Iconic Traders SessionsIconicTraders Sessions. D.D. indicatior, markiert die highs and lows (Asia & London Session)
Indicators and strategies
Sharpe Ratio Forced Selling StrategyThis study introduces the “Sharpe Ratio Forced Selling Strategy”, a quantitative trading model that dynamically manages positions based on the rolling Sharpe Ratio of an asset’s excess returns relative to the risk-free rate. The Sharpe Ratio, first introduced by Sharpe (1966), remains a cornerstone in risk-adjusted performance measurement, capturing the trade-off between return and volatility. In this strategy, entries are triggered when the Sharpe Ratio falls below a specified low threshold (indicating excessive pessimism), and exits occur either when the Sharpe Ratio surpasses a high threshold (indicating optimism or mean reversion) or when a maximum holding period is reached.
The underlying economic intuition stems from institutional behavior. Institutional investors, such as pension funds and mutual funds, are often subject to risk management mandates and performance benchmarking, requiring them to reduce exposure to assets that exhibit deteriorating risk-adjusted returns over rolling periods (Greenwood and Scharfstein, 2013). When risk-adjusted performance improves, institutions may rebalance or liquidate positions to meet regulatory requirements or internal mandates, a behavior that can be proxied effectively through a rising Sharpe Ratio.
By systematically monitoring the Sharpe Ratio, the strategy anticipates when “forced selling” pressure is likely to abate, allowing for opportunistic entries into assets priced below fundamental value. Exits are equally mechanized, either triggered by Sharpe Ratio improvements or by a strict time-based constraint, acknowledging that institutional rebalancing and window-dressing activities are often time-bound (Coval and Stafford, 2007).
The Sharpe Ratio is particularly suitable for this framework due to its ability to standardize excess returns per unit of risk, ensuring comparability across timeframes and asset classes (Sharpe, 1994). Furthermore, adjusting returns by a dynamically updating short-term risk-free rate (e.g., US 3-Month T-Bills from FRED) ensures that macroeconomic conditions, such as shifting interest rates, are accurately incorporated into the risk assessment.
While the Sharpe Ratio is an efficient and widely recognized measure, the strategy could be enhanced by incorporating alternative or complementary risk metrics:
• Sortino Ratio: Unlike the Sharpe Ratio, the Sortino Ratio penalizes only downside volatility (Sortino and van der Meer, 1991). This would refine entries and exits to distinguish between “good” and “bad” volatility.
• Maximum Drawdown Constraints: Integrating a moving window maximum drawdown filter could prevent entries during persistent downtrends not captured by volatility alone.
• Conditional Value at Risk (CVaR): A measure of expected shortfall beyond the Value at Risk, CVaR could further constrain entry conditions by accounting for tail risk in extreme environments (Rockafellar and Uryasev, 2000).
• Dynamic Thresholds: Instead of static Sharpe thresholds, one could implement dynamic bands based on the historical distribution of the Sharpe Ratio, adjusting for volatility clustering effects (Cont, 2001).
Each of these risk parameters could be incorporated into the current script as additional input controls, further tailoring the model to different market regimes or investor risk appetites.
References
• Cont, R. (2001) ‘Empirical properties of asset returns: stylized facts and statistical issues’, Quantitative Finance, 1(2), pp. 223-236.
• Coval, J.D. and Stafford, E. (2007) ‘Asset Fire Sales (and Purchases) in Equity Markets’, Journal of Financial Economics, 86(2), pp. 479-512.
• Greenwood, R. and Scharfstein, D. (2013) ‘The Growth of Finance’, Journal of Economic Perspectives, 27(2), pp. 3-28.
• Rockafellar, R.T. and Uryasev, S. (2000) ‘Optimization of Conditional Value-at-Risk’, Journal of Risk, 2(3), pp. 21-41.
• Sharpe, W.F. (1966) ‘Mutual Fund Performance’, Journal of Business, 39(1), pp. 119-138.
• Sharpe, W.F. (1994) ‘The Sharpe Ratio’, Journal of Portfolio Management, 21(1), pp. 49-58.
• Sortino, F.A. and van der Meer, R. (1991) ‘Downside Risk’, Journal of Portfolio Management, 17(4), pp. 27-31.
Williams Percent Range proOverview
Williams Percent Range Pro is a powerful divergence detection tool based on the Williams %R oscillator.
It automatically identifies and plots regular and hidden divergences between price action and the %R oscillator, providing traders with early indications of potential trend reversals or trend continuations.
This indicator enhances the classic Williams %R by adding intelligent divergence detection logic, customizable visualization, and integrated alert conditions — making it a highly versatile tool for both manual and automated trading.
