Fisher Volume Transform | AlphaNattFisher Volume Transform | AlphaNatt
A powerful oscillator that applies the Fisher Transform - converting price into a Gaussian normal distribution - while incorporating volume weighting to identify high-probability reversal points with institutional participation.
"The Fisher Transform reveals what statistics professors have known for decades: when you transform market data into a normal distribution, turning points become crystal clear."
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🎲 THE MATHEMATICS
Fisher Transform Formula:
The Fisher Transform converts any bounded dataset into a Gaussian distribution:
y = 0.5 × ln((1 + x) / (1 - x))
Where x is normalized price (-1 to 1 range)
Why This Matters:
Market extremes become statistically identifiable
Turning points are amplified and clarified
Removes the skew from price distributions
Creates nearly instantaneous signals at reversals
Volume Integration:
Unlike standard Fisher Transform, this version weights price by relative volume:
High volume moves get more weight
Low volume moves get filtered out
Identifies institutional participation
Reduces false signals from retail chop
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💎 KEY ADVANTAGES
Statistical Edge: Transforms price into normal distribution where extremes are mathematically defined
Volume Confirmation: Only signals with volume support
Early Reversal Detection: Fisher Transform amplifies turning points
Clean Signals: Gaussian distribution reduces noise
No Lag: Mathematical transformation, not averaging
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⚙️ SETTINGS OPTIMIZATION
Fisher Period (5-30):
5-9: Very sensitive, many signals
10: Default - balanced sensitivity
15-20: Moderate smoothing
25-30: Major reversals only
Volume Weight (0.1-1.0):
0.1-0.3: Minimal volume influence
0.5-0.7: Balanced price/volume
0.7: Default - strong volume weight
0.8-1.0: Volume dominant
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📊 TRADING SIGNALS
Primary Signals:
Zero Cross Up: Bullish momentum shift
Zero Cross Down: Bearish momentum shift
Signal Line Cross: Early reversal warning
Extreme Readings (±75): Potential reversal zones
Visual Interpretation:
Cyan zones: Bullish momentum
Magenta zones: Bearish momentum
Gradient intensity: Strength of move
Histogram: Raw momentum power
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🎯 OPTIMAL USAGE
Best Market Conditions:
Range-bound markets (reversals clear)
High volume periods
Major support/resistance levels
Divergence hunting
Trading Strategies:
1. Extreme Reversal:
Enter when oscillator exceeds ±75 and reverses
2. Zero Line Momentum:
Trade crosses of zero line with volume confirmation
3. Signal Line Strategy:
Early entry on signal line crosses
4. Divergence Trading:
Price makes new high/low but Fisher doesn't
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Developed by AlphaNatt | Quantitative Trading Systems
Version: 1.0
Classification: Statistical Transform Oscillator
Not financial advice. Always DYOR.
Ortalanmış Osilatörler
Momentum+This script provides a colored histogram of recent price action with the price derivative method for finding momentum.
buy sell ultra systemWhat it is
EMA-POC Momentum System Ultra combines a proven trend stack (EMA 20/50/238), a price-of-control layer (POC via Bar-POC or VWAP alternative), and a momentum trigger (RSI) to surface higher-quality entries only when multiple, independent conditions align. This is not a cosmetic mashup; each component gates the others.
How components work together
Trend (EMA 20/50/238): Defines short/medium/long bias and filters counter-trend signals.
POC (Bar-POC or Alt-POC/VWAP): Locates the most-traded/weighted price area; a neutral band around POC helps avoid chop.
Control background: Above POC → buyers likely in control; below → sellers.
Momentum (RSI): Entry arrows print only when RSI confirms with trend and price location vs POC; optional “cross 50” requirement reduces noise.
Optional HTF trend: Confluence with a higher-timeframe EMA stack for stricter filtering.
Why it’s original/useful
Signals require confluence of (1) EMA trend stack, (2) POC location and neutral-zone filtering, (3) momentum confirmation, (4) optional slope and distance-to-POC checks, and (5) optional HTF trend. This reduces false positives compared with using any layer in isolation.
How to use
Markets/TFs: Built for XAUUSD (Gold) and US30. Works 1m–1h for intraday; 2h–4h for swing.
Entries:
Long: EMA stack bullish, price above POC, not in neutral band, RSI condition true → “Buy” arrow.
Short: Opposite conditions → “Sell” arrow.
Stops/Targets (suggested):
Initial stop beyond POC/neutral band or recent swing.
First target around 1R; trail with EMA20/50 or structure breaks.
Settings to tune:
POC Mode: Bar-POC (highest-volume bar’s close over lookback) or Alt-POC (VWAP).
Neutral Band %: 0.10–0.35 typical intraday.
Min distance from POC: 0.10–0.50% helps avoid low-RR entries right at POC.
RSI: Choose “cross 50” for stricter triggers or simple >/< 50 for more signals.
HTF trend: Turn on for extra confluence.
Alerts:
Buy Signal and Sell Signal (separate), or one Combined Buy/Sell alert.
Set to “Once per bar close” if you want only confirmed arrows.
Repainting / limitations
Shapes can move until bar close (standard Pine behavior) when using intrabar conditions; final confirmation at close. No system guarantees profitability—forward test and adapt to your market/instrument.
Clean chart
The published chart contains only this script so outputs are easy to identify.
Versions / updates
Use Publish → Update for minor changes; do not create new publications for small tweaks. If you fork to preserve older behavior, explain why and how your fork differs.
Changelog
v1.1 – Tuning for Gold/US30, neutral-band & distance filters, optional HTF trend, combined alert.
v1.0 – Initial public release (EMA stack + POC modes + RSI + alerts).
License & credits
Open-source for learning and improvement. Please credit on forks and explain modifications in your description.
Momentum Index [BigBeluga]The Momentum Index is an innovative indicator designed to measure the momentum of price action by analyzing the distribution of positive and negative momentum values over a defined period. By incorporating delta-based calculations and smoothing techniques, it provides traders with a clear and actionable representation of market momentum dynamics.
