Harmonic Sniper Trigger [Fisher] - PyraTime**Concept: Precision Momentum**
The Harmonic Sniper Trigger is a custom-tuned implementation of the Fisher Transform, designed specifically to identify sharp market reversals with zero lag. Unlike standard moving averages that react slowly to price changes, the Fisher Transform uses Gaussian probability to convert price into a normal distribution, creating clear, sharp turning points.
This indicator serves as the *Trigger* component of the PyraTime system. While Time Cycles tell you *when* to look, this indicator tells you *what* to do.
Key Features
Visual Signal Markers : Prints clear "B" (Buy) and "S" (Sell) labels on the oscillator pane for instant recognition.
Trend Fills : Dynamic Green/Red shading between the signal lines makes it easy to identify trend direction at a glance.
Integrated Alerts: Fully compatible with TradingView alerts, allowing you to be notified the second momentum flips.
How to Use This Indicator
This tool is designed to filter out noise and identify the exact moment a trend reverses.
1. Wait for the Setup: Do not trade every signal. This indicator is most powerful when price is approaching a key support/resistance level or a specific Time Pivot.
2. The Trigger: When the Fisher line crosses the Signal line (changing from Red to Green or vice versa), it confirms that momentum has mathematically shifted.
3. The Execution: Use this crossover as your entry signal *only* if it aligns with your broader market thesis.
Best Practice:
Use this in conjunction with a Time-Cycle indicator (such as the GPM Architecture).
Scenario: Price hits a Vertical Time Line.
Action: Wait for this Fisher indicator to print a "B" or "S".
Result: You enter exactly at the pivot, minimizing drawdown.
Disclaimer: This tool is for technical analysis purposes only. Past performance does not guarantee future results.
ניתוח מגמה
Zig Zag & Trendlines with Dynamic Threshold ATRPercentage Zig Zag with Dynamic Threshold
This Pine Script indicator is an advanced Zig Zag tool that identifies and tracks price pivots based on a percentage move required for reversal, offering a clear visual representation of volatility-adjusted trends.
Core Functionality (The Reversal Threshold):
Unlike standard Zig Zag indicators that use a fixed price difference, this indicator calculates the required reversal size (%X) dynamically using the Average True Range (ATR).
It calculates the ATR as a percentage of the current price (ATR%).
The final threshold is this ATR% multiplied by a user-defined factor (default 3x).
This means the reversal threshold is wider during volatile periods and narrower during quiet periods, adapting automatically to market conditions. Users can optionally revert to a fixed percentage if desired.
Trend Extension Lines:
The indicator draws two unique, dynamic trend lines connecting the last two significant Highs and the last two significant Lows. Crucially, these lines do not wait for the entire Zig Zag leg to confirm:
If the price is actively forming a new up-leg, the High Extension Line connects the last confirmed High to the current extreme high of the active move.
The Low Extension Line functions similarly for the downtrend.
This feature allows the user to visualize dynamic support and resistance levels based on the current, active trend structure defined by the percentage threshold.
Apex Trend & Liquidity Master (SMC)v7.2The Apex Trend & Liquidity Master (SMC)v7.2 is a comprehensive trading system designed to solve a specific problem: how to integrate Trend Following, Classic Supply & Demand, and Smart Money Concepts (SMC) onto a single chart without creating visual chaos.
Most indicators force traders to choose between high-lag trend filters or noisy price action concepts. This script combines both into a unified workflow. It uses a sophisticated "Ghost Mode" transparency engine to keep internal market structures subtle, ensuring the trader's focus remains on price action and the dominant trend.
Core Philosophy
This tool operates on the principle of "External Trend, Internal Liquidity." It forces the trader to respect the macro direction (Trend Cloud) while using micro-structure (FVGs, Order Blocks) for precision entries.
Key Features
Trend Architecture (The Context) The foundation of the script is a dynamic Hull Moving Average (HMA) combined with ATR volatility bands. This creates a "Trend Cloud" that visualizes the dominant market state.
Teal Cloud: Bullish Context (Look for Longs).
Maroon Cloud: Bearish Context (Look for Shorts).
Classic Liquidity (The Targets) The script identifies major Swing Highs and Swing Lows based on pivot sensitivity. These are rendered as solid blocks and represent "External Liquidity." These are your primary Take Profit targets or major reversal zones.
Smart Money Concepts (The Entry) The script automatically detects internal market structure, including:
BOS (Break of Structure): Signals trend continuation.
CHoCH (Change of Character): Signals potential trend reversal.
Order Blocks & FVGs: Institutional footprints that act as magnets for price. These feature "Ghost Mode" styling (high transparency, no borders) and "Auto-Mitigation" (they are deleted immediately when price closes through them) to keep the chart clean.
Signal & Risk Engine
Entry Signals: Momentum-based Buy/Sell labels that filter out chop using ADX.
Trailing Stop: A Chandelier-style ATR trailing stop line to assist in trade management and locking in profits.
Visual Legend & Color Hierarchy
To allow for instant chart processing, the colors follow a strict hierarchy:
Context (Dark/Deep Colors): The Trend Cloud and Bar Colors use Deep Teal and Maroon. These indicate the background environment.
Action (Neon Colors): Signals, BOS/CHoCH lines, and the Trailing Stop use Neon Green and Neon Red. These require immediate attention.
Major Levels (Solid Colors): Classic Supply & Demand zones use Standard Forest Green and Brick Red. These are hard targets.
Internal Zones (Pale/Ghost Colors): Order Blocks and FVGs use Pale Mint and Pale Rose with high transparency. These are background areas of interest for entries.
How to Use This Indicator
For the highest probability setups, use a "Confluence Approach" rather than trading signals in isolation:
Identify Direction: Look at the Trend Cloud. Do not trade against the color of the cloud.
Wait for Pullback: Wait for price to retrace into a "Ghost Zone" (Fair Value Gap or Order Block) nested inside the trend.
Wait for Trigger: Look for a Neon "Buy" or "Sell" signal, or a BOS line break in the direction of the trend.
Manage Risk: Use the Trailing Stop line to manage your position.
Target Liquidity: Aim for the solid Classic Supply/Demand zones as exit points.
Settings & Customization
Trend Length: Default is 55 (Swing). Lower this to 20-30 for Scalping.
Signal Toggles: Signals and Trailing Stops are enabled by default but can be toggled off for a pure price-action view.
Sensitivity: The Pivot Lookback (Default 10) controls how many Supply/Demand zones appear.
Disclaimer
This script is for educational and informational purposes only. It does not constitute financial advice. Trading in financial markets involves a high degree of risk, and you should not trade with money you cannot afford to lose. Past performance of any trading system or methodology is not necessarily indicative of future results. Always perform your own due diligence and use proper risk management.
Renko ScalperWhat it is-
A lightweight Renko Scalper that combines Renko brick direction with an internal EMA trend filter and MACD confirmation to signal high-probability short-term entries. EMAs are used internally (hidden from the chart) so the visual remains uncluttered.
Signals-
Buy arrow: Renko direction turns bullish AND EMA trend up AND MACD histogram positive.
Sell arrow: Renko direction turns bearish AND EMA trend down AND MACD histogram negative.
Consecutive same-direction signals are suppressed (only one arrow per direction until opposite signal).
Visuals-
Buy / Sell arrows (large) above/below bars.
Chart background tints green/red after the respective signal for easy glance recognition.
Inputs:-
Renko Box Size (points)
EMA Fast / EMA Slow
MACD fast/slow/signal lengths
How to use-
Add to chart
Use smaller Renko box sizes for scalping, larger for swing-like entries.
Confirm signal with price action and volume—this indicator is a signal generator, not a full automated system.
Use alerts (built in) to receive Buy / Sell arrow notifications.
Alerts-
Buy Arrow — buySignal
Sell Arrow — sellSignal
Buy Background / Sell Background — background-color state alerts
Recommended settings-
Timeframes: 1m–15m for scalping, 5m for balanced intraday.
Symbols: liquid futures/currency pairs/major crypto.
Disclaimer
This script is educational and not financial advice. Backtest and forward test on a demo account before live use. Past performance is not indicative of future results. Use proper risk management.
THF Ultimate AIO Scalper & Trend PRO This is a comprehensive "All-In-One" trading suite designed to identify high-probability setups by combining **Trend Following**, **Price Action (FVG)**, and **Ichimoku Cloud** systems.
The indicator is designed to be "Ready-to-Trade" out of the box, with all major confluence filters active by default. It helps traders avoid false signals by ensuring that momentum, trend, and support/resistance levels are in alignment.
### 🛠️ Key Features & Components:
**1. Trend & Scalp Engine:**
* **Scalp Signals:** Fast EMA crossovers (7/21) for quick entries.
* **Trend Filter:** Signals are filtered by a long-term SMA (200) to ensure you are trading with the dominant trend.
* **Golden/Death Cross:** Automatically highlights major trend shifts (SMA 50 crossing SMA 200).