Features
Automatic Divergence Detection
Regular Divergence (signals trend reversals)
Hidden Divergence (signals trend continuations)
Customizable Settings
Period length, source price, color customization for each divergence type
Visual Enhancements
Overbought, Mid, and Oversold levels (-20, -50, -80)
Shaded background for easier visual interpretation
Pivot Detection
Identifies key swing points on the Williams %R line for divergence comparison
Integrated Alerts
Set up alerts for each type of divergence without coding
Lightweight and Optimized
Designed for fast loading and efficient operation on any timeframe
How It Works
Williams %R Calculation
The script calculates the Williams %R as follows:
%R = 100 × (Close - Highest High over Period) ÷ (Highest High - Lowest Low)
This results in a value that moves between -100 and 0, indicating overbought and oversold conditions.
Pivot Detection
The indicator uses pivot highs and pivot lows on the %R line to determine important swing points.
Pivot logic is based on comparing neighboring candles (5 bars to the left and 5 bars to the right by default).
Divergence Detection
1. Regular Divergence
Regular Bullish Divergence:
Price makes a Lower Low
Williams %R makes a Higher Low
→ Signals potential upward reversal
Regular Bearish Divergence:
Price makes a Higher High
Williams %R makes a Lower High
→ Signals potential downward reversal
2. Hidden Divergence
Hidden Bullish Divergence:
Price makes a Higher Low
Williams %R makes a Lower Low
→ Signals potential upward continuation
Hidden Bearish Divergence:
Price makes a Lower High
Williams %R makes a Higher High
→ Signals potential downward continuation
Each type of divergence is plotted with a specific label and customizable color on the indicator.
Input Parameters
Input Description
Length Period length for Williams %R calculation (default: 14)
Source Data source (default: Close)
Show Regular Divergence Enable/disable regular divergence detection
Show Hidden Divergence Enable/disable hidden divergence detection
Regular Bullish Color Color for regular bullish divergence labels
Regular Bearish Color Color for regular bearish divergence labels
Hidden Bullish Color Color for hidden bullish divergence labels
Hidden Bearish Color Color for hidden bearish divergence labels
Visual Elements
Horizontal Lines:
-20: Overbought zone
-50: Mid-level (dashed line)
-80: Oversold zone
Background Shading:
Fills between -20 and -80 for better visual focus on active trading zones.
Divergence Labels:
Bull = Regular Bullish Divergence
Bear = Regular Bearish Divergence
H Bull = Hidden Bullish Divergence
H Bear = Hidden Bearish Divergence
Each label appears exactly at the pivot points of the Williams %R line, offset slightly for clarity.
Alerts
You can create TradingView alerts based on the following conditions:
Regular Bullish Divergence Detected
Regular Bearish Divergence Detected
Hidden Bullish Divergence Detected
Hidden Bearish Divergence Detected
This allows fully automated trading setups or mobile push notifications.
Example alert message:
"Williams %R Regular Bullish Divergence Detected"
Usage Tips
Entry Strategy:
Combine divergence signals with trend confirmation indicators like EMA/SMA, MACD, or Volume.
Exit Strategy:
Monitor when price reaches key resistance/support zones or overbought/oversold levels on the %R.
Higher Accuracy:
Always confirm divergences with price action patterns such as breakouts, candlestick formations, or trendline breaks.
Conclusion
The Williams Percent Range Pro indicator brings powerful divergence detection and customization features to a classic momentum oscillator.
It provides clear visual and alert-based trading signals that help you anticipate major turning points or trend continuations in any market and timeframe.
Whether you are a swing trader, day trader, or scalper, this tool can be an essential addition to your technical analysis toolkit.
1-Hour Candlestick Patterns on 15m Chartplots 1 hour candlesticks on lower timeframe so there is no need to jump from higher time frame to lower time frame.
Cointegration Buy and Sell Signals [EdgeTerminal]The Cointegration Buy And Sell Signals is a sophisticated technical analysis tool to spot high-probability market turning points — before they fully develop on price charts.
Most reversal indicators rely on raw price action, visual patterns, or basic and common indicator logic — which often suffer in noisy or trending markets. In most cases, they lag behind the actual change in trend and provide useless and late signals.
This indicator is rooted in advanced concepts from statistical arbitrage, mean reversion theory, and quantitative finance, and it packages these ideas in a user-friendly visual format that works on any timeframe and asset class.
It does this by analyzing how the short-term and long-term EMAs behave relative to each other — and uses statistical filters like Z-score, correlation, volatility normalization, and stationarity tests to issue highly selective Buy and Sell signals.
This tool provides statistical confirmation of trend exhaustion, allowing you to trade mean-reverting setups. It fades overextended moves and uses signal stacking to reduce false entries. The entire indicator is based on a very interesting mathematically grounded model which I will get into down below.
Here’s how the indicator works at a high level:
EMAs as Anchors: It starts with two Exponential Moving Averages (EMAs) — one short-term and one long-term — to track market direction.
Statistical Spread (Regression Residuals): It performs a rolling linear regression between the short and long EMA. Instead of using the raw difference (short - long), it calculates the regression residual, which better models their natural relationship.
Normalize the Spread: The spread is divided by historical price volatility (ATR) to make it scale-invariant. This ensures the indicator works on low-priced stocks, high-priced indices, and crypto alike.
