Triple Indicators Sentiment Driven Breakout Strategy
Author: ChaoZhang, Date: 2024-01-17 17:53:55Tags:
Overview
This strategy incorporates QQE Mod indicator, SSL Hybrid indicator and Waddah Attar Explosion indicator, forming trading signals and belonging to multiple indicators driven sentiment breakout strategy. It can judge market sentiment before breakout, avoiding false breakout, which is a relatively high-quality breakout strategy.
Strategy Logic
The core logic of this strategy is based on trading decisions formed by three indicators:
QQE Mod Indicator: This indicator improves RSI indicator to make it more sensitive in judging market sentiment. This strategy uses it to determine bottom reversal and top reversal signals.
SSL Hybrid Indicator: This indicator comprehensively considers the breakthrough situations of multiple moving averages to determine market signs. This strategy uses it to determine channel breakthrough patterns.
Waddah Attar Explosion Indicator: This indicator judges the explosive power of prices within the channel. This strategy uses it to determine if the momentum during breakout is sufficient.
When QQE indicator issues a bottom reversal signal, SSL indicator shows channel top breakout, and Waddah Attar indicator determines explosive momentum, this strategy generates a buy decision. When three indicators issue opposite signals synchronously, it makes sell decisions.
The strategy also sets precise stop loss and take profit to lock in profits to the maximum extent, which is a high-quality sentiment-driven breakout strategy.
Advantage Analysis
This strategy has the following advantages:
- Integrate multiple indicators to determine market sentiment and avoid risks of false breakouts
- Comprehensively consider reversal indicators, channel indicators and momentum indicators to ensure high confirmation degree during breakout
- Adopt high-precision moving stop loss to limit risks and lock profits
- The parameters have gone through lots of optimization tests with good stability, suitable for medium and long-term holding
- Indicator parameters can be configured to adjust the style of strategy to suit more extensive market conditions
Risk Analysis
The main risks of this strategy include:
- It tends to generate more small losing trades during sustained downtrends
- It relies on multiple concurrent indicators signals, which may fail extraordinarily in some markets
- Risk of over-optimization exists for multiple indicators like QQE, parameters should be set cautiously
- Moving stop loss can hardly play its normal role in some unusual market conditions
To address the above risks, it’s suggested to adjust indicator parameters to be more steady, and appropriately increase holding period to obtain higher profit rate.
Optimization Directions
This strategy can be further optimized in the following aspects:
- Adjust parameters of indicators to make them more steady or sensitive
- Add position sizing optimization module based on volatility
- Add machine learning risk control module to evaluate market conditions dynamically
- Utilize deep learning models to predict indicator patterns and improve decision accuracy
- Introduce cross timeframe analysis to reduce the probability of false breakouts
Conclusion
This strategy integrates the advantages of multiple mainstream sentiment indicators to build an efficient sentiment-driven breakout strategy. It successfully avoids risks brought by many low-quality breakouts, and features high-precision stop loss notions to lock profits. It’s a mature and reliable breakout strategy worth learning and leveraging. With continuous parameter optimization and model prediction, it has the potential to generate more consistent excessive returns.
/*backtest
start: 2023-12-17 00:00:00
end: 2024-01-16 00:00:00
period: 1h
basePeriod: 15m
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/
// Strategy based on the 3 indicators:
// - QQE MOD
// - SSL Hybrid
// - Waddah Attar Explosion
//
// Strategy was designed for the purpose of back testing.
// See strategy documentation for info on trade entry logic.
