BERLIN Renegade - Baseline & RangeThis is the baseline and range candles part of a larger algorithm called the "BERLIN Renegade". It is based on the NNFX way of trading, with some modifications.
The baseline is used for price crossover signals, and consists of the LSMA. When price is below the baseline, the background turns red, and when it is above the baseline, the background turns green.
It also includes a modified version of the Range Identifier by LazyBear. This version calculates the same, but draws differently. It remove the baseline signal color if the Range Identifier signals there is a possible trading range forming.
The main way of identifying ranges is using the BERLIN Range Index. A panel version of this indicator is included in another part of the algorithm, but the bar color version is included here, to make the ranges even more visible and easier to avoid.
Search in scripts for "algo"
Low Frequency Fourier TransformThis Study uses the Real Discrete Fourier Transform algorithm to generate 3 sinusoids possibly indicative of future price.
I got information about this RDFT algorithm from "The Scientist and Engineer's Guide to Digital Signal Processing" By Steven W. Smith, Ph.D.
It has not been tested thoroughly yet, but it seems that that the RDFT isn't suited for predicting prices as the Frequency Domain Representation shows that the signal is similar to white noise, showing no significant peaks, indicative of very low periodicity of price movements.
Correlation MATRIX (Flexible version)Hey folks
A quick unrelated but interesting foreword
Hope you're all good and well and tanned
Me? I'm preparing the opening of my website where we're going to offer the Algorithm Builder Single Trend, Multiple Trends, Multi-Timeframe and plenty of others across many platforms (TradingView, FXCM, MT4, PRT). While others are at the beach and tanning (Yes I'm jealous, so what !?!), we're working our a** off to deliver an amazing looking website and great indicators and strategies for you guys.
Today I worked in including the Trade Manager Pro version and the Risk/Reward Pro version into all our Algorithm Builders. Here's a teaser
We're going to have a few indicators/strategies packages and subscriptions will open very soon.
The website should open in a few weeks and we still have loads to do ... (#no #summer #holidays #for #dave)
I see every message asking me to allow access to my Algorithm Builders but with the website opening shortly, it will be better for me to manage the trials from there - otherwise, it's duplicated and I can't follow all those requests
As you can probably all understand, it becomes very challenging to publish once a day with all that workload so I'll probably slow down (just a bit) and maybe posting once every 2/3 days until the website will be over (please forgive me for failing you). But once it will open, the daily publishing will resume again :) (here's when you're supposed to be clapping guys....)
While I'm so honored by all the likes, private messages and comments encouraging me, you have to realize that a script always takes me about 2/3 hours of work (with research, coding, debugging) but I'm doing it because I like it. Only pushing the brake a bit because of other constraints
INDICATOR OF THE DAY
I made a more flexible version of my Correlation Matrix .
You can now select the symbols you want and the matrix will update automatically !!! Let me repeat it once more because this is very cool... You can now select the symbols you want and the matrix will update automatically :)
Actually, I have nothing more to say about it... that's all :) Ah yes, I added a condition to detect negative correlation and they're being flagged with a black dot
Definition : Negative correlation or inverse correlation is a relationship between two variables whereby they move in opposite directions.
A negative correlation is a key concept in portfolio construction, as it enables the creation of diversified portfolios that can better withstand portfolio volatility and smooth out returns.
Correlation between two variables can vary widely over time. Stocks and bonds generally have a negative correlation, but in the decade to 2018, their correlation has ranged from -0.8 to 0.2. (Source : www.investopedia.com
See you maybe tomorrow or in a few days for another script/idea.
Be sure to hit the thumbs up to cheer me up as your likes will be the only sunlight I'll get for the next weeks.... because working on building a great offer for you guys.
Dave
____________________________________________________________
- I'm an officially approved PineEditor/LUA/MT4 approved mentor on codementor. You can request a coaching with me if you want and I'll teach you how to build kick-ass indicators and strategies
Jump on a 1 to 1 coaching with me
- You can also hire for a custom dev of your indicator/strategy/bot/chrome extension/python
SMA/pivot/Bollinger/MACD/RSI en pantalla gráficoMulti-indicador con los indicadores que empleo más pero sin añadir ventanas abajo.
Contiene:
Cruce de 3 medias móviles
La idea es no tenerlas en pantalla, pero están dibujadas también. Yo las dejo ocultas salvo que las quiera mirar para algo.
Lo que presento en pantalla es la media lenta con verde si el cruce de las 3 marca alcista, amarillo si no está claro y rojo si marca bajista.
Pivot
Normalmente los tengo ocultos pero los muestro cuando me interesa. Están todos aunque aparezcan 2 seguidos.
Bandas de Bollinger
No dibujo la línea central porque empleo la media como tal.
Parabollic SAR
Lo empleo para dibujar las ondas de Elliott como postula Matías Menéndez Larre en el capítulo 11 de su libro "Las ondas de Elliott". Así que, aunque se puede mostrar, lo mantengo oculto y lo que muestro es dónde cambia (SAR cambio).
MACD
No está dibujado porque necesitaría sacarlo del gráfico.
Marco en la parte superior cuándo la señal sobrepasa al MACD hacia arriba o hacia abajo con un flecha indicando el sentido de esta señal.
RSI
Similar al MACD pero en la parte inferior.
Probablemente, programe otro indicador para visualizar en una ventanita MACD, RSI y volumen todo junto. El volumen en la principal hay veces que no te permite ver bien alguna sombra y los otros 2 te quitan mucho espacio para graficar si los tienes permanentemente en 2 ventanas separadas.
DFT - Dominant Cycle Period 8-50 bars - John EhlerThis is the translation of discret cosine tranform (DCT) usage by John Ehler for finding dominant cycle period (DC).
The price is first filtered to remove aliasing noise(bellow 8 bars) and trend informations(above 50 bars), then the power is computed.
The trick here is to use a normalisation against the maximum power in order to get a good frequency resolution.
Current limitation in tradingview does not allow to display all of the periods, still the DC period is plot after beeing computed based on the center of gravity algo.
The DC period can be used to tune all of the indicators based on the cycles of the markets. For instance one can use this (DC period)/2 as an input for RSI.
Hope you find this of some interrest.
[naoligo] Simple ADXI'm publishing this indicator just for study purposes, because the result is exactly the same as DMI without the smoothing factor. It is exactly the same as ADX Wilder from MT5.
I was looking for the algorithm all over and it was a pain to find the right formula, meaning: one that would match with the built-in ones. After several study and comparison, I still didn't find the algorithm that match with the MT5's built-in simple ADX ...
Enjoy!
Patrones de entrada/salida V.1.0 -BETA-Este algoritmo intenta identificar patrones o fractales dentro de los movimientos de precios para dar señales de compra o venta de activos.
Zero Lag MACD Enhanced - Version 1.1ENHANCED ZERO LAG MACD
Version 1.1
Based on ZeroLag EMA - see Technical Analysis of Stocks and Commodities, April 2000
Original version by user Glaz. Thanks !
Ideas and code from @yassotreyo version.
Tweaked by Albert Callisto (AC)
New features:
Added original signal line formula
Added optional EMA on MACD
Added filling between the MACD and signal line
I looked at other versions of the zero lag and noticed that the histogram was slightly different. After looking at other zero lags on TV, I noticed that the algorithm implementation of Glanz generated a modified signal line. I decided to add the old version to be compliant with the original algorithm that you will find in other platforms like MT4, FXCM, etc.
So now you can choose if you want the original algorithm or Glanz version. It's up to you then to choose which one you prefer. I also added an extra EMA applied on the MACD. This is used in a system I am currently studying and can be of some interest to filter out false signals.
Acc/Dist. Cloud with Fractal Deviation Bands by @XeL_ArjonaACCUMULATION / DISTRIBUTION CLOUD with MORPHIC DEVIATION BANDS
Ver. 2.0.beta.23:08:2015
by Ricardo M. Arjona @XeL_Arjona
DISCLAIMER
The Following indicator/code IS NOT intended to be a formal investment advice or recommendation by the author, nor should be construed as such. Users will be fully responsible by their use regarding their own trading vehicles/assets.
