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."
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
🎲 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
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
💎 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
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
⚙️ 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
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
📊 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
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
🎯 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
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Developed by AlphaNatt | Quantitative Trading Systems
Version: 1.0
Classification: Statistical Transform Oscillator
Not financial advice. Always DYOR.
中心震荡指标
Ark FCI OscillatorFinancial Conditions Index Oscillator
This indicator tracks week-over-week changes in the National Financial Conditions Index (NFCI), providing a dynamic view of evolving financial conditions in the United States.
Overview
The National Financial Conditions Index (NFCI) is a comprehensive weekly composite index published by the Federal Reserve Bank of Chicago. It measures financial conditions across U.S. money markets, debt and equity markets, and the traditional and shadow banking systems.
Interpretation
Positive values indicate improving financial conditions
Negative values signal deteriorating financial conditions
Risk assets demonstrate particular sensitivity to changes in financial conditions, making this oscillator valuable for market timing and risk assessment.
Alternative Data Source
Users can modify the source to FRED:NFCIRISK to focus specifically on risk dynamics. The NFCIRISK subindex isolates volatility and funding risk measures within the financial sector, capturing market volatility indicators and liquidity shortage probabilities while excluding broader credit and leverage conditions.
Hurst Momentum Oscillator | AlphaNattHurst Momentum Oscillator | AlphaNatt
An adaptive oscillator that combines the Hurst Exponent - which identifies whether markets are trending or mean-reverting - with momentum analysis to create signals that automatically adjust to market regime.
"The Hurst Exponent reveals a hidden truth: markets aren't always trending. This oscillator knows when to ride momentum and when to fade it."
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
📐 THE MATHEMATICS
Hurst Exponent (H):
Measures the long-term memory of time series:
H > 0.5: Trending (persistent) behavior
H = 0.5: Random walk
H < 0.5: Mean-reverting behavior
Originally developed for analyzing Nile river flooding patterns, now used in:
Fractal market analysis
Network traffic prediction
Climate modeling
Financial markets
The Innovation:
This oscillator multiplies momentum by the Hurst coefficient:
When trending (H > 0.5): Momentum is amplified
When mean-reverting (H < 0.5): Momentum is reduced
Result: Adaptive signals based on market regime
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
💎 KEY ADVANTAGES
Regime Adaptive: Automatically adjusts to trending vs ranging markets
False Signal Reduction: Reduces momentum signals in mean-reverting markets
Trend Amplification: Stronger signals when trends are persistent
Mathematical Edge: Based on fractal dimension analysis
No Repainting: All calculations on historical data
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
📊 TRADING SIGNALS
Visual Interpretation:
Cyan zones: Bullish momentum in trending market
Magenta zones: Bearish momentum or mean reversion
Background tint: Blue = trending, Pink = mean-reverting
Gradient intensity: Signal strength
Trading Strategies:
1. Trend Following:
Trade momentum signals when background is blue (trending)
2. Mean Reversion:
Fade extreme readings when background is pink
3. Regime Transition:
Watch for background color changes as early warning
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
🎯 OPTIMAL USAGE
Best Conditions:
Strong trending markets (crypto bull runs)
Clear ranging markets (forex sessions)
Regime transitions
Multi-timeframe analysis
Market Applications:
Crypto: Excellent for identifying trend persistence
Forex: Detects when pairs are ranging
Stocks: Identifies momentum stocks
Commodities: Catches persistent trends
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Developed by AlphaNatt | Fractal Market Analysis
Version: 1.0
Classification: Adaptive Regime Oscillator
Not financial advice. Always DYOR.
Argentum Flag [AGP]Ver.2.1Technical Description of the "Argentum Flag " Indicator
The "Argentum Flag " is a multifaceted trading indicator designed to provide a comprehensive view of market dynamics by combining elements of trend, volatility, momentum, and volume analysis. Its architecture is built on the synergy of multiple technical tools, allowing traders to make more informed decisions by reducing market noise and focusing on high-probability inflection points.