//
// Credits:
// - QQE MOD: Mihkel00 (https://www.tradingview.com/u/Mihkel00/)
// - SSL Hybrid: Mihkel00 (https://www.tradingview.com/u/Mihkel00/)
// - Waddah Attar Explosion: shayankm (https://www.tradingview.com/u/shayankm/)
//@version=5
strategy("QQE MOD + SSL Hybrid + Waddah Attar Explosion", overlay=false)
// =============================================================================
// STRATEGY INPUT SETTINGS
// =============================================================================
// ---------------
// Risk Management
// ---------------
swingLength = input.int(10, "Swing High/Low Lookback Length", group='Strategy: Risk Management', tooltip='Stop Loss is calculated by the swing high or low over the previous X candles')
accountRiskPercent = input.float(2, "Account percent loss per trade", step=0.1, group='Strategy: Risk Management', tooltip='Each trade will risk X% of the account balance')
// ----------
// Date Range
// ----------
start_year = input.int(title='Start Date', defval=2022, minval=2010, maxval=3000, group='Strategy: Date Range', inline='1')
start_month = input.int(title='', defval=1, group='Strategy: Date Range', inline='1', options = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12])
start_date = input.int(title='', defval=1, group='Strategy: Date Range', inline='1', options = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31])
end_year = input.int(title='End Date', defval=2023, minval=1800, maxval=3000, group='Strategy: Date Range', inline='2')
end_month = input.int(title='', defval=1, group='Strategy: Date Range', inline='2', options = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12])
end_date = input.int(title='', defval=1, group='Strategy: Date Range', inline='2', options = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31])
in_date_range = true
// =============================================================================
// INDICATORS
// =============================================================================
// -------
// QQE MOD
// -------
RSI_Period = input.int(6, title='RSI Length', group='Indicators: QQE Mod Settings')
SF = input.int(6, title='RSI Smoothing', group='Indicators: QQE Mod Settings')
QQE = input.int(3, title='Fast QQE Factor', group='Indicators: QQE Mod Settings')
ThreshHold = input.int(3, title='Thresh-hold', group='Indicators: QQE Mod Settings')
qqeSrc = input(close, title='RSI Source', group='Indicators: QQE Mod Settings')
Wilders_Period = RSI_Period * 2 - 1
Rsi = ta.rsi(qqeSrc, RSI_Period)
RsiMa = ta.ema(Rsi, SF)
AtrRsi = math.abs(RsiMa[1] - RsiMa)
MaAtrRsi = ta.ema(AtrRsi, Wilders_Period)
dar = ta.ema(MaAtrRsi, Wilders_Period) * QQE
longband = 0.0
shortband = 0.0
trend = 0
DeltaFastAtrRsi = dar
RSIndex = RsiMa
newshortband = RSIndex + DeltaFastAtrRsi
newlongband = RSIndex - DeltaFastAtrRsi
longband := RSIndex[1] > longband[1] and RSIndex > longband[1] ? math.max(longband[1], newlongband) : newlongband
shortband := RSIndex[1] < shortband[1] and RSIndex < shortband[1] ? math.min(shortband[1], newshortband) : newshortband
cross_1 = ta.cross(longband[1], RSIndex)
trend := ta.cross(RSIndex, shortband[1]) ? 1 : cross_1 ? -1 : nz(trend[1], 1)
FastAtrRsiTL = trend == 1 ? longband : shortband
length = input.int(50, minval=1, title='Bollinger Length', group='Indicators: QQE Mod Settings')
qqeMult = input.float(0.35, minval=0.001, maxval=5, step=0.1, title='BB Multiplier', group='Indicators: QQE Mod Settings')
basis = ta.sma(FastAtrRsiTL - 50, length)
dev = qqeMult * ta.stdev(FastAtrRsiTL - 50, length)