**2. Price Action (Fair Value Gaps):**
* **FVG Detection:** Highlights unmitigated Bullish and Bearish imbalance zones. These act as high-probability targets or re-entry zones.
* **Dashboard:** A built-in panel tracks the number of active vs. mitigated gaps.
* **Mitigation Lines:** Automatically draws lines when price tests an FVG level.
**3. Ichimoku Cloud Overlay:**
* Displays the full Ichimoku system (Tenkan, Kijun, and Kumo Cloud) to identify dynamic support/resistance and trend strength.
* **Usage:** Perfect for confirming breakout signals when price is above/below the Cloud.
**4. Momentum & Volume:**
* **Volume Coloring:** Bars are colored based on relative volume strength.
* **RSI & MACD:** Integrated buy/sell signals to spot overbought/oversold conditions instantly.
### 🎯 How to Trade (Confluence Strategy):
The power of this script lies in **Confluence** (multiple indicators agreeing):
* **Buy Setup:**
1. Price is above the **Ichimoku Cloud** and **SMA 200**.
2. Wait for a **"SCALP BUY"** signal or **"Trend BUY"** label.
3. Confirm that price is reacting to a **Bullish FVG** (Green Box).
4. **RSI/MACD** should show bullish momentum.
* **Sell Setup:**
1. Price is below the **Ichimoku Cloud** and **SMA 200**.
2. Wait for a **"SCALP SELL"** signal.
3. Confirm rejection from a **Bearish FVG** (Red Box).
---
**CREDITS & ATTRIBUTION:**
* **Fair Value Gap Logic:** This script utilizes the open-source FVG calculation method originally developed by **LuxAlgo**. We have integrated this logic with our custom trend system to provide a complete trading view.
* **Trend Logic:** Custom compilation of Moving Average crossovers and Ichimoku standard calculations.
*Disclaimer: This tool is for educational purposes only. Always manage your risk.*
Hurst Exponent - Detrended Fluctuation AnalysisIn stochastic processes, chaos theory and time series analysis, detrended fluctuation analysis (DFA) is a method for determining the statistical self-affinity of a signal. It is useful for analyzing time series that appear to be long-memory processes and noise.
█ OVERVIEW
We have introduced the concept of Hurst Exponent in our previous open indicator Hurst Exponent (Simple). It is an indicator that measures market state from autocorrelation. However, we apply a more advanced and accurate way to calculate Hurst Exponent rather than simple approximation. Therefore, we recommend using this version of Hurst Exponent over our previous publication going forward. The method we used here is called detrended fluctuation analysis. (For folks that are not interested in the math behind the calculation, feel free to skip to "features" and "how to use" section. However, it is recommended that you read it all to gain a better understanding of the mathematical reasoning).
█ Detrend Fluctuation Analysis
Detrended Fluctuation Analysis was first introduced by by Peng, C.K. (Original Paper) in order to measure the long-range power-law correlations in DNA sequences . DFA measures the scaling-behavior of the second moment-fluctuations, the scaling exponent is a generalization of Hurst exponent.
The traditional way of measuring Hurst exponent is the rescaled range method. However DFA provides the following benefits over the traditional rescaled range method (RS) method:
• Can be applied to non-stationary time series. While asset returns are generally stationary, DFA can measure Hurst more accurately in the instances where they are non-stationary.
• According the the asymptotic distribution value of DFA and RS, the latter usually overestimates Hurst exponent (even after Anis- Llyod correction) resulting in the expected value of RS Hurst being close to 0.54, instead of the 0.5 that it should be. Therefore it's harder to determine the autocorrelation based on the expected value. The expected value is significantly closer to 0.5 making that threshold much more useful, using the DFA method on the Hurst Exponent (HE).
• Lastly, DFA requires lower sample size relative to the RS method. While the RS method generally requires thousands of observations to reduce the variance of HE, DFA only needs a sample size greater than a hundred to accomplish the above mentioned.
█ Calculation
DFA is a modified root-mean-squares (RMS) analysis of a random walk. In short, DFA computes the RMS error of linear fits over progressively larger bins (non-overlapped “boxes” of similar size) of an integrated time series.
Our signal time series is the log returns. First we subtract the mean from the log return to calculate the demeaned returns. Then, we calculate the cumulative sum of demeaned returns resulting in the cumulative sum being mean centered and we can use the DFA method on this. The subtraction of the mean eliminates the “global trend” of the signal. The advantage of applying scaling analysis to the signal profile instead of the signal, allows the original signal to be non-stationary when needed. (For example, this process converts an i.i.d. white noise process into a random walk.)
We slice the cumulative sum into windows of equal space and run linear regression on each window to measure the linear trend. After we conduct each linear regression. We detrend the series by deducting the linear regression line from the cumulative sum in each windows. The fluctuation is the difference between cumulative sum and regression.
We use different windows sizes on the same cumulative sum series. The window sizes scales are log spaced. Eg: powers of 2, 2,4,8,16... This is where the scale free measurements come in, how we measure the fractal nature and self similarity of the time series, as well as how the well smaller scale represent the larger scale.
As the window size decreases, we uses more regression lines to measure the trend. Therefore, the fitness of regression should be better with smaller fluctuation. It allows one to zoom into the “picture” to see the details. The linear regression is like rulers. If you use more rulers to measure the smaller scale details you will get a more precise measurement.
The exponent we are measuring here is to determine the relationship between the window size and fitness of regression (the rate of change). The more complex the time series are the more it will depend on decreasing window sizes (using more linear regression lines to measure). The less complex or the more trend in the time series, it will depend less. The fitness is calculated by the average of root mean square errors (RMS) of regression from each window.
Root mean Square error is calculated by square root of the sum of the difference between cumulative sum and regression. The following chart displays average RMS of different window sizes. As the chart shows, values for smaller window sizes shows more details due to higher complexity of measurements.
The last step is to measure the exponent. In order to measure the power law exponent. We measure the slope on the log-log plot chart. The x axis is the log of the size of windows, the y axis is the log of the average RMS. We run a linear regression through the plotted points. The slope of regression is the exponent. It's easy to see the relationship between RMS and window size on the chart. Larger RMS equals less fitness of the regression. We know the RMS will increase (fitness will decrease) as we increases window size (use less regressions to measure), we focus on the rate of RMS increasing (how fast) as window size increases.
If the slope is < 0.5, It means the rate of of increase in RMS is small when window size increases. Therefore the fit is much better when it's measured by a large number of linear regression lines. So the series is more complex. (Mean reversion, negative autocorrelation).
If the slope is > 0.5, It means the rate of increase in RMS is larger when window sizes increases. Therefore even when window size is large, the larger trend can be measured well by a small number of regression lines. Therefore the series has a trend with positive autocorrelation.
If the slope = 0.5, It means the series follows a random walk.
█ FEATURES
• Sample Size is the lookback period for calculation. Even though DFA requires a lower sample size than RS, a sample size larger > 50 is recommended for accurate measurement.
• When a larger sample size is used (for example = 1000 lookback length), the loading speed may be slower due to a longer calculation. Date Range is used to limit numbers of historical calculation bars. When loading speed is too slow, change the data range "all" into numbers of weeks/days/hours to reduce loading time. (Credit to allanster)
• “show filter” option applies a smoothing moving average to smooth the exponent.
• Log scale is my work around for dynamic log space scaling. Traditionally the smallest log space for bars is power of 2. It requires at least 10 points for an accurate regression, resulting in the minimum lookback to be 1024. I made some changes to round the fractional log space into integer bars requiring the said log space to be less than 2.
• For a more accurate calculation a larger "Base Scale" and "Max Scale" should be selected. However, when the sample size is small, a larger value would cause issues. Therefore, a general rule to be followed is: A larger "Base Scale" and "Max Scale" should be selected for a larger the sample size. It is recommended for the user to try and choose a larger scale if increasing the value doesn't cause issues.
The following chart shows the change in value using various scales. As shown, sometimes increasing the value makes the value itself messy and overshoot.
When using the lowest scale (4,2), the value seems stable. When we increase the scale to (8,2), the value is still alright. However, when we increase it to (8,4), it begins to look messy. And when we increase it to (16,4), it starts overshooting. Therefore, (8,2) seems to be optimal for our use.
█ How to Use
Similar to Hurst Exponent (Simple). 0.5 is a level for determine long term memory.
• In the efficient market hypothesis, market follows a random walk and Hurst exponent should be 0.5. When Hurst Exponent is significantly different from 0.5, the market is inefficient.
• When Hurst Exponent is > 0.5. Positive Autocorrelation. Market is Trending. Positive returns tend to be followed by positive returns and vice versa.
• Hurst Exponent is < 0.5. Negative Autocorrelation. Market is Mean reverting. Positive returns trends to follow by negative return and vice versa.
