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.
Buscar en scripts para "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
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.
Multi-Distribution Volume Profile (Zeiierman)█ Overview
Multi-Distribution Volume Profile (Zeiierman) is a flexible, structure-first volume profile tool that lets you reshape how volume is distributed across price, from classic uniform profiles to advanced statistical curves like Gaussian, Lognormal, Student-t, and more.
Instead of forcing every market into a single "one-size-fits-all" profile, this tool lets you model how volume is likely concentrated inside each bar (body vs wicks, midpoint, tails, center bias, right-skew, heavy tails, etc.) and then stacks that behavior across a whole lookback window to build a rich, multi-distribution map of traded activity.
On top of that, it overlays a dynamic Center Band (value area) and a fade/gradient model that can color each price row by volume, hits, recency, volatility, reversals, or even liquidity voids, turning a plain profile into a multi-dimensional context map.
Highlights
Choose from multiple Profile Build Modes , including uniform, body-only, wick-only, midpoint/close/open, center-weighted, and a suite of probability-style distributions (Gaussian, Lognormal, Weibull, Student-t, etc.)
Flexible anchor layout: draw the profile on Right/Left (horizontal) or Bottom/Top (vertical) to fit any chart layout
Value Area / Center Band computed from volume quantiles around the POC.
Gradient-based Fade Metrics: volume, price hits, freshness (time decay), volatility impact, dwell time, reversal density, compression, and liquidity voids
Separate bullish vs bearish volume at each price row for directional structure insights
█ How It Works
⚪ Profile Construction
The script scans a user-defined Bars Included window and finds the full high–low span of that zone. It then divides this range into a user-controlled number of Price Levels (rows).
For each historical bar within the window:
It measures the candle’s price range, body, and wicks.
It assigns volume to rows according to the selected Profile Build Mode, for example:
* Range Uniform – volume spread evenly across the full high–low range.
* Range Body Only / Range Wick Only – concentrate volume inside the body or wicks only.
* Midpoint / Close / Open Only – allocate volume entirely into one price row (pinpoint modeling).
HL2 / Body Center Weighted – center weights around the middle of the range/body.
Recent-Weighted Volume – amplify newer bars using exponential time decay.
Volume Squared (Hard) – aggressively boost bars with large volume.
Up Bars Only / Down Bars Only – filter volume to only bullish or bearish bars.
For more advanced shapes, the script uses continuous distributions across the bar’s span:
Linear, Triangular, Exponential to High
Cosine Centered, PERT
Gaussian, Lognormal, Cauchy, Laplace
Pareto, Weibull, Logistic, Gumbel
Gamma, Beta, Chi-Square, Student-t, F-Shape
Each distribution produces a weight for each row within the bar’s range, normalized so the total volume remains consistent, but the shape of where that volume lands changes.
⚪ POC & Center Band (Value Area)
Once all rows are accumulated:
The row with the highest total volume becomes the Point of Control (POC)
The script computes cumulative volume and finds the band that wraps a user-defined Center of Profile % (e.g., 68%) around the center of distribution.
This range is displayed as a central band, often treated like a value area where price has spent the most “effort” trading.
⚪ Gradient Fade Engine
Each row also gets a fade metric, chosen in Fade Metric:
Volume – opacity based on relative volume.
Price Hits – how frequently that row was touched.
Blended (Vol+Hits) – average of volume & hits.
Freshness – emphasizes recent activity, controlled by Decay.
Volatility Impact – rows that saw larger ranges contribute more.
Dwell Time – where price “camped” the longest.
Reversal Density – where direction changes cluster.
Compression – tight-range compression zones.
Liquidity Void – inverse of volume (thin liquidity zones).
When Apply Gradient is enabled, the row’s bullish/bearish colors are tinted from faint to strong based on this chosen metric, effectively turning the profile into a heatmap of your chosen structural property.
█ How to Use
⚪ Explore Different Distribution Assumptions
Switch between multiple Profile Build Modes to see how your assumptions about intrabar volume affect structure:
Use Range Uniform for classical profile reading.
Deploy Gaussian, Logistic, or Cosine shapes to emphasize central clustering.
Try Pareto, Lognormal, or F-Shape to focus on tail / extremal activity.
Use Recent-Weighted Volume to prioritize the most recent structural behavior.
This is especially useful for traders who want to test how different modeling assumptions change perceived value areas and levels of interest.
⚪ Identify Value, Acceptance & Rejection Zones
Use the POC and Center of Profile (%) band to distinguish:
High-acceptance zones – wide central band, thick rows, strong gradient → fair value areas
Rejection zones & tails – thin extremes, low dwell time, high volatility or reversal density
These regions can be used as:
Targets and origin zones for mean reversion
Context for breakout validation (leaving value)
Bias reference for intraday rotations or swing rotations
⚪ Read Directional Structure Within the Profile
Because each row is split into bullish vs bearish contributions, you can visually read:
Where buyers dominated a price region (large bullish slice)
Where sellers absorbed or defended (large bearish slice)
Combining this with Fade Metrics like Reversal Density, Dwell Time, or Freshness turns the profile into a structural order-flow map, without needing raw tick-by-tick volume data.