🔵 Key Features:
Delta-Based Momentum Analysis:
Calculates the momentum of price by comparing its current state to its value from a defined number of bars back.
Inside a loop, it evaluates whether momentum values are above or below zero, producing a delta value that reflects the net momentum direction and intensity.
Double EMA Smoothing:
Smooths the raw delta-based momentum values with a double EMA filter, reducing noise and providing a clearer trend signal.
tmi(len) =>
sum = 0.0
sum1 = 0.0
above = 0.0
below = 0.0
src_ = src - src
for i = 0 to len
sum := sum + (src_ > nz(src_ ) ? 1 : -1)
sum1 := sum1 + (sum > 0 ? 1 : -1)
sum1 := emaEma(sum1, 10)
for i = 1 to len
above := above + (sum1 > 0 ? 1 : 0)
below := below + (sum1 > 0 ? 0 : 1)
Directional Momentum Signals:
Generates momentum shift signals and displays them on both the oscillator and the main chart:
- △ Aqua Triangles: Represent upward momentum shifts.
- ▽ Red Triangles: Represent downward momentum shifts.
Dynamic Gradient Display:
Highlights momentum zones with gradient fills:
- Aqua shades for positive momentum (above zero).
- Red shades for negative momentum (below zero).
Dashboard Display:
A dashboard summarizing the count of momentum values above and below zero for the defined period (Sentiment Length e.g. 100), helping traders assess market sentiment at a glance.
🔵 How It Works:
The indicator takes price momentum as its source and evaluates the number of momentum values above and below zero within a defined period.
The delta calculation aggregates this information, providing a net representation of the prevailing market momentum.
A double EMA filter is applied to the delta values, smoothing the momentum line and enhancing signal clarity.
Momentum shifts are highlighted with visual signals on the oscillator and price chart, while the gradient display provides a visual representation of intensity.
🔵 Use Cases:
Momentum Tracking: Identify whether market momentum is predominantly bullish or bearish.
Signal Confirmation: Use chart-based signals to confirm potential trend reversals or continuation.
Analyze Market Strength: Leverage the dashboard to quickly assess the distribution of momentum over the chosen period.
Overbought/Oversold Conditions: Utilize gradient zones to detect areas of momentum extremes and possible price exhaustion.
Momentum Index offers a refined approach to analyzing momentum dynamics, combining delta-based calculations with smoothing techniques and intuitive visuals, making it an essential tool for traders looking to anticipate market movements effectively.
Logit Transform -EasyNeuro-Logit Transform
This script implements a novel indicator inspired by the Fisher Transform, replacing its core arctanh-based mapping with the logit transform. It is designed to highlight extreme values in bounded inputs from a probabilistic and statistical perspective.
Background: Fisher Transform
The Fisher Transform, introduced by John Ehlers , is a statistical technique that maps a bounded variable x (between a and b) to a variable approximately following a Gaussian distribution. The standard form for a normalized input y (between -1 and 1) is F(y) = 0.5 * ln((1 + y)/(1 - y)) = arctanh(y).
This transformation has the following properties:
Linearization of extremes:
Small deviations around the mean are smooth, while movements near the boundaries are sharply amplified.
Gaussian approximation:
After transformation, the variable approximates a normal distribution, enabling analytical techniques that assume normality.
Probabilistic interpretation:
The Fisher Transform can be linked to likelihood ratio tests, where the transform emphasizes deviations from median or expected values in a statistically meaningful way.
In technical analysis, this allows traders to detect turning points or extreme market conditions more clearly than raw oscillators alone.
Logit Transform as a Generalization
The logit function is defined for p between 0 and 1 as logit(p) = ln(p / (1 - p)).
Key properties of the logit transform:
Maps probabilities in (0, 1) to the entire real line, similar to the Fisher Transform.
Emphasizes values near 0 and 1, providing sharp differentiation of extreme states.
Directly interpretable in terms of odds and likelihood ratios: logit(p) = ln(odds).
From a statistical viewpoint, the logit transform corresponds to the canonical link function in binomial generalized linear models (GLMs). This provides a natural interpretation of the transformed variable as the logarithm of the likelihood ratio between success and failure states, giving a rigorous probabilistic framework for extreme value detection.
Theoretical Advantages
Distributional linearization:
For inputs that can be interpreted as probabilities, the logit transform creates a variable approximately linear in log-odds, similar to Fisher’s goal of Gaussianization but with a probabilistic foundation.
Extreme sensitivity:
By amplifying small differences near 0 or 1, it allows for sharper detection of market extremes or overbought/oversold conditions.
Statistical interpretability:
Provides a link to statistical hypothesis testing via likelihood ratios, enabling integration with probabilistic models or risk metrics.
Applications in Technical Analysis
Oscillator enhancement:
Apply to RSI, Stochastic Oscillators, or other bounded indicators to accentuate extreme values with a well-defined probabilistic interpretation.
Comparative study:
Use alongside the Fisher Transform to analyze the effect of different nonlinear mappings on market signals, helping to uncover subtle nonlinearity in price behavior.
Probabilistic risk assessment:
Transforming input series into log-odds allows incorporation into statistical risk models or volatility estimation frameworks.
Practical Considerations
The logit diverges near 0 and 1, requiring careful scaling or smoothing to avoid numerical instability. As with the Fisher Transform, this indicator is not a standalone trading signal and should be combined with complementary technical or statistical indicators.
In summary, the Logit Transform builds upon the Fisher Transform’s theoretical foundation while introducing a probabilistically rigorous mapping. By connecting extreme-value detection to odds ratios and likelihood principles, it provides traders and analysts with a mathematically grounded tool for examining market dynamics.
X-Scalp by LogicatX-Scalp by Logicat — Clean-Range MTF Scalper
Turn noisy intraday action into clear, actionable scalps. X-Scalp builds “Clean Range” zones only when three timeframes agree (default: M30/M15/M5), then waits for a single, high-quality M5 confirmation to print a BUY/SELL label. It’s fast, simple, and ruthlessly focused on precision.