Z-Score: It computes a Z-score of the normalized spread to measure how “extreme” the current deviation is from its historical average.
Dynamic Thresholds: Unlike most tools that use fixed thresholds (like Z = ±2), this one calculates dynamic thresholds using historical percentiles (e.g., top 10% and bottom 10%) so that it adapts to the asset's current behavior to reduce false signals based on market’s extreme volatility at a certain time.
Z-Score Momentum: It tracks the direction of the Z-score — if Z is extreme but still moving away from zero, it's too early. It waits for reversion to start (Z momentum flips).
Correlation Check: Uses a rolling Pearson correlation to confirm the two EMAs are still statistically related. If they diverge (low correlation), no signal is shown.
Stationarity Filter (ADF-like): Uses the volatility of the regression residual to determine if the spread is stationary (mean-reverting) — a key concept in cointegration and statistical arbitrage. It’s not possible to build an exact ADF filter in Pine Script so we used the next best thing.
Signal Control: Prevents noisy charts and overtrading by ensuring no back-to-back buy or sell signals. Each signal must alternate and respect a cooldown period so you won’t be overwhelmed and won’t get a messy chart.
Important Notes to Remember:
The whole idea behind this indicator is to try to use some stat arb models to detect shifting patterns faster than they appear on common indicators, so in some cases, some assumptions are made based on historic values.
This means that in some cases, the indicator can “jump” into the conclusion too quickly. Although we try to eliminate this by using stationary filters, correlation checks, and Z-score momentum detection, there is still a chance some signals that are generated can be too early, in the stock market, that's the same as being incorrect. So make sure to use this with other indicators to confirm the movement.
How To Use The Indicator:
You can use the indicator as a standalone reversal system, as a filter for overbought and oversold setups, in combination with other trend indicators and as a part of a signal stack with other common indicators for divergence spotting and fade trades.
The indicator produces simple buy and sell signals when all criteria is met. Based on our own testing, we recommend treating these signals as standalone and independent from each other . Meaning that if you take position after a buy signal, don’t wait for a sell signal to appear to exit the trade and vice versa.
This is why we recommend using this indicator with other advanced or even simple indicators as an early confirmation tool.
The Display Table:
The floating diagnostic table in the top-right corner of the chart is a key part of this indicator. It's a live statistical dashboard that helps you understand why a signal is (or isn’t) being triggered, and whether the market conditions are lining up for a potential reversal.
1. Z-Score
What it shows: The current Z-score value of the volatility-normalized spread between the short EMA and the regression line of the long EMA.
Why it matters: Z-score tells you how statistically extreme the current relationship is. A Z-score of:
0 = perfectly average
> +2 = very overbought
< -2 = very oversold
How to use it: Look for Z-score reaching extreme highs or lows (beyond dynamic thresholds). Watch for it to start reversing direction, especially when paired with green table rows (see below)
2. Z-Score Momentum
What it shows: The rate of change (ROC) of the Z-score:
Zmomentum=Zt − Zt − 1
Why it matters: This tells you if the Z-score is still stretching out (e.g., getting more overbought/oversold), or reverting back toward the mean.
How to use it: A positive Z-momentum after a very low Z-score = potential bullish reversal A negative Z-momentum after a very high Z-score = potential bearish reversal. Avoid signals when momentum is still pushing deeper into extremes
3. Correlation
What it shows: The rolling Pearson correlation coefficient between the short EMA and long EMA.
Why it matters: High correlation (closer to +1) means the EMAs are still statistically connected — a key requirement for cointegration or mean reversion to be valid.
How to use it: Look for correlation > 0.7 for reliable signals. If correlation drops below 0.5, ignore the Z-score — the EMAs aren’t moving together anymore
4. Stationary
What it shows: A simplified "Yes" or "No" answer to the question:
“Is the spread statistically stable (stationary) and mean-reverting right now?”
Why it matters: Mean reversion strategies only work when the spread is stationary — that is, when the distance between EMAs behaves like a rubber band, not a drifting cloud.
How to use it: A "Yes" means the indicator sees a consistent, stable spread — good for trading. "No" means the market is too volatile, disjointed, or chaotic for reliable mean reversion. Wait for this to flip to "Yes" before trusting signals
5. Last Signal
What it shows: The last signal issued by the system — either "Buy", "Sell", or "None"
Why it matters: Helps avoid confusion and repeated entries. Signals only alternate — you won’t get another Buy until a Sell happens, and vice versa.
How to use it: If the last signal was a "Buy", and you’re watching for a Sell, don’t act on more bullish signals. Great for systems where you only want one position open at a time
6. Bars Since Signal
What it shows: How many bars (candles) have passed since the last Buy or Sell signal.
Why it matters: Gives you context for how long the current condition has persisted
How to use it: If it says 1 or 2, a signal just happened — avoid jumping in late. If it’s been 10+ bars, a new opportunity might be brewing soon. You can use this to time exits if you want to fade a recent signal manually
Indicator Settings:
Short EMA: Sets the short-term EMA period. The smaller the number, the more reactive and more signals you get.
Long EMA: Sets the slow EMA period. The larger this number is, the smoother baseline, and more reliable trend bases are generated.
Z-Score Lookback: The period or bars used for mean & std deviation of spread between short and long EMAs. Larger values result in smoother signals with fewer false positives.
Volatility Window: This value normalizes the spread by historical volatility. This allows you to prevent scale distortion, showing you a cleaner and better chart.
Correlation Lookback: How many periods or how far back to test correlation between slow and long EMAs. This filters out false positives when EMAs lose alignment.
Hurst Lookback: The multiplier to approximate stationarity. Lower leads to more sensitivity to regime change, higher produces a more stricter filtering.
Z Threshold Percentile: This value sets how extreme Z-score must be to trigger a signal. For example, 90 equals only top/bottom 10% of extremes, 80 = more frequent.
Min Bars Between Signals: This hard stop prevents back-to-back signals. The idea is to avoid over-trading or whipsaws in volatile markets even when Hurst lookback and volatility window values are not enough to filter signals.
Some More Recommendations:
We recommend trying different EMA pairs (10/50, 21/100, 5/20) for different asset behaviors. You can set percentile to 85 or 80 if you want more frequent but looser signals. You can also use the Z-score reversion monitor for powerful confirmation.
Session Times + Strenght M7This Script Aims to Define Session Times, and Rank those. It can help to adjust your Strategy to Higher Volatility, if you choose to use the Session Volatility and Strenght Index from 1-10. Your timezone on Trading View should be NY. You can customize the Following in Settings: Weight of Volatility & Narrative Regarding the ranking + Transparency of the Lines. SP:SPX FX:EURUSD OANDA:EURUSD CAPITALCOM:USDJPY AMEX:SPY NASDAQ:QQQ TVC:DXY CAPITALCOM:USDJPY CME_MINI:NQ1! OANDA:XAUUSD FX:GBPUSD
Scalping Strategy with Fixed CooldownThis is a sample scalping strategy is designed for short-term trading on lower timeframes.
Entry Signals: Utilizes Hull Moving Average (HullMA) crossovers to generate buy and sell signals.
Filters:
-Bollinger Bands and RSI to avoid overbought or oversold conditions.
-VWAP to confirm trend direction, ensuring trades align with momentum.
Cooldown Mechanism: Implements a bar-based cooldown period to prevent immediate re-entries after trade closures, reducing the risk of overtrading.
BollingerBands MTF | AlchimistOfCrypto🌌 Bollinger Bands – Unveiling Market Volatility Fields 🌌
"The Bollinger Bands, reimagined through quantum mechanics principles, visualizes the probabilistic distribution of price movements within a multi-dimensional volatility field. This indicator employs principles from wave function mathematics where standard deviation creates probabilistic boundaries, similar to electron cloud models in quantum physics. Our implementation features algorithmically enhanced visualization derived from extensive mathematical modeling, creating a dynamic representation of volatility compression and expansion cycles with adaptive glow effects that highlight the critical moments where volatility phase transitions occur."
📊 Professional Trading Application
The Bollinger Bands Quantum transcends traditional volatility measurement with a sophisticated gradient illumination system that reveals the underlying structure of market volatility fields. Scientifically calibrated for multiple timeframes and featuring eight distinct visual themes, it enables traders to perceive volatility contractions and expansions with unprecedented clarity.
⚙️ Indicator Configuration
- Volatility Field Parameters 📏
Python-optimized settings for specific market conditions:
- Period: 20 (default) - The quantum time window for volatility calculation
- StdDev Multiplier: 2.0 - The probabilistic boundary coefficient
- MA Type: SMA/EMA/VWMA/WMA/RMA - The quantum field smoothing algorithm
- Visual Theming 🎨
Eight scientifically designed visual palettes optimized for volatility pattern recognition:
- Neon (default): High-contrast green/red scheme enhancing volatility transition visibility
- Cyan-Magenta: Vibrant palette for maximum volatility boundary distinction
- Yellow-Purple: Complementary colors for enhanced compression/expansion detection
- Specialized themes (Green-Red, Forest Green, Blue Ocean, Orange-Red, Grayscale): Each calibrated for different market environments
- Opacity Control 🔍
- Variable transparency system (0-100) allowing seamless integration with price action
- Adaptive glow effect that intensifies during volatility phase transitions
- Quantum field visualization that reveals the probabilistic nature of price movements
🚀 How to Use
1. Select Visualization Parameters ⏰: Adjust period and standard deviation to match market conditions
2. Choose MA Type 🎚️: Select the appropriate smoothing algorithm for your trading strategy
3. Select Visual Theme 🌈: Choose a color scheme that enhances your personal pattern recognition
4. Adjust Opacity 🔎: Fine-tune visualization intensity to complement your chart analysis
5. Identify Volatility Phases ✅: Monitor band width to detect compression (pre-breakout) and expansion (trend)
6. Trade with Precision 🛡️: Enter during band contraction for breakouts, or trade mean reversion using band boundaries
7. Manage Risk Dynamically 🔐: Use band width as volatility-based position sizing parameter
Sharpe & Sortino Ratio PROSharpe & Sortino Ratio PRO offers an advanced and more precise way to calculate and visualize the Sharpe and Sortino Ratios for financial assets on TradingView. Its main goal is to provide a scientifically accurate method for assessing the risk-adjusted performance of assets, both in the short and long term. Unlike TradingView’s built-in metrics, this script correctly handles periodic returns, uses optional logarithmic returns, properly annualizes both returns and volatility, and adjusts for the risk-free rate — all critical factors for truly meaningful Sharpe and Sortino calculations.