⚪ Use Fade Metrics for Contextual Heatmaps
Each Fade Metric can be used for a different analytical lens:
Volume / Blended – emphasize where volume and activity are concentrated.
Freshness – highlight the most recently active zones that still matter.
Volatility Impact & Compression – spot areas of explosive moves vs coiled ranges.
Reversal Density – locate micro turning points and battle zones.
Liquidity Void – visually pop out thin regions that may act as speedways or magnets.
█ Settings
Profile Build Mode – Selects how each bar’s volume is distributed across its price range (uniform, body/wick, midpoint/close/open, center-weighted, or statistical distribution families).
Bars Included – Number of bars used to build the profile from the current bar backward.
Price Levels – Vertical resolution of the profile: more levels = smoother but heavier.
Anchor Side – Where the profile is drawn on the chart: Right, Left, Bottom, or Top.
Offset (bars) – Horizontal offset from the last bar to the profile when using Right/Left modes.
Apply Gradient – Toggles the fade/heatmap coloring based on the selected metric.
Fade Metric – Chooses the property driving row opacity (Volume, Hits, Freshness, Volatility Impact, Dwell Time, Reversal Density, Compression, Liquidity Void).
Decay – Time-decay factor for Freshness (values close to 1 keep older activity relevant for longer).
Profile Thickness – Relative thickness of the profile along the time axis, as a % of the lookback window.
Center of Profile (%) – Volume percentage used to define the central band (value area) around the POC.
-----------------
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.
IDLP – Intraday Daily Levels Pro [FXSMARTLAB]🔥 IDLP – Intraday Daily Levels Pro
IDLP – Intraday Daily Levels Pro is a precision toolkit for intraday traders who rely on objective daily structure instead of repainting indicators and noisy signals.
Every level plotted by IDLP is derived from one simple rule:
Today’s trading decisions must be based on completed market data only.
That means:
✅ No use of the current day’s unfinished data for levels
✅ No lookahead
✅ No hidden repaint behavior
IDLP reconstructs the previous trading day from the intraday chart and then projects that structure forward onto the current session, giving you a stable, institutional-style intraday map.
🧱 1. Previous Daily Levels (Core Structure)
IDLP extracts and displays the full previous daily structure, which you can toggle on/off individually via the inputs:
Previous Daily High (PDH)
Previous Daily Low (PDL)
Previous Daily Open
Previous Daily Close,
Previous Daily Mid (50% of the range)
Previous Daily Q1 (25% of the range)
Previous Daily Q3 (75% of the range)
All of these come from the day that just closed and are then locked for the entire current session.
What these levels tell you:
PDH / PDL – true extremes of yesterday’s price action (liquidity zones, breakout/reversal points).
Previous Daily Open / Close – how the market positioned itself between session start and end
Mid (50%) – equilibrium level of the previous day’s auction.
Q1 / Q3 (25% / 75%) internal structure of the previous day’s range, dividing it into four equal zones and helping you see if price is trading in the lower, middle, or upper quarter of yesterday’s range.
All these levels are non-repaint: once the day is completed, they are fixed and never change when you scroll, replay, or backtest.
🎯 2. Previous Day Pivot System (P, S1, S2, R1, R2)
IDLP includes a classic floor-trader pivot grid, but critically:
It is calculated only from the previous day’s high, low, and close.
So for the current session, the following are fixed:
Pivot P – central reference level of the previous day.
Support 1 (S1) and Support 2 (S2)
Resistance 1 (R1) and Resistance 2 (R2)
These levels are widely used by institutional desks and algos to structure:
mean-reversion plays, breakout zones, intraday targets, and risk placement.
Everything in this section is non-repaint because it only uses the previous day’s fully closed OHLC.
📏 3. 1-Day ADR Bands Around Previous Daily Open
Instead of a multi-day ADR, IDLP uses a pure 1-Day ADR logic:
ADR = Range of the previous day
ADR = PDH − PDL
From that, IDLP builds two clean bands centered around the previous daily Open:
ADR Upper Band = Previous Day Open + (ADR × Multiplier)
ADR Lower Band = Previous Day Open − (ADR × Multiplier)
The multiplier is user-controlled in the inputs:
ADR Multiplier (default: 0.8)
This lets you choose how “tight” or “wide” you want the ADR envelope to be around the previous day’s open.
