QSL Upside/DownsideThe QSL Upside/Downside Indicator helps traders estimate potential gains and losses using Conditional Value at Risk (cVaR), a statistical measure that assesses both downside risk and upside potential beyond standard volatility. Instead of fixed timeframes (daily, weekly, etc.), traders can set a custom lookback period (in days) to analyze market behavior over their preferred time frame.
How It Works
The indicator calculates cVaR over the chosen period to determine how much an investment could move up or down based on past price behavior. It does this by:
• Mean Return – The average price movement over the period.
• Standard Deviation – Measures price fluctuations from the average.
• cVaR Confidence Interval (95%) – Estimates worst-case losses, meaning the downside projection reflects the worst 5% of expected losses.
• Upside Potential (Best 5%) – Instead of only considering risk, this indicator also calculates the potential upside by measuring returns in the top 5% of past price movements.
This provides a more complete view of what traders can expect—both in terms of risk and potential reward.
Key Features
✅ Custom Lookback Period – Set any number of days to analyze.
✅ cVaR Calculation (95% Confidence Interval) – Identifies extreme downside risks.
✅ Upside Potential (Best 5%) – Estimates how much an investment could rise in a best-case scenario.
✅ Clear Table Display – Quickly see projected best and worst-case portfolio values.
Understanding Probabilities: Upside & Downside Potential
Most traders focus on risk, but it’s equally important to understand potential gains. This indicator provides a probability-based view of expected market moves:
• 95% Confidence Interval (Downside cVaR) – There’s a 5% chance that losses could exceed this level.
• 95% Confidence Interval (Upside cVaR) – There’s a 5% chance that gains could be greater than this level.
• The remaining 90% of expected returns fall between these two extremes.
By knowing both potential losses and gains, traders can make more balanced, data-driven decisions rather than only focusing on worst-case scenarios.
Why Use This Indicator?
🔹 Better Risk & Reward Assessment – Understand both downside risk and upside potential.
🔹 More Realistic Market Projections – Uses probabilities instead of simple historical averages.
🔹 Flexible & Customizable – Works with any asset and any time period.
With this tool, QSL members can strategically plan trades, knowing the expected best and worst-case outcomes with a 95% probability range. 🚀
อินดิเคเตอร์และกลยุทธ์
RSI Divergence_v1This indicator detects RSI Divergences (both regular and reverse) to identify potential reversals and trend continuations. It integrates ADX & DI for trend strength confirmation, MACD from the weekly timeframe for momentum validation, and ATR-based stop loss levels for risk management.
Have back tested with Nifty50 with Positive returns and Drawdown %. TIA.
QSL Rolling VolatilityThis script calculates the rolling annualized volatility of an asset, helping traders measure how much its returns fluctuate over time. It uses logarithmic daily returns and computes the standard deviation over a custom lookback period (default: 252 trading days = 1 year) to capture historical volatility. The result is scaled to an annualized figure by multiplying by √252, making it comparable across different timeframes.
🔹 Key Features:
• Customizable Lookback Period: Set in days to fit different trading strategies.
• Annualized Output: Expresses volatility in yearly terms for consistency with financial models.
• Rolling Calculation: Continuously updates to reflect recent market conditions.
• Clear Visualization: Plots volatility as a time-series indicator and displays the latest value with a label.
This tool is ideal for risk management, position sizing, and strategy optimization in quantitative trading. 🚀
QSL Rolling Annualized VolatilityThis script calculates the rolling annualized volatility of an asset, helping traders measure how much its returns fluctuate over time. It uses logarithmic daily returns and computes the standard deviation over a custom lookback period (default: 252 trading days = 1 year) to capture historical volatility. The result is scaled to an annualized figure by multiplying by √252, making it comparable across different timeframes.
🔹 Key Features:
• Customizable Lookback Period: Set in days to fit different trading strategies.
• Annualized Output: Expresses volatility in yearly terms for consistency with financial models.
• Rolling Calculation: Continuously updates to reflect recent market conditions.
• Clear Visualization: Plots volatility as a time-series indicator and displays the latest value with a label.
This tool is ideal for risk management, position sizing, and strategy optimization in quantitative trading. 🚀
Simple TestPurpose: This indicator identifies potential liquidity zones and grabs based on the previous week's price action.
Key Components:
Tracks previous week's high and low prices
Plots these levels as dotted lines (red for high, green for low)
Detects "liquidity grabs" when price exceeds these levels but closes back within them
Logic Explained:
prevWeekHigh and prevWeekLow are updated at the start of each new week using the highest high and lowest low of the past 7 periods
A "Bear Trap" (red triangle up) appears when price exceeds the previous week's high but closes below it
A "Bull Trap" (green triangle down) appears when price falls below the previous week's low but closes above it
Visualization:
Red dotted line: Previous week's high
Green dotted line: Previous week's low
Red triangle up: Bearish liquidity grab
Green triangle down: Bullish liquidity grab
Trade ValueA simple indicator that calculates and displays the trade value (volume × close price). Using a transparency technique, the indicator shows values in the Data Window without cluttering the chart.