1. Dynamic AGP Bands (EMA 36 and Percentage Levels)
The core of the indicator is a 36-period Exponential Moving Average (EMA), which acts as the price's baseline and center of gravity. From this EMA, the script plots dynamic bands at predefined percentages (Base, Prime, and Vortex).
Logic: These bands are not static like Bollinger Bands; they expand and contract in response to the underlying EMA. This methodology helps identify relative volatility and trend strength. When the price trades within these bands, it's considered to be in a range or a controlled consolidation.
Benefit to the Trader: They provide a quick visual of dynamic support and resistance levels. A price movement beyond the Vortex band can signal an extreme market imbalance, suggesting potential trend exhaustion or a high-energy breakout.
2. Breakout Signals (Signals)
The indicator generates plotshape signals when the price stays outside the volatility bands for a specific number of consecutive bars (2 for the Prime band and 3 for the Vortex band).
Logic: These signals act as an overextension detection system. The underlying principle is that once the price breaks and holds outside these zones, the probability of a pullback or a reversal increases significantly. The lastSignalBarIndex logic prevents signal overload and ensures a cooling-off period, eliminating noise from consecutive signals.
Benefit to the Trader: It provides clear visual alerts for taking profits or looking for potential reversals. A trader can use the Vortex band exit signal (⌾) as confirmation to close a long or short position, while the Prime band signal (⍲) can indicate a potential pullback for a trend-following entry.
3. Bar Volume Analysis (Barcolor)
The script introduces a sophisticated bar coloring system that classifies volume activity relative to a 50-period Simple Moving Average (SMA).
Logic: The coloring is based not only on whether the bar is bullish or bearish but also on the magnitude of the volume. For instance, extreme volume (more than 3.5 times the average volume) is colored blue, indicating institutional participation or a high-impact event. High (1.8x) or average (0.6x - 1.7x) volume is distinguished with other colors, providing a visual map of the underlying strength behind each price move.
Benefit to the Trader: It allows for a quick identification of bars with the highest market conviction. A bearish price bar with extreme volume (extreme_volume_bearish) might signal significant liquidation, while a bullish bar with extreme volume (extreme_volume_bullish) could suggest strong accumulation.
4. Real-Time Monitoring Tables (EMA and RSI)
The indicator includes two data tables in the bottom corner of the screen, acting as a dashboard for multi-timeframe analysis.
EMA Table (Fibonacci): This table shows the current values of a series of Fibonacci-based EMAs (13, 21, 34, etc.). The background color of each cell indicates whether the current price is above (white) or below (blue) the corresponding EMA.
Logic: This table allows traders to assess the trend bias across different timeframes, from short to long-term. An alignment of multiple EMAs in the same direction (e.g., all white) confirms a strong trend.
Benefit to the Trader: It provides a quick check for trend confirmation. For example, before opening a long position on a 5-minute chart, a trader can verify if the overall trend on higher timeframes (e.g., 4h or 1D) is also bullish.
RSI Table (Multi-Timeframe): This table shows the Relative Strength Index (RSI) values across multiple timeframes, from 1 minute to monthly. The cell lights up orange if the RSI is in the overbought zone (> 77) or white if it's in the oversold zone (< 23).
Logic: The use of request.security enables the fetching of data from other timeframes on the current bar. This is a crucial component for multi-timeframe divergence analysis.
Benefit to the Trader: It helps identify overbought or oversold conditions across different trading horizons, which is vital for spotting large-scale reversals. If the 1D and 4h RSIs are overbought, a long position on a lower timeframe could be high-risk.
Competitive Advantages for Traders
The "Argentum Flag " is not just a simple indicator; it's a consolidated technical analysis suite that saves time and effort. Instead of overlaying multiple indicators, a trader gets all the relevant information in a single view. The contextualized volume analysis and volatility-based signals are invaluable tools for filtering out low-quality entries and exits. Finally, the real-time monitoring tables provide a multi-timeframe perspective that is fundamental for validating market direction and managing risk.
In trading, the convergence of multiple technical data points is key to increasing the probability of success. This indicator provides precisely that convergence, enabling both novice and experienced traders to make more precise and strategic decisions.