However, we can't really tell if the Hurst exponent value is generated by random chance by only looking at the 0.5 level. Even if we measure a pure random walk, the Hurst Exponent will never be exactly 0.5, it will be close like 0.506 but not equal to 0.5. That's why we need a level to tell us if Hurst Exponent is significant.
So we also computed the 95% confidence interval according to Monte Carlo simulation. The confidence level adjusts itself by sample size. When Hurst Exponent is above the top or below the bottom confidence level, the value of Hurst exponent has statistical significance. The efficient market hypothesis is rejected and market has significant inefficiency.
The state of market is painted in different color as the following chart shows. The users can also tell the state from the table displayed on the right.
An important point is that Hurst Value only represents the market state according to the past value measurement. Which means it only tells you the market state now and in the past. If Hurst Exponent on sample size 100 shows significant trend, it means according to the past 100 bars, the market is trending significantly. It doesn't mean the market will continue to trend. It's not forecasting market state in the future.
However, this is also another way to use it. The market is not always random and it is not always inefficient, the state switches around from time to time. But there's one pattern, when the market stays inefficient for too long, the market participants see this and will try to take advantage of it. Therefore, the inefficiency will be traded away. That's why Hurst exponent won't stay in significant trend or mean reversion too long. When it's significant the market participants see that as well and the market adjusts itself back to normal.
The Hurst Exponent can be used as a mean reverting oscillator itself. In a liquid market, the value tends to return back inside the confidence interval after significant moves(In smaller markets, it could stay inefficient for a long time). So when Hurst Exponent shows significant values, the market has just entered significant trend or mean reversion state. However, when it stays outside of confidence interval for too long, it would suggest the market might be closer to the end of trend or mean reversion instead.
Larger sample size makes the Hurst Exponent Statistics more reliable. Therefore, if the user want to know if long term memory exist in general on the selected ticker, they can use a large sample size and maximize the log scale. Eg: 1024 sample size, scale (16,4).
Following Chart is Bitcoin on Daily timeframe with 1024 lookback. It suggests the market for bitcoin tends to have long term memory in general. It generally has significant trend and is more inefficient at it's early stage.
Chandelier Exit + Pivots + MA + Swing High/LowIt combines four indicators.
For use in the Hero course.
Advanced S&D Engine | ZikZak-Trader30About This Script
This is a fully custom-built Supply & Demand Zone detection engine for TradingView written by ZikZak-Trader30 (Kotdwar, UK). The script identifies potential key supply and demand zones based on market structure and pattern logic widely used by professional traders.
Detected Patterns:
RBR (Rally-Base-Rally, demand)
DBD (Drop-Base-Drop, supply)
RBD (Rally-Base-Drop, supply)
DBR (Drop-Base-Rally, demand)
Features Highlight
Detailed configurable zone filtering (freshness, gap detection, time spent, width, Fibonacci confluence, etc.)
Fair and adjustable scoring system for zone strength
Automatic management/removal of old or retested/violated zones
Optional Fibonacci level confluence and dynamic labeling
Transparency Statement
How It Works:
This script uses well-known price action concepts and compares candles’ movement, consolidation, and breakout patterns to mark S&D zones.
There are no repaints or future leaks: all logic is based entirely on historical and current bars.
Parameters and variables are fully described in the script inputs. The zone scoring and removal logic is also visible in the code for transparency.
IMPORTANT: Usage & Fair-Use Policy
This script is provided for educational and informational purposes only.
It should not be considered as financial advice or a trading signal.
Trading/investing involves risk—always do your own research or consult a financial advisor before making trading decisions.
Past performance or backtest results are not necessarily indicative of future results.
License & Fair Use
The code is original, written by ZikZak-Trader30.
All logic and comments are visible for users to study, adapt, or improve for personal, non-commercial use within TradingView.
You may NOT resell, repackage, or repost this script as your own.
If you fork or publicly remix/adapt the script, please credit "ZikZak-Trader30" and do not remove this disclosure section.
If you use ideas or snippets, kindly reference this script and author.
Absolutely NO plagiarized or resold code is permitted. This script is not for re-sale.
Acknowledgements
This indicator was inspired by years of price action study and usage of public S&D scripts. While the pattern logic is classic in nature, the version and scoring are original.
No proprietary datasets or paid logic from other sources are included.
Minor ideas on zone freshness and Fibonacci blending are common in the TradingView S&D community and have been custom-implemented here.
THF Scalp & Trend + FVG [English]This indicator is a comprehensive "All-In-One" trading suite designed for Scalpers and Day Traders who look for confluence between Trend Following indicators and Price Action (Fair Value Gaps).
It combines two powerful concepts into a single chart overlay:
1. Moving Average Crossovers & Trend Filtering (THF Logic).
2. Fair Value Gaps (FVG) detection for entry/exit targets.
### 🛠️ Key Features:
**1. Trend & Scalp Signals:**
- **Scalp Signals:** Based on fast EMA crossovers (default 7/21). These signals can be filtered by a long-term SMA (200) to ensure you are trading with the major trend.
- **Trend Signals:** Identifies stronger trend shifts using EMA 21 crossing SMA 50.
- **Major Crosses:** Automatically highlights Golden Cross (SMA 50 > 200) and Death Cross events.
**2. Price Action (FVG - Fair Value Gaps):**
- Integrated **LuxAlgo's Fair Value Gap** logic to identify imbalances in the market.
- Displays Bullish/Bearish zones which act as magnets for price or support/resistance levels.
- Includes a Dashboard to track mitigated vs. unmitigated zones.
**3. Momentum & Volume Confluence:**
- **Visual Volume:** Candles are colored based on volume relative to the average (Volume SMA).
- **RSI & MACD Signals:** Optional overlays to spot overbought/oversold conditions or momentum shifts directly on the chart.
### 🎯 How to Use:
- **For Scalping:** Wait for a "SCALP BUY" signal while the price is above the SMA 200 (Trend Filter). Use the FVG boxes as potential Take Profit targets.
- **For Trend Trading:** Look for the "Trend BUY" label and confirm with the Golden Cross.
- **Stop Loss:** Can be placed below the recent swing low or below the EMA 50.
----------------------------------------------------------------
**CREDITS & ATTRIBUTION:**
This script is a mashup of custom trend logic and open-source community codes.
- **Fair Value Gap:** Full credit goes to **LuxAlgo** for the FVG detection algorithm and dashboard logic. This script utilizes their open-source calculation methods to enhance the trend strategy.
- **Trend Logic:** Based on classic Moving Average crossover strategies tailored for scalping.
*Disclaimer: This tool is for educational purposes only. Always manage your risk.*
Alper-EMAAlper-EMA
Description:
This indicator allows you to display 5 customizable EMAs (Exponential Moving Averages) on a single chart. Each EMA can be configured independently with length, color, visibility, and calculation timeframe.
Features:
5 fully customizable EMAs
Set individual length and color for each EMA
Toggle visibility for each EMA
Multi-timeframe calculation: e.g., display EMA300 calculated on a 30-minute timeframe while viewing a 1-minute chart
Labels display EMA period and timeframe for clarity
Adjustable label size: tiny / small / normal / large
Clear and readable plot lines
Use Cases:
Monitor multiple timeframe EMAs simultaneously
Analyze trend and support/resistance levels
Track EMA crossovers for strategy development
Note:
This indicator is suitable for both short-term (scalping) and medium-to-long term analysis. The multi-timeframe feature allows you to see different EMA perspectives on a single chart quickly.
Relative Strength Heatmap [BackQuant]Relative Strength Heatmap
A multi-horizon RSI matrix that compresses 20 different lookbacks into a single panel, turning raw momentum into a visual “pressure gauge” for overbought and oversold clustering, trend exhaustion, and breadth of participation across time horizons.
What this is
This indicator builds a strip-style heatmap of 20 RSIs, each with a different length, and stacks them vertically as colored tiles in a single pane. Every tile is colored by its RSI value using your chosen palette, so you can see at a glance:
How many “fast” versus “slow” RSIs are overbought or oversold.
Whether momentum is concentrated in the short lookbacks or spread across the whole curve.
When momentum extremes cluster, signalling strong market pressure or exhaustion.
On top of the tiles, the script plots two simple breadth lines:
A white line that counts how many RSIs are above 70 (overbought cluster).
A black line that counts how many RSIs are below 30 (oversold cluster).
This turns a single symbol’s RSI ladder into a compact “market pressure gauge” that shows not only whether RSI is overbought or oversold, but how many different horizons agree at the same time.
Core idea
A single RSI looks at one length and one timescale. Markets, however, are driven by flows that operate on multiple horizons at once. By computing RSI over a ladder of lengths, you approximate a “term structure” of strength:
Short lengths react to immediate swings and very recent impulses.
Medium lengths reflect swing behaviour and local trends.
Long lengths reflect structural bias and higher timeframe regime.
When many lengths agree, for example 10 or more RSIs all above 70, it suggests broad participation and strong directional pressure. When only a few fast lengths stretch to extremes while longer ones stay neutral, the move is more fragile and more likely to mean-revert.