The embedded code and ideas within this work are FREELY AND PUBLICLY available on the Web for NON LUCRATIVE ACTIVITIES and must remain as is.
Pine Script code MOD's and adaptations by @XeL_Arjona with special mention in regard of:
Buy (Bull) and Sell (Bear) "Power Balance Algorithm by Vadim Gimelfarb published at Stocks & Commodities V. 21:10 (68-72).
Custom Weighting Coefficient for Exponential Moving Average (nEMA) adaptation work by @XeL_Arjona with contribution help from @RicardoSantos at TradingView @pinescript chat room.
Morphic Numbers (PHI & Plastic) Pine Script adaptation from it's algebraic generation formulas by @XeL_Arjona
Fractal Deviation Bands idea by @XeL_Arjona
CHANGE LOG:
ACCUMULATION / DISTRIBUTION CLOUD: I decided to change it's name from the Buy to Sell Pressure. The code is essentially the same as older versions and they are the center core (VORTEX?) of all derived New stuff which are:
MORPHIC NUMBERS: The "Golden Ratio" expressed by the result of the constant "PHI" and the newer and same in characteristics "Plastic Number" expressed as "PN". For more information about this regard take a look at: HERE!
CUSTOM(K) EXPONENTIAL MOVING AVERAGE: Some code has cleaned from last version to include as custom function the nEMA , which use an additional input (K) to customise the way the "exponentially" is weighted from the custom array. For the purpose of this indicator, I implement a volatility algorithm using the Average True Range of last 9 periods multiplied by the morphic number used in the fractal study. (Golden Ratio as default) The result is very similar in response to classic EMA but tend to accelerate or decelerate much more responsive with wider bars presented in trending average.
FRACTAL DEVIATION BANDS: The main idea is based on the so useful Standard Deviation process to create Bands in favor of a multiplier (As John Bollinger used in it's own bands) from a custom array, in which for this case is the "Volume Pressure Moving Average" as the main Vortex for the "Fractallitly", so then apply as many "Child bands" using the older one as the new calculation array using the same morphic constant as multiplier (Like Fibonacci but with other approach rather than %ratios). Results are AWSOME! Market tend to accelerate or decelerate their Trend in favor of a Fractal approach. This bands try to catch them, so please experiment and feedback me your own observations.
EXTERNAL TICKER FOR VOLUME DATA: I Added a way to input volume data for this kind of study from external tickers. This is just a quicky-hack given that currently TradingView is not adding Volume to their Indexes so; maybe this is temporary by now. It seems that this part of the code is conflicting with intraday timeframes, so You are advised.
This CODE is versioned as BETA FOR TESTING PROPOSES. By now TradingView Admins are changing lot's of things internally, so maybe this could conflict with correct rendering of this study with special tickers or timeframes. I will try to code by itself just the core parts of this study in order to use them at discretion in other areas. ALL NEW IDEAS OR MODIFICATIONS to these indicator(s) are Welcome in favor to deploy a better and more accurate readings. I will be very glad to be notified at Twitter or TradingView accounts at: @XeL_Arjona
Universal Moving Average🙏🏻 UMA (Universal Moving Average) represents the most natural and prolly ‘the’ final general universal entity for calculating rolling typical value for any type of time-series. Simply via different weighting schemes applied together, it encodes:
Location of each datapoint in corresponding fields (price, time, volume)
Informational relevance of each datapoint via using windowing functions that are fundamental in nature and go beyond DSP inventions & approximations
Innovation in state space (in our case = volatility)
The real beauty of this development: being simply a weighting scheme that can be applied to anything: be it weighted median , weighted quantile regression, or weighted KDE , or a simple weighted mean (like in this script). As long as a method accepts weights, you can harness the power of this entity. It means that final algorithmic complexity will match your initial tool.
As a moving ‘average’ it beats ALMA, KAMA, MAMA, VIDYA and all others because it is a simple and general entity, and all it does is encoding ‘all’ available information. I think that post might anger a lot of people, because lotta things will be realized as legacy and many paywalls gonna be ignored, specially for the followers of DSP cult, the ones who yet don’t understand that aggregated tick data is not a signal omg, it’s a completely different type of time series where your methods simply don’t fit even closely. I am also sorry to inform y’all, that spectral analysis is much closer to state-space methods in spirit than to DSP. But in fact DSP is cool and I love it, well for actual signals xD
...
Weights explained & how to use them: as I already said, the whole thing is based on combining different set of weights, and you can turn them on/off in script settings. Btw I've set em up defaults so you can use the thing on price data out of the box right away.
Price, Time, Volume weights: encode location of every datapoint in Price & TIme & Volume field
Howtouse: u have to disable one weight that corresponds to the field you apply UMA to. E.g if you apply UMA to prices, you turn off price weighting And turn on time and volume weighting. Or if you apply UMA to volume delta, you turn off volume weighting And turn on price and time weighting.
Higher prices are more important, this asymmetry is confirmed and even proved by the fact that prices can’t be negative (don’t even mention that incorrect rollover on CL contract in 2k20...).
Signal weights: encode actuality/importance/relevance of datapoints.
Howtouse: in DSP terms, it provides smoothing, but also compensates for the lag it introduces. This smoothness is useful if you use slope reversals for signal generation aka watching peaks and valleys in a moving average shape. It's also better to perturb smoothed outputs with this , this way you inject high freq content back, But in controlled way!
Signal = information.
The fundamental universal entity behind so-called “smoothing” in DSP has nothing to do with signals and goes eons beyond DSP. This is simply about measuring the relevance of data in time.
First, new datapoints need some time to be “embedded” into the timeline, you can think of it as time proof, kinda stuff needs time to be proved, accepted; while earliest datapoints lose relevance in time.
Second, along with the first notion, at the same time there’s the counter notion that simply weights new data more, acting as a counterweight from the down-weighting of the latest datapoints introduced by the first notion.
The first part can be represented as PDF of beta(2, 2) window (a set of weights in our case). It’s actually well known as the Welch window, that lives in between so called statistical and DSP worlds, emerges in multiple contexts. Mainstream DSP users tho mostly don’t use this one, they use primitive legacy windowing function, you can find all kinds on this wiki page.
Now the second part, where DSP adepts usually stop, is to introduce the second compensating windowing function. Instead they try to reduce window size, or introduce other kinds of volatility weights, do some tricks, but it ain’t provides obviously. The natural step here is to simply use the integral of the initial window; if the initial window is beta(2, 2) then what we simply need is CDF of beta(2, 2), in fact the vertically inverted shape of it aka survival function . That’s it bros. Simply as that.
When both of these are applied you have smth magical, your output becomes smooth and yet not lagging. No arbitrary windowing functions, tricks with data modification etc
Why beta(2, 2)? It naturally arises in many contexts, it’s based on one of the most fundamental functions in the universe: x^2. It has finite support. I can talk more bout it on request, but I am absolutely sure this is it.
^^ impulse response of the resulting weighs together (green) compared with uniform weights aka boxcar (red). Made with this script .
Weighing by state: encodes state-space innovation of each datapoint, basically magnitude of changes, strength of these changes, aka volatility.
Howtouse: this makes your moving average volatility aware in proper math ways. The influence of datapoints will be stronger when changes are stronger. This is weighting by innovations, or weighting by volatility by using squared returns.
Why squared returns? They encode state‑space innovations properly because the innovation of any continuous‑time semimartingale is about its quadratic variation, and quadratic variation is built from squared increments, not absolute increments.
Adaptive length is not the right way to introduce adaptivity by volatility xD. When you weight datapoints by squared returns you’re already dynamically varying ‘effective’ data size, you don’t need anything else.
...
It’s all good, progress happens, that’s how the Universe works, that's how Universal Moving Average works. Time to evolve. I might update other scripts with this complete weighting scheme, either by my own desire or your request.
...
∞
cd_VW_Cx IMPROVED - Quant VWAP System: Regime, Magnets & Z-ScoQuant VWAP System: Regime, Magnets & Z-Score Matrix
This indicator is a comprehensive Quantitative Trading System designed to move beyond simple support and resistance. Instead of static lines, it uses Statistical Probability (Z-Score) and Standard Deviation to define the current market regime, identify institutional value zones, and project high-probability liquidity targets.