What it does
Clean Range zones: Drawn from the last completed M30 candle only when M30/M15/M5 align (all green or all red).
Size filter (pips): Ignore tiny, low-value ranges with a configurable minimum height (auto-pip detection included).
Extend-until-mitigated: Zones stretch right and “freeze” on first mitigation (close inside or close beyond, your choice). Optional fade when mitigated.
Laser M5 entries (one per box):
Red M5 bar inside a green zone → SELL
Green M5 bar inside a red zone → BUY
Prints once per zone on the closed M5 candle—no spam.
Quality of life: Keep latest N zones, customizable colors, optional H4 reference lines, alert conditions for both zone creation and entries.
Why traders love it
Clarity: Filters chop; you see only aligned zones and one clean trigger.
Speed: Designed for scalpers on FX, XAU/USD, indices, and more.
Control: Tune lookback, pip threshold, mitigation logic, and visuals to fit your playbook.
Tips
Use on liquid sessions for best results.
Combine with your risk model (fixed R, partials at mid/edge, etc.).
Backtest different pip filters per symbol.
Disclaimer: No indicator guarantees profits. Trade responsibly and manage risk.
POC Migration Velocity (POC-MV) [PhenLabs]📊POC Migration Velocity (POC-MV)
Version: PineScript™v6
📌Description
The POC Migration Velocity indicator revolutionizes market structure analysis by tracking the movement, speed, and acceleration of Point of Control (POC) levels in real-time. This tool combines sophisticated volume distribution estimation with velocity calculations to reveal hidden market dynamics that conventional indicators miss.
POC-MV provides traders with unprecedented insight into volume-based price movement patterns, enabling the early identification of continuation and exhaustion signals before they become apparent to the broader market. By measuring how quickly and consistently the POC migrates across price levels, traders gain early warning signals for significant market shifts and can position themselves advantageously.
The indicator employs advanced algorithms to estimate intra-bar volume distribution without requiring lower timeframe data, making it accessible across all chart timeframes while maintaining sophisticated analytical capabilities.
🚀Points of Innovation
Micro-POC calculation using advanced OHLC-based volume distribution estimation
Real-time velocity and acceleration tracking normalized by ATR for cross-market consistency
Persistence scoring system that quantifies directional consistency over multiple periods
Multi-signal detection combining continuation patterns, exhaustion signals, and gap alerts
Dynamic color-coded visualization system with intensity-based feedback
Comprehensive customization options for resolution, periods, and thresholds
🔧Core Components
POC Calculation Engine: Estimates volume distribution within each bar using configurable price bands and sophisticated weighting algorithms
Velocity Measurement System: Tracks the rate of POC movement over customizable lookback periods with ATR normalization
Acceleration Calculator: Measures the rate of change of velocity to identify momentum shifts in POC migration
Persistence Analyzer: Quantifies how consistently POC moves in the same direction using exponential weighting
Signal Detection Framework: Combines trend analysis, velocity thresholds, and persistence requirements for signal generation
Visual Rendering System: Provides dynamic color-coded lines and heat ribbons based on velocity and price-POC relationships
🔥Key Features
Real-time POC calculation with 10-100 configurable price bands for optimal precision
Velocity tracking with customizable lookback periods from 5 to 50 bars
Acceleration measurement for detecting momentum changes in POC movement
Persistence scoring to validate signal strength and filter false signals
Dynamic visual feedback with blue/orange color scheme indicating bullish/bearish conditions
Comprehensive alert system for continuation patterns, exhaustion signals, and POC gaps
Adjustable information table displaying real-time metrics and current signals
Heat ribbon visualization showing price-POC relationship intensity
Multiple threshold settings for customizing signal sensitivity
Export capability for use with separate panel indicators
🎨Visualization
POC Connecting Lines: Color-coded lines showing POC levels with intensity based on velocity magnitude
Heat Ribbon: Dynamic colored ribbon around price showing POC-price basis intensity
Signal Markers: Clear exhaustion top/bottom signals with labeled shapes
Information Table: Real-time display of POC value, velocity, acceleration, basis, persistence, and current signal status
Color Gradients: Blue gradients for bullish conditions, orange gradients for bearish conditions
📖Usage Guidelines
POC Calculation Settings
POC Resolution (Price Bands): Default 20, Range 10-100. Controls the number of price bands used to estimate volume distribution within each bar
Volume Weight Factor: Default 0.7, Range 0.1-1.0. Adjusts the influence of volume in POC calculation
POC Smoothing: Default 3, Range 1-10. EMA smoothing period applied to the calculated POC to reduce noise
Velocity Settings
Velocity Lookback Period: Default 14, Range 5-50. Number of bars used to calculate POC velocity
Acceleration Period: Default 7, Range 3-20. Period for calculating POC acceleration
Velocity Significance Threshold: Default 0.5, Range 0.1-2.0. Minimum normalized velocity for continuation signals
Persistence Settings
Persistence Lookback: Default 5, Range 3-20. Number of bars examined for persistence score calculation
Persistence Threshold: Default 0.7, Range 0.5-1.0. Minimum persistence score required for continuation signals
Visual Settings
Show POC Connecting Lines: Toggle display of colored lines connecting POC levels
Show Heat Ribbon: Toggle display of colored ribbon showing POC-price relationship
Ribbon Transparency: Default 70, Range 0-100. Controls transparency level of heat ribbon
Alert Settings
Enable Continuation Alerts: Toggle alerts for continuation pattern detection
Enable Exhaustion Alerts: Toggle alerts for exhaustion pattern detection
Enable POC Gap Alerts: Toggle alerts for significant POC gaps
Gap Threshold: Default 2.0 ATR, Range 0.5-5.0. Minimum gap size to trigger alerts
✅Best Use Cases
Identifying trend continuation opportunities when POC velocity aligns with price direction
Spotting potential reversal points through exhaustion pattern detection
Confirming breakout validity by monitoring POC gap behavior
Adding volume-based context to traditional technical analysis
Managing position sizing based on POC-price basis strength
⚠️Limitations
POC calculations are estimations based on OHLC data, not true tick-by-tick volume distribution
Effectiveness may vary in low-volume or highly volatile market conditions
Requires complementary analysis tools for complete trading decisions
Signal frequency may be lower in ranging markets compared to trending conditions
Performance optimization needed for very short timeframes below 1-minute
💡What Makes This Unique
Advanced Estimation Algorithm: Sophisticated method for calculating POC without requiring lower timeframe data
Velocity-Based Analysis: Focus on POC movement dynamics rather than static levels
Comprehensive Signal Framework: Integration of continuation, exhaustion, and gap detection in one indicator
Dynamic Visual Feedback: Intensity-based color coding that adapts to market conditions
Persistence Validation: Unique scoring system to filter signals based on directional consistency
🔬How It Works
Volume Distribution Estimation:
Divides each bar into configurable price bands for volume analysis
Applies sophisticated weighting based on OHLC relationships and proximity to close
Identifies the price level with maximum estimated volume as the POC
Velocity and Acceleration Calculation:
Measures POC rate of change over specified lookback periods
Normalizes values using ATR for consistent cross-market performance
Calculates acceleration as the rate of change of velocity
Signal Generation Process:
Combines trend direction analysis using EMA crossovers
Applies velocity and persistence thresholds to filter signals
Generates continuation, exhaustion, and gap alerts based on specific criteria
💡Note:
This indicator provides estimated POC calculations based on available OHLC data and should be used in conjunction with other analysis methods. The velocity-based approach offers unique insights into market structure dynamics but requires proper risk management and complementary analysis for optimal trading decisions.
