ChaoZhang
Overview
This strategy combines multiple technical indicators such as RSI, MACD, OBV, CCI, CMF, MFI and VWMACD to detect divergences between price and volume to identify potential entry opportunities. The strategy also incorporates user dip detection indicators to generate trading signals when high volatility and depth or VFI conditions are met. The strategy only goes long and uses tracking stop loss to gradually accumulate positions.
Strategy Logic
Calculate indicators like RSI, MACD, OBV, CCI, CMF, MFI and VWMACD, and detect divergences between the indicators and historical prices using an adaptive linear regression method. Generate buy signals when an indicator makes a new low while the price does not.
Based on user input volatility threshold and depth percentage threshold, combined with VFI indicator filtering, generate signals on candlesticks that meet high volatility and depth tests.
After initial long entry, if the price breaks the last long entry price by a configured percentage, add another long position.
Use tracking stop loss to close positions when reaching configured take profit ratio.
Advantage Analysis
Multi-factor combination makes comprehensive use of price and volume indicators to improve signal reliability.
Adaptive linear regression method detects divergences and avoids subjectivity of manual judgment.
Incorporating volatility, depth/VFI indicators helps discover reversal opportunities.
Multi-entry accumulation allows full use of pullbacks, and tracking stop profit helps lock in profits.
Risk Analysis
Complex multi-factor judgment may affect actual performance depending on parameter optimization and divergence detection effectiveness.
Unidirectional holding has higher risk, large losses may occur if judgment is wrong.
Loss may be amplified in repeated adding model, position size needs to be carefully controlled.
Pay attention to impact of trading fees on actual profit.
Optimization Directions
Test combinations of different parameters and indicators to select optimal configuration.
Add stop loss strategies to control per trade and maximum losses.
Consider opportunities in both directions to diversify risks.
Incorporate machine learning methods to automatically optimize parameters.
Summary
This strategy identifies entry timing through a combination of technical indicators, and uses user defined conditions and VFI filtering to eliminate false signals. It takes advantage of pullbacks to accumulate positions chasing the trend, which helps capture opportunities in trends. But it also faces risks of wrong judgment and unidirectional holding. Appropriate optimization on indicator parameters, stop loss strategies etc. is needed to reduce risks and expand profit space.
/*backtest
start: 2023-02-13 00:00:00
end: 2024-02-19 00:00:00
period: 1d
basePeriod: 1h
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/
// This Pine Script™ code is subject to the terms of the Mozilla Public License 2.0 at https://mozilla.org/MPL/2.0/
// © mkose81
//@version=5
strategy("RSI ve MACD Uyumsuzluğu Stratejisi (Sadece Long)", overlay=true, max_bars_back=4000,use_bar_magnifier= true,pyramiding=40)
// RSI Hesaplama
rsi = ta.rsi(close, 14)
float botRSI = na
botRSI := ta.pivotlow(5, 5)
botcRSI = 0
botcRSI := botRSI ? 5 : nz(botcRSI[1]) + 1
newbotRSI = ta.pivotlow(5, 0)
emptylRSI = true
if not na(newbotRSI) and newbotRSI < low[botcRSI]