Typical use cases:
Identify realistic intraday extension targets, Spot exhaustion moves beyond ADR bands, Frame reversals after reaching volatility extremes, Align trades with or against volatility expansion
Again, since ADR is calculated only from the completed previous day, these bands are totally non-repaint during the current session.
🔒 4. True Non-Repaint Architecture
The internal logic of IDLP is built to guarantee non-repaint behavior:
It reconstructs each day using time("D") and tracks:
dayOpen, dayHigh, dayLow, dayClose for the current day
prevDayOpen, prevDayHigh, prevDayLow, prevDayClose for the previous day
At the moment a new day starts:
The “current day” gets “frozen” into prevDay*
These prevDay* values then drive: Previous Daily Levels, Pivots, ADR.
During the current day:
All these “previous day” values stay fixed, no matter what happens.
They do not move in real time, they do not shift in replay.
This means:
What you see in the past is exactly what you would have seen live.
No fake backtests.
No illusion of perfection from repainting behavior.
🎯 5. Designed For Intraday Traders
IDLP – Intraday Daily Levels Pro is made for:
- Day traders and scalpers
- Index and FX traders
- Prop firm challenge trading
- Traders using ICT/SMC-style levels, liquidity, and range logic
- Anyone who wants a clean, institutional-style daily framework without noise
You get:
Previous Day OHLC
Mid / Q1 / Q3 of the previous range
Previous-Day Pivots (P, S1, S2, R1, R2)
1-Day ADR Bands around Previous Day Open
All calculated only from closed data, updated once per day, and then locked.
Macro Timing Window Signal ⏱️ Macro Timing Window Signal – Check/X Indicator
This indicator displays a green check mark ✔️ or red X ✖️ in the top-right corner of the chart based on a repeating macro time cycle that divides every hour into active and inactive windows.
How it works:
• ✔️ Green Check (Active Macro Window):
Appears from xx:45 → xx:15 of the next hour (30-minute macro window).
• ✖️ Red X (Inactive Macro Window):
Appears from xx:16 → xx:44 (mid-hour cooldown window).
• Optional flash signal at the exact macro flip points (xx:45, xx:00, xx:15) to highlight transitions.
• Supports sound alerts so you never miss the start or end of a macro window.
This tool is designed for traders who incorporate macro-driven time cycles, liquidity sessions, or algorithmic delivery windows into their strategy.
The display is fixed on-screen, clean, and unobtrusive, ensuring instant recognition of the current macro state without cluttering the chart.
UT Bot Pro Max (Maks Edition)Script v2.0
UT Bot Pro Max is an advanced, high-precision evolution of the well-known UT Bot indicator.
This version is fully rebuilt into a complete decision-making system that evaluates trend structure, volatility conditions, momentum signals, and entry quality.
It is designed for traders who want clear, structured signals supported by objective filters and transparent reasoning.
1. Core Engine: ATR-Based Trailing Logic
At the heart of the system is an ATR dynamic trailing stop.
It is responsible for:
detecting trend reversals
identifying breakout conditions
switching between long and short bias
determining signal strength
Unlike simple ATR lines, this engine adapts to momentum expansion and contraction, forming the backbone for every signal.
2. Three-Tier Signal Structure
Each signal is classified into one of three levels based on the number of confirmations:
Strong Signals
ATR breakout
trend filter (price relative to EMA200)
RSI filter (oversold/overbought context)
This is the highest-quality confirmation and is suitable for full-size entries.
Medium Signals
ATR breakout
trend filter
(no RSI filter)
This represents a valid trend continuation but with slightly reduced confirmation.
Weak Signals
ATR breakout only
(no trend filter, no RSI filter)
This is an early-stage impulse which can evolve into a stronger move.
The multi-level classification allows the trader to size positions rationally and avoid over-committing during uncertain market conditions.
3. Move-Since-Entry Tracking
When a new long or short position is detected, the indicator records the entry price and automatically tracks the percentage movement from that point.
This offers:
real-time monitoring of open trade performance
objective context for managing exits
clear visualization of progress since entry
4. Smart State-Change Alerts
Instead of simple “BUY” or “SELL” messages, the script sends highly structured alerts whenever the internal state changes.
Each alert includes:
the symbol and timeframe
signal direction and strength
recommended position size based on signal tier
ATR values
RSI value and its state
trend context (bullish, bearish, neutral)
distance from ATR trailing stop
movement since entry
previous state reference (optional)
This makes it ideal for automated systems, algorithmic routing, or Telegram-based signal delivery.
5. Professional On-Chart Status Table
The indicator displays a refined information panel containing:
current signal state (Strong / Medium / Weak / Hold)
ATR signal direction
trend filter result
RSI value and condition
distance to trailing stop (percentage)
current position (long / short / flat)
entry recommendation based on signal strength
ATR value and additional context in expanded mode
There is also a compact mode optimized specifically for mobile trading.