repo: github.com
ترکیب اندیکاتورها برای سیگنالهای پیشرفته//@version=5
indicator("ترکیب اندیکاتورها برای سیگنالهای پیشرفته", overlay=true)
// تنظیمات پارامترهای اندیکاتورها
fast_length = input.int(9, title="طول دوره MA سریع")
slow_length = input.int(21, title="طول دوره MA کند")
rsi_length = input.int(14, title="طول دوره RSI")
macd_fast_length = input.int(12, title="طول دوره MACD سریع")
macd_slow_length = input.int(26, title="طول دوره MACD کند")
macd_signal_length = input.int(9, title="طول دوره سیگنال MACD")
// محاسبه میانگینهای متحرک
fast_ma = ta.sma(close, fast_length)
slow_ma = ta.sma(close, slow_length)
// محاسبه RSI
rsi = ta.rsi(close, rsi_length)
// محاسبه MACD
= ta.macd(close, macd_fast_length, macd_slow_length, macd_signal_length)
// شرایط برای سیگنالها
buy_condition = (ta.crossover(fast_ma, slow_ma)) and (rsi < 30) and (macd_line > signal_line)
sell_condition = (ta.crossunder(fast_ma, slow_ma)) and (rsi > 70) and (macd_line < signal_line)
// نمایش سیگنالها روی نمودار
plotshape(series=buy_condition, title="سیگنال خرید", location=location.belowbar, color=color.green, style=shape.labelup, text="خرید")
plotshape(series=sell_condition, title="سیگنال فروش", location=location.abovebar, color=color.red, style=shape.labeldown, text="فروش")
// هشدارها برای سیگنالها
alertcondition(buy_condition, title="سیگنال خرید", message="سیگنال خرید ایجاد شد!")
alertcondition(sell_condition, title="سیگنال فروش", message="سیگنال فروش ایجاد شد!")
ICT OTE StrategyBased on ICT's OTE Strategy. Feel free to test and where can be improved. Enjoy!
NB! Need to know ICT OTE concept to understand strategy.
QSL Rolling Annualized VolatilityThis script calculates the rolling annualized volatility of an asset, helping traders measure how much its returns fluctuate over time. It uses logarithmic daily returns and computes the standard deviation over a custom lookback period (default: 252 trading days = 1 year) to capture historical volatility. The result is scaled to an annualized figure by multiplying by √252, making it comparable across different timeframes.
🔹 Key Features:
Customizable Lookback Period: Set in days to fit different trading strategies.
Annualized Output: Expresses volatility in yearly terms for consistency with financial models.
Rolling Calculation: Continuously updates to reflect recent market conditions.
Clear Visualization: Plots volatility as a time-series indicator and displays the latest value with a label.
This tool is ideal for risk management, position sizing, and strategy optimization in quantitative trading. 🚀
ATR BAND SCALPINGwe can use this indicator with other indicators to determined reversal and exit point
Intraday Combo Indicator Strategyworks for intraday in indian markets especially with lower time frame
SMA 20/50/150/2004 simple SMAs to detect the symbol's trend. The SMA 20 and 50 show you the short term trend. The SMA 150 and 200 show you the long term trend. SMA is preferred over EMA due to EMA being too fast.
TestLibraryLibrary "TestLibrary"
TODO: add library description here
kez_f1(x)
TODO: add function description here
Parameters:
x (float) : TODO: add parameter x description here
Returns: TODO: add what function returns
kez_ema(_x, _per)
TODO: функция экспоненциальной средней
Parameters:
_x (float)
_per (float)
Returns: TODO: возвращает EMA
Scalping Strategy//@version=5
strategy("Scalping Strategy", overlay=true)
// Indicators
ma50 = ta.sma(close, 50)
ema20 = ta.ema(close, 20)
ema200 = ta.ema(close, 200)
rsi = ta.rsi(close, 14)
osc = ta.stoch(close, high, low, 14)
vol = volume
// Trend Confirmation
bullishTrend = ema20 > ema200 and close > ma50
bearishTrend = ema20 < ema200 and close < ma50
// RSI Divergence Detection
rsiOverbought = rsi > 70
rsiOversold = rsi < 30
// Oscillator Confirmation
oscBull = osc < 20
oscBear = osc > 80
// Volume Confirmation
highVolume = vol > ta.sma(vol, 20)
// Entry Conditions
buySignal = bullishTrend and rsiOversold and oscBull and highVolume
sellSignal = bearishTrend and rsiOverbought and oscBear and highVolume
// Execute Trades
if buySignal
strategy.entry("Buy", strategy.long)
if sellSignal
strategy.entry("Sell", strategy.short)
// Plot indicators
plot(ma50, color=color.blue, title="MA 50")
plot(ema20, color=color.green, title="EMA 20")
plot(ema200, color=color.red, title="EMA 200")
Scalping Strategy//@version=5
strategy("Scalping Strategy", overlay=true)
// Indicators
ma50 = ta.sma(close, 50)
ema20 = ta.ema(close, 20)
ema200 = ta.ema(close, 200)
rsi = ta.rsi(close, 14)
osc = ta.stoch(close, high, low, 14)
vol = volume
// Trend Confirmation
bullishTrend = ema20 > ema200 and close > ma50
bearishTrend = ema20 < ema200 and close < ma50
// RSI Divergence Detection
rsiOverbought = rsi > 70
rsiOversold = rsi < 30
// Oscillator Confirmation
oscBull = osc < 20
oscBear = osc > 80
// Volume Confirmation
highVolume = vol > ta.sma(vol, 20)
// Entry Conditions
buySignal = bullishTrend and rsiOversold and oscBull and highVolume
sellSignal = bearishTrend and rsiOverbought and oscBear and highVolume
// Execute Trades
if buySignal
strategy.entry("Buy", strategy.long)
if sellSignal
strategy.entry("Sell", strategy.short)
// Plot indicators
plot(ma50, color=color.blue, title="MA 50")
plot(ema20, color=color.green, title="EMA 20")
plot(ema200, color=color.red, title="EMA 200")
MA Сrosses Multi TF [PowerEn] This indicator is a useful tool for traders, who use MAs and crosses in trading.