Users can customize the rolling analysis window (e.g., 252 periods for one year on daily data) and the long-term smoothing period (e.g., 1260 periods for five years). There’s also an option to select between linear and logarithmic returns and to manually input a risk-free rate if real-time data from FRED (the 3-Month T-Bill Rate via FRED:DGS3MO) is unavailable. Based on the chart’s timeframe (daily, weekly, or monthly), the script automatically adjusts the risk-free rate to a per-period basis.
The Sharpe Ratio is calculated by first determining the asset’s excess returns (returns after subtracting the risk-free return per period), then computing the average and standard deviation of those excess returns over the specified window, and finally annualizing these figures separately — in line with best scientific practices (Sharpe, 1994). The Sortino Ratio follows a similar approach but only considers negative returns, focusing specifically on downside risk (Sortino & Van der Meer, 1991).
To enhance readability, the script visualizes the ratios using a color gradient: strong negative values are shown in red, neutral values in yellow, and strong positive values in green. Additionally, the long-term averages for both Sharpe and Sortino are plotted with steady colors (teal and orange, respectively), making it easier to spot enduring performance trends.
Why calculating Sharpe and Sortino Ratios manually on TradingView is necessary?
While TradingView provides basic Sharpe and Sortino Ratios, they come with significant methodological flaws that can lead to misleading conclusions about an asset’s true risk-adjusted performance.
First, TradingView often computes volatility based on the standard deviation of price levels rather than returns (TradingView, 2023). This method is problematic because it causes the volatility measure to be directly dependent on the asset’s absolute price. For instance, a stock priced at $1,000 will naturally show larger absolute daily price moves than a $10 stock, even if their percentage changes are similar. This artificially inflates the measured standard deviation and, as a result, depresses the calculated Sharpe Ratio.
Second, TradingView frequently neglects to adjust for the risk-free rate. By treating all returns as risky returns, the computed Sharpe Ratio may significantly underestimate risk-adjusted performance, especially when interest rates are high (Sharpe, 1994).
Third, and perhaps most critically, TradingView doesn’t properly annualize the mean excess return and the standard deviation separately. In correct financial math, the mean excess return should be multiplied by the number of periods per year, while the standard deviation should be multiplied by the square root of the number of periods per year (Cont, 2001; Fabozzi et al., 2007). Incorrect annualization skews the Sharpe and Sortino Ratios and can lead to under- or overestimating investment risk.
These flaws lead to three major issues:
• Overstated volatility for high-priced assets.
• Incorrect scaling between returns and risk.
• Sharpe Ratios that are systematically biased downward, especially in high-price or high-interest environments.
How to properly calculate Sharpe and Sortino Ratios in Pine Script?
To get accurate results, the Sharpe and Sortino Ratios must be calculated using the correct methodology:
1. Use returns, not price levels, to calculate volatility. Ideally, use logarithmic returns for better mathematical properties like time additivity (Cont, 2001).
2. Adjust returns by subtracting the risk-free rate on a per-period basis to obtain true excess returns.
3. Annualize separately:
• Multiply the mean excess return by the number of periods per year (e.g., 252 for daily data).
• Multiply the standard deviation by the square root of the number of periods per year.
4. Finally, divide the annualized mean excess return by the annualized standard deviation to calculate the Sharpe Ratio.
The Sortino Ratio follows the same structure but uses downside deviations instead of standard deviations.
By following this scientifically sound method, you ensure that your Sharpe and Sortino Ratios truly reflect the asset’s real-world risk and return characteristics.
References
• Cont, R. (2001). Empirical properties of asset returns: stylized facts and statistical issues. Quantitative Finance, 1(2), pp. 223–236.
• Fabozzi, F.J., Gupta, F. and Markowitz, H.M. (2007). The Legacy of Modern Portfolio Theory. Journal of Investing, 16(3), pp. 7–22.
• Sharpe, W.F. (1994). The Sharpe Ratio. Journal of Portfolio Management, 21(1), pp. 49–58.
• Sortino, F.A. and Van der Meer, R. (1991). Downside Risk: Capturing What’s at Stake in Investment Situations. Journal of Portfolio Management, 17(4), pp. 27–31.