Risk Warning (Disclaimer)
Trading in financial markets carries a significant risk of loss and is not suitable for all investors. The information and signals provided by this indicator are for educational and analysis purposes only and should not be construed as financial advice. The past performance of any trading system or methodology is not necessarily indicative of future results. The user assumes all responsibility for their own trading decisions and any resulting losses or gains.
Script_Algo - Double Smoothed CCI Strategy📉 The uniqueness of this non-trending oscillator strategy lies in the combination of two smoothed CCI lines: one signals entry into a position from overbought/oversold zones, and the other serves as a trend filter for entries. The smoothing of the fast and slow CCI lines significantly reduces market noise, allowing the filtering of false signals often generated by the standard CCI.
📚 For those unfamiliar with CCI:
The Commodity Channel Index (CCI) is a momentum-based oscillator used to identify overbought and oversold conditions.
It helps traders spot potential trend reversals or confirm trend strength by comparing the current price to its average over a period of time.
1️⃣ General Principle of Operation
⚡ Fast CCI: Generates main signals when exiting oversold and overbought zones.
📈 Slow CCI: Acts as a trend filter. For long positions, the slow CCI must be above zero (confirmation of an uptrend), and for short positions, it must be below zero (confirmation of a downtrend). This prevents the strategy from opening trades against the dominant trend.
🛡️ Dynamic ATR Stop-Loss: Unlike fixed-percentage stop-losses, a stop tied to the Average True Range (ATR) considers market volatility. During calm periods, the stop will be narrower, allowing for more profit capture. In highly volatile periods, the stop becomes wider, protecting against premature closures caused by noise.
📊 Comprehensive Risk Management: The strategy uses not only a take-profit based on signals (exit into the opposite zone) but also a protective ATR stop-loss and a mechanism to close trades upon receiving an opposite signal (e.g., closing a long when a short signal appears).
💡 Usefulness of the Strategy:
👨💻 For traders: Provides clear, mathematically justified entry and exit signals with built-in loss protection.
📉 For analysts: Visualizes the behavior of the double CCI on a separate panel, allowing study of the interaction of the fast and slow lines and their reaction to levels without mandatory trades.
📚 For learning: An excellent example of combining multiple indicators and capital management tools into a single trading system.
2️⃣ Detailed Algorithm Logic
📥 Long Entry Signals:
The fast smoothed CCI was below the oversold level (oversold_level, e.g., -100) and crossed this level upward (fast_exits_oversold).
The slow CCI at this moment is above zero (confirming an uptrend).
If both conditions are met, a long position is opened.
📤 Long Exit: Happens under one of these conditions:
The fast CCI crosses the overbought level (overbought_level) downward (exit_long).
The price reaches a stop-loss level calculated as entry price - (ATR * multiplier).
An opposite short signal appears (enter_short).
📥 Short Entry Signals:
The fast CCI was above the overbought level (overbought_level, e.g., 100) and crossed this level downward (fast_exits_overbought).
The slow CCI at this moment is below zero (confirming a downtrend).
If both conditions are met, a short position is opened.
📤 Short Exit: Happens under one of these conditions:
The fast CCI crosses the oversold level (oversold_level) upward (exit_short).
The price reaches a stop-loss level calculated as entry price + (ATR * multiplier).
An opposite long signal appears (enter_long).
3️⃣ Default Settings Description
⚙️ General Strategy Settings (strategy):
overlay=false: The indicator is displayed in a separate panel below the chart, not overlaid on it.
default_qty_type=strategy.cash, default_qty_value=1000, initial_capital=100000: The strategy manages a virtual capital of 100,000 USD, using 1,000 USD per trade.
commission_value=0.1, slippage=1: Commission (0.1%) and slippage (1 tick) are considered for more realistic testing.
⚡ Fast CCI (Signal Generator):
Length: 8 (short enough for quick price reactions).
Source: hlc3 (average of High, Low, Close).
Smoothing: WMA (Weighted Moving Average) for smoother results than SMA.