This script makes that structure visible as a heatmap instead of forcing you to run many separate RSI panes.
How it works
1) Generating RSI lengths
You control three parameters in the calculation settings:
RS Period – the base RSI length used for the shortest strip.
RSI Step – the amount added to each successive RSI length.
RSI Multiplier – a global scaling factor applied after the step.
Each of the 20 RSIs uses:
RSI length = round((base_length + step × index) × multiplier) , where the index goes from 0 to 19.
That means:
RSI 1 uses (len + step × 0) × mult.
RSI 2 uses (len + step × 1) × mult.
…
RSI 20 uses (len + step × 19) × mult.
You can keep the ladder dense (small step and multiplier) or stretch it across much longer horizons.
2) Heatmap layout and grouping
Each RSI is plotted as an “area” strip at a fixed vertical level using histbase to stack them:
RSI 1–5 form Group 1.
RSI 6–10 form Group 2.
RSI 11–15 form Group 3.
RSI 16–20 form Group 4.
Each group has a toggle:
Show only Group 1 and 2 if you care mainly about fast and medium horizons.
Show all groups for a full spectrum from very short to very long.
Hide any group that feels redundant for your workflow.
The actual numeric RSI values are not plotted as lines. Instead, each strip is drawn as a horizontal band whose fill color represents the current RSI regime.
3) Palette-based coloring
Each tile’s color is driven by the RSI value and your chosen palette. The script includes several palettes:
Viridis – smooth green to yellow, good for subtle reading.
Jet – strong blue to red sequence with high contrast.
Plasma – purple through orange to yellow.
Custom Heat – cool blues to neutral grey to hot reds.
Gray – grayscale from white to black for minimalistic layouts.
Cividis, Inferno, Magma, Turbo, Rainbow – additional scientific and rainbow-style maps.
Internally, RSI values are bucketed into ranges (for example, below 10, 10–20, …, 90–100). Each bucket maps to a unique colour for that palette. In all schemes, low RSI values are mapped to the “cold” or darker side and high RSI values to the “hot” or brighter side.
The result is a true momentum heatmap:
Cold or dark tiles show low RSI and oversold or compressed conditions.
Mid tones show neutral or mid-range RSI.
Warm or bright tiles show high RSI and overbought or stretched conditions.
4) Bull and bear breadth counts
All 20 RSI values are collected into an array each bar. Two counters are then calculated:
Bull count – how many RSIs are above 70.
Bear count – how many RSIs are below 30.
These are plotted as:
A white line (“RSI > 70 Count”) for the overbought cluster.
A black line (“RSI < 30 Count”) for the oversold cluster.
If you enable the “Show Bull and Bear Count” option, you get an immediate reading of how many of the 20 horizons are stretched at any moment.
5) Cluster alerts and background tagging
Two alert conditions monitor “strong cluster” regimes:
RSI Heatmap Strong Bull – triggers when at least 10 RSIs are above 70.
RSI Heatmap Strong Bear – triggers when at least 10 RSIs are below 30.
When one of these conditions is true, the indicator can tint the background of the chart using a soft version of the current palette. This visually marks stretches where momentum is extreme across many lengths at once, not just on a single RSI.
What it plots
In one oscillator window, the indicator provides:
Up to 20 horizontal RSI strips, each representing a different RSI length.
Color-coded tiles reflecting the current RSI value for each length.
Group toggles to show or hide each block of five RSIs.
An optional white line that counts how many RSIs are above 70.
An optional black line that counts how many RSIs are below 30.
Optional background highlights when the number of overbought or oversold RSIs passes the strong-cluster threshold.
How it measures breadth and pressure
Single-symbol breadth
Breadth is usually defined across a basket of symbols, such as how many stocks advance versus decline. This indicator uses the same concept across time horizons for a single symbol. The question becomes:
“How many different RSI lengths are stretched in the same direction at once?”
Examples:
If only 2 or 3 of the shortest RSIs are above 70, bull count stays low. The move is fast and local, but not yet broadly supported.
If 12 or more RSIs across short, medium and long lengths are above 70, the bull count spikes. The move has broad momentum and strong upside pressure.
If 10 or more RSIs are below 30, bear count spikes and you are in a broad oversold regime.
This is breadth of momentum within one market.
Market pressure gauge
The combination of heatmap tiles and breadth lines acts as a pressure gauge:
High bull count with warm colors across most strips indicates strong upside pressure and crowded long positioning.
High bear count with cold colors across most strips indicates strong downside pressure and capitulation or forced selling.
Low counts with a mixed heatmap indicate neutral pressure, fragmented flows, or range-bound conditions.
You can treat the strong-cluster alerts as “extreme pressure” signals. When they fire, the market is heavily skewed in one direction across many horizons.
How to read the heatmap
Horizontal patterns (through time)
Look along the time axis and watch how the colors evolve:
Persistent hot tiles across many strips show sustained bullish pressure and trend strength.
Persistent cold tiles across many strips show sustained bearish pressure and weak demand.
Frequent flipping between hot and cold colours indicates a choppy or mean-reverting environment.
Vertical structure (across lengths at one bar)
Focus on a single bar and read the column of tiles from top to bottom:
Short RSIs hot, long RSIs neutral or cool: early trend or short-term fomo. Price has moved fast, longer horizons have not caught up.
Short and long RSIs all hot: mature, entrenched uptrend. Broad participation, high pressure, greater risk of blow-off or late-entry vulnerability.
Short RSIs cold but long RSIs mid to high: pullback in a higher timeframe uptrend. Dip-buy and continuation setups are often found here.
Short RSIs high but long RSIs low: countertrend rallies within a broader downtrend. Good hunting ground for fades and short entries after a bounce.
Bull and bear breadth lines
Use the two lines as simple, numeric breadth indicators:
A rising white line shows more RSIs pushing above 70, so bullish pressure is expanding in breadth.
A rising black line shows more RSIs pushing below 30, so bearish pressure is expanding in breadth.
When both lines are low and flat, few horizons are extreme and the market is in mid-range territory.
Cluster zones
When either count crosses the strong threshold (for example 10 out of 20 RSIs in extreme territory):
A strong bull cluster marks a broadly overbought regime. Trend followers may see this as confirmation. Mean-reversion traders may see it as a late-stage or blow-off context.
A strong bear cluster marks a broadly oversold regime. Downtrend traders see strong pressure, but the risk of sharp short-covering bounces also increases.
Trading applications
Trend confirmation
Use the heatmap and breadth lines as a trend filter:
Prefer long setups when the heatmap shows mostly mid to high RSIs and the bull count is rising.
Avoid fresh shorts when there is a strong bull cluster, unless you are specifically trading exhaustion.
Prefer short setups when the heatmap is mostly low RSIs and the bear count is rising.
Avoid aggressive longs when a strong bear cluster is active, unless you are trading reflexive bounces.
Mean-reversion timing
Treat cluster extremes as exhaustion zones:
Look for reversal patterns, failed breakouts, or order flow shifts when bull count is very high and price starts to stall or diverge.
Look for reflexive bounce potential when bear count is very high and price stops making new lows or shows absorption at the lows.
Use the palette and counts together: hot tiles plus a peaking white line can mark blow-off conditions, cold tiles plus a peaking black line can mark capitulation.
Regime detection and risk toggling
Use the overall shape of the ladder over time:
If upper strips stay warm and lower strips stay neutral or warm for extended periods, the market is in an uptrend regime. You can justify higher risk for long-biased strategies.
If upper strips stay cold and lower strips stay neutral or cold, the market is in a downtrend regime. You can justify higher risk for short-biased strategies or defensive positioning.
If colours and counts flip frequently, you are likely in a range or choppy regime. Consider reducing size or using more tactical, short-term strategies.
Multi-horizon synchronization
You can think of each RSI length as a proxy for a different “speed” of the same market:
When only fast RSIs are stretched, the move is local and less robust.
When fast, medium and slow RSIs align, the move has multi-horizon confirmation.
You can require a minimum bull or bear count before allowing your main strategy to engage.
Spotting hidden shifts
Sometimes price appears flat or drifting, but the heatmap quietly cools or warms:
If price is sideways while many hot tiles fade toward neutral, momentum is decaying under the surface and trend risk is increasing.
If price is sideways while many cold tiles climb back toward neutral, selling pressure is decaying and the tape is repairing itself.
Settings overview
Calculation Settings
RS Period – base RSI length for the shortest strip.
RSI Step – the increment added to each successive RSI length.
RSI Multiplier – scales all generated RSI lengths.
Calculation Source – the input series, such as close, hlc3 or others.
Plotting and Coloring Settings
Heatmap Color Palette – choose between Viridis, Jet, Plasma, Custom Heat, Gray, Cividis, Inferno, Magma, Turbo or Rainbow.
Show Group 1 – toggles RSI 1–5.