• TradingView (2023). Help Center - Understanding Sharpe and Sortino Ratios. Available at: www.tradingview.com (Accessed: 25 April 2025).
Pi Cycle | AlchimistOfCrypto Pi Cycle Top Indicator - A Powerful Market Phase Detector
Developed by AlchimistOfCrypto
🧪 The Pi Cycle uses mathematical harmony to identify Bitcoin market cycle tops
with remarkable precision. Just as elements react at specific temperatures,
Bitcoin price behaves predictably when these two moving averages converge! 🧬
⚗️ The formula measures when the 111-day SMA crosses below the 350-day SMA × 2,
creating a perfect alchemical reaction that has successfully identified the
major cycle tops in 2013, 2017, and 2021.
🔬 Like the Golden Ratio in nature, this indicator reveals the hidden
mathematical structure within Bitcoin's chaotic price movements.
🧮 When the reaction occurs, prepare for molecular breakdown! 🔥
Day Trading NR4/NR7 + 2BarNR/3BarNR + ID + MomentumDay Trading Version: The High-Precision Momentum Setup
The Day Trading Version of this strategy is designed for traders who need quick, high-probability setups that work in real-time throughout the trading day. It’s a dynamic approach that blends classic price compression patterns with crucial intraday filters like VWAP and MACD, ensuring you’re only executing trades when everything lines up for success.
Price Compression: Focuses on NR4, NR7, and Inside Day patterns, offering clear signals when stocks are in tight ranges—ideal for a breakout or breakdown. These setups identify periods of compression that often precede explosive moves.
Trend Alignment: Price must be above the 20 EMA, with the 10 EMA above the 20 EMA, confirming a trend that's worthy of entering. These filters keep you on the right side of the market, ensuring you’re trading in the direction of momentum.
VWAP Filter: The price must be above VWAP for long trades, keeping you in sync with intraday institutional flow. This ensures you're aligning with the market’s overall bias.
MACD Confirmation: The fast MACD line needs to be at least 5% above or below the slow line, ensuring that the trade has sufficient momentum. For long trades, the MACD must be positive, confirming upward strength.
This strategy is built for momentum-focused traders who thrive on fast action and want to capture intraday volatility. Perfect for day traders who need to identify reliable setups on the fly, with clear rules and filters that make entering and exiting positions easier than ever.
Relative Volume CandlesVisualizes candlesticks with transparency based on volume relative to a moving average. Higher-than-average volume makes candles more opaque, while lower volume increases transparency—helping you spot significant price movements at a glance!
Features:
Customizable up/down candle colors (default: green/red)
Adjustable lookback period for volume averaging (default: 21)
Fine-tune transparency with base transparency (default: 80) and scale (default: 2.0)
Overlay directly on your chart for seamless analysis
Swing Trading NR4/NR7 + 2BarNR/3BarNR + Inside Day + TrendSwing Trading Version: The Ultimate Momentum Setup
The Swing Trading Version of this strategy is tailored for traders looking to capture multi-day price movements in high-momentum stocks. It’s a carefully crafted approach combining classic patterns like NR4, NR7, and Inside Day with powerful trend filters to find the best opportunities for significant gains.
Price Compression: Identifies stocks in periods of consolidation using the NR4 and NR7 patterns, along with 2-Bar and 3-Bar Narrow Ranges—key indicators of potential volatility and breakout.
Trend Confirmation: The strategy ensures trades align with the broader trend by confirming that price is above the 20 EMA and that the 10 EMA is above the 20 EMA. This guarantees that you’re trading in the direction of strength.
Inside Day Filter: The Inside Day pattern is only triggered when the candlestick is within 1 ATR from the 10 EMA (or 20 EMA if below), ensuring you're not chasing a trade too far from a support level.
Clean, Powerful Signals: With a clear focus on momentum and price compression, you'll only get actionable signals backed by multiple layers of confirmation, including volatility and price structure.
This setup is perfect for traders seeking to ride out trends and capture sizeable moves, with an emphasis on simplicity and precision. Ideal for those who prefer to hold trades for multiple days while still maintaining control over their entries and exits.
Trend Degree Dashboard (Table)📈 Trend Degree Dashboard (Table) — v1.0
This indicator calculates and displays the trend angle (in degrees) based on the linear regression of the selected source (default: close) over a user-defined lookback period (default: 21 bars).
The trend angle gives a quick visual reference of the current market slope — positive (uptrend) or negative (downtrend).
A dashboard table shows the trend angle directly on the chart, with a background color:
🟩 Green background for positive angles (uptrend)
🟥 Red background for negative angles (downtrend)
🔧 Features:
Customizable Lookback Period: Set the number of candles to consider for trend calculation.
Source Selection: Apply the analysis to close, open, high, low, or any other price series.
Dashboard Positioning: Choose where the dashboard appears (Top Left, Top Right, Bottom Left, Bottom Right).
Clean Table Design: Minimalistic and easy-to-read dashboard with automatic background color highlighting based on trend direction.
⚙️ How It Works:
It uses Linear Regression to measure the slope between two consecutive points.