It is engineered for Day Traders and Scalpers (Crypto & Futures) who need to know if the market is Trending, Ranging, or preparing for a Breakout.
1. The "Regime" System (Standard Deviation Bands)
The core engine anchors a VWAP (Volume Weighted Average Price) to your chosen timeframe (Daily, Weekly, or Monthly) and projects volatility bands based on market variance.
The Trend Zone (Inner Band / 1.0 SD): This is the "Fair Value" zone. In a healthy trend, price will pull back into this zone and hold. A hold here signals a high-probability continuation (Trend Following).
The Reversion Zone (Outer Band / 2.0 SD): This represents a statistical extreme. Price rarely sustains movement beyond 2 Standard Deviations without a reversion. A touch of this band signals "Overbought" or "Oversold" conditions.
2. Liquidity Magnets (Virgin VWAPs)
The script automatically tracks "Unvisited VWAPs" from previous sessions. These are price levels where significant volume occurred but have not yet been re-tested.
The Logic: Algorithms often target these "open loops." The script visualizes them as Blue Dashed Lines with price tags.
Smart Scaling (Anti-Scrunch): Includes a custom "Ghost Engine" that automatically hides or "ghosts" magnets that are too far away. This prevents your chart from being squashed (scrunched) on lower timeframes, keeping your candles perfectly readable while still tracking targets in the background.
3. The Quant Matrix (Dashboard)
A real-time Heads-Up Display (HUD) that interprets the data for you:
Regime: Detects Volatility Squeezes. If the bands compress, it signals "⚠ SQUEEZE", warning you to stop mean-reversion trading and prepare for an explosive breakout.
Bias: Color-coded Trend Direction (Bullish/Bearish) based on VWAP slope.
Signal: actionable text prompts such as "BUY DIP" (Trend Following), "FADE EXT" (Mean Reversion), or "PREP BREAK" (Squeeze).
4. Visual Intelligence
Bold Day Separators: Clear, vertical dotted dividers with Date Stamps to instantly separate trading sessions.
Dynamic Labels: Floating labels on the right axis identify exactly which deviation level is which, preventing chart confusion.
How to Use
Strategy A: The Trend Pullback (continuation)
Check Matrix: Ensure Bias is BULLISH (Green).
Wait: Allow price to pull back into the Inner Band (Dark Green Zone).
Trigger: If price holds the Center VWAP or the -1.0 SD line, enter Long.
Target: The next Liquidity Magnet above or the +2.0 SD band.
Strategy B: The Reversion Fade (Counter-Trend)
Check Matrix: Ensure price is labeled "EXTREME" or Signal says "FADE EXT".
Trigger: Price touches or pierces the Outer Band (2.0 SD).
Action: Enter counter-trend (Short) with a target back to the Center VWAP (Mean Reversion).
Strategy C: The Magnet Target
Identify a "MAGNET" line (Blue Dashed) near current price.
These act as high-probability Take Profit levels. Price will often rush to these levels to "close the loop" before reversing.
Settings
Anchor: Daily (default), Weekly, or Monthly.
Magnet Focus Range: Adjusts how aggressively the script hides distant magnets to fix chart scaling (Default: 2%).
Visuals: Fully customizable colors, label sizes, and dashboard position.
cd_VW_CxOverview
The cd_VW_Cx is a sophisticated trend analysis tool designed to quantify market momentum using Multi-Period VWAP (Volume Weighted Average Price). Unlike standard indicators, this script evaluates the current price relationship across multiple historical VWAP anchors to generate a real-time "Confidence Score" ranging from -100 to +100.
💡 Key Features
• Dynamic Anchoring: Seamlessly switch between Daily, Weekly, or Monthly open anchors to align with your trading style (Scalping, Day Trading, or Swing).
• Algorithmic Scoring (The Score Box): The indicator compares the current VWAP against historical periods.
o Score > +70: Strong Bullish Momentum.
o Score < -70: Strong Bearish Momentum.
• Polyline Rendering: Utilizes Pine Script v6’s advanced polyline architecture for high-performance, sleek visual plotting that doesn't clutter your chart.
• Institutional Support/Resistance: Historical VWAP levels are color-coded, often acting as "invisible" magnetic zones where institutional orders are clustered.
🛠 How to Trade with cd_VW_Cx
1. Momentum Confirmation: Look for the Score Box to turn Teal (Bullish) or Red (Bearish). This indicates that the current trend has statistical backing from multiple previous sessions.
2. The Breakout Signal: The script tracks price crossovers of the current VWAP. A "Bullish Breakout" combined with a high score is a high-probability entry signal.
3. Visual Guidance: Use the custom labels to identify which specific day/week/month’s VWAP is currently being tested as support or resistance.
⚙️ Customizable Settings
• Anchor Selection: Choose the calculation basis (Daily, Weekly, Monthly).
• Thresholds: Adjust the sensitivity of the Bullish/Bearish alerts (Default is +/- 70).
• Visuals: Full control over table positioning, font sizes, and color palettes to match your chart theme.
📢 cd_VW_Cx: Multi-Period VWAP Scoring & Analysis Guide
🔍 Overview & Visual Logic
The labels next to the VWAP levels dynamically change based on your Anchor selection:
• Daily Open: Displays the Day Name (e.g., Monday, Tuesday).
• Weekly Open: Displays the Week Number (1 – 52).
• Monthly Open: Displays the Month Number (1 – 12).
•
General View:
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🚦 How to Filter & Track Your Assets
You can monitor your favorite assets using two powerful methods:
1. Real-Time Alerts
Stay updated with TradingView notifications:
• Per Asset: Track a single pair.
• Watchlist Basis: Monitor your entire list at once. Alert Setup Guide:
2. Pine Screener Integration
Filter the market effortlessly using the Pine Screener. Pine Screener View:
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⚙️ Settings & Configuration
• Timeframe Selection: Your chart timeframe must be lower than the selected Anchor timeframe. (e.g., If "Daily Open" is selected, the timeframe should be lower than 1D).
• Anchor Choice: Select Daily, Weekly, or Monthly opens.
• Source Selection: Default value is set to ohlc4. Source Settings:
Filtering Criteria Examples:
• Bullish Filtering: Find assets with high momentum scores.
• Bullish Breakout (Single Criteria): Filters assets that have closed above the current VWAP level.
• Combined Strength (Score + Breakout): Filters assets that have a Score > 70 AND a fresh VWAP Breakout simultaneously.
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⚠️ Important Notes & Warnings
• Calculation Logic: The indicator calculates levels and scores on timeframes lower than the anchor. It is best used on timeframes that are close to but lower than the anchor.
• Avoid Extreme Gaps: Using a very low timeframe (e.g., 1m) with a very high anchor (e.g., Monthly) increases the risk of erroneous results.
• Optimization: The default score threshold of 70 is a starting point; I recommend adjusting it based on your own trading experience.
• The Power of Confluence: VWAP levels are naturally strong. Their significance increases when they coincide with institutional levels like PDH (Previous Day High), Session H/L, or HTF FVG.
• Experience Matters: A high score alone is not enough for an entry. Always combine this data with your personal strategy.
________________________________________
💬 Community & Feedback
I would love to hear your suggestions regarding the scoring logic or visual improvements! Feel free to share your thoughts in the comments.
Happy Trading! 🚀
Kijun Sen Standard Deviation | QuantLapse SystemsOverview
The Kijun Sen Standard Deviation indicator by QuantLapse Systems is a volatility-aware trend-following framework that combines the structural equilibrium of the Kijun Sen (基準線) with statistically adaptive standard deviation bands.
By anchoring trend detection to market structure and confirming direction through volatility expansion, the indicator delivers a cleaner, more reliable regime classification across varying market conditions.
Rather than reacting to short-term noise, the system focuses on identifying statistically justified trend phases , making it well-suited for disciplined, rule-based trading.
Technical Composition, Calculation, Key Components & Features
📌 Kijun Sen (基準線) – Structural Trend Baseline
Calculated as the midpoint between the highest high and lowest low over a user-defined period.
Represents market equilibrium and structural balance rather than short-term momentum.
Naturally adapts to expanding and contracting price ranges.
Provides a stable baseline for regime detection and volatility validation.