diffRSI = (newbotRSI - low[botcRSI]) / botcRSI
llineRSI = newbotRSI - diffRSI
for x = 1 to botcRSI - 1 by 1
if close[x] < llineRSI
emptylRSI := false
break
llineRSI -= diffRSI
emptylRSI
// Pozitif Uyumsuzluk Alım Sinyali - RSI
alRSI = 0
if emptylRSI and not na(newbotRSI)
if rsi[botcRSI] < rsi
alRSI := 1
// MACD Hesaplama
[macd, signal, _] = ta.macd(close, 21, 55, 8)
float botMACD = na
botMACD := ta.pivotlow(5, 5)
botcMACD = 0
botcMACD := botMACD ? 5 : nz(botcMACD[1]) + 1
newbotMACD = ta.pivotlow(5, 0)
emptylMACD = true
if not na(newbotMACD) and newbotMACD < low[botcMACD]
diffMACD = (newbotMACD - low[botcMACD]) / botcMACD
llineMACD = newbotMACD - diffMACD
for x = 1 to botcMACD - 1 by 1
if close[x] < llineMACD
emptylMACD := false
break
llineMACD -= diffMACD
emptylMACD
// Pozitif Uyumsuzluk Alım Sinyali - MACD
alMACD = 0
if emptylMACD and not na(newbotMACD)
if macd[botcMACD] < macd
alMACD := 1
// OBV Hesaplama ve Uyumsuzluk Tespiti
obv = ta.cum(ta.change(close) > 0 ? volume : ta.change(close) < 0 ? -volume : 0)
float botOBV = na
botOBV := ta.pivotlow(5, 5)
botcOBV = 0
botcOBV := botOBV ? 5 : nz(botcOBV[1]) + 1
newbotOBV = ta.pivotlow(5, 0)
emptylOBV = true
if not na(newbotOBV) and newbotOBV < obv[botcOBV]
diffOBV = (newbotOBV - obv[botcOBV]) / botcOBV
llineOBV = newbotOBV - diffOBV
for x = 1 to botcOBV - 1 by 1
if obv[x] < llineOBV
emptylOBV := false
break
llineOBV -= diffOBV
emptylOBV
// Pozitif Uyumsuzluk Alım Sinyali - OBV
alOBV = 0
if emptylOBV and not na(newbotOBV)
if obv[botcOBV] < obv
alOBV := 1
// CCI Hesaplama ve Uyumsuzluk Tespiti
cci = ta.cci(close, 20)
float botCCI = na
botCCI := ta.pivotlow(5, 5)
botcCCI = 0
botcCCI := botCCI ? 5 : nz(botcCCI[1]) + 1
newbotCCI = ta.pivotlow(5, 0)
emptylCCI = true
if not na(newbotCCI) and newbotCCI < cci[botcCCI]
diffCCI = (newbotCCI - cci[botcCCI]) / botcCCI
llineCCI = newbotCCI - diffCCI
for x = 1 to botcCCI - 1 by 1
if cci[x] < llineCCI
emptylCCI := false
break
llineCCI -= diffCCI
emptylCCI
// Pozitif Uyumsuzluk Alım Sinyali - CCI
alCCI = 0
if emptylCCI and not na(newbotCCI)
if cci[botcCCI] < cci
alCCI := 1
// CMF Hesaplama
length = 20
mfm = ((close - low) - (high - close)) / (high - low)
mfv = mfm * volume
cmf = ta.sma(mfv, length) / ta.sma(volume, length)
float botCMF = na
botCMF := ta.pivotlow(5, 5)
botcCMF = 0
botcCMF := botCMF ? 5 : nz(botcCMF[1]) + 1
newbotCMF = ta.pivotlow(5, 0)
emptylCMF = true
if not na(newbotCMF) and newbotCMF < cmf[botcCMF]
diffCMF = (newbotCMF - cmf[botcCMF]) / botcCMF
llineCMF = newbotCMF - diffCMF
for x = 1 to botcCMF - 1 by 1
if cmf[x] < llineCMF
emptylCMF := false
break
llineCMF -= diffCMF
emptylCMF
// Pozitif Uyumsuzluk Alım Sinyali - CMF
alCMF = 0
if emptylCMF and not na(newbotCMF)
if cmf[botcCMF] < cmf
alCMF := 1
// MFI Hesaplama
lengthMFI = 14
mfi = ta.mfi(close, lengthMFI)
float botMFI = na
botMFI := ta.pivotlow(mfi, 5, 5)
botcMFI = 0
botcMFI := botMFI ? 5 : nz(botcMFI[1]) + 1
newbotMFI = ta.pivotlow(mfi, 5, 0)
emptylMFI = true
if not na(newbotMFI) and newbotMFI < mfi[botcMFI]
diffMFI = (newbotMFI - mfi[botcMFI]) / botcMFI
llineMFI = newbotMFI - diffMFI
for x = 1 to botcMFI - 1 by 1
if mfi[x] < llineMFI
emptylMFI := false
break
llineMFI -= diffMFI
emptylMFI
// Pozitif Uyumsuzluk Alım Sinyali - MFI
alMFI = 0
if emptylMFI and not na(newbotMFI)
if mfi[botcMFI] < mfi
alMFI := 1
// VWMACD Hesaplama
fastLength = 12
slowLength = 26