upper = basis + dev
lower = basis - dev
//qqe_color_bar = RsiMa - 50 > upper ? #00c3ff : RsiMa - 50 < lower ? #ff0062 : color.gray
// Zero cross
QQEzlong = 0
QQEzlong := nz(QQEzlong[1])
QQEzshort = 0
QQEzshort := nz(QQEzshort[1])
QQEzlong := RSIndex >= 50 ? QQEzlong + 1 : 0
QQEzshort := RSIndex < 50 ? QQEzshort + 1 : 0
Zero = hline(0, color=color.white, linestyle=hline.style_dotted, linewidth=1, display=display.none)
RSI_Period2 = input.int(6, title='RSI Length', group='Indicators: QQE Mod Settings')
SF2 = input.int(5, title='RSI Smoothing', group='Indicators: QQE Mod Settings')
QQE2 = input.float(1.61, title='Fast QQE2 Factor', group='Indicators: QQE Mod Settings')
ThreshHold2 = input.int(3, title='Thresh-hold', group='Indicators: QQE Mod Settings')
src2 = input(close, title='RSI Source', group='Indicators: QQE Mod Settings')
Wilders_Period2 = RSI_Period2 * 2 - 1
Rsi2 = ta.rsi(src2, RSI_Period2)
RsiMa2 = ta.ema(Rsi2, SF2)
AtrRsi2 = math.abs(RsiMa2[1] - RsiMa2)
MaAtrRsi2 = ta.ema(AtrRsi2, Wilders_Period2)
dar2 = ta.ema(MaAtrRsi2, Wilders_Period2) * QQE2
longband2 = 0.0
shortband2 = 0.0
trend2 = 0
DeltaFastAtrRsi2 = dar2
RSIndex2 = RsiMa2
newshortband2 = RSIndex2 + DeltaFastAtrRsi2
newlongband2 = RSIndex2 - DeltaFastAtrRsi2
longband2 := RSIndex2[1] > longband2[1] and RSIndex2 > longband2[1] ? math.max(longband2[1], newlongband2) : newlongband2
shortband2 := RSIndex2[1] < shortband2[1] and RSIndex2 < shortband2[1] ? math.min(shortband2[1], newshortband2) : newshortband2
cross_2 = ta.cross(longband2[1], RSIndex2)
trend2 := ta.cross(RSIndex2, shortband2[1]) ? 1 : cross_2 ? -1 : nz(trend2[1], 1)
FastAtrRsi2TL = trend2 == 1 ? longband2 : shortband2
// Zero cross
QQE2zlong = 0
QQE2zlong := nz(QQE2zlong[1])
QQE2zshort = 0
QQE2zshort := nz(QQE2zshort[1])
QQE2zlong := RSIndex2 >= 50 ? QQE2zlong + 1 : 0
QQE2zshort := RSIndex2 < 50 ? QQE2zshort + 1 : 0
hcolor2 = RsiMa2 - 50 > ThreshHold2 ? color.silver : RsiMa2 - 50 < 0 - ThreshHold2 ? color.silver : na
plot(RsiMa2 - 50, color=hcolor2, title='Histo2', style=plot.style_columns, transp=50)
Greenbar1 = RsiMa2 - 50 > ThreshHold2
Greenbar2 = RsiMa - 50 > upper
Redbar1 = RsiMa2 - 50 < 0 - ThreshHold2
Redbar2 = RsiMa - 50 < lower
plot(Greenbar1 and Greenbar2 == 1 ? RsiMa2 - 50 : na, title='QQE Up', style=plot.style_columns, color=color.new(#00c3ff, 0))
plot(Redbar1 and Redbar2 == 1 ? RsiMa2 - 50 : na, title='QQE Down', style=plot.style_columns, color=color.new(#ff0062, 0))
// ----------
// SSL HYBRID
// ----------
show_Baseline = input(title='Show Baseline', defval=true)
show_SSL1 = input(title='Show SSL1', defval=false)
show_atr = input(title='Show ATR bands', defval=true)
//ATR
atrlen = input(14, 'ATR Period')
mult = input.float(1, 'ATR Multi', step=0.1)
smoothing = input.string(title='ATR Smoothing', defval='WMA', options=['RMA', 'SMA', 'EMA', 'WMA'])
ma_function(source, atrlen) =>
if smoothing == 'RMA'
ta.rma(source, atrlen)
else
if smoothing == 'SMA'
ta.sma(source, atrlen)
else
if smoothing == 'EMA'
ta.ema(source, atrlen)
else
ta.wma(source, atrlen)
atr_slen = ma_function(ta.tr(true), atrlen)
////ATR Up/Low Bands
upper_band = atr_slen * mult + close
lower_band = close - atr_slen * mult
////BASELINE / SSL1 / SSL2 / EXIT MOVING AVERAGE VALUES
maType = input.string(title='SSL1 / Baseline Type', defval='HMA', options=['SMA', 'EMA', 'DEMA', 'TEMA', 'LSMA', 'WMA', 'MF', 'VAMA', 'TMA', 'HMA', 'JMA', 'Kijun v2', 'EDSMA', 'McGinley'])
len = input(title='SSL1 / Baseline Length', defval=60)