Show Group 2 – toggles RSI 6–10.
Show Group 3 – toggles RSI 11–15.
Show Group 4 – toggles RSI 16–20.
Show Bull and Bear Count – enables or disables the two breadth lines.
Alerts
RSI Heatmap Strong Bull – fires when the number of RSIs above 70 reaches or exceeds the configured threshold (default 10).
RSI Heatmap Strong Bear – fires when the number of RSIs below 30 reaches or exceeds the configured threshold (default 10).
Tuning guidance
Fast, tactical configurations
Use a small base RS Period, for example 2 to 5.
Use a small RSI Step, for tight clustering around the fast horizon.
Keep the multiplier near 1.0 to avoid extreme long lengths.
Focus on Group 1 and Group 2 for intraday and short-term trading.
Swing and position configurations
Use a mid-range RS Period, for example 7 to 14.
Use a moderate RSI Step to fan out into slower horizons.
Optionally use a multiplier slightly above 1.0.
Keep all four groups enabled for a full view from fast to slow.
Macro or higher timeframe configurations
Use a larger base RS Period.
Use a larger RSI Step so the top of the ladder reaches very slow lengths.
Focus on Group 3 and Group 4 to see structural momentum.
Treat clusters as regime markers rather than frequent trading signals.
Notes
This indicator is a contextual tool, not a standalone trading system. It does not model execution, spreads, slippage or fundamental drivers. Use it to:
Understand whether momentum is narrow or broad across horizons.
Confirm or filter existing signals from your primary strategy.
Identify environments where the market is crowded into one side.
Distinguish between isolated spikes and truly broad pressure moves.
The Relative Strength Heatmap is designed to answer a simple but powerful question:
“How many versions of RSI agree with what I am seeing on the chart?”
By compressing those answers into a single panel with clear colour coding and breadth lines, it becomes a practical, visual gauge of momentum breadth and market pressure that you can overlay on any trading framework.
MFM – Light Context HUD (Minimal)Overview
MFM Light Context HUD is the free version of the Market Framework Model. It gives you a fast and clean view of the current market regime and phase without signals or chart noise. The HUD shows whether the asset is in a bullish or bearish environment and whether it is in a volatile, compression, drift, or neutral phase. This helps you read structure at a glance.
Asset availability
The free version works only on a selected list of five assets.
Supported symbols are
SP:SPX
TVC:GOLD
BINANCE:BTCUSD
BINANCE:ETHUSDT
OANDA:EURUSD
All other assets show a context banner only.
How it works
The free version uses fixed settings based on the original MFM model. It calculates the regime using a higher timeframe RSI ratio and identifies the current phase using simplified momentum conditions. The chart stays clean. Only a small HUD appears in the top corner. Full visual phases, ratio logic, signals, and auto tune are part of the paid version.
The free version shows the phase name only. It does not display colored phase zones on the chart.
Phase meaning
The Market Framework Model uses four structural phases to describe how the market
behaves. These are not signals but context layers that show the underlying environment.
Volatile (Phase 1)
The market is in a fast, unstable or directional environment. Price can move aggressively with
stronger momentum swings.
Compression (Phase 2)
The market is in a contracting state. Momentum slows and volatility decreases. This phase
often appears before expansion, but it does not predict direction.
Drift (Phase 3)
The market moves in a more controlled, persistent manner. Trends are cleaner and volatility
is lower compared to volatile phases.
No phase
No clear structural condition is active.
These phases describe market structure, not trade entries. They help you understand the conditions you are trading in.
Cross asset context
The Market Framework Model reads markets as a multi layer system. The full version includes cross asset analysis to show whether the asset is acting as a leader or lagger relative to its benchmark. The free version uses the same internal benchmark logic for regime detection but does not display the cross asset layer on the chart.
Cross asset structure is a core part of the MFM model and is fully available in the paid version.
Included in this free version
Higher timeframe regime
Current phase name
Clean chart output
Context only
Works on a selected set of assets
Not included
No forecast signals
No ratio leader or lagger logic
No MRM zones
No MPF timing
No auto tune
The full version contains all features of the complete MFM model.
Full version
You can find the full indicator here:
payhip.com
More information
Model details and documentation:
mfm.inratios.com
Momentum Framework Model free HUD indicator User Guide: mfm.inratios.com
Disclaimer
The Market Framework Model (MFM) and all related materials are provided for educational and informational purposes only. Nothing in this publication, the indicator, or any associated charts should be interpreted as financial advice, investment recommendations, or trading signals. All examples, visualizations, and backtests are illustrative and based on historical data. They do not guarantee or imply any future performance. Financial markets involve risk, including the potential loss of capital, and users remain fully responsible for their own decisions. The author and Inratios© make no representations or warranties regarding the accuracy, completeness, or reliability of the information provided. MFM describes structural market context only and should not be used as the sole basis for trading or investment actions.
By using the MFM indicator or any related insights, you agree to these terms.
© 2025 Inratios. Market Framework Model (MFM) is protected via i-Depot (BOIP) – Ref. 155670. No financial advice.
EMA Percent Angle & Slope VisualizerEMA Percent Angle & Slope Visualizer is a powerful trend-strength tool that measures the true geometric slope of an EMA using percent-normalized angle calculations.
Unlike raw angle or ATR-based angle methods, this indicator uses the formula:
angle = atan( (EMA_t - EMA_(t-1)) / EMA_(t-1) ) * (180 / pi)
This gives you a universal slope measurement that works across stocks, indices, currencies, and crypto — regardless of price scale.
🔍 Features
Percent-normalized EMA angle for accurate trend strength
Auto-detected slope segments
Dynamic EMA color
🟢 Bullish slope
🔴 Bearish slope
⚪ Neutral (angle below threshold)
Dashed slope lines drawn only during valid slope runs
Angle label displayed at slope end
Works on any timeframe
Designed for momentum traders, trend followers, breakout traders, and algo developers
📌 Why Percent-Normalized Angle?
Raw price angle is meaningless because angles depend on chart scaling.
Percent-normalized angle gives a true slope, equal across all instruments.
✔ Tip
Slopes above +0.15° and below –0.15° represent strong trend phases for Nifty.
Adjust threshold for your timeframe according to your script
Viprasol Elite Flow Pro - Premium Order Flow & Trend System═══════════════════════════════════════════════════════════════
🔥 VIPRASOL ELITE FLOW PRO
Professional Order Flow & Trend Detection System
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📊 WHAT IS THIS INDICATOR?
Viprasol Elite Flow Pro is a comprehensive trading system that combines institutional order flow analysis with adaptive trend detection. Unlike basic indicators, this tool identifies high-probability setups by analyzing where smart money is likely positioning, while filtering signals through multiple confirmation layers.
This indicator is designed for traders who want to:
✓ Identify premium (supply) and discount (demand) zones automatically
✓ Detect trend direction with adaptive cloud technology
✓ Spot high-volume rejection points before major moves
✓ Filter low-quality signals with intelligent confirmation logic
✓ Track market strength in real-time via elite dashboard
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🎯 CORE FEATURES
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1️⃣ ELITE TREND ENGINE
• Adaptive Moving Average system (Fast/Adaptive/Smooth modes)
• Dynamic trend cloud that expands/contracts with volatility
• Real-time trend state tracking (Bullish/Bearish/Ranging)
• Trend strength meter (0-10 scale)
• ATR-based volatility adjustments
2️⃣ ORDER FLOW DETECTION
• Automatic Premium Zone (Supply) identification
• Automatic Discount Zone (Demand) identification
• Smart zone extension - zones remain valid until broken
• Zone rejection detection with price action confirmation
• Customizable zone strength (5-30 bars lookback)
3️⃣ VOLUME INTELLIGENCE
• Volume spike detection (configurable threshold)
• Climax bar identification (exhaustion signals)
• Volume filter for signal validation
• Institutional activity detection
4️⃣ SMART SIGNAL SYSTEM
• 3 Signal Modes: Aggressive, Balanced, Conservative
• Multi-layer confirmation logic
• Automatic profit targets (2:1 risk-reward)
• Stop loss suggestions based on ATR
• Prevents overtrading with bars-since-signal filter
5️⃣ ELITE DASHBOARD (HUD)
• Real-time trend direction and strength
• Volume status monitoring
• Active zones counter
• Market volatility gauge
• Current signal status
• 4 positioning options, compact mode available
6️⃣ PREMIUM STYLING
• 4 Professional color themes (Cyber/Gold/Ocean/Fire)
• Adjustable transparency and label sizes
• Clean, institutional-grade visuals
• Optimized for all chart types
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📖 HOW TO USE THIS INDICATOR
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STEP 1: TREND IDENTIFICATION
→ Green Cloud = Bullish trend - look for LONG opportunities
→ Red Cloud = Bearish trend - look for SHORT opportunities
→ Purple Cloud = Ranging - wait for breakout or fade extremes
STEP 2: ZONE ANALYSIS
→ PREMIUM (Red) zones = Potential resistance/supply areas
→ DISCOUNT (Green) zones = Potential support/demand areas
→ Price rejecting from zones = high-probability setups
STEP 3: SIGNAL CONFIRMATION
→ Wait for "LONG" or "SHORT" labels to appear
→ Check dashboard for trend strength (Moderate/Strong preferred)
→ Confirm volume status is "HIGH" or "CLIMAX"
→ Entry: Enter when label appears
→ Stop Loss: Use dotted line (1 ATR away)
→ Take Profit: Use dashed line (2 ATR away)
STEP 4: RISK MANAGEMENT
→ Never risk more than 1-2% per trade
→ Use the provided stop loss levels
→ Trail stops as price moves in your favor
→ Avoid trading during low volatility periods
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⚙️ RECOMMENDED SETTINGS
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FOR SCALPING (1M - 5M):
- Trend Type: Fast
- Sensitivity: 15
- Signal Mode: Aggressive
- Zone Strength: 8
FOR DAY TRADING (15M - 1H):
- Trend Type: Adaptive
- Sensitivity: 21 (default)
- Signal Mode: Balanced
- Zone Strength: 12 (default)
FOR SWING TRADING (4H - Daily):
- Trend Type: Smooth
- Sensitivity: 34
- Signal Mode: Conservative
- Zone Strength: 20
BEST MARKETS:
✓ Crypto (BTC, ETH, major altcoins)
✓ Forex (Major pairs: EUR/USD, GBP/USD)
✓ Indices (S&P 500, NASDAQ, DAX)
✓ High-liquidity stocks
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🎓 UNDERSTANDING THE METHODOLOGY
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This indicator is built on three core concepts:
1. ORDER FLOW THEORY
Markets move between premium (expensive) and discount (cheap) zones. Smart money accumulates in discount zones and distributes in premium zones. This indicator identifies these zones automatically.