Сrosses MAs Multi TF will allow you to display on the graph:
1) up to six MA with different settings (length, type, style);
2) the crosses of the three MA pairs with the visualization selection;
3) setting different timeframes for MAs (from 1m to 1M);
4) using labels, you can clearly see parameters of MA (length, type, timeframe);
5) using signals of crosses MAs, you can create alerts.
Merged Trading Script [BigBeluga]Merger Of two pole oscillator and Volumatic variable dynamic average to create perfect sell and buy signals
Ultimate Gold Trading StrategyAdaptive ATR-based Stop-Loss & Take-Profit
✔ Fair Value Gap (FVG) detection for Smart Money trading
✔ 200 EMA Trend Filter to avoid counter-trend trades
✔ Exit trades when SuperTrend flips direction
✔ Multi-Timeframe (4H) SuperTrend confirmation
🔥 These refinements will make your indicator even more powerful and reduce false signals!
Would you like me to implement these changes in your script? 🚀
You said:
ok add all
ChatGPT said:
Edited
✅ Ultimate Gold Trading Strategy Fully Optimized! 🚀🔥
🎯 New Enhancements Added:
1️⃣ ✅ ATR-Based Adaptive Stop-Loss & Take-Profit
Dynamic SL/TP adjusts to market volatility instead of a fixed percentage.
2️⃣ 📈 Fair Value Gap (FVG) Detection
Detects Smart Money price inefficiencies for better trade accuracy.
3️⃣ 📊 200 EMA Trend Filter
Prevents counter-trend trades, ensuring higher probability trades.
4️⃣ ⏳ Multi-Timeframe SuperTrend Confirmation (4H)
Aligns lower timeframe trades with a higher timeframe trend.
5️⃣ 🔄 Exit Trade on Trend Reversal
Closes position if SuperTrend flips, locking in profits before reversals.
✅ Final Strategy Flow:
✔ Buy Conditions:
SuperTrend is bullish
MACD crosses up
Order Block confirmation
RSI is oversold (<30)
Volume above SMA
Price above 200 EMA
Fair Value Gap confirmation
Higher timeframe (4H) SuperTrend is bullish
✔ Sell Conditions:
SuperTrend is bearish
MACD crosses down
Order Block confirmation
RSI is overbought (>70)
Volume above SMA
Price below 200 EMA
Fair Value Gap confirmation
Higher timeframe (4H) SuperTrend is bearish
✔ Exit Strategy:
When the trend reverses (SuperTrend flips direction).
📌 How to Use in TradingView
Copy & Paste this script into Pine Editor.
Click Add to Chart.
Enable Buy/Sell Alerts for auto notifications.
🚀 This strategy is now optimized for HIGH ACCURACY and SMART MONEY TRADING! 🔥
Would you like any further modifications or improvements? 💡
You said:
Invalid assignment. Cannot assign a tuple to a variable 'htfSuperTrend'. error comes
ChatGPT said:
Edited
I've fixed the invalid assignment issue by correctly extracting the SuperTrend and direction from the higher timeframe (4H) request.
🔧 Fix Implemented:
Changed:
pinescript
Copy
htfSuperTrend = request.security(syminfo.tickerid, "4H", ta.supertrend(multiplier, atrLength))
(which caused an error)
To:
pinescript
Copy
= request.security(syminfo.tickerid, "4H", ta.supertrend(multiplier, atrLength))
htfTrend = htfDirection == 1
(which properly extracts both values from the function)
This should now work without errors. ✅
Let me know if you need further modifications! 🚀🔥
Double RSIthis double rsi is very easy to read. the zero line determines whether trend is bearish or bullish. look for cross up at the zero line and vice versa
Daily Weekly Monthly Yearly Opens/Highs/LowsCredit to @sbtnc , I just added highs and lows to his script from here:
