 = 0.0
    e1 := (src - e0) * (1 - beta) + beta * nz(e1[1])
    e2 = 0.0
    e2 := (e0 + phaseRatio * e1 - nz(jma[1])) * pow(1 - alpha, 2) + pow(alpha, 2) * nz(e2[1])
    jma := e2 + nz(jma[1])

variant(src, type, len ) =>
    v1 = sma(src, len)                                                  // Simple
    v2 = ema(src, len)                                                  // Exponential
    v3 = 2 * v2 - ema(v2, len)                                          // Double Exponential
    v4 = 3 * (v2 - ema(v2, len)) + ema(ema(v2, len), len)               // Triple Exponential
    v5 = wma(src, len)                                                  // Weighted
    v6 = vwma(src, len)                                                 // Volume Weighted
    v7 = na(v5[1]) ? sma(src, len) : (v5[1] * (len - 1) + src) / len    // Smoothed
    v8 = wma(2 * wma(src, len / 2) - wma(src, len), round(sqrt(len)))   // Hull
    v9 = linreg(src, len, lsmaOffset)                                   // Least Squares
    v10 = alma(src, len, almaOffset, almaSigma)                         // Arnaud Legoux
    v11 = kama(src, len)                                                // KAMA
    ema1 = ema(src, len)
    ema2 = ema(ema1, len)
    v13 = t3(src, len)                                                  // T3
    v14 = ema1+(ema1-ema2)                                              // Zero Lag Exponential
    v15 = hwma(src, len)                                                // Henderson Moving average thanks to  @everget
    ahma = 0.0
    ahma := nz(ahma[1]) + (src - (nz(ahma[1]) + nz(ahma[len])) / 2) / len //Ahrens Moving Average 
    v16 = ahma
    v17 = get_jurik( len, phase, power, src) 
    type=="EMA"?v2 : type=="DEMA"?v3 : type=="TEMA"?v4 : type=="WMA"?v5 : type=="VWMA"?v6 :
     type=="SMMA"?v7 : type=="Hull"?v8 : type=="LSMA"?v9 : type=="ALMA"?v10 : type=="KAMA"?v11 :
     type=="T3"?v13 : type=="ZEMA"?v14 : type=="HWMA"?v15 : type=="AHMA"?v16 : type=="JURIK"?v17 : v1

smoothMA(c, maLoop, type, len) =>
	ma_c = 0.0
	if maLoop == 1
		ma_c := variant(c, type, len)
	if maLoop == 2
		ma_c := variant(variant(c ,type, len),type, len)
	if maLoop == 3
		ma_c := variant(variant(variant(c ,type, len),type, len),type, len)
	if maLoop == 4
		ma_c := variant(variant(variant(variant(c ,type, len),type, len),type, len),type, len)
	if maLoop == 5
		ma_c := variant(variant(variant(variant(variant(c ,type, len),type, len),type, len),type, len),type, len)
	ma_c

// Smoothing HA Function
smoothHA( o, h, l, c ) =>
    hao = 0.0
    hac = ( o + h + l + c ) / 4
    hao := na(hao[1])?(o + c / 2 ):(hao[1] + hac[1])/2
    hah = max(h, max(hao, hac))
    hal = min(l, min(hao, hac))
	[hao, hah, hal, hac]

// ---- Main Selection ----
haSmooth   = input(false, title=" Use HA as source ? " )
length     = input(60, title=" MA1 Length", minval=1, maxval=1000)
maLoop     = input(2, title=" Nr. of MA1 Smoothings ", minval=1, maxval=5)
type       = input("EMA", title="MA Type", options=["SMA", "EMA", "DEMA", "TEMA", "WMA", "VWMA", "SMMA", "Hull", "LSMA", "ALMA", "KAMA", "ZEMA", "HWMA", "AHMA", "JURIK", "T3"])

// ---- BODY SCRIPT ----
[ ha_open, ha_high, ha_low, ha_close ] = smoothHA(open, high, low, close)

_close_ma = haSmooth ? ha_close : close

_close_smoothed_ma = smoothMA( _close_ma, maLoop, type, length)

maColor = _close_smoothed_ma > _close_smoothed_ma[1] ? color.lime : color.red
plot(_close_smoothed_ma, title= "MA - Trend",  color=maColor, transp=85, linewidth = 4)

long     = _close_smoothed_ma > _close_smoothed_ma[1] and _close_smoothed_ma[1] < _close_smoothed_ma[2]
short    = _close_smoothed_ma < _close_smoothed_ma[1] and _close_smoothed_ma[1] > _close_smoothed_ma[2]

plotshape( short , title="Short", color=color.red,  transp=80, style=shape.triangledown, location=location.abovebar, size=size.small)
plotshape( long ,  title="Long",  color=color.lime, transp=80, style=shape.triangleup,   location=location.belowbar, size=size.small)

//* Backtesting Period Selector | Component *//
//* Source: https://www.tradingview.com/script/eCC1cvxQ-Backtesting-Period-Selector-Component *//
testStartYear   = input(2018, "Backtest Start Year",minval=1980)
testStartMonth  = input(1, "Backtest Start Month",minval=1,maxval=12)
testStartDay    = input(1, "Backtest Start Day",minval=1,maxval=31)
testPeriodStart = timestamp(testStartYear,testStartMonth,testStartDay,0,0)
testStopYear    = 9999 //input(9999, "Backtest Stop Year",minval=1980)
testStopMonth   = 12 // input(12, "Backtest Stop Month",minval=1,maxval=12)
testStopDay     = 31 //input(31, "Backtest Stop Day",minval=1,maxval=31)
testPeriodStop  = timestamp(testStopYear,testStopMonth,testStopDay,0,0)
testPeriod() => time >= testPeriodStart and time <= testPeriodStop ? true : false

if testPeriod() and long
    strategy.entry( "long", strategy.long )

if testPeriod() and short
    strategy.entry( "short", strategy.short )

---

• सोमवार इन्वर्सन इंट्राडे ट्रेंड रणनीति का पालन करना
• एडीएक्स फ़िल्टर्ड चंदे क्रॉल स्टॉप लॉस ट्रेंड फॉलोिंग स्ट्रैटेजी
• चलती औसत रणनीति के साथ प्रवृत्ति विचलन सूचकांक
• गतिशीलता अभिन्न संकेतक रणनीति
• एमएसीडी मूविंग एवरेज क्रॉसओवर ट्रेंड ट्रेलिंग स्टॉप लॉस के साथ रणनीति का पालन करना
• दोतरफा ट्रेंड कैप्चरिंग फ्यूजन रणनीति
• मूल्य ब्रेकथ्रू बोलिंगर बैंड ए रणनीति
• आरओसी ट्रेडिंग रणनीति पर आधारित आरएसआई
• कल की उच्च ब्रेकआउट रणनीति
• रणनीति का अनुसरण करने वाली प्रवृत्ति
• दोहरी चलती औसत क्रॉसओवर ट्रेंड ट्रेडिंग रणनीति
• कनेक्टिकट कछुआ प्रणाली
• रणनीति का अनुसरण करने वाली प्रवृत्ति
• दोहरी लेजर ट्रेंड-खोज रणनीति
• ईएमए ऑसिलेटर ट्रेंड फॉलोिंग स्ट्रैटेजी
• त्रिगुट चलती औसत क्रॉसओवर रणनीति
• गति ब्रेकआउट पर आधारित प्रवृत्ति ट्रैकिंग रणनीति
• यादृच्छिक अस्थिरता रणनीति
• सुपर इम्पोटम रणनीति
• आकार ब्लॉक रणनीति