2. ADAPTIVE TREND FOLLOWING
Unlike fixed-period moving averages, the Elite Trend Engine adjusts to current market volatility, providing more accurate trend signals in both trending and ranging conditions.
3. CONFLUENCE-BASED ENTRIES
Signals only trigger when multiple conditions align:
- Price in correct zone (premium for shorts, discount for longs)
- Trend confirmation (cloud color matches direction)
- Volume validation (spike or climax present)
- Price action strength (strong rejection candles)
This multi-layer approach dramatically reduces false signals.
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🔔 ALERT SETUP
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This indicator includes 5 alert types:
1. Long Signal → Triggers when buy conditions met
2. Short Signal → Triggers when sell conditions met
3. Volume Climax → Warns of pot
ICT Fair Value Gap (FVG) Detector │ Auto-Mitigated │ 2025Accurate ICT / Smart Money Concepts Fair Value Gap (FVG) detector
Features:
• Detects both Bullish (-FVG) and Bearish (+FVG) using strict 3-candle rule
• Boxes automatically extend right until price mitigates them
• Boxes auto-delete when price closes inside the gap (true mitigation)
• No repainting – 100% reliable
• Clean, lightweight, and works on all markets & timeframes
• Fully customizable colors and transparency
How to use:
– Bullish FVG (green) = potential support / buy zone in uptrend
– Bearish FVG (red) = potential resistance / sell zone in downtrend
Exactly matches The Inner Circle Trader (ICT) methodology used by thousands of SMC traders in 2024–2025.
Enjoy and trade safe!
[CT] Donchian Histogram w/Candle ColorsDonchian Histogram, originally created by RafaelZioni and enhanced with optional price bar coloring, is a momentum-style oscillator that shows where the current close sits inside a dynamic Donchian channel and how that position is evolving over time. The script calculates a rolling high and low over a multi-session lookback period based on your chosen Donchian timeframe, then normalizes the close within that range to create a percentage position between the recent high and low. This normalized value is smoothed with a signal length and plotted as a histogram around a zero line, making it easy to see whether price is pressing toward the upper side of its recent range, the lower side, or oscillating near the middle. Positive values indicate that price is trading closer to the Donchian high, negative values indicate price is closer to the Donchian low, and the magnitude of the histogram reflects how strongly price is favoring one side of the range. The color logic highlights this state visually: stronger positive conditions can be shown in teal, moderate positive conditions in lime, stronger negative conditions in red, and neutral or transitional states in orange. The script also includes an option to color the actual chart candles with the same colors as the histogram, so traders can see Donchian-based pressure directly on the main price chart without constantly looking down at the lower pane. The indicator works on completed bars using standard highest/lowest and moving average functions, so it behaves like a normal oscillator and does not use any lookahead tricks. It is best used as a contextual tool to gauge whether price is pushing to the edges of its recent range or reverting toward balance, and to visually synchronize that information with candle colors when desired.
Relative Volume EMA (RVOL)Relative Volume EMA (RVOL) measures the current bar’s volume relative to its typical volume over a selected lookback period.
It helps traders identify whether a price move is supported by real participation or if it’s occurring on weak, low-quality volume.
This version uses:
RVOL = Current Volume ÷ Volume EMA
Volume EMA Length: adjustable
Signal Threshold: a customizable horizontal line (default = 1.2)
How to Use
1. RVOL > 1.2 → High-Quality Momentum
A value above 1.2 indicates that the current bar has at least 20% more volume than normal, suggesting:
Strong conviction
Algorithmic activity
Momentum-backed breakout or breakdown
Higher probability trend continuation
These bars are ideal for confirming entries after a technical setup (e.g., pullback, engulfing pattern, Ichimoku trend confirmation, etc.).
2. RVOL < 1.0 → Weak or Low-Quality Move
When RVOL is below 1.0:
Volume is below average
Moves are more likely to fail or reverse
Breakouts are unreliable
Triggers lack institutional participation
These bars are best avoided for trade entries.
Why This Indicator Is Useful
In many strategies, price alone is not enough.
RVOL acts as a filter to ensure that your signals occur during times when the market is actually active and committed.
Typical use cases:
Confirm trend-following entries
Validate pullbacks and breakout candles
Filter out low-volume chop
Identify session-based volume surges
Improve risk-to-reward quality by entering only during true momentum
Recommended Settings
EMA Length: 20
Threshold Line: 1.2
Works well on Forex, Crypto, and Indices
Best used on 15m, 30m, 1H, and 4H charts
Regime MapRegime Map — Volatility State Detector
This indicator is a PineScript friendly approximation of a more advanced Python regime-analysis engine.
The original backed identifies market regimes using structural break detection, Hidden-Markov Models, wavelet decomposition, and long-horizon volatility clustering. Since Pine Script cannot execute these statistical models directly, this version implements a lightweight, real-time proxy using realised volatility and statistical thresholds.
The purpose is to provide a clear visual map of evolving volatility conditions without requiring any heavy offline computation.
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Mathematical Basis: Python vs Pine
1. Volatility Estimation
Python (Realised Volatility):
RVₜ = √N × stdev( log(Pₜ) − log(Pₜ₋₁) )
Pine Approximation:
RVₜ = stdev( log(Pₜ) − log(Pₜ₋₁), lookback )
Rationale:
Realised volatility captures volatility clustering — a key characteristic of regime transitions.
________________________________________
2. Regime Classification
Python (HMM Volatility States):
Volatility is modelled as belonging to hidden states with different means and variances:
State μ₁, σ₁
State μ₂, σ₂
State μ₃, σ₃
with state transitions determined by a probability matrix.
Pine Approximation (Z-Score Regimes):
Zₜ = ( RVₜ − mean(RV) ) / stdev(RV)
Regime assignment:
• Regime 0 (Low Vol): Zₜ < Zₗₒw
• Regime 1 (Normal): Zₗₒw ≤ Zₜ ≤ Zₕᵢgh
• Regime 2 (High Vol): Zₜ > Zₕᵢgh
Rationale:
Z-scores provide clean statistical boundaries that behave similarly to HMM state separation but are computable in real time.
________________________________________
3. Structural Break Detection vs Rolling Windows
Python (Bai–Perron Structural Breaks):
Segments the volatility series into periods with distinct statistical properties by minimising squared error over multiple regimes.
Pine Approximation:
Rolling mean and rolling standard deviation of volatility over a long window.
Rationale:
When structural breaks are not available, long-window smoothing approximates slow regime changes effectively.
________________________________________
4. Multi-Scale Cycles
Python (Wavelet Decomposition):
Volatility decomposed into long-cycle (A₄) and short-cycle components (D bands).
Pine Approximation:
Single-scale smoothing using long-horizon averages of RV.
Rationale:
Wavelets reveal multi-frequency behaviour; Pine captures the dominant low-frequency component.
________________________________________
Indicator Output
The background colour reflects the active volatility regime:
• Low Volatility (Green): trending behaviour, cleaner directional movement
• Normal Volatility (Yellow): balanced environment
• High Volatility (Red): sharp swings, traps, mean-reversion phases
Regime labels appear on the chart, with a status panel displaying the current regime.