signalSmoothing = 9
vwmacd = ta.ema(close, fastLength) - ta.ema(close, slowLength)
signalLine = ta.ema(vwmacd, signalSmoothing)
histogram = vwmacd - signalLine
// VWMACD Uyumsuzluk Tespiti
float botVWMACD = na
botVWMACD := ta.pivotlow(histogram, 5, 5)
botcVWMACD = 0
botcVWMACD := botVWMACD ? 5 : nz(botcVWMACD[1]) + 1
newbotVWMACD = ta.pivotlow(histogram, 5, 0)
emptylVWMACD = true
if not na(newbotVWMACD) and newbotVWMACD < histogram[botcVWMACD]
diffVWMACD = (newbotVWMACD - histogram[botcVWMACD]) / botcVWMACD
llineVWMACD = newbotVWMACD - diffVWMACD
for x = 1 to botcVWMACD - 1 by 1
if histogram[x] < llineVWMACD
emptylVWMACD := false
break
llineVWMACD -= diffVWMACD
emptylVWMACD
// Pozitif Uyumsuzluk Alım Sinyali - VWMACD
alVWMACD = 0
if emptylVWMACD and not na(newbotVWMACD)
if histogram[botcVWMACD] < histogram
alVWMACD := 1
//Dipci indikator
lengthd= 130
coef = 0.2
vcoef = 2.5
signalLength = 5
smoothVFI = false
ma(x, y) =>
smoothVFI ? ta.sma(x, y) : x
typical = hlc3
inter = math.log(typical) - math.log(typical[1])
vinter = ta.stdev(inter, 30)
cutoff = coef * vinter * close
vave = ta.sma(volume, lengthd)[1]
vmax = vave * vcoef
vc = volume < vmax ? volume : vmax //min( volume, vmax )
mf = typical - typical[1]
iff_4 = mf < -cutoff ? -vc : 0
vcp = mf > cutoff ? vc : iff_4
vfi = ma(math.sum(vcp, lengthd) / vave, 3)
vfima = ta.ema(vfi, signalLength)
d = vfi - vfima
// Kullanıcı girdileri
volatilityThreshold = input.float(1.005, title="Volume Percentage Threshold")
pinThreshold = input.float(1.005, title="Deep Percentage Threshold")
// Hesaplamalar
volatilityPercentage = (high - low) / open
pinPercentage = close > open ? (high - close) / open : (close - low) / open
// Volatilite koşulu ve VFI ile filtreleme
voldip = volatilityPercentage >= volatilityThreshold or pinPercentage >= pinThreshold
volCondition = voldip and vfi< 0 // VFI değeri 0'dan küçükse volCondition aktif olacak
threeCommasEntryComment = input.string(title="3Commas Entry Comment", defval="")
threeCommasExitComment = input.string(title="3Commas Exit Comment", defval="")
takeProfitPerc = input.float(1, title="Take Profit Percentage (%)") / 100
fallPerc = input.float(5, title="Percentage for Additional Buy (%)") / 100
// Değişkenlerin tanımlanması
var float lastBuyPrice = na
var float tpPrice = na
var int lastTpBar = na
// Alım koşulları
longCondition = alRSI or alMACD or alOBV or alCCI or alCMF or alMFI or alVWMACD or volCondition
// Son alım fiyatını saklamak için değişken
// İlk alım stratejisi
if (longCondition and strategy.position_size == 0)
strategy.entry("Long", strategy.long,comment=threeCommasEntryComment)
lastBuyPrice := open
// İkinci ve sonraki alım koşulları (son alım fiyatının belirlenen yüzde altında)
if (open < lastBuyPrice * (1 - fallPerc) and strategy.position_size > 0)
strategy.entry("Long Add", strategy.long,comment=threeCommasEntryComment)
lastBuyPrice := open
// Kar alma fiyatını hesaplama ve strateji çıkışı
tp_price = strategy.position_avg_price * (1 + takeProfitPerc)
if strategy.position_size > 0
strategy.exit("Exit Long", "Long", limit=tp_price,comment=threeCommasExitComment)
strategy.exit("Exit Long Add", "Long Add", limit=tp_price,comment=threeCommasExitComment)
tpPrice := na // Pozisyon kapandığında TP çizgisini sıfırla
// Kar alma seviyesi çizgisi çizme
plot(strategy.position_size > 0 ? tp_price : na, color=color.green, title="Take Profit Line")