Converts the slope into degrees using the arctangent function (atan) for a geometric interpretation of trend strength and direction.
Updates the dashboard table live with the latest angle value.
✅ Script Highlights:
Non-repainting: Once a bar closes, its value is fixed.
Efficient performance: Lightweight table visualization with no heavy calculations.
Clear trading signals: Positive angles suggest bullish momentum, negative angles suggest bearish momentum.
⚠️ Disclaimer:
This script is a technical analysis tool designed to assist in decision-making but does not guarantee results.
Please use it alongside other tools and practice proper risk management. Always test any indicator on demo accounts before applying it to live trading.
EMA golden cross strategy by Anuj Guptait just shows the golden crossovers. golden cross overs/unders are highly probable price points
Swing Trading NR4/NR7 + 2BarNR/3BarNR + Trend📜 Description:
NR4, NR7, 2-Bar NR, and 3-Bar NR Compression Scanner (Swing Trading Version)
This script spots serious price compressions (NR4, NR7, 2-Bar NR, 3-Bar NR) on the daily chart, with simple but ruthless trend confirmation.
It's leaner. It's cleaner. It's built for those who don’t like getting caught with their pants down in messy sideways markets.
The scanner conditions are:
NR4 and NR7 patterns: Today's daily range must be the narrowest compared to the last 4 or 7 days.
2-Bar and 3-Bar Narrow Ranges: The narrowest two-day or three-day ranges relative to the previous 20 sets.
Trend filter:
Closing price must be above the 20 EMA.
The 10 EMA must be above the 20 EMA.
Visuals:
Background highlights whenever a compression setup forms.
Shape markers above or below the bars to mark the opportunity.
📈 Why Use This?
Some have said swing trading is like sipping fine wine — slow, measured, deliberate.
I won’t say they’re wrong.
But there’s also the part where you grab the bottle, smash it over the head of bad setups, and only drink the good stuff.
This scanner lets you find daily compressions inside healthy trends.
The kind of coils that can explode in your favour — and not the fake-outs that empty your account while you cry into your keyboard.
🛠️ Built for Traders Who:
Trade on daily candles, not minute charts.
Want high-quality entries without second-guessing.
Understand that real breakouts come from contraction, not chaos.
Like their setups clean, focused, and simple enough to stick to under pressure.
NR4/NR7 + 2BarNR/3BarNR + Trend + Refined MACD + VWAP📜 Description:
NR4, NR7, 2-Bar NR, and 3-Bar NR Compression Scanner with Trend & Momentum Filters
This script identifies extreme price compressions (NR4, NR7, 2-Bar NR, 3-Bar NR) combined with strict trend and momentum conditions for higher-probability setups.
It’s not just about spotting contraction — it’s about ensuring the right environment for expansion.
The scanner conditions are:
NR4 and NR7 patterns: Today's range must be the narrowest compared to the last 4 or 7 days.
2-Bar and 3-Bar Narrow Ranges: The narrowest two or three day ranges compared to the last 20 sets of two/three days.
Trend filter:
Price must be above the 20 EMA.
The 10 EMA must be above the 20 EMA.
MACD proximity filter:
The MACD fast line must either be above the slow line or within 5% range below the slow line.
VWAP filter:
Price must be trading above VWAP.
Visuals:
Background colours highlight detected compression patterns aligned with trend.
Shape markers above or below bars for quick visual confirmation.
📈 Why Use This?
Some have said that trading is a waiting game. I won't say they're wrong.
This scanner doesn't just throw every tight-range day at you. It finds the coils in context — trending, gaining momentum, ready to spring.
If you chase trades like a fool in a brothel, you'll get taken for a ride.
If you wait for the right compression, at the right moment, with the right backing...
Well, let's just say, you might just start looking like you actually know what you're doing.
🛠️ Built for Traders Who:
Prefer strong trends over messy ranges.
Want systematic setups, not random guessing.
Like stacking probabilities rather than praying to the trading gods.
Enjoy catching breakouts when everyone else is still scratching their heads.
Weekday Colors with Time Highlighting by NabojeetThis script is a Pine Script (version 6) indicator called "Weekday Colors with Time Highlighting" designed for TradingView charts. It has several key functions:
1. **Weekday Color Coding**:
- Assigns different background colors to each trading day (Monday through Friday)
- Allows users to customize the color for each day
- Includes toggles to enable/disable colors for specific days
2. **Time Range Highlighting**:
- Highlights a specific time period (e.g., 18:15-18:30) on every trading day
- Uses a custom color that can be adjusted by the user
- The time range is specified in HHMM-HHMM format
3. **High/Low Line Drawing**:
- Automatically identifies the highest high and lowest low points within the specified time range
- Draws horizontal lines at these levels when the time period ends
- Lines extend forward in time to serve as support/resistance references
- Users can customize the line color, width, and style (solid, dotted, or dashed)
The script is organized into logical sections with input parameters grouped by function (Weekday Colors, Weekday Display, Time Highlighting, and Horizontal Lines). Each section's inputs are customizable through the indicator settings panel.