Smoothing Length: 5 (removes part of the noise).
📈 Slow CCI (Trend Filter):
Length: 20 (standard mid-term trend period).
Source: close.
Smoothing: WMA.
Smoothing Length: 21 (even stronger smoothing for a clean trend line).
📊 Levels:
Overbought Level: 100 (classic CCI level).
Oversold Level: -100 (classic CCI level).
🛡️ Stop-Loss (ATR):
ATR Length: 6 (short period for quick adaptation).
ATR Multiplier: 10.0 (very wide stop, designed for long-term trade holding and noise filtering).
💰 As seen in backtests, this strategy shows a steadily growing equity curve with minor drawdowns. On the highly liquid crypto pair XRPUSDT, the algorithm demonstrated a fairly high win rate and relatively high profit factor on a 4-hour timeframe over 4 years, though the overall profit is moderate.
⚠️ Important Notes
Always remember: Strategy results may not repeat in the future.
The market constantly changes, so:
✅ Monitor the situation
✅ Backtest regularly
✅ Adjust settings for each asset
Also remember about possible bugs in any algorithmic trading strategy.
Even if a script is well-tested, no one knows what unpredictable events the market may bring tomorrow.
⚠️ Risk Management:
Do not risk more than 1% of your deposit per trade, otherwise you may lose your account balance, since this strategy works without stop losses.
⚠️ Disclaimer
The author of the strategy does not encourage anyone to use this algorithm and bears no responsibility for any possible financial losses resulting from its application!
Any decision to use this strategy is made personally by the owners of TradingView accounts and cryptocurrency exchange accounts.
📝 Final Notes
This is not the final version. I already have ideas on how to improve it further, so follow me to not miss updates.
🐞 Bug Reports
If you notice any bugs or inconsistencies in my algorithm,
please let me know — I will try to fix them as quickly as possible.
💬 Feedback & Suggestions
If you have any ideas on how this or any of my other strategies can be improved, feel free to write to me. I will try to implement your suggestions in the script.
Wishing everyone good luck and stable profits! 🚀💰
(SVD+CVD) + DivergenceCombines multiple CVD indicators all into one. Infinitely useful for determining buyer/seller aggression.
Histogram shows both singular and an additive bar, white CVD line shows them cumulatively plotted, green and red lines show cumulative buy or sell with a vertical line to indicate the dropoff period.
I used some of JollyWizards code from his indicator, and tweaked a few things, along with adding some features.
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.
MACD, RSI & Stoch + Divergences
Best results with combination My_EMA_clouds and Market Mood Maker
This script is a comprehensive technical analysis tool that combines several popular indicators and divergence detection features.
The main components of the script include:
* **MACD indicator** with histogram displaying moving averages and their divergence
* **RSI (Relative Strength Index)** for momentum analysis
* **Stochastic Oscillator** for overbought/oversold levels
* **Divergence detection** system identifying both regular and hidden bullish/bearish divergences between price action and oscillators
Key features:
* Customizable settings for each indicator (periods, smoothing parameters)
* Flexible visualization options (lines, arrows, labels)
* Multiple oscillator display modes (RSI, Stochastic, MACD, or Histogram)
* Pivot point detection for accurate divergence identification
* Configurable lookback period for analysis
* Color-coded signals for easy interpretation
* Horizontal levels for overbought/oversold zones
* Interactive settings panel for customization
The script provides traders with a comprehensive toolkit for identifying potential reversal points and confirming trend directions through divergence analysis across multiple timeframes and indicators.
анный скрипт представляет собой комплексный инструмент технического анализа, который объединяет несколько популярных индикаторов и систему обнаружения дивергенций.
Основные компоненты скрипта включают:
Индикатор MACD с гистограммой, отображающей скользящие средние и их расхождения
Индекс относительной силы (RSI) для анализа импульса
Стохастический осциллятор для определения уровней перекупленности/перепроданности
Система обнаружения дивергенций, выявляющая как обычные, так и скрытые бычьи/медвежьи дивергенции между ценовым движением и осцилляторами
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.