Acts as the anchor for deviation bands and persistent trend-state logic.
Unlike fast or reactive moving averages, the Kijun Sen emphasizes price structure and equilibrium , making it especially effective for higher-quality trend confirmation.
📌 Volatility Adjustment – Standard Deviation Bands
Standard deviation is calculated over a configurable lookback to measure current price dispersion.
Upper and lower envelopes are formed by applying a deviation multiplier to the Kijun Sen.
Band width expands during volatility surges and contracts during consolidation.
Creates proportional, volatility-aware thresholds instead of static offsets.
Visually represents market energy through expanding and compressing channels.
These adaptive bands ensure that trend signals only occur when volatility supports directional movement.
📌 Trend Signal & Regime Calculation
Bullish Trend is confirmed when price closes above the upper deviation band.
Bearish Trend is confirmed when price closes below the lower deviation band.
Once established, the trend state persists until an opposing volatility break occurs.
This persistence reduces whipsaws and improves regime stability.
Trend state is reinforced with color-coded lines, envelopes, and background shading.
This volatility-confirmed persistence model is visible in the chart, where trends remain intact through minor pullbacks and only flip on decisive expansion.
How It Works in Trading
✅ Volatility-Confirmed Trend Detection – Requires expansion beyond deviation bands.
✅ Noise Suppression – Filters low-energy price movement within volatility envelopes.
✅ Regime Persistence – Maintains trend state until statistical invalidation.
✅ Immediate Visual Context – Direction, strength, and transitions are clear at a glance.
Visual Representation
Trend signals are displayed directly on price using both line and background context:
🟢 Green / Teal Kijun & Envelope → Confirmed bullish regime.
🔴 Red / Pink Kijun & Envelope → Confirmed bearish regime.
Semi-transparent band fill visualizes volatility expansion and compression.
Buy and Sell labels appear only on confirmed regime transitions.
The lower panel includes:
Strategy equity curve based on trend exposure.
Buy & Hold equity for performance comparison.
Background regime shading synchronized with trend state.
Features and User Inputs
The Kijun Sen Standard Deviation framework offers a focused yet powerful set of configurable inputs:
Kijun Sen Length – Controls structural trend sensitivity.
Standard Deviation Controls – Adjust lookback length and multiplier for regime strictness.
Backtesting & Date Filters – Define evaluation periods and starting conditions.
Display Options – Toggle labels, equity curves, and background shading.
Color Customization – Fully configurable buy/sell colors for trends and equity curves.
These controls allow users to balance responsiveness, stability, and clarity without overfitting.
Practical Applications
The Kijun Sen Standard Deviation indicator is designed for traders who prioritize structure, volatility confirmation, and regime awareness.
Primary Trend Filtering – Identify and stay aligned with dominant market direction.
Volatility-Aware Trend Following – Participate only when price expansion confirms intent.
Risk-Managed Exposure – Avoid chop during compression and transitional phases.
Systematic Strategy Development – Use as a regime engine or higher-timeframe filter.
Performance Evaluation – Compare trend-following equity against buy-and-hold benchmarks.
This framework bridges classical Ichimoku structure with modern statistical validation.
Conclusion
The Kijun Sen Standard Deviation indicator by QuantLapse Systems represents a refined evolution of Ichimoku-based trend analysis.
By integrating the structural equilibrium of the Kijun Sen with adaptive standard deviation confirmation, the system delivers clearer regime classification, reduced noise, and more reliable trend participation.
Rather than attempting to predict price, it focuses on confirming when trends are statistically justified .
Who should use Kijun Sen Standard Deviation:
📊 Trend-Following Traders – Stay aligned with dominant market structure.
⚡ Momentum & Swing Traders – Enter only on volatility-backed expansions.
🤖 Systematic & Algorithmic Traders – Ideal as a regime filter or trend-state engine.
Past performance is not indicative of future results.
Disclaimer: All trading involves risk, and no indicator can guarantee profitability.
Strategic Advice: Always backtest thoroughly, optimize parameters responsibly, and align settings with your timeframe, asset class, and risk tolerance before live deployment.
Composite Fear & Greed IndexComposite Fear & Greed Index
This is an advanced, professional-grade sentiment analysis engine designed to quantify market psychology. Unlike standard oscillators that rely on a single metric, this script uses a weighted composite of four distinct technical components to generate a holistic "Fear & Greed" score.
It includes Multi-Timeframe (MTF) capabilities, proprietary FOMO/Panic detection logic, and Zero-Lag trend analysis.
1. Unique Mathematical Methodology
This script is not a simple overlay of existing indicators. It uses a Composite Normalization Engine to blend four distinct metrics into a single, bounded 0-100 oscillator.
The "Mashup" Problem Solved: Standard indicators like MACD are "unbounded" (they can go to infinity), while RSI is "bounded" (0-100). You cannot simply average them.
Our Solution: This script calculates the Z-Score of the MACD histogram relative to its historical deviation and normalizes it into a 0-100 percentile. This allows for a mathematically valid combination with RSI and Bollinger Bands.
The Component Logic:
Momentum (RSI): (Weight: 30%) Pure price velocity.
Volatility (Bollinger %B): (Weight: 25%) Relative position within volatility bands.
Trend Strength (Normalized MACD): (Weight: 25%) Uses the custom Z-Score logic described above.
Trend Integrity (ZLEMA): (Weight: 20%) We replaced the standard SMA with a custom Zero-Lag Exponential Moving Average (ZLEMA) algorithm. This removes the "lag" associated with traditional sentiment analysis, allowing the index to react to crypto volatility in real-time.
The Calculation: These raw values are weighted and smoothed to produce the final Index Value.
Greater than 80: Extreme Greed (High risk of reversal)
Less than 20: Extreme Fear (Potential accumulation zone)
2. Unique Features
A. FOMO & Panic Event Detection The script does not just track price; it tracks behavior.
FOMO (Fear Of Missing Out): Triggered when Price breaks the Upper Bollinger Band + RSI is Overbought + Volume spikes > 2.5x the average. This often marks local tops.
PANIC: Triggered when Price drops significantly in one bar + Volume spikes > 3.0x the average + RSI is Oversold. This often marks capitulation bottoms.
B. Divergence Detection The script automatically detects and plots Regular Bullish and Bearish divergences between Price and the Sentiment Index.
Bullish Divergence: Price makes a Lower Low, but Sentiment makes a Higher Low (indicating waning selling pressure).
Bearish Divergence: Price makes a Higher High, but Sentiment makes a Lower High (indicating waning buying pressure). Note: The script plots these signals precisely on the indicator line corresponding to the pivot point.
C. Multi-Timeframe (MTF) Engine Users can view the "Daily" sentiment score while trading on a 5-minute or 15-minute chart. This allows scalpers to align their trades with the higher-timeframe market psychology.
3. Usage Guide
Step 1: Trend Alignment Look at the dashboard or the main line color. Green indicates Greed/Uptrend, Red indicates Fear/Downtrend.
Step 2: Extremes
Sell/Take Profit: When the Index crosses 80 (Extreme Greed) or a "FOMO" triangle appears.
Buy/Long: When the Index crosses 20 (Extreme Fear) or a "PANIC" triangle appears.
Step 3: Confirmation Use the Divergence Dots as confirmation. A "Panic" signal followed by a "Bullish Divergence" dot is a high-probability reversal setup.
Settings
Timeframe: Select the MTF resolution (default is Chart).
Weights: You can adjust the influence of RSI, MACD, BB, or Trend to fit your specific asset class.
Visuals: Fully customizable colors, table position, and toggle switches for shapes/backgrounds.
Disclaimer: This script is for informational purposes only and does not constitute financial advice.
Daily/Weekly Swing Highs-Lows + Candle PatternsDescription
Daily/Weekly Swing Highs-Lows + Candle Patterns
This indicator plots the most recent Daily and Weekly Swing Highs and Lows (key support/resistance levels) using a simple and effective logic: a swing high/low is confirmed when the previous bar's extreme is higher/lower than both the current and the one before it.