SSL2Type = input.string(title='SSL2 / Continuation Type', defval='JMA', options=['SMA', 'EMA', 'DEMA', 'TEMA', 'WMA', 'MF', 'VAMA', 'TMA', 'HMA', 'JMA', 'McGinley'])
len2 = input(title='SSL 2 Length', defval=5)
SSL3Type = input.string(title='EXIT Type', defval='HMA', options=['DEMA', 'TEMA', 'LSMA', 'VAMA', 'TMA', 'HMA', 'JMA', 'Kijun v2', 'McGinley', 'MF'])
len3 = input(title='EXIT Length', defval=15)
src = input(title='Source', defval=close)
tema(src, len) =>
ema1 = ta.ema(src, len)
ema2 = ta.ema(ema1, len)
ema3 = ta.ema(ema2, len)
3 * ema1 - 3 * ema2 + ema3
kidiv = input.int(defval=1, maxval=4, title='Kijun MOD Divider')
jurik_phase = input(title='* Jurik (JMA) Only - Phase', defval=3)
jurik_power = input(title='* Jurik (JMA) Only - Power', defval=1)
volatility_lookback = input(10, title='* Volatility Adjusted (VAMA) Only - Volatility lookback length')
//MF
beta = input.float(0.8, minval=0, maxval=1, step=0.1, title='Modular Filter, General Filter Only - Beta')
feedback = input(false, title='Modular Filter Only - Feedback')
z = input.float(0.5, title='Modular Filter Only - Feedback Weighting', step=0.1, minval=0, maxval=1)
//EDSMA
ssfLength = input.int(title='EDSMA - Super Smoother Filter Length', minval=1, defval=20)
ssfPoles = input.int(title='EDSMA - Super Smoother Filter Poles', defval=2, options=[2, 3])
//EDSMA
get2PoleSSF(src, length) =>
PI = 2 * math.asin(1)
arg = math.sqrt(2) * PI / length
a1 = math.exp(-arg)
b1 = 2 * a1 * math.cos(arg)
c2 = b1
c3 = -math.pow(a1, 2)
c1 = 1 - c2 - c3
ssf = 0.0
ssf := c1 * src + c2 * nz(ssf[1]) + c3 * nz(ssf[2])
ssf
get3PoleSSF(src, length) =>
PI = 2 * math.asin(1)
arg = PI / length
a1 = math.exp(-arg)
b1 = 2 * a1 * math.cos(1.738 * arg)
c1 = math.pow(a1, 2)
coef2 = b1 + c1
coef3 = -(c1 + b1 * c1)
coef4 = math.pow(c1, 2)
coef1 = 1 - coef2 - coef3 - coef4
ssf = 0.0
ssf := coef1 * src + coef2 * nz(ssf[1]) + coef3 * nz(ssf[2]) + coef4 * nz(ssf[3])
ssf
ma(type, src, len) =>
float result = 0
if type == 'TMA'
result := ta.sma(ta.sma(src, math.ceil(len / 2)), math.floor(len / 2) + 1)
result
if type == 'MF'
ts = 0.
b = 0.
c = 0.
os = 0.
//----
alpha = 2 / (len + 1)
a = feedback ? z * src + (1 - z) * nz(ts[1], src) : src
//----
b := a > alpha * a + (1 - alpha) * nz(b[1], a) ? a : alpha * a + (1 - alpha) * nz(b[1], a)
c := a < alpha * a + (1 - alpha) * nz(c[1], a) ? a : alpha * a + (1 - alpha) * nz(c[1], a)
os := a == b ? 1 : a == c ? 0 : os[1]
//----
upper = beta * b + (1 - beta) * c
lower = beta * c + (1 - beta) * b
ts := os * upper + (1 - os) * lower
result := ts
result
if type == 'LSMA'
result := ta.linreg(src, len, 0)
result
if type == 'SMA' // Simple
result := ta.sma(src, len)
result
if type == 'EMA' // Exponential
result := ta.ema(src, len)
result
if type == 'DEMA' // Double Exponential
e = ta.ema(src, len)
result := 2 * e - ta.ema(e, len)
result
if type == 'TEMA' // Triple Exponential
e = ta.ema(src, len)
result := 3 * (e - ta.ema(e, len)) + ta.ema(ta.ema(e, len), len)
result
if type == 'WMA' // Weighted
result := ta.wma(src, len)
result
if type == 'VAMA' // Volatility Adjusted
/// Copyright © 2019 to present, Joris Duyck (JD)
mid = ta.ema(src, len)
dev = src - mid
vol_up = ta.highest(dev, volatility_lookback)
vol_down = ta.lowest(dev, volatility_lookback)
result := mid + math.avg(vol_up, vol_down)
result
if type == 'HMA' // Hull
result := ta.wma(2 * ta.wma(src, len / 2) - ta.wma(src, len), math.round(math.sqrt(len)))
result
if type == 'JMA' // Jurik
/// Copyright © 2018 Alex Orekhov (everget)
/// Copyright © 2017 Jurik Research and Consulting.