6. Optional Heikin Ashi Mode
The indicator can operate using Heikin Ashi close values for traders who prefer smooth, noise-reduced visualizations.
The internal logic is recalculated automatically.
7. Trend-Colored Candles
An optional feature allows candle coloring based on price position relative to the ATR stop line, highlighting bullish and bearish phases directly on the chart.
What This Indicator Provides
Accurate, context-aware entry signals
Scalable position sizing through multi-tier structure
Objective trend confirmation
Breakout detection with volatility adaptation
Continuous tracking of open position performance
Detailed real-time explanations through alerts
A complete visual dashboard consolidating all key metrics
UT Bot Pro Max (Maks Edition) is built as a practical tool for daily trading.
It is suitable for scalping, day trading, swing trading, automated alerts, and mobile workflows.
LiquidityPulse Higher Timeframe Consecutive Candle Run LevelsLiquidityPulse Higher Timeframe Consecutive Candle Run Levels
Research suggests that financial markets can alternate between trend-persistence and mean-reversion regimes, particularly at short (intraday) or very long timeframes. Extended directional moves, whether prolonged intraday rallies or sell-offs, also carry a statistically higher chance of retracing or reversing (Safari & Schmidhuber, 2025). In addition, studies examining support and resistance behaviour show that swing highs or lows formed after strong directional moves may act as structurally and psychologically important price levels, where subsequent price interactions have an increased likelihood of stalling or bouncing rather than passing through directly (Chung & Bellotti, 2021). By highlighting higher-timeframe candle runs and marking their extremal levels, this indicator aims to display areas where directional momentum previously stopped, providing contextual "watch levels" that traders may incorporate into their broader analysis.
How this information is used in the indicator:
When a sequence of consecutive higher-timeframe candles prints in the same direction, the indicator highlights the lower-timeframe chart with a green or red background, depending on whether the higher-timeframe run was bullish or bearish. The highest high (for a bull run) or lowest low (for a bear run) of that sequence forms a recent extremum, and this value is plotted as a swing-high or swing-low level. These levels appear only after the required number of consecutive higher-timeframe candles (set by the user) have closed, and they continue updating as long as the higher-timeframe streak remains intact. A level "freezes" and stops updating only when an opposite-colour higher-timeframe candle closes (e.g., a red candle ending a bull run, or a green candle ending a bear run). Once frozen, the level remains fixed to preserve that structural information for future analysis or retests. The number of past bull/bear levels displayed on the chart is also adjustable in the settings.
Why capture a level after a long directional run:
When price moves in one direction for several consecutive candles (e.g. 4, 5, or more), it reflects strong directional bias, often associated with momentum, liquidity imbalance, or liquidity grabs. Once that sequence breaks, the final level reached marks a point of exhaustion or structural resistance/support, where that bias failed to continue. These inflection points are often used by traders and trading algorithms to assess potential reversals, retests, or breakout setups. By freezing these levels once the run ends, the indicator creates a map of historically significant price zones, allowing traders to observe how price behaves around them over time.
Additional information displayed by the indicator:
Each detected run includes a label showing the run length (the number of consecutive higher-timeframe candles in the streak) along with the source timeframe used for detection. The indicator also displays an overstretch marker: this numerical value appears when the total size of the candle bodies within the run exceeds a user-defined multiple of the average higher-timeframe body size (default: 1.5x). This helps highlight runs that were unusually strong or extended relative to typical volatility. You can also enable alerts that trigger when this overstretch ratio exceeds a higher threshold.
Key Settings
Timeframe: Choose which HTF to analyse (e.g., 15m, 1h, 4h)
Minimum Candle Run Length: Define how many consecutive candles are needed to trigger a level (e.g., 4)
Overstretch Settings: Customize detection threshold and alert trigger (in multiples of average body size)
Background Tints: Enable/disable visual highlights for bull and bear runs
Display Capacity: Choose how many past bull/bear levels to show
How Traders Can Use This Indicator
Traders can:
-Watch levels for retests, reversals, breakouts, or consolidation
-Identify areas where price showed strong directional conviction
-Spot extended or aggressive moves based on overstretch detection
-Monitor how price reacts when retesting prior run levels
-Build confluence with your existing levels, zones, or indicators
Disclaimer
This tool does not reflect true order flow, liquidity, or institutional positioning. It is a visual aid that highlights specific candle behaviour patterns and does not produce predictive signals. All analysis is subject to interpretation, and past price behaviour does not imply future outcomes.
References:
Trends and Reversion in Financial Markets on Time Scales from Minutes to Decades (Sara A. Safari & Christof Schmidhuber, 2025)
Evidence and Behaviour of Support and Resistance Levels in Financial Time Series (Chung & Bellotti, 2021)