Adaptive Convergence Divergence### Adaptive Convergence Divergence (ACD)
By Gurjit Singh
The Adaptive Convergence Divergence (ACD) reimagines the classic MACD by replacing fixed moving averages with adaptive moving averages. Instead of a static smoothing factor, it dynamically adjusts sensitivity based on price momentum, relative strength, volatility, fractal roughness, or volume pressure. This makes the oscillator more responsive in trending markets while filtering noise in choppy ranges.
#### 📌 Key Features
1. Dual Adaptive Structure: The oscillator uses two adaptive moving averages to form its convergence-divergence line, with EMA/RMA as signal line:
* Primary Adaptive (MA): Fast line, reacts quickly to changes.
* Following Adaptive (FAMA): Slow line, with half-alpha smoothing for confirmation.
2. Adaptive MA Types
* ACMO: Adaptive CMO (momentum)
* ARSI: Adaptive RSI (relative strength)
* FRMA: Fractal Roughness (volatility + fractal dimension)
* VOLA: Volume adaptive (volume pressure)
3. PPO Option: Switch between classic MACD or Percentage Price Oscillator (PPO) style calculation.
4. Signal Smoothing: Choose between EMA or Wilder’s RMA.
5. Visuals: Colored oscillator, signal line, histogram with adaptive transparency.
6. Alerts: Bullish/Bearish crossovers built-in.
#### 🔑 How to Use
1. Add to chart: Works on any timeframe and asset.
2. Choose MA Type: Experiment with ACMO, ARSI, FRMA, or VOLA depending on market regime.
3. Crossovers:
* Bullish (🐂): Oscillator crosses above signal → potential long entry.
* Bearish (🐻): Oscillator crosses below signal → potential short entry.
4. Histogram: expansion = strengthening trend; contraction = weakening trend.
5. Divergences:
* Bullish (hidden strength): Price pushes lower, but ACD turns higher = potential upward reversal.
* Bearish (hidden weakness): Price pushes higher, but ACD turns lower = potential downward reversal.
6. Customize: Adjust lengths, smoothing type, and PPO/MACD mode to match your style.
7. Set Alerts:
* Enable Bullish or Bearish crossover alerts to catch momentum shifts in real time.
#### 💡 Tips
* PPO mode normalizes values across assets, useful for cross-asset analysis.
* Wilder’s smoothing is gentler than EMA, reducing whipsaws in sideways conditions.
* Adaptive smoothing helps reduce false divergence signals by filtering noise in choppy ranges.
3 SMA + RSI + MACD + MTF Ultimate Dashboard🎯 Overview:
High-precision trading indicator combining trend, momentum, and multi-timeframe confirmation for reliable buy/sell signals in Forex, Crypto, and other markets.
🔹 Core Features:
📈 3 SMAs (7/25/99) – Short, Medium & Long-term trend detection
⚡ RSI Filter – Avoid weak signals (Buy >55 / Sell <45)
💎 MACD with Threshold – Reduce false crossovers
⏱️ Multi-Timeframe Trend (H4) – Confirm overall market direction
✅ Dashboard & Signals:
🟢 Clear Buy & Sell arrows on chart
📊 Live dashboard showing filter status & total signals
🔔 Audio & Push Alerts – Mobile/Desktop/Webhook
💎 Benefits:
⚡ Minimizes false signals
📈 Works on M15, H1, H4, Daily
🎯 Combines trend, momentum, and confirmation filters in one dashboard
⚠️ Note: Signals are generated only after candle close for maximum reliability.
3 SMA + RSI + MACD + MTF Ultimate Dashboard🎯 Overview:
High-precision trading indicator combining trend, momentum, and multi-timeframe confirmation for reliable buy/sell signals in Forex, Crypto, and other markets.
🔹 Core Features:
📈 3 SMAs (7/25/99) – Short, Medium & Long-term trend detection
⚡ RSI Filter – Avoid weak signals (Buy >55 / Sell <45)
💎 MACD with Threshold – Reduce false crossovers
⏱️ Multi-Timeframe Trend (H4) – Confirm overall market direction
✅ Dashboard & Signals:
🟢 Clear Buy & Sell arrows on chart
📊 Live dashboard showing filter status & total signals
🔔 Audio & Push Alerts – Mobile/Desktop/Webhook
💎 Benefits:
⚡ Minimizes false signals
📈 Works on M15, H1, H4, Daily
🎯 Combines trend, momentum, and confirmation filters in one dashboard
⚠️ Note: Signals are generated only after candle close for maximum reliability.