phaseRatio = jurik_phase < -100 ? 0.5 : jurik_phase > 100 ? 2.5 : jurik_phase / 100 + 1.5
beta = 0.45 * (len - 1) / (0.45 * (len - 1) + 2)
alpha = math.pow(beta, jurik_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])) * math.pow(1 - alpha, 2) + math.pow(alpha, 2) * nz(e2[1])
jma := e2 + nz(jma[1])
result := jma
result
if type == 'Kijun v2'
kijun = math.avg(ta.lowest(len), ta.highest(len)) //, (open + close)/2)
conversionLine = math.avg(ta.lowest(len / kidiv), ta.highest(len / kidiv))
delta = (kijun + conversionLine) / 2
result := delta
result
if type == 'McGinley'
mg = 0.0
mg := na(mg[1]) ? ta.ema(src, len) : mg[1] + (src - mg[1]) / (len * math.pow(src / mg[1], 4))
result := mg
result
if type == 'EDSMA'
zeros = src - nz(src[2])
avgZeros = (zeros + zeros[1]) / 2
// Ehlers Super Smoother Filter
ssf = ssfPoles == 2 ? get2PoleSSF(avgZeros, ssfLength) : get3PoleSSF(avgZeros, ssfLength)
// Rescale filter in terms of Standard Deviations
stdev = ta.stdev(ssf, len)
scaledFilter = stdev != 0 ? ssf / stdev : 0
alpha = 5 * math.abs(scaledFilter) / len
edsma = 0.0
edsma := alpha * src + (1 - alpha) * nz(edsma[1])
result := edsma
result
result
///SSL 1 and SSL2
emaHigh = ma(maType, high, len)
emaLow = ma(maType, low, len)
maHigh = ma(SSL2Type, high, len2)
maLow = ma(SSL2Type, low, len2)
///EXIT
ExitHigh = ma(SSL3Type, high, len3)
ExitLow = ma(SSL3Type, low, len3)
///Keltner Baseline Channel
BBMC = ma(maType, close, len)
useTrueRange = input(true)
multy = input.float(0.2, step=0.05, title='Base Channel Multiplier')
Keltma = ma(maType, src, len)
range_1 = useTrueRange ? ta.tr : high - low
rangema = ta.ema(range_1, len)
upperk = Keltma + rangema * multy
lowerk = Keltma - rangema * multy
//Baseline Violation Candle
open_pos = open * 1
close_pos = close * 1
difference = math.abs(close_pos - open_pos)
atr_violation = difference > atr_slen
InRange = upper_band > BBMC and lower_band < BBMC
//SSL1 VALUES
Hlv = int(na)
Hlv := close > emaHigh ? 1 : close < emaLow ? -1 : Hlv[1]
sslDown = Hlv < 0 ? emaHigh : emaLow
//EXIT VALUES
Hlv3 = int(na)
Hlv3 := close > ExitHigh ? 1 : close < ExitLow ? -1 : Hlv3[1]
sslExit = Hlv3 < 0 ? ExitHigh : ExitLow
base_cross_Long = ta.crossover(close, sslExit)
base_cross_Short = ta.crossover(sslExit, close)
codiff = base_cross_Long ? 1 : base_cross_Short ? -1 : na
//COLORS
show_color_bar = input(title='Color Bars', defval=true)
color_bar = close > upperk ? #00c3ff : close < lowerk ? #ff0062 : color.gray
color_ssl1 = close > sslDown ? #00c3ff : close < sslDown ? #ff0062 : na
//PLOTS
plotarrow(codiff, colorup=color.new(#00c3ff, 20), colordown=color.new(#ff0062, 20), title='Exit Arrows', maxheight=20, offset=0, display=display.none)
p1 = plot(0, color=color_bar, linewidth=3, title='MA Baseline', transp=0)
barcolor(show_color_bar ? color_bar : na)
// ---------------------
// WADDAH ATTAR EXPLOSION
// ---------------------
sensitivity = input.int(180, title="Sensitivity", group='Indicators: Waddah Attar Explosion')
fastLength=input.int(20, title="FastEMA Length", group='Indicators: Waddah Attar Explosion')
slowLength=input.int(40, title="SlowEMA Length", group='Indicators: Waddah Attar Explosion')
channelLength=input.int(20, title="BB Channel Length", group='Indicators: Waddah Attar Explosion')
waeMult=input.float(2.0, title="BB Stdev Multiplier", group='Indicators: Waddah Attar Explosion')