This indicator would be particularly useful for traders who:
- Want visual distinction between different trading days
- Focus on specific time periods each day (like market opens, closes, or specific sessions)
- Use intraday support/resistance levels from key time periods
- Want to quickly identify session highs and lows
The implementation resets tracking variables at the beginning of each new time range and draws the lines once the time period ends, ensuring accurate high/low marking for each day's specified time window.
Author - Nabojeet
Gaussian Channel StrategyGaussian Channel Strategy — User Guide
1. Concept
This strategy builds trades around the Gaussian Channel. Based on Pine Script v4 indicator originally published by Donovan Wall. With rework to v6 Pine Script and adding entry and exit functions.
The channel consists of three dynamic lines:
Line Formula Purpose
Filter (middle) N-pole Gaussian filter applied to price Market "equilibrium"
High Band Filter + (Filtered TR × mult) Dynamic upper envelope
Low Band Filter − (Filtered TR × mult) Dynamic lower envelope
A position is opened when price crosses a user-selected line in a user-selected direction.
When the smoothed True Range (Filtered TR) becomes negative, the raw bands can flip (High drops below Low).
The strategy automatically reorders them so the upper band is always above the lower band.
Visual colors still flip, but signals stay correct.
2. Entry Logic
Choose a signal line for longs and/or shorts: Filter, Upper band, or Lower band.
Choose a cross direction (Cross Up or Cross Down).
A signal remains valid for Lookback bars after the actual cross, as long as price is still on the required side of the line.
When the opposite signal appears, the current position is closed or reversed depending on Reverse on opposite.
3. Parameters
Group Setting Meaning
Source & Filter Source Price series used (close, hlc3, etc.)
Poles (N) Number of Gaussian filter poles (1-9). More poles ⇒ smoother but laggier
Sampling Period Main period length of the channel
Filtered TR Multiplier Width of the bands in fractions of smoothed True Range
Reduced Lag Mode Adds a lag-compensation term (faster but noisier)
Fast Response Mode Blends 1-pole & N-pole outputs for quicker turns
Signals Long → signal line / Short → signal line Which line generates signals
Long when price / Short when price Direction of the cross
Lookback bars for late entry Bars after the cross that still allow an entry
Trading Enable LONG/SHORT-side trades Turn each side on/off
On opposite signal: reverse True: reverse -- False: flat
Misc Start trading date Ignores signals before this timestamp (back-test focus)
4. Quick Start
Add the strategy to a chart. Default: hlc3, N = 4, Period = 144.
Select your signal lines & directions.
Example: trend trading – Long: Filter + Cross Up, Short: Filter + Cross Down.
Disable either side if you want long-only or short-only.
Tune Lookback (e.g. 3) to catch gaps and strong impulses.
Run Strategy Tester, optimise period / multiplier / stops (add strategy.exit blocks if needed).
When satisfied, connect alerts via TradingView webhooks or use the builtin broker panel.
5. Notes
Commission & slippage are not preset – adjust them in Properties → Commission & Slippage.
Works on any market and timeframe, but you should retune Sampling Period and Multiplier for each symbol.
No stop-loss / take-profit is included by default – feel free to add with strategy.exit.
Start trading date lets you back-test only recent history (e.g. last two years).
6. Disclaimer
This script is for educational purposes only and does not constitute investment advice.
Use entirely at your own risk. Back-test thoroughly and apply sound risk management before trading real capital.
Real Relative Strength vs SPY (Clean Visual)This indicator plots Real Relative Strength/Weakness (RS/RW) of any stock relative to SPY, normalised by ATR. Designed to aid trading aligned to RDT philosophy.
Designed for intraday and swing traders to quickly identify stocks showing true institutional strength or weakness compared to the market.
Uses a clean, color-coded center-line display for fast reading of live RS/RW performance.
It automatically syncs to whatever timeframe you’re trading (5min, 15min, 1hr)
Default comparison ticker is SPY (you can easily swap if needed later)
Length = 12 by default → (rolling 1-hour window on M5 chart)
Clean green/red visual breakout = immediately obvious relative strength or weakness!
How to use
Strong Green move above zero ➔ RS developing ➔ Long bias
Strong Red move below zero ➔ RW developing ➔ Short bias
Choppy around zero ➔ No clear edge ➔ maybe avoid that stock
Quarterly Fundamentals Table by GauravThis Pine Script v3 overlay paints a compact, six‐column table in the top‐right of your chart that begins with your stock’s market capitalization and sector/industry, then lays out quarterly fundamentals—Sales, Sales QoQ%, PAT, PAT QoQ% and OPM%—across the most recent four fiscal quarters (dynamically labeled by month and year). It pulls data via request.financial(), formats large numbers into lakhs/crores, calculates quarter‐over‐quarter growth, and sizes text for clarity, giving swing traders an at‐a‐glance view of key fundamental trends alongside price action.