MACD Aspray Hybrid Bars (teal/red) = raw momentum (Aspray Histogram).
Teal line = smooth curve of the histogram (Aspray Line).
Orange line = 9-EMA of that line (new signal).
Zero line for reference.
MACD X Cross with PlotThe default MACD indicator with the crossover added at the top of the MACD plot pane. Arrow up for MACD crossover signal line. Arrow down for MACD crossunder signal line.
Radial Basis Kernel RSI for LoopRadial Basis Kernel RSI for Loop
What it is
An RSI-style oscillator that uses a radial basis function (RBF) kernel to compute a similarity-weighted average of gains and losses across many lookback lengths and kernel widths (γ). By averaging dozens of RSI estimates—each built with different parameters—it aims to deliver a smoother, more robust momentum signal that adapts to changing market conditions.
How it works
The script measures up/down price changes from your chosen Source (default: close).
For each combination of RSI length and Gamma (γ) in your ranges, it builds an RSI where recent bars that look most similar (by price behavior) get more weight via an RBF kernel.
It averages all those RSIs into a single value, then smooths it with your selected Moving Average type (SMA, EMA, WMA, HMA, DEMA) and a light regression-based filter for stability.
Inputs you can tune
Min/Max RSI Kernel Length & Step: Range of RSI lookbacks to include in the ensemble (e.g., 20→40 by 1) or (e.g., 30→50 by 1).
Min/Max Gamma & Step: Controls the RBF “width.” Lower γ = broader similarity (smoother); higher γ = more selective (snappier).
Source: Price series to analyze.
Overbought / Oversold levels: Defaults 70 / 30, with a midline at 50. Shaded regions help visualize extremes.
MA Type & Period (Confluence): Final smoothing on the averaged RSI line (e.g., DEMA(44) by default).
Red “OB” labels when the line crosses down from extreme highs (~80) → potential overbought fade/exit areas.
Green “OS” labels when the line crosses up from extreme lows (~20) → potential oversold bounce/entry areas.
How to use it
Treat it like RSI, but expect fewer whipsaws thanks to the ensemble and kernel weighting.
Common approaches:
Look for crosses back inside the bands (e.g., down from >70 or up from <30).
Use the 50 midline for directional bias (above = bullish momentum tilt; below = bearish).
Combine with trend filters (e.g., your chart MA) for higher-probability signals.
Performance note: This is really heavy and depending on how much time your subscription allows you could experience this timing out. Increasing the step size is the easiest way to reduce the load time.
Works on any symbol or timeframe. Like any oscillator, best used alongside price action and risk management rather than in isolation.
REMS Snap Shot OverlayThe REMS Snap Shot indicator is a multi-factor, confluence-based system that combines momentum (RSI, Stochastic RSI), trend (EMA, MACD), and optional filters (volume, MACD histogram, session time) to identify high-probability trade setups. Signals are only triggered when all enabled conditions align, giving the trader a filtered, visually clear entry signal.
This indicator uses an optional 'look-back' feature where in it will signal an entry based on the recency of specified cross events.
To use the indicator, select which technical indicators you wish to filter, the session you wish to apply (default is 9:30am - 4pm EST, based on your chart time settings), and if which cross events you wish to trigger a reset on the cooldown.
The default settings filter the 4 major technical indicators (RSI, EMAs, MACD, Stochastic RSI) but optional filters exist to further fine tune Stochastic Range, MACD momentum and strength, and volume, with optional visual cues for MACD position, Stochastic RSI position, and volume.
EMAs can be drawn on the chart from this indicator with optional shaded background.
This indicator is an alternative to REMS First Strike, which uses a recency filter instead of a cool down.
REMS First Strike OverlayThe REMS First Strike indicator is a multi-factor, confluence-based system that combines momentum (RSI, Stochastic RSI), trend (EMA, MACD), and optional filters (volume, MACD histogram, session time) to identify high-probability trade setups. Signals are only triggered when all enabled conditions align, giving the trader a filtered, visually clear entry signal.
This indicator uses an optional 'cool down' feature where in it will signal an entry only after any of the specified cross events occur.
To use the indicator, select which technical indicators you wish to filter, the session you wish to apply (default is 9:30am - 4pm EST, based on your chart time settings), and if which cross events you wish to trigger a reset on the cooldown.
The default settings filter the 4 major technical indicators (RSI, EMAs, MACD, Stochastic RSI) but optional filters exist to further fine tune Stochastic Range, MACD momentum and strength, and volume, with optional visual cues for MACD position, Stochastic RSI position, and volume.
EMAs can be drawn on the chart from this indicator with optional shaded background.
This indicator is an alternative to REMS Snap Shot, which uses a recency filter instead of a cool down.
Persistence# Persistence
## What it does
Measures **price change persistence**, defined as the percentage of bars within a lookback window that closed higher than the prior close. A high value means the instrument has been closing up frequently, which can indicate durable momentum. This mirrors Stockbee’s idea: *select stocks with high price change persistence*, and then combine **momentum plus persistence**.
## Can be used for scanning in PineScreener
## Calculation
* `isUp` is true when `close > close `.
* `countUp` counts true instances over the last `len` bars.
* `pctUp = 100 * countUp / len`, bounded between 0 and 100.
* A 50% level is a natural baseline. Above 50% suggests more up closes than down closes in the window.
## Inputs
* **Lookback bars (`len`)**: default 252 for roughly one trading year on a daily chart. On weekly charts use something like 52, on monthly charts use 12.
## How to use
1. **Screen for persistence**
Sort a watchlist by the plotted value, higher is better. Many momentum traders start looking above 58 to 65 percent, then layer a trend filter.
2. **Combine with momentum**
Examples, pick tickers with:
* `pctUp > 60`, and price above a rising EMA50 or EMA100.
* `pctUp rising` and weekly ROC positive.
3. **Switch timeframe to change the horizon**
* Daily chart with `len = 252` approximates one year.
* Weekly chart with `len = 52` approximates one year.
* Monthly chart with `len = 12` approximates one year.
## TC2000 equivalence
Stockbee’s TC2000 expression:
```
CountTrue(c > c1, 252)
```
## Interpretation guide
* **70 to 90**: very strong persistence; often trend leaders, check for extensions and risk controls.
* **60 to 70**: constructive persistence; good hunting ground for swing setups that also pass momentum filters.
* **50**: neutral baseline; around random up vs down frequency.
* **Below 50**: persistent weakness; consider only for mean reversion or short strategies.
## Practical tips
* **Event effects**: ex-dividend gaps can reduce persistence on high yield names. Earnings gaps can swing the value sharply.
* **Survivorship bias**: when backtesting on curated lists, persistence can look cleaner than in live scans.
* **Liquidity**: thin names may show noisy persistence due to erratic prints.
## Reference to Stockbee
* “One way to select stocks for swing trading is to find those with high price change persistence.”
* “Persistence can be calculated on a daily, monthly, or weekly timeframe.”
* TC2000 function: `CountTrue(c > c1, 252)`
* Example noted in the tweet: CVNA had very high one-year price persistence at the time of that post.
* Takeaway: **look for momentum plus persistence**, not persistence alone.
FlowFusion Money Flow — FP + VWAP Drift + PVT (−100..+100)Title (ASCII only)
FlowFusion Money Flow — Flow Pressure + Rolling VWAP Drift + PVT (Normalized −100..+100)
Short Description
Original money-flow oscillator combining Flow Pressure, Rolling VWAP Drift, and PVT Momentum into one normalized score (−100..+100) with a signal line, thresholds, optional component plots, and ready-made alerts.
Full Description (meets “originality & usefulness”)
What’s original
FlowFusion Money Flow is not a generic mashup. It builds a single score from three complementary, volume-aware components that target different facets of order flow:
Flow Pressure (FP) — In-bar directional drive scaled by relative volume.
Drive
=
close
−
open
max
(
high
−
low
,
tick
)
∈
=
max(high−low, tick)
close−open
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Relative Volume
=
volume
average volume over
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=
average volume over fpLen
volume
.
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=
Drive
×
RelVol
FP
raw
=Drive×RelVol then squashed (softsign) to
.
Why it belongs: distinguishes real pushes (big body and big volume) from noise.
Rolling VWAP Drift — Direction of VWAP itself over a rolling window, normalized by ATR.
𝑉
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𝑡
=
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)
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VWAP
t
=
∑Vol
∑(TP×Vol)
over vwapLen.
Drift
=
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=
ATR
VWAP
t
−VWAP
t−1
→ squashed to
.
Why it belongs: persistent VWAP movement signals sustained accumulation/distribution.
PVT Momentum — Price-Volume Trend standardized (z-score) and squashed.
𝑃
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PVT
t
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t−1
+Vol×
Close
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ΔClose
.
𝑧
=
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(
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)
StDev
(
𝑃
𝑉
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)
z=
StDev(PVT)
PVT−SMA(PVT)
→ squashed to
.
Why it belongs: captures volume-weighted trend pressure without relying on price alone.
Composite score:
Score
=
𝑤
𝐹
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Score=
w
FP
+w
VWAP
+w
PVT
w
FP
⋅FP+w
VWAP
⋅VWAP_Drift+w
PVT
⋅PVT_Mom
with a Signal = SMA(Score, sigLen). Thresholds mark strong accumulation/distribution zones.
How it works (step-by-step)
Compute FP, VWAP Drift, PVT Momentum.
Normalize each to the same
scale.
Weighted average → FlowFusion Score.
Smooth with a Signal line to reduce whipsaw.
Optional background shading when Score exceeds thresholds.
How to use
Direction filter:
Score > 0 favors longs; Score < 0 favors shorts.
Momentum turns:
Score crosses above Signal → setup for long; below → setup for short.
Strength zones:
Above Upper Threshold (default +40) = strong buy pressure; below Lower (−40) = strong sell pressure.
Confluence:
Best near S/R, trendlines, or HTF bias. For scalping on 1–5m, consider sigLen 9–13 and thresholds ±40 to ±50.
Alerts included: zero cross, zone entries, and Score/Signal crossovers.
Inputs (key)
fpLen (20): relative-volume lookback for Flow Pressure.
vwapLen (34): rolling VWAP window.
pvtLen (50): PVT z-score window.
sigLen (9): Signal smoothing.
Weights: wFP, wVWAP, wPVT to bias the blend.
Thresholds: upperBand / lowerBand (defaults +40/−40).
Display: toggle component plots and background shading.
Best practices
Trending markets: increase wVWAP (VWAP Drift) or widen thresholds.
Ranging markets: increase wFP and wPVT; take quicker profits.
News: wait for bar close confirmation or reduce size.
Data quality: use consistent volume feeds (especially in crypto).
Limitations
Oscillators can stay extreme in strong trends; use structure/trend filters.
Volume anomalies (illiquid pairs, API glitches) can distort signals—sanity-check with another venue when possible.
Disclaimer
This indicator is for educational purposes only and is not financial advice. Trading involves risk; past performance does not guarantee future results. Always paper-trade first and use appropriate risk controls.
ForecastForecast (FC), indicator documentation
Type: Study, not a strategy
Primary timeframe: 1D chart, most plots and the on-chart table only render on daily bars
Inspiration: Robert Carver’s “forecast” concept from Advanced Futures Trading Strategies, using normalized, capped signals for comparability across markets
⸻
What the indicator does
FC builds a volatility-normalized momentum forecast for a chosen symbol, optionally versus a benchmark. It combines an EWMAC composite with a channel breakout composite, then caps the result to a common scale. You can run it in three data modes:
• Absolute: Forecast of the selected symbol
• Relative: Forecast of the ratio symbol / benchmark
• Combined: Average of Absolute and Relative
A compact table can summarize the current forecast, short-term direction on the forecast EMAs, correlation versus the benchmark, and ATR-scaled distances to common price EMAs.