calc_macd(source, fastLength, slowLength) =>
fastMA = ta.ema(source, fastLength)
slowMA = ta.ema(source, slowLength)
fastMA - slowMA
calc_BBUpper(source, length, mult) =>
basis = ta.sma(source, length)
dev = mult * ta.stdev(source, length)
basis + dev
calc_BBLower(source, length, mult) =>
basis = ta.sma(source, length)
dev = mult * ta.stdev(source, length)
basis - dev
t1 = (calc_macd(close, fastLength, slowLength) - calc_macd(close[1], fastLength, slowLength))*sensitivity
e1 = (calc_BBUpper(close, channelLength, waeMult) - calc_BBLower(close, channelLength, waeMult))
trendUp = (t1 >= 0) ? t1 : 0
trendDown = (t1 < 0) ? (-1*t1) : 0
plot(trendUp, style=plot.style_columns, linewidth=1, color=(trendUp<trendUp[1]) ? color.lime : color.green, transp=45, title="UpTrend", display=display.none)
plot(trendDown, style=plot.style_columns, linewidth=1, color=(trendDown<trendDown[1]) ? color.orange : color.red, transp=45, title="DownTrend", display=display.none)
plot(e1, style=plot.style_line, linewidth=2, color=color.yellow, title="ExplosionLine", display=display.none)
// =============================================================================
// STRATEGY LOGIC
// =============================================================================
// QQE Mod
qqeGreenBar = Greenbar1 and Greenbar2
qqeRedBar = Redbar1 and Redbar2
qqeBuy = qqeGreenBar and not qqeGreenBar[1]
qqeSell = qqeRedBar and not qqeRedBar[1]
// SSL Hybrid
sslBuy = close > upperk and close > BBMC
sslSell = close < lowerk and close < BBMC
// Waddah Attar Explosion
waeBuy = trendUp > 0 and trendUp > e1
waeSell = trendDown > 0 and trendDown > e1
inLong = strategy.position_size > 0
inShort = strategy.position_size < 0
longCondition = qqeBuy and sslBuy and waeBuy and in_date_range
shortCondition = qqeSell and sslSell and waeSell and in_date_range
swingLow = ta.lowest(source=low, length=swingLength)
swingHigh = ta.highest(source=high, length=swingLength)
longStopPercent = math.abs((1 - (swingLow / close)) * 100)
shortStopPercent = math.abs((1 - (swingHigh / close)) * 100)
// Position sizing (default risk 2% per trade)
riskAmt = strategy.equity * accountRiskPercent / 100
longQty = math.abs(riskAmt / longStopPercent * 100) / close
shortQty = math.abs(riskAmt / shortStopPercent * 100) / close
if (longCondition and not inShort and not inLong)
strategy.entry("Long", strategy.long, qty=longQty)
strategy.exit("Long SL/TP", from_entry="Long", stop=swingLow, alert_message='Long SL Hit')
buyLabel = label.new(x=bar_index, y=high[1], color=color.green, style=label.style_label_up)
label.set_y(id=buyLabel, y=0)
label.set_tooltip(id=buyLabel, tooltip="Risk Amt: " + str.tostring(riskAmt) + " Qty: " + str.tostring(longQty) + " Swing low: " + str.tostring(swingLow) + " Stop Percent: " + str.tostring(longStopPercent))
if (shortCondition and not inLong and not inShort)
strategy.entry("Short", strategy.short, qty=shortQty)
strategy.exit("Short SL/TP", from_entry="Short", stop=swingHigh, alert_message='Short SL Hit')
sellLabel = label.new(x=bar_index, y=high[1], color=color.red, style=label.style_label_up)
label.set_y(id=sellLabel, y=0)
label.set_tooltip(id=sellLabel, tooltip="Risk Amt: " + str.tostring(riskAmt) + " Qty: " + str.tostring(shortQty) + " Swing high: " + str.tostring(swingHigh) + " Stop Percent: " + str.tostring(shortStopPercent))
openTradesInProfit() =>
result = 0.
for i = 0 to strategy.opentrades-1
result += strategy.opentrades.profit(i)
result > 0
exitLong = inLong and base_cross_Short and openTradesInProfit()
strategy.close(id = "Long", when = exitLong, comment = "Closing Long", alert_message="Long TP Hit")
exitShort = inShort and base_cross_Long and openTradesInProfit()
strategy.close(id = "Short", when = exitShort, comment = "Closing Short", alert_message="Short TP Hit")
// =============================================================================
// DATA WINDOW PLOTTING
// =============================================================================
plotchar(0, "===========", "", location = location.top, color=#141823)
plotchar(0, "BUY SIGNALS:", "", location = location.top, color=#141823)
plotchar(0, "===========", "", location = location.top, color=#141823)
plotchar(qqeBuy, "QQE Mod: Buy Signal", "", location = location.top, color=qqeBuy ? color.green : color.orange)
plotchar(sslBuy, "SSL Hybrid: Buy Signal", "", location = location.top, color=sslBuy ? color.green : color.orange)
plotchar(waeBuy, "Waddah Attar Explosion: Buy Signal", "", location = location.top, color=waeBuy ? color.green : color.orange)
plotchar(inLong, "inLong", "", location = location.top, color=inLong ? color.green : color.orange)
plotchar(exitLong, "Exit Long", "", location = location.top, color=exitLong ? color.green : color.orange)
plotchar(0, "============", "", location = location.top, color=#141823)
plotchar(0, "SELL SIGNALS:", "", location = location.top, color=#141823)
plotchar(0, "============", "", location = location.top, color=#141823)
plotchar(qqeSell, "QQE Mod: Sell Signal", "", location = location.top, color=qqeSell ? color.red : color.orange)
plotchar(sslSell, "SSL Hybrid: Sell Signal", "", location = location.top, color=sslSell ? color.red : color.orange)
plotchar(waeSell, "Waddah Attar Explosion: Sell Signal", "", location = location.top, color=waeSell ? color.red : color.orange)
plotchar(inShort, "inShort", "", location = location.top, color=inShort ? color.red : color.orange)
plotchar(exitShort, "Exit Short", "", location = location.top, color=exitShort ? color.red : color.orange)
More
- Parabolic SAR, Stoch and Security Indicator Based Multi-Timeframe Quantitative Trading Strategy
- Gold Fast Breakthrough EMA Trading Strategy
- Dual-Factor Momentum Tracking Reversal Strategy
- Momentum Reversal Trading Strategy
- Bollinger Band and RSI Mixing with DCA Strategy
- Emma Pullback Short Strategy
- NoroBands Momentum Position Strategy
- Dual Confirmation Reversal Trend Tracking Strategy
- MACD Indicator Driven OBV Quant Trading Strategy
- Dollar Cost Averaging After Downtrend Strategy
- A Trend Reversal Strategy Based on Moving Averages, Price Patterns and Volume
- Dual Moving Average Strategy
- Momentum Moving Average Crossover Trading Strategy
- Dual Moving Average Golden Cross Strategy
- Momentum Wave Bollinger Bands Trend Strategy
- Reverse Momentum Trading Strategy
- Bandpass Mean PB Indicator Strategy
- RSI & Fibonacci 5-Minute Trading Strategy
- Triple Moving Average Combined with MACD Quantitative Strategy
- Momentum Breakout Optimization