________________________________________
Operational Logic
1. Compute log returns
2. Calculate short-horizon realised volatility
3. Compute long-horizon mean and standard deviation
4. Derive volatility Z-score
5. Assign regime classification
6. Update background colour and labels
This provides a stable, real-time map of market state transitions.
________________________________________
Practical Applications
Intraday Trading
• Low-volatility regimes favour trend and breakout continuation
• High-volatility regimes favour mean reversion and wide stop placement
Swing Trading
• Compression phases often precede multi-day trending moves
• Volatility expansions accompany distribution or panic events
Risk Management
• Enables volatility-adjusted position sizing
• Helps avoid leverage during expansion regimes
________________________________________
Notes
• Does not repaint
• Fully configurable thresholds and lookbacks
• Works across indices, stocks, FX, crypto
• Designed for real-time volatility regime identification
________________________________________
Disclaimer
This script is intended solely for educational and research purposes.
It does not constitute financial advice or a recommendation to buy or sell any instrument.
Trading involves risk, and past volatility patterns do not guarantee future outcomes.
Users are responsible for their own trading decisions, and the author assumes no liability for financial loss.
Superior-Range Bound Renko - Alerts - 11-29-25 - Signal LynxSuperior-Range Bound Renko – Alerts Edition with Advanced Risk Management Template
Signal Lynx | Free Scripts supporting Automation for the Night-Shift Nation 🌙
1. Overview
This is the Alerts & Indicator Edition of Superior-Range Bound Renko (RBR).
The Strategy version is built for backtesting inside TradingView.
This Alerts version is built for automation: it emits clean, discrete alert events that you can route into webhooks, bots, or relay engines (including your own Signal Lynx-style infrastructure).
Under the hood, this script contains the same core engine as the strategy:
Adaptive Range Bounding based on volatility
Renko Brick Emulation on standard candles
A stack of Laguerre Filters for impulse detection
K-Means-style Adaptive SuperTrend for trend confirmation
The full Signal Lynx Risk Management Engine (state machine, layered exits, AATS, RSIS, etc.)
The difference is in what we output:
Instead of placing historical trades, this version:
Plots the entry and RM signals in a separate pane (overlay = false)
Exposes alertconditions for:
Long Entry
Short Entry
Close Long
Close Short
TP1, TP2, TP3 hits (Staged Take Profit)
This makes it ideal as the signal source for automated execution via TradingView Alerts + Webhooks.
2. Quick Action Guide (TL;DR)
Best Timeframe:
4H and above. This is a swing-trading / position-trading style engine, not a micro-scalper.
Best Assets:
Volatile but structured markets, e.g.:
BTC, ETH, XAUUSD (Gold), GBPJPY, and similar high-volatility majors or indices.
Script Type:
indicator() – Alerts & Visualization Only
No built-in order placement
All “orders” are emitted as alerts for your external bot or manual handling
Strategy Type:
Volatility-Adaptive Trend Following + Impulse Detection
using Renko-like structure and multi-layer Laguerre filters.
Repainting:
Designed to be non-repainting on closed candles.
The underlying Risk Management engine is built around previous-bar data (close , high , low ) for execution-critical logic.
Intrabar values can move while the bar is forming (normal for any advanced signal), but once a bar closes, the alert logic is stable.
Recommended Alert Settings:
Condition: one of the built-in signals (see section 3.B)
Options: “Once Per Bar Close” is strongly recommended for automation
Message: JSON, CSV, or simple tokens – whatever your webhook / relay expects
3. Detailed Report: How the Alerts Edition Works
A. Relationship to the Strategy Version
The Alerts Edition shares the same internal logic as the strategy version:
Same Adaptive Lookback and volatility normalization
Same Range and Close Range construction
Same Renko Brick Emulator and directional memory (renkoDir)
Same Fib structures, Laguerre stack, K-Means SuperTrend, and Baseline signals (B1, B2)
Same Risk Management Engine and layered exits
In the strategy script, these signals are wired into strategy.entry, strategy.exit, and strategy.close.
In the alerts script:
We still compute the final entry/exit signals (Fin, CloseEmAll, TakeProfit1Plot, etc.)
Instead of placing trades, we:
Plot them for visual inspection
Expose them via alertcondition(...) so that TradingView can fire alerts.
This ensures that:
If you use the same settings on the same symbol/timeframe, the Alerts Edition and Strategy Edition agree on where entries and exits occur.
(Subject only to normal intrabar vs. bar-close differences.)
B. Signals & Alert Conditions
The alerts script focuses on discrete, automation-friendly events.
Internally, the main signals are:
Fin – Final entry decision from the RM engine
CloseEmAll – RM-driven “hard close” signal (for full-position exits)
TakeProfit1Plot / 2Plot / 3Plot – One-time event markers when each TP stage is hit
On the chart (in the separate indicator pane), you get:
plot(Fin) – where:
+2 = Long Entry event
-2 = Short Entry event
plot(CloseEmAll) – where:
+1 = “Close Long” event
-1 = “Close Short” event
plot(TP1/TP2/TP3) (if Staged TP is enabled) – integer tags for TP hits:
+1 / +2 / +3 = TP1 / TP2 / TP3 for Longs
-1 / -2 / -3 = TP1 / TP2 / TP3 for Shorts
The corresponding alertconditions are:
Long Entry
alertcondition(Fin == 2, title="Long Entry", message="Long Entry Triggered")
Fire this to open/scale a long position in your bot.
Short Entry
alertcondition(Fin == -2, title="Short Entry", message="Short Entry Triggered")
Fire this to open/scale a short position.
Close Long
alertcondition(CloseEmAll == 1, title="Close Long", message="Close Long Triggered")
Fire this to fully exit a long position.
Close Short
alertcondition(CloseEmAll == -1, title="Close Short", message="Close Short Triggered")
Fire this to fully exit a short position.
TP 1 Hit
alertcondition(TakeProfit1Plot != 0, title="TP 1 Hit", message="TP 1 Level Reached")
First staged take profit hit (either long or short). Your bot can interpret the direction based on position state or message tags.
TP 2 Hit
alertcondition(TakeProfit2Plot != 0, title="TP 2 Hit", message="TP 2 Level Reached")
TP 3 Hit
alertcondition(TakeProfit3Plot != 0, title="TP 3 Hit", message="TP 3 Level Reached")
Together, these give you a complete trade lifecycle:
Open Long / Short
Optionally scale out via TP1/TP2/TP3
Close remaining via Close Long / Close Short
All while the Risk Management Engine enforces the same logic as the strategy version.
C. Using This Script for Automation
This Alerts Edition is designed for:
Webhook-based bots
Execution relays (e.g., your own Lynx-Relay-style engine)
Dedicated external trade managers
Typical setup flow:
Add the script to your chart
Same symbol, timeframe, and settings you use in the Strategy Edition backtests.
Configure Inputs:
Longs / Shorts enabled
Risk Management toggles (SL, TS, Staged TP, AATS, RSIS)
Weekend filter (if you do not want weekend trades)
RBR-specific knobs (Adaptive Lookback, Brick type, ATR vs Standard Brick, etc.)
Create Alerts for Each Event Type You Need:
Long Entry
Short Entry
Close Long
Close Short
TP1 / TP2 / TP3 (optional, if your bot handles partial closes)
For each:
Condition: the corresponding alertcondition
Option: “Once Per Bar Close” is strongly recommended
Message:
You can use structured JSON or a simple token set like:
{"side":"long","event":"entry","symbol":"{{ticker}}","time":"{{timenow}}"}
or a simpler text for manual trading like:
LONG ENTRY | {{ticker}} | {{interval}}
Wire Up Your Bot / Relay:
Point TradingView’s webhook URL to your execution engine
Parse the messages and map them into:
Exchange
Symbol
Side (long/short)
Action (open/close/partial)
Size and risk model (this script does not position-size for you; it only signals when, not how much.)
Because the alerts come from a non-repainting, RM-backed engine that you’ve already validated via the Strategy Edition, you get a much cleaner automation pipeline.
D. Repainting Protection (Alerts Edition)
The same protections as the Strategy Edition apply here:
Execution-critical logic (trailing stop, TP triggers, SL, RM state changes) uses previous bar OHLC:
open , high , low , close
No security() with lookahead or future-bar dependencies.
This means:
Alerts are designed to fire on states that would have been visible at bar close, not on hypothetical “future history.”
Important practical note:
Intrabar: While a bar is forming, internal conditions can oscillate.
Bar Close: With “Once Per Bar Close” alerts, the fired signal corresponds to the final state of the engine for that candle, matching your Strategy Edition expectations.
4. For Developers & Modders
You can treat this Alerts script as an ”RM + Alert Framework” and inject any signal logic you want.
Where to plug in:
Find the section:
// BASELINE & SIGNAL GENERATION
You’ll see how B1 and B2 are built from the RBR stack and then combined:
baseSig = B2
altSig = B1
finalSig = sigSwap ? baseSig : altSig
To use your own logic:
Replace or wrap the code that sets baseSig / altSig with your own conditions:
e.g., RSI, MACD, Heikin Ashi filters, candle patterns, volume filters, etc.
Make sure your final decision is still:
2 → Long / Buy signal
-2 → Short / Sell signal
0 → No trade
finalSig is then passed into the RM engine and eventually becomes Fin, which:
Drives the Long/Short Entry alerts
Interacts with the RM state machine to integrate properly with AATS, SL, TS, TP, etc.
Because this script already exposes alertconditions for key lifecycle events, you don’t need to re-wire alerts each time — just ensure your logic feeds into finalSig correctly.
This lets you use the Signal Lynx Risk Management Engine + Alerts wrapper as a drop-in chassis for your own strategies.
5. About Signal Lynx
Automation for the Night-Shift Nation 🌙
Signal Lynx builds tools and templates that help traders move from:
“I have an indicator” → “I have a structured, automatable strategy with real risk management.”
This Superior-Range Bound Renko – Alerts Edition is the automation-focused companion to the Strategy Edition. It’s designed for:
Traders who backtest with the Strategy version
Then deploy live signals with this Alerts version via webhooks or bots
While relying on the same non-repainting, RM-driven logic
We release this code under the Mozilla Public License 2.0 (MPL-2.0) to support the Pine community with:
Transparent, inspectable logic
A reusable Risk Management template
A reference implementation of advanced adaptive logic + alerts
If you are exploring full-stack automation (TradingView → Webhooks → Exchange / VPS), keep Signal Lynx in your search.
License: Mozilla Public License 2.0 (Open Source).
If you build improvements or helpful variants, please consider sharing them back with the community.
Super-AO Engine - Sentiment Ribbon - 11-29-25Super-AO Sentiment Ribbon by Signal Lynx
Overview:
The Super-AO Sentiment Ribbon is the visual companion to the Super-AO Strategy Suite.
While the main strategy handles the complex mathematics of entries and risk management, this tool provides a simple "Traffic Light" visual at the top of your chart to gauge the overall health of the market.
How It Works:
This indicator takes the core components of the Super-AO strategy (The SuperTrend and the Awesome Oscillator), calculates the spread between them and the current price, and generates a normalized "Sentiment Score."
Reading the Colors:
🟢 Lime / Green: Strong Upward Momentum. Ideally, you only want to take Longs here.
🟤 Olive / Yellow: Trend is weakening. Be careful with new entries, or consider taking profit.
⚪ Gray: The "Kill Zone." The market is chopping sideways. Automated strategies usually suffer here.
🟠 Orange / Red: Strong Downward Momentum. Ideally, you only want to take Shorts here.
Integration:
This script uses the same default inputs as our Super-AO Strategy Template and Alerts Template. Use them together to confirm your automated entries visually.
About Signal Lynx:
Free Scripts supporting Automation for the Night-Shift Nation 🌙
(www.signallynx.com)
Bull/Bear/Consolidation Zones Hariss 369This indicator helps to identify bullish, bearish, and consolidation zones using EMA and ATR-based calculations. It visually highlights zones on the chart and provides buy and sell signals with ATR-based stop-loss (SL) and take-profit (TP) levels.
Key Features:
EMA Trend Filter: Determines the direction of the market.
Bull / Bear / Consolidation Zones: Colored zones to easily spot market phases.
ATR-Based SL & TP: Automatic calculation for each trade signal.
Buy / Sell Signals: Based on price relative to EMA and consolidation zones.
Relative Volume (RVOL) Filter: Optional filter to trade only when volume is significant, helping reduce low-probability signals.
Extended Zones: Option to extend zones forward until a breakout occurs.
Customizable Inputs: EMA length, ATR length, multipliers, RVOL period & multiplier, and toggle RVOL filter.
How to Use:
Identify bull/bear/consolidation zones on your chart. (These are already there) You can change the line as well zone color according to your needs.
Look for buy signals above EMA and consolidation zone, or sell signals below EMA and consolidation zone. The buy and sell labels are already there.
Confirm with RVOL filter (optional) to ensure higher volume support.
Use the plotted SL and TP levels for trade management.
This tool is designed for trend-following and market structure traders who want a visual guide to high-probability trading zones combined with volume confirmation.
One can also trail with EMA in trending market.
Super-AO with Risk Management Alerts Template - 11-29-25Super-AO with Risk Management: ALERTS & AUTOMATION Edition
Signal Lynx | Free Scripts supporting Automation for the Night-Shift Nation 🌙
1. Overview
This is the Indicator / Alerts companion to the Super-AO Strategy.
While the Strategy version is built for backtesting (verifying profitability and checking historical performance), this Indicator version is built for Live Execution.
We understand the frustration of finding a great strategy, only to realize you can't easily hook it up to your trading bot. This script solves that. It contains the exact same "Super-AO" logic and "Risk Management Engine" as the strategy version, but it is optimized to send signals to automation platforms like Signal Lynx, 3Commas, or any Webhook listener.
2. Quick Action Guide (TL;DR)
Purpose: Live Signal Generation & Automation.
Workflow:
Use the Strategy Version to find profitable settings.
Copy those settings into this Indicator Version.
Set a TradingView Alert using the "Any Alert() function call" condition.
Best Timeframe: 4 Hours (H4) and above.
Compatibility: Works with any webhook-based automation service.
3. Why Two Scripts?
Pine Script operates in two distinct modes:
Strategy Mode: Calculates equity, drawdowns, and simulates orders. Great for research, but sometimes complex to automate.
Indicator Mode: Plots visual data on the chart. This is the preferred method for setting up robust alerts because it is lighter weight and plots specific values that automation services can read easily.
The Golden Rule: Always backtest on the Strategy, but trade on the Indicator. This ensures that what you see in your history matches what you execute in real-time.
4. How to Automate This Script
This script uses a "Visual Spike" method to trigger alerts. Instead of drawing equity curves, it plots numerical values at the bottom of your chart when a trade event occurs.
The Signal Map:
Blue Spike (2 / -2): Entry Signal (Long / Short).
Yellow Spike (1 / -1): Risk Management Close (Stop Loss / Trend Reversal).
Green Spikes (1, 2, 3): Take Profit Levels 1, 2, and 3.
Setup Instructions:
Add this indicator to your chart.
Open your TradingView "Alerts" tab.
Create a new Alert.
Condition: Select SAO - RM Alerts Template.
Trigger: Select Any Alert() function call.
Message: Paste your JSON webhook message (provided by your bot service).
5. The Logic Under the Hood
Just like the Strategy version, this indicator utilizes:
SuperTrend + Awesome Oscillator: High-probability swing trading logic.
Non-Repainting Engine: Calculates signals based on confirmed candle closes to ensure the alert you get matches the chart reality.
Advanced Adaptive Trailing Stop (AATS): Internally calculates volatility to determine when to send a "Close" signal.
6. About Signal Lynx
Automation for the Night-Shift Nation 🌙
We are providing this code open source to help traders bridge the gap between manual backtesting and live automation. This code has been in action since 2022.
If you are looking to automate your strategies, please take a look at Signal Lynx in your search.
License: Mozilla Public License 2.0 (Open Source). If you make beneficial modifications, please release them back to the community!
$TGM | Topological Geometry Mapper (Custom)TGM | Topological Geometry Mapper (Custom) – 2025 Edition
The first indicator that reads market structure the way institutions actually see it: through persistent topological features (Betti-1 collapse) instead of lagging price patterns.
Inspired by algebraic topology and persistent homology, TGM distills regime complexity into a single, real-time proxy using the only two macro instruments that truly matter:
• CBOE:VIX – market fear & convexity
• TVC:DXY – dollar strength & global risk appetite
When the weighted composite β₁ persistence drops below the adaptive threshold → market structure radically simplifies. Noise dies. Order flow aligns. A directional explosion becomes inevitable.
Features
• Structural Barcode Visualization – instantly see complexity collapsing in real time
• Dynamic color system:
→ Neon green = long breakout confirmed
→ red = short breakout confirmed
→ yellow = simplification in progress (awaiting momentum)
→ deep purple = complex/noisy regime
• Clean HUD table with live β₁ value, threshold, regime status and timestamp
• Built-in high-precision alerts (Long / Short / Collapse)
• Zero repaint – uses only confirmed data
• Works on every timeframe and every market
Best used on:
BTC, ETH, ES/NQ, EURUSD, GBPUSD, NAS100, SPX500, Gold – anywhere liquidity is institutional.
This is not another repainted RSI or MACD mashup.
This is structural regime detection at the topological level.
Welcome to the future of market geometry.
Made with love for the real traders.
Open-source. No paywalls. No BS.
#topology #betti #smartmoney #ict #smc #orderflow #regime #institutional