⸻
PineScreener, relative-strength screening
This indicator is excellent for screening on relative strength in PineScreener, since the forecast is volatility-normalized and capped on a common scale.
Available PineScreener columns
PineScreener reads the plotted series. You will see at least these columns:
• FC, the capped forecast
• from EMA20, (price − EMA20) / ATR in ATR multiples
• from EMA50, (price − EMA50) / ATR in ATR multiples
• ATR, ATR as a percent of price
• Corr, weekly correlation with the chosen benchmark
Relative mode and Combined mode are recommended for cross-sectional screens. In Relative mode the calculation uses symbol / benchmark, so ensure the ratio ticker exists for your data source.
⸻
How it works, step by step
1. Volatility model
Compute exponentially weighted mean and variance of daily percent returns on D, annualize, optionally blend with a long lookback using 10y %, then convert to a price-scaled sigma.
2. EWMAC momentum, three legs
Daily legs: EMA(8) − EMA(32), EMA(16) − EMA(64), EMA(32) − EMA(128).
Divide by price-scaled sigma, multiply by leg scalars, cap to Cap = 20, average, then apply a small FDM factor.
3. Breakout momentum, three channels
Smoothed position inside 40, 80, and 160 day channels, each scaled, then averaged.
4. Composite forecast
Average the EWMAC composite and the breakout composite, then cap to ±20.
Relative mode runs the same logic on symbol / benchmark.
Combined mode averages Absolute and Relative composites.
5. Weekly correlation
Pearson correlation between weekly closes of the asset and the benchmark over a user-set length.
6. Direction overlay
Two EMAs on the forecast series plus optional green or red background by sign, and optional horizontal level shading around 0, ±5, ±10, ±15, ±20.
⸻
Plots
• FC, capped forecast on the daily chart
• 8-32 Abs, 8-32 Rel, single-leg EWMAC plus breakout view
• 8-32-128 Abs, 8-32-128 Rel, three-leg composite views
• from EMA20, from EMA50, (price − EMA) / ATR
• ATR, ATR as a percent of price
• Corr, weekly correlation with the benchmark
• Forecast EMA1 and EMA2, EMAs of the forecast with an optional fill
• Backgrounds and guide lines, optional sign-based background, optional 0, ±5, ±10, ±15, ±20 guides
Most plots and the table are gated by timeframe.isdaily. Set the chart to 1D to see them.
⸻
Inputs
Symbol selection
• Absolute, Relative, Combined
• Vs. benchmark for Relative mode and correlation, choices: SPY, QQQ, XLE, GLD
• Ticker or Freeform, for Freeform use full TradingView notation, for example NASDAQ:AAPL
Engine selection
• Include:
• 8-32-128, three EWMAC legs plus three breakouts
• 8-32, simplified view based on the 8-32 leg plus a 40-day breakout
EMA, applied to the forecast
• EMA1, EMA2, with line-width controls, plus color and opacity
Volatility
• Span, EW volatility span for daily returns
• 10y %, blend of long-run volatility
• Thresh, Too volatile, placeholders in this version
Background
• Horizontal bg, level shading, enabled by default
• Long BG, Hedge BG, colors and opacities
Show
• Table, Header, Direction, Gain, Extension
• Corr, Length for correlation row
Table settings
• Position, background, opacity, text size, text color
Lines
• 0-lines, 10-lines, 5-lines, level guides
⸻
Reading the outputs
• Forecast > 0, bullish tilt; Forecast < 0, bearish or hedge tilt
• ±10 and ±20 indicate strength on a uniform scale
• EMA1 vs EMA2 on the forecast, EMA1 above EMA2 suggests improving momentum
• Table rows, label colored by sign, current forecast value plus a green or red dot for the forecast EMA cross, optional daily return percent, weekly correlation, and ATR-scaled EMA9, EMA20, EMA50 distances
⸻
Data handling, repainting, and performance
• Daily and weekly series are fetched with request.security().
• Calculations use closed bars, values can update until the bar closes.
• No lookahead, historical values do not repaint.
• Weekly correlation updates during the week, it finalizes on weekly close.
• On intraday charts most visuals are hidden by design.
⸻
Good practice and limitations
• This is a research indicator, not a trading system.
• The fixed Cap = 20 keeps a common scale, extreme moves will be clipped.
• Relative mode depends on the ratio symbol / benchmark, ensure both legs have data for your feed.
⸻
Credits
Concept inspired by Robert Carver’s forecast methodology in Advanced Futures Trading Strategies. Implementation details, parameters, and visuals are specific to this script.
⸻
Changelog
• First version
⸻
Disclaimer
For education and research only, not financial advice. Always test on your market and data feed, consider costs and slippage before using any indicator in live decisions.
Colored Trix with spike detectionColored TRIX with Spike Detection
This indicator combines multiple TRIX oscillators (periods 5, 7, 10, 14) with advanced spike detection capabilities. Key features:
Dynamic Color Coding: TRIX lines change color based on value (positive/negative) and slope direction, providing instant visual feedback on momentum shifts
Multi-Period Analysis: Four different TRIX periods offer comprehensive momentum analysis across various timeframes
Intelligent Spike Detection: Automatically identifies significant TRIX spikes using percentile-based thresholds and distance measurements from recent highs/lows
Visual Markers: Highlights important levels with yellow dots and reference lines showing lowest, median, and average TRIX values during spike periods
Customizable Parameters: Adjustable spike thresholds, distance percentiles, and color schemes to fit your trading style
Alert System: Built-in alerts for positive and negative spike detection
The indicator helps traders identify momentum changes, oversold/overbought conditions, and potential reversal points through sophisticated spike analysis. Perfect for swing trading and trend following strategies.
Standardized Cumulative Deltas [LuxAlgo]The Standardized Cumulative Deltas tool allows traders to compare the cumulative standardized open-close difference for up to 10 different tickers, allowing them to visualize the general sentiment for all selected tickers.
These results allow the construction of two areas showing the average or extreme bullish and bearish cumulative change for all enabled tickers, providing a summarized view of the overall ticker group sentiment.
🔶 USAGE
This tool is meant to give a full picture of the individuals and/or overall selected tickers, and unlike classical indicators, the displayed series of values is not meant to be directly interpreted over time.
Given the selected lookback period, a majority of observations being above 0 indicate an overall bullish market for the asset.
By default, the auto lookback period feature is enabled, allowing the tool to use all the visible bars for its calculations. Traders can also set the lookback period manually. The above chart uses a fixed lookback period of 500.
Up to 10 tickers can be used. While major cryptocurrencies are set by default, the users can set a specific basket of assets, such as US equities, forex pairs, commodities, etc.
🔹 Densities
The provided areas, here called densities, can be used to get an overall sentiment of the selected tickers. The upper density (bullish) processes positive deltas, while the lower one (bearish) processes negative ones.
Interpretation is subject to the selected "Density Mode".
Average: Densities track the average bullish/bearish cumulative deltas for the selected tickers. For example, a more prominent bullish density would indicate that, on average, cumulative deltas were positive across the tickers.
Envelope: Densities track the extreme values made by bullish/bearish cumulative deltas for the selected tickers. Here, a more prominent density would indicate more volatile bullish/bearish movements, depending on the density.
🔹 Dashboard
The tool features a dashboard with active tickers and their respective colors for traders' convenience.
🔶 DETAILS
🔹 Densities
Densities are obtained by applying a forward-backward exponential moving average on the average, or the highest/lowest cumulative series, depending on the selected Density Mode.
The resulting densities are smoothed by the "Smoothing" parameter located in the Settings panel, with higher values returning smoother envelopes with less variability.
Do note that the smoothing method used here is subject to repainting.
🔶 SETTINGS
Lookback: Select the lookback period and enable/disable the Auto Lookback feature
Tickers: Enable/disable and select up to 10 tickers and their colors
Density Mode: Determine how densities are calculated
🔹 Dashboard
Show Dashboard: Enable/disable the dashboard
Position: Select the dashboard position
Size: Select the dashboard size
🔹 Style
Density: Enable/disable the density areas
Bullish Density: Select the color of the top density area
Bearish Density: Select the color of the bottom density area
Smoothing: Select the smoothing constant for the EMA calculation
Dynamic Momentum Oscillator with Adaptive ThresholdsDynamic Momentum Oscillator with Adaptive Thresholds (DMO-AT)
This advanced indicator is designed to provide traders with a robust tool for identifying momentum shifts, overbought/oversold conditions, and potential reversals in any market. Unlike traditional oscillators with fixed thresholds, DMO-AT uses adaptive levels that adjust based on current volatility (via ATR) and incorporates volume weighting for more accurate signals in high-volume environments.
#### Key Features:
- **Momentum Calculation**: A normalized momentum value derived from price changes, optionally weighted by volume for enhanced sensitivity.
- **Adaptive Thresholds**: Overbought and oversold levels dynamically adjust using ATR, making the indicator adaptable to volatile or ranging markets.
- **Signal Line**: An EMA of the momentum for crossover signals, helping confirm trend directions.
- **Divergence Detection**: Built-in alerts for bullish and bearish divergences between price and momentum.
- **Visual Enhancements**: Background coloring for quick zone identification, dashed static lines for reference, and a customizable stats table displaying real-time values.
- **Alerts**: Multiple alert conditions for crossovers, zone entries, and divergences to keep you notified without constant chart watching.
#### How to Use:
1. Add the indicator to your chart via TradingView's indicator search.
2. Customize inputs: Adjust the momentum length, source, ATR length, and threshold multiplier to fit your trading style (e.g., shorter lengths for scalping, longer for swing trading).
3. Interpret Signals:
- **Crossover**: Momentum crossing above the signal line suggests bullish momentum; below indicates bearish.
- **Zones**: Entering the overbought (red) zone may signal a potential sell; oversold (green) for buys.
- **Divergences**: Use alerts to spot hidden opportunities where price and momentum disagree.
4. Combine with other tools like moving averages or support/resistance for confluence.
5. Enable the stats table for at-a-glance insights on the chart.
This indicator is versatile across timeframes and assets, from stocks to crypto. It's optimized for clarity and performance, with no repainting.
VWMA MACD Trend Grinder Buy/Sell SignalsDescription:
This indicator combines a VWMA-based MACD with volume and trend filters to reduce false buy and sell signals.
It is designed to give more reliable entry and exit points in trending markets while avoiding low-volume noise.
Features:
1. VWMA MACD:
- MACD is calculated using Volume-Weighted Moving Averages (VWMA) instead of standard EMAs.
- Histogram shows the difference between MACD and its signal line.
2. Volume Filter:
- Signals are only triggered when current volume exceeds a multiple of its moving average.
- Reduces false signals in low-volume periods.
3. Trend Filter:
- Only triggers buy signals when price is above a long-term VWMA (uptrend).
- Only triggers sell signals when price is below the long-term VWMA (downtrend).
- Helps avoid counter-trend trades.
4. Plots:
- MACD (blue), Signal (orange), Histogram (green/red)
- Trend VWMA (purple)
- Buy and Sell arrows in the indicator pane (green/red)
5. Alerts:
- Configurable alerts for buy and sell signals filtered by volume and trend.
Inputs:
- Fast Length: VWMA period for the fast MACD line (default 12)
- Slow Length: VWMA period for the slow MACD line (default 26)
- Signal Length: EMA period for the MACD signal line (default 9)
- Volume MA Length: Length for volume moving average filter (default 20)
- Volume Threshold Multiplier: Multiplier for volume filter (default 1.2)
- Trend VWMA Length: Period for long-term trend VWMA (default 50)
- Price Source: Close, HL2, HLC3, OHLC4
Usage:
- Use as a confirmation tool along with other analysis techniques.
- Buy when the green triangle appears (MACD crossover, above trend VWMA, sufficient volume).
- Sell when the red triangle appears (MACD crossunder, below trend VWMA, sufficient volume).
- Trend VWMA helps visually confirm the market trend.