Features:
• Daily Swing Highs/Lows (teal/maroon circles) – toggleable
• Weekly Swing Highs/Lows (blue/purple circles) – optional
• Visual separators for new daily and weekly bars (light background color)
• Daily candle pattern labels (optional):
- US = Up Swing (strong bullish continuation)
- DS = Down Swing (strong bearish continuation)
- IN = Inside Bar
- OUT = Outside Bar
• Daily close position labels (optional):
- P = Positive (close in upper 25% of the range)
- mP = minor Positive (50–75%)
- mN = minor Negative (25–50%)
- N = Negative (lower 25%)
All elements are fully customizable (colors, visibility) and work on any timeframe.
Best suited for intraday timeframes (1 min to 4 hours) where daily and weekly key levels provide important context for price action and reversals.
The optional "Trading session length" input is mainly useful for markets with shorter sessions (e.g., European indices) and does not affect swing detection.
Open-source, free to use and modify.
How to Use the Indicator + Practical Use Case
Key Settings (Inputs)
Trading session length (hours) → Default 8.5 h (useful for FTSEMIB, DAX, etc.). Leave it as is unless you trade a market with a different session length.
Daily Swing Levels → Show/Hide daily swing highs (teal) and lows (maroon).
Weekly Swing Levels → Usually keep off on intraday charts to avoid clutter (turn on for higher-timeframe context).
Daily Candle Patterns → Enable only if you want to see US/DS/IN/OUT labels on the daily close.
Close Position (P/mP/mN/N) → Enable if you want to quickly see how strong/weak the daily close was.
What You See on the Chart
Teal circles = Last confirmed daily swing high (resistance).
Maroon circles = Last confirmed daily swing low (support).
Blue/purple circles (if enabled) = Weekly swing high/low.
Light gray background = Start of a new trading day.
Purple background (if weekly enabled) = Start of a new week.
Small labels on daily close (if enabled):
- US = strong bullish day
- DS = strong bearish day
- IN = inside bar (consolidation)
- OUT = outside bar (expansion)
- P/mP/mN/N = how far the close was from the high/low of the day.
Best Timeframes 1 min to 240 min charts → Daily levels act as major support/resistance zones for intraday trading.
Avoid using on daily or higher charts (the logic is designed for intraday context).
Why this works well intraday:
The daily swing high/low levels are high-probability zones where institutions and algorithms often defend positions. On intraday charts, they act as “magnets” for price, giving you clean entries and exits with clear invalidation levels.
This indicator keeps your chart clean while providing exactly the context most intraday traders need: key daily levels + daily momentum context.
QUANT TRADING ENGINE [PointAlgo]Quant Trading Engine is a quantitative market-analysis indicator that combines multiple statistical factors to study trend behavior, mean reversion, volatility, execution efficiency, and market stability.
The indicator converts raw price behavior into standardized signals to help evaluate directional bias and risk conditions in a systematic way.
This script focuses on factor alignment and regime awareness, not prediction certainty.
Design Philosophy
Markets move through different regimes such as trending, ranging, volatile expansion, and instability.
This indicator attempts to model these regimes by blending:
Momentum strength
Mean-reversion pressure
Volatility risk
Trend filtering
Execution context (VWAP)
Correlation structure
Each component is normalized and combined into a single Quant Alpha framework.
Factor Construction
1. Momentum Factor
Measures directional strength using percentage price change over a rolling window.
Standardized using mean and standard deviation.
Represents trend continuation pressure.
2. Mean Reversion Factor
Measures deviation from a longer moving average.
Standardized to identify stretched conditions.
Designed to capture counter-trend behavior.
Directional Clamping
Mean-reversion signals are dynamically restricted:
No counter-trend buying during downtrends.
No counter-trend selling during uptrends.
Allows both sides only in neutral regimes.
This prevents conflicting signals in strong trends.
3. Volatility Factor
Uses realized volatility derived from price changes.
Penalizes environments where volatility deviates significantly from its norm.
Acts as a risk adjustment rather than a directional driver.
4. Composite Quant Alpha
The final Quant Alpha is a weighted blend of:
Momentum
Mean reversion (trend-clamped)
Volatility risk
The composite is standardized into a Z-score, allowing consistent interpretation across instruments and timeframes.
Signal Logic
Buy signal occurs when Quant Alpha crosses above zero.
Sell signal occurs when Quant Alpha crosses below zero.
Zero-cross logic is used to represent shifts from negative to positive statistical bias and vice versa.
Signals reflect statistical regime change, not trade instructions.
Volatility Smile Context
Measures price deviation from its statistical distribution.
Identifies skewed conditions where upside or downside volatility becomes dominant.
Highlights extreme deviations that may imply elevated derivative risk.
Exotic Risk Conditions
Detects sudden price expansion combined with volatility spikes.
Highlights environments where execution and risk become unstable.
Visual background cues are used for awareness only.
Execution Context (VWAP)
Measures price distance from VWAP.
Used to assess execution efficiency rather than direction.
Helps identify stretched conditions relative to average traded price.
Correlation Structure
Evaluates short-term return correlations.
Detects when price behavior becomes less predictable.
Flags structural instability rather than trend direction.
Visualization
The indicator plots:
Quant Alpha (scaled) with directional coloring
Volatility smile deviation
Price vs VWAP distance
Correlation structure
Signal markers indicate Quant Alpha zero-cross events and risk conditions.
Dashboard
A compact dashboard summarizes:
Trend filter state
Quant Alpha polarity and value
Individual factor readings
Current action state (Buy / Sell / Wait / Risk)
The dashboard provides a real-time snapshot of internal model conditions.
Usage Notes
Designed for analytical interpretation and research.
Best used alongside price action and risk management tools.
Factor behavior depends on instrument liquidity and volatility.
Not optimized for illiquid or irregular markets.
Disclaimer
This script is provided for educational and analytical purposes only.
It does not provide financial, investment, or trading advice.
All outputs should be independently validated before making any trading decisions.
Key Levels: Volume Profile POCProfessional Intraday Key Levels (CST)
This is a comprehensive, institutional-grade Pine Script indicator designed for intraday traders (Futures, Stocks, Options) operating in the Central Time Zone. It automatically plots the most significant support and resistance levels used by algorithms and professional desks.
1. Core Levels Monitored
Daily Levels: Previous Day High (PDH), Low (PDL), Open, Close, and the 50% Midpoint (Equilibrium).
Volume Profile POC: Unlike standard indicators that use a simple average, this calculates the Volume Weighted Average Price (VWAP) of the previous day to determine the true "Fair Value" or Point of Control. Plotted with a thicker, distinct purple line.
Weekly Magnets: Previous Week High (PWH) and Low (PWL), which often act as major targets for breakouts or reversals.
Pre-Market Data: Tracks the High and Low established between 03:00 AM – 08:30 AM CST.
Opening Range (OR): Automatically captures the High and Low of the first 60 minutes of the regular session (08:30 AM – 09:30 AM CST).
2. Smart Visualization Features
Anti-Overlap Labels: If two levels (e.g., Pre-Market High and Previous Day High) are within 0.02% of each other, the script automatically merges them into a single label (e.g., "PDH & Pre-Market High") to prevent chart clutter.
Source Tracing: Trace lines extend backward from the current price level to the exact candle where that High or Low was formed (for Pre-Market and Opening Range levels), giving you instant context on when the level was created.
Clean Readability: Labels are displayed in bold, solid text without price numbers, ensuring a clean chart that focuses on level identification rather than data overload.
3. Technical Precision
Time Zone Locked: Hardcoded to America/Chicago to ensure Pre-Market and Opening Range calculations remain accurate regardless of your local computer settings.
Non-Repainting: Daily and Weekly levels are locked using closed-candle data (lookahead_on), ensuring lines do not shift during the trading day.
Buffer Safe: Optimized drawing logic prevents historical buffer errors, even on lower timeframes (1m/5m).
4. Customization
Toggle Everything: Every single level has an individual "Show/Hide" checkbox in the settings.
Label Sizing: Adjustable text size (Tiny to Huge) and offset positioning.
Compact Mode: Option to switch between full names ("Previous Day High") and abbreviations ("PDH").
Bollinger Bands Forecast with Signals (Zeiierman)█ Overview
Bollinger Bands Forecast with Signals (Zeiierman) extends classic Bollinger Bands into a forward-looking framework. Instead of only showing where volatility has been, it projects where the basis (midline) and band width are likely to drift next, based on recent trend and volatility behavior.
The projection is built from the measured slopes of the Bollinger basis, the standard deviation (or ATR, depending on the mode), and a volatility “breathing” component. On top of that, the script includes an optional projected price path that can be blended with a deterministic random walk, plus rejection signals to highlight failed band breaks.
█ How It Works
⚪ Bollinger Core
The script first computes standard Bollinger Bands using the selected Source, Length, and Multiplier:
Basis = SMA(Source, Length)
Band width = Multiplier × StDev(Source, Length)
Upper/Lower = Basis ± Width
This remains the “live” (non-forecast) structure on the chart.
⚪ Trend & Volatility Slope Estimation
To project forward, the indicator measures directional drift and volatility drift using linear regression differences:
Basis slope from the Bollinger basis
StDev slope from the Bollinger deviation
ATR slope for ATR-based projection mode
These slopes drive the forecast bands forward, reflecting the market’s recent directional and volatility regime.
⚪ Projection Engine (Forecast Bands)
At the last bar, the indicator draws projected basis, upper, and lower lines out to Forecast Bars. The projected basis can be:
Trend (straight linear projection)
Curved (ease-in/out transition toward projected endpoints)
Smoothed (extra smoothing on projected basis/width)
⚪ Price Path Projection + Optional Random Walk
In addition to projecting the bands, the script can draw a price forecast path made of a small number of zigzag swings.
Each swing targets a point offset from the projected basis by a multiple of the projected half-width (“width units”).
Decay gradually reduces swing size as the forecast deepens.
The Optional Random Walk Blend adds a deterministic drift component to the zigzag path. It’s not true randomness; it’s a stable pseudo-random sequence, so the drawing doesn’t jump around on refresh, while still adding “natural” variation.
⚪ Rejection Signals
Signals are based on failed attempts to break a band:
Bear Signal (Down): price tries to push above the upper band, then falls back inside, while still closing above the basis.
Bull Signal (Up): price tries to push below the lower band, then returns back inside, while still closing below the basis.
█ How to Use
⚪ Forward Support/Resistance Corridors
Treat the projected upper/lower bands as a future volatility envelope, not a guarantee:
The upper projection ≈ is likely a resistance level if the regime persists
The lower projection ≈ is likely a support level if the regime persists
Best used for trade planning, targets, and “where price could travel” under similar conditions.
⚪ Regime Read: Trend + Volatility
The projection shape is informative:
Rising basis + expanding width → trend with increasing volatility (needs wider stops / more caution)
Flat basis + compressing width → contraction regime (often precedes expansion)
⚪ Signals for Mean-Reversion / Failed Breakouts
The rejection markers are useful for fade-style setups:
A Down signal near/after upper-band failure can imply rotation back toward the basis.
An Up signal near/after lower-band failure can imply snap-back toward the basis.
With MA filtering enabled, signals are constrained to align with the broader bias, helping reduce chop-driven noise.
█ Related Publications
Donchian Predictive Channel (Zeiierman)
█ Settings
⚪ Bollinger Band
Controls the live Bollinger Bands on the chart.
Source – Price used for calculations.
Length – Lookback period; higher = smoother, lower = more reactive.
Multiplier – Bandwidth; higher = wider bands, lower = tighter bands.
⚪ Forecast
Controls the forward projection of the Bollinger Bands.
Forecast Bars – How far into the future the bands are projected.
Trend Length – Lookback used to estimate trend and volatility slopes.
Forecast Band Mode – Defines projection behavior (linear, curved, breathing, ATR-based, or smoothed).
⚪ Price Forecast
Controls the projected price path inside the bands.
ZigZag Swings – Number of projected oscillations.
Amplitude – Distance from basis, measured in bandwidth units.
Decay – Shrinks swings further into the forecast.
⚪ Random-Walk
Adds controlled randomness to the price path.
Enable – Toggle random-walk influence.
Blend – Strength of randomness vs. zigzag.
Step Size – Size of random steps (band-width units).
Decay – Reduces randomness as the forecast deepens.
Seed – Changes the (stable) random sequence.
⚪ Signals
Controls rejection/mean-reversion signals.
Show Signals – Enable/disable signal markers.
MA Filter (Type/Length) – Filters signals by trend direction.
-----------------
Disclaimer
The content provided in my scripts, indicators, ideas, algorithms, and systems is for educational and informational purposes only. It does not constitute financial advice, investment recommendations, or a solicitation to buy or sell any financial instruments. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
Quantum Darvas BoxesQuantum Darvas Boxes - The Modern Evolution
The original Darvas Box methodology, conceived by Nicolas Darvas in the 1950s, revolutionized breakout trading by identifying consolidation phases as "boxes." However, modern markets move with algorithmic speed and fractal volatility that often trigger false breakouts. Quantum Darvas Boxes were designed not as a nostalgic tribute, but as a computational upgrade. By anchoring boxes to volatility-adjusted boundaries rather than raw highs/lows, and introducing adaptive stability mechanisms, this indicator transforms a classic discretionary tool into a systematic, noise-filtered engine.
Description & Improvements
Quantum Darvas Boxes solve the three fatal flaws of the original: false breakouts, arbitrary box sizing, and lack of confirmation. Instead of drawing boxes at exact recent highs/lows, it creates volatility-buffered boundaries using ATR, ensuring breakouts require meaningful momentum. The boxes remain anchored until a confirmed close beyond the buffer occurs, preventing the constant redrawing that plagued traditional Darvas implementations. Built-in volume and RSI filters add discretionary-grade confirmation to pure price action. Visually, the system presents as a stable, semi-transparent blue zone between red (resistance) and lime (support) lines, with clear triangle signals appearing only on validated breakouts.
How It's Based on Darvas
The core philosophy remains true to Darvas' 1950s methodology:
Identify Consolidation: Finds price ranges where the market consolidates
Draw Box: Creates a "box" representing the accumulation zone
Breakout Trading: Enters when price breaks out of the box with momentum
Volatility-Adjusted Boundaries
Original: Boxes at exact highs/lows → prone to false breakouts
QDB: Boxes set at High - (ATR × Multiplier) and Low + (ATR × Multiplier)
→ Breakouts require meaningful momentum, not just price tags
→ Adapts to different volatility regimes
Signal Logic:
Long: Close above box top, previous close was inside box
Short: Close below box bottom, previous close was inside box
Ideal Settings:
For daily charts, use lookback=13 and mult=2.4.
For intraday (1H-4H), reduce to lookback=8 and mult=1.8. Enable volume filter in trending markets and RSI filter in ranging conditions.
Trade Execution: Enter long on the green triangle below the bar following a close above the red top line; enter short on the red triangle above the bar after a close below the lime bottom line. The background glow provides immediate visual confirmation.
Risk Management: Set stops at the opposite box boundary. The volatility multiplier inherently calculates a risk buffer—larger multipliers create wider, higher-conviction boxes; smaller multipliers produce more frequent, sensitive signals. This system excels in trending markets and provides clear exit/reversal points, transforming Darvas's original speculation into a quantified, repeatable edge.
VWAP Flow ParmezanThe "Official Bank Flow VWAP" is a comprehensive trading suite designed for institutional Forex traders.
This indicator solves the problem of chart clutter by combining two critical components of liquidity: Price (Value) and Time (Sessions). It is specifically optimized for EUR/USD and GBP/USD on intraday timeframes (M5, M15), helping you identify high-probability setups where "Fair Value" meets "Volatility."
Key Features
1. Multi-Timeframe VWAP Hierarchy Unlike standard indicators, this tool visualizes the interaction between three distinct timeframes:
Daily VWAP (Dynamic Color): Your primary trend filter. Green when Bullish (Price > VWAP), Red when Bearish (Price < VWAP).
Weekly VWAP (Orange Dots): Represents the medium-term balance. Acts as a magnet for mean reversion mid-week.
Monthly VWAP (Purple Line): The institutional "line in the sand." Major support/resistance level.
2. Standard Deviation Bands (Market Balance) The indicator plots SD1 and SD2 bands around the Daily VWAP:
Inner Zone (SD1): Represents the "Fair Value" area.
Outer Bands (SD2): Represents overbought/oversold conditions. Useful for identifying mean reversion plays back to the center.
3. Official Exchange Sessions (Time) Forget confusing "killzones." This tool highlights the Official Open times for major exchanges, adjusted for Daylight Savings via New York time:
London Open (08:00 LDN): The start of European volume.
New York Open (08:00 NY): The injection of US liquidity.
London Close/Fix: The daily overlap close, often marking trend reversals.
Note: Sessions are visualized with non-intrusive black "shadow" backgrounds to keep your chart clean.
4. "Ghost" Levels (Previous VWAP) A unique feature that plots the closing VWAP level of the previous day. Institutional algorithms often target these "untested" levels as Take Profit targets or liquidity pools.
How to Use
Trend Following: If Price is above the Daily VWAP (Green) during the London Open, look for Long entries targeting the SD1/SD2 upper bands.
Mean Reversion: If Price hits the SD2 Band while far away from the Weekly VWAP, look for a reversal back to the mean.
Confluence: The strongest signals occur when price touches a key VWAP level (e.g., Weekly VWAP) specifically during the highlighted Session Start times.
Settings
Timezone: Defaults to America/New_York to automatically handle DST shifts for London/NY opens.
Visuals: Fully customizable colors and transparency. Default is set to a "Dark Mode" friendly professional palette.
Shannon Entropy (Quant Lab)🟦 Shannon Entropy = The level of "order" or "chaos" in the market.
This indicator gives you the answer to the question:
"Is the market currently orderly and understandable, or is it random and chaotic?"
No other classical indicator can accurately show this.
The value of Entropy is between 0 and 1:
⸻
🟩 1) Entropy = 0.0 – 0.3 → Structured, orderly, readable market
During these periods, the price:
• A trend forms • Ranges work clearly • Patterns (head & shoulders, flag, triangle) form smoothly • Systems like Z-score, VWAP, EMA work very cleanly • Data for modeling (algorithmic strategies, ML) is high quality
Think of this region as follows:
The market "works according to rules," it's easy to trade.
⸻
🟧 2) Entropy = 0.3 – 0.7 → Normal behavior region
In this region:
• Neither too orderly nor too chaotic
• Most systems operate at an average rate • We can say the market is healthy
It is tradable; however, the conditions are not perfect.
⸻
🟥 3) Entropy = 0.7 – 1.0 → Chaos / Noise / Manipulation region
This is the MOST DANGEROUS REGION OF THE MARKET.
What happens?
• Prices jump randomly left and right. • Wicks increase excessively. • Fake breakouts multiply. • The win rate of strategies decreases. • Trend-following systems constantly generate "false signals." • Even mean-reversion systems are caught off guard. • ML models learn junk data during these periods. • Generally, news, liquidation cascades, and manipulation periods increase entropy.
This period perfectly illustrates:
"There is no logic in this market right now — it's moving randomly."
Therefore, it's a period where you need to be very careful:
Reduce position size. • Trade less. • Avoid unnecessary risks. • Tighten stop losses. • Don't use leverage.
This is your risk alert panel.
⸻
🔥 The real superpower Entropy gives you: Trend selection and system selection
Entropy → Determines which strategy you will use.
✔ Low Entropy → Trend following or mean-reversion that works like a toy
✔ High Entropy → Even opening a trade is risky
✔ Normal Entropy → Most strategies work
Building a strategy without this information is unprofessional.
⸻
🧠 Critical summary (you can even copy and paste it as a description in TradingView):
Low entropy → market is structured, patterns & trends are reliable
High entropy → market is chaotic, noisy, unpredictable; avoid aggressive trading
Entropy tells you if your strategy has a high chance or low chance of working
⸻
🟦 Signals Entropy gives in practice:
🔹 Entropy is falling →
The market is stabilizing → A major trend or strong move is approaching.
🔹 Entropy is rising →
The market is becoming chaotic → Sudden spike, a period of trading in prayer mode, extra risk.
🔹 Low Entropy + VR > 1 + High ER → FULL TREND MARKET
A true “trend paradise” period.
🔹 Low Entropy + VR < 1 + High FDI → RANGE MARKET
A paradise of mean reversion.
🔹 High Entropy + High VoV → DANGEROUS PERIOD
Big explosions, news, and liquidations happen here.
⸻
⭐ IN SHORT:
Entropy = an indicator of how randomly the market behaves.
• 0–0.3 → regular, good, reliable market
• 0.3–0.7 → normal market
• 0.7–1.0 → chaotic, dangerous market
It tells you at a glance whether you should trade during this period or not.
Mutanabby_AI | ONEUSDT_MR1
ONEUSDT Mean-Reversion Strategy | 74.68% Win Rate | 417% Net Profit
This is a long-only mean-reversion strategy designed specifically for ONEUSDT on the 1-hour timeframe. The core logic identifies oversold conditions following sharp declines and enters positions when selling pressure exhausts, capturing the subsequent recovery bounce.
Backtested Period: June 2019 – December 2025 (~6 years)
Performance Summary
| Metric | Value |
|--------|-------|
| Net Profit | +417.68% |
| Win Rate | 74.68% |
| Profit Factor | 4.019 |
| Total Trades | 237 |
| Sharpe Ratio | 0.364 |
| Sortino Ratio | 1.917 |
| Max Drawdown | 51.08% |
| Avg Win | +3.14% |
| Avg Loss | -2.30% |
| Buy & Hold Return | -80.44% |
Strategy Logic :
Entry Conditions (Long Only):
The strategy seeks confluence of three conditions that identify exhausted selling:
1. Prior Move Filter:*The price change from 5 bars ago to 3 bars ago must be ≥ -7% (ensures we're not entering during freefall)
2. Current Move Filter: The price change over the last 2 bars must be ≤ 0% (confirms momentum is stalling or reversing)
3. Three-Bar Decline: The price change from 5 bars ago to 3 bars ago must be ≤ -5% (confirms a significant recent drop occurred)
When all three conditions align, the strategy identifies a potential reversal point where sellers are exhausted.
Exit Conditions:
- Primary Exit: Close above the previous bar's high while the open of the previous bar is at or below the close from 9 bars ago (profit-taking on strength)
- Trailing Stop: 11x ATR trailing stop that locks in profits as price rises
Risk Management
- Position Sizing:Fixed position based on account equity divided by entry price
- Trailing Stop:11× ATR (14-period) provides wide enough room for crypto volatility while protecting gains
- Pyramiding:Up to 4 orders allowed (can scale into winning positions)
- **Commission:** 0.1% per trade (realistic exchange fees included)
Important Disclaimers
⚠️ This is NOT financial advice.
- Past performance does not guarantee future results
- Backtest results may contain look-ahead bias or curve-fitting
- Real trading involves slippage, liquidity issues, and execution delays
- This strategy is optimized for ONEUSDT specifically — results may differ on other pairs
- Always test before risking real capital
Recommended Usage
- Timeframe:*1H (as designed)
- Pair: ONEUSDT (Binance)
- Account Size: Ensure sufficient capital to survive max drawdown
Source Code
Feedback Welcome
I'm sharing this strategy freely for educational purposes. Please:
- Drop a comment with your backtesting results any you analysis
- Share any modifications that improve performance
- Let me know if you spot any issues in the logic
Happy trading
As a quant trader, do you think this strategy will survive in live trading?
Yes or No? And why?
I want to hear from you guys
Elliott Wave Full Fractal System v2.0Elliott Wave Full Fractal System v2.0 – Q.C. FINAL (Guaranteed R/R)
Elliott Wave Full Fractal System is a multi-timeframe wave engine that automatically labels Elliott impulses and ABC corrections, then builds a rule-based, ATR-driven risk/reward framework around the “W3–W4–W5” leg.
“Guaranteed R/R” here means every order is placed with a predefined stop-loss and take-profit that respect a minimum Reward:Risk ratio – it does not mean guaranteed profits.
Core Idea
This strategy turns a full fractal Elliott Wave labelling engine into a systematic trading model.
It scans fractal pivots on three wave degrees (Primary, Intermediate, Minor) to detect 5-wave impulses and ABC corrections.
A separate “Trading Degree” pivot stream, filtered by a 200-EMA trend filter and ATR-based dynamic pivots, is then used to find W4 pullback entries with a minimum, user-defined Reward:Risk ratio.
Default Properties & Risk Assumptions
The backtest uses realistic but conservative defaults:
// Default properties used for backtesting
strategy(
"Elliott Wave Full Fractal System - Q.C. FINAL (Guaranteed R/R)",
overlay = true,
initial_capital = 10000, // realistic account size
default_qty_type = strategy.percent_of_equity,
default_qty_value = 1, // 1% risk per trade
commission_type = strategy.commission.cash_per_contract,
commission_value = 0.005, // example stock commission
slippage = 0 // see notes below
)
Account size: 10,000 (can be changed to match your own account).
Position sizing: 1% of equity per trade to keep risk per idea sustainable and aligned with TradingView’s recommendations.
Commission: 0.005 cash per contract/share as a realistic example for stock trading.
Slippage: set to 0 in code for clarity of “pure logic” backtesting. Real-life trading will experience slippage, so users should adjust this according to their market and broker.
Always re-run the backtest after changing any of these values, and avoid using high risk fractions (5–10%+) as that is rarely sustainable.
1. Full Fractal Wave Engine
The script builds and maintains four pivot streams using ATR-adaptive fractals:
Primary Degree (Macro Trend):
Captures the large swings that define the major trend. Labels ①–⑤ and ⒶⒷⒸ using blue “Circle” labels and thicker lines.
Intermediate Degree (Trading Degree):
Captures the medium swings (swing-trading horizon). Uses teal labels ( (1)…(5), (A)(B)(C) ).
Minor Degree (Micro Structure):
Tracks short-term swings inside the larger waves. Uses red roman numerals (i…v, a b c).
ABC Corrections (Optional):
When enabled, the engine tries to detect standard A–B–C corrective structures that follow a completed 5-wave impulse and plots them with dashed lines.
Each degree uses a dynamic pivot lookback that expands when ATR is above its EMA, so the system naturally requires “stronger” pivots in volatile environments and reacts faster in quiet conditions.
2. Theory Rules & Strict Mode
Normal Mode: More permissive detection. Designed to show more wave structures for educational / exploratory use.
Strict Mode: Enforces key Elliott constraints:
Wave 3 not shorter than waves 1 and 5.
No invalid W4 overlap with W1 (for standard impulses).
ABC Logic: After a confirmed bullish impulse, the script expects a down-up-down corrective pattern (A,B,C). After a bearish impulse, it looks for up-down-up.
3. Trend Filter & Pivots
EMA Trend Filter: A configurable EMA (default 200) is used as a non-wave trend filter.
Price above EMA → Only long setups are considered.
Price below EMA → Only short setups are considered.
ATR-Adaptive Pivots: The pivot engine scales its left/right bars based on current ATR vs ATR EMA, making waves and trading pivots more robust in volatile regimes.
4. Dynamic Risk Management (Guaranteed R/R Engine)
The trading engine is designed around risk, not just pattern recognition:
ATR-Based Stop:
Stop-loss is placed at:
Entry ± ATR × Multiplier (user-configurable, default 2.0).
This anchors risk to current volatility.
Minimum Reward:Risk Ratio:
For each setup, the script:
Computes the distance from entry to stop (risk).
Projects a take-profit target at risk × min_rr_ratio away from entry.
Only accepts the setup if risk is positive and the required R:R ratio is achievable.
Result: Every order is created with both TP and SL at a predefined distance, so each trade starts with a known, minimum Reward:Risk profile by design.
“Guaranteed R/R” refers exclusively to this order placement logic (TP/SL geometry), not to win-rate or profitability.
5. Trading Logic – W3–W4–W5 Pattern
The Trading pivot stream (separate from visual wave degrees) looks for a simple but powerful pattern:
Bullish structure:
Sequence of pivots forms a higher-high / higher-low pattern.
Price is above the EMA trend filter.
A strong “W3” leg is confirmed with structure rules (optionally stricter in Strict mode).
Entry (Long – W4 Pullback):
The “height” of W3 is measured.
Entry is placed at a configurable Fibonacci pullback (default 50%) inside that leg.
ATR-based stop is placed below entry.
Take-profit is projected to satisfy min Reward:Risk.
Bearish structure:
Mirrored logic (lower highs/lows, price below EMA, W3 down, W4 retrace up, W5 continuation down).
Once a valid setup is found, the script draws a colored box around the entry zone and a label describing the type of signal (“LONG SETUP” or “SHORT SETUP”) with the suggested limit price.
6. Orders & Execution
Entry Orders: The strategy uses limit orders at the computed W4 level (“Sniper Long” or “Sniper Short”).
Exits: A single strategy.exit() is attached to each entry with:
Take-profit at the projected minimum R:R target.
Stop-loss at ATR-based level.
One Trade at a Time: New setups are only used when there is no open position (strategy.opentrades == 0) to keep the logic clear and risk contained.
7. Visual Guide on the Chart
Wave Labels:
Primary: ①,②,③,④,⑤, ⒶⒷⒸ
Intermediate: (1)…(5), (A)(B)(C)
Minor: i…v, a b c
Trend EMA: Single blue EMA showing the dominant trend.
Setup Boxes:
Green transparent box → long entry zone.
Red transparent box → short entry zone.
Labels: “LONG SETUP / SHORT SETUP” labels mark the proposed limit entry with price.
8. How to Use This Strategy
Attach the strategy to your chart
Choose your market (stocks, indices, FX, crypto, futures, etc.) and timeframe (for example 1h, 4h, or Daily). Then add the strategy to the chart from your Scripts list.
Start with the default settings
Leave all inputs on their defaults first. This lets you see the “intended” behaviour and the exact properties used for the published backtest (account size, 1% risk, commission, etc.).
Study the wave map
Zoom in and out and look at the three wave degrees:
Blue circles → Primary degree (big picture trend).
Teal (1)…(5) → Intermediate degree (swing structure).
Red i…v → Minor degree (micro waves).
Use this to understand how the engine is interpreting the Elliott structure on your symbol.
Watch for valid setups
Look for the coloured boxes and labels:
Green box + “LONG SETUP” label → potential W4 pullback long in an uptrend.
Red box + “SHORT SETUP” label → potential W4 pullback short in a downtrend.
Only trades in the direction of the EMA trend filter are allowed by the strategy.
Check the Reward:Risk of each idea
For each setup, inspect:
Limit entry price.
ATR-based stop level.
Projected take-profit level.
Make sure the minimum Reward:Risk ratio matches your own rules before you consider trading it.
Backtest and evaluate
Open the Strategy Tester:
Verify you have a decent sample size (ideally 100+ trades).
Check drawdowns, average trade, win-rate and R:R distribution.
Change markets and timeframes to see where the logic behaves best.
Adapt to your own risk profile
If you plan to use it live:
Set Initial Capital to your real account size.
Adjust default_qty_value to a risk level you are comfortable with (often 0.5–2% per trade).
Set commission and slippage to realistic broker values.
Re-run the backtest after every major change.
Use as a framework, not a signal machine
Treat this as a structured Elliott/R:R framework:
Filter signals by higher-timeframe trend, major S/R, volume, or fundamentals.
Optionally hide some wave degrees or ABC labels if you want a cleaner chart.
Combine the system’s structure with your own trade management and discretion.
Best Practices & Limitations
This is an approximate Elliott Wave engine based on fractal pivots. It does not replace a full discretionary Elliott analysis.
All wave counts are algorithmic and can differ from a manual analyst’s interpretation.
Like any backtest, results depend heavily on:
Symbol and timeframe.
Sample size (more trades are better).
Realistic commission/slippage settings.
The 0-slippage default is chosen only to show the “raw logic”. In real markets, slippage can significantly impact performance.
No strategy wins all the time. Losing streaks and drawdowns will still occur even with a strict R:R framework.
Disclaimer
This script is for educational and research purposes only and does not constitute financial advice or a recommendation to buy or sell any security. Past performance, whether real or simulated, is not indicative of future results. Always test on multiple symbols/timeframes, use conservative risk, and consult your financial advisor before trading live capital.
