Line breakI decided to help TradingView programmers and wrote code that converts a standard candles / bars to a line break chart. The built-in linebreak() and security() functions for constructing a Linear Break chart are bad, the chart is not built correctly, and does not correspond to the Line Breakout chart built into TradingView. I’m talking about simulating the Linear Break lines using the plotcandle() annotation, because these are the same candles without shadows. When you try to use the market simulator, when the gaps are turned on in the security() function, nothing is added to the chart, and when turned off, a completely different line break chart is drawn. Do not try to write strategies based on the built-in linebreak() function! The developers write in the manual: "Please note that you cannot plot Line Break boxes from Pine script exactly as they look. You can only get a series of numbers similar to OHLC values for Line Break charts and use them in your algorithms." However, it is possible to build a “Linear Breakthrough” chart exactly like the “Linear Breakthrough" chart built into TradingView. Personally, I had enough Pine Script functionality.
For a complete understanding of how such a graph is built, you can refer to Steve Nison's book “BEYOND JAPANESE CANDLES” and see the instructions for creating a “Three-Line Breakthrough” chart (the number of lines for a breakthrough is three):
Rule 1: if today's price is above the base price (closing the first candle), draw a white line from the base price to the new maximum price (before closing).
or Rule 2: if today's price is below the base price, draw a black line from the base price to the new low of prices (before closing).
Rule 3: if today's price is no different from the base, do not draw any line.
Rule 4: if today's price rises above the maximum of the first line, shift to the column to the right and draw a new white line from the previous maximum to the new maximum of prices.
Rule 5: if the price is below the low of the first line, move one column to the right and draw a new black line down from the previous low to the new low of prices.
Rule 6: if the price is kept in the range of the first line, nothing is applied to the chart.
Rule 7: if the market reaches a new maximum, surpassing the maximum of previous lines, move to the column to the right and draw a new white line up to a new maximum.
Rule 8: if today's price is below the low of previous lines (i.e. there is a new low), move to the right column and draw a new black line down to a new low.
Rule 9: if the price is in the range of the first two lines, nothing is applied to the chart.
Rule 10: if there is a series of three white lines, a new white line is drawn when a new maximum is reached (even if it is only one tick higher than the old one). Under the same conditions, for drawing a black reversal line, the price should fall below the minimum of the series of the last three white lines. Such a black line is called a black reversal line. It runs from the base of the highest white line to a new low of price.
Rule 11: if there is a series of three black lines, a new black line is drawn when a new minimum is reached. Under the same conditions, for drawing a white line, called a white reversal line, the price must exceed the maximum of the previous three black lines. This line is drawn from the top of the lowest black line to a new high of the price.
So, the script was not small, but the idea is extremely simple: if you need to break n lines to build a line, then among these n lines (or less, if this is the beginning of the chart), the maximum or minimum of closures and openings will be searched. If the current candles closed above or below these highs or lows, then a new line is added to the chart on the current candles (trend or breakout). According to my observations, this script draws a chart that is completely identical to the Line Breakout chart built into TradingView, but of course with gaps, as there is time in the candles / bar chart. I stuffed all the logic into a wrapper in the form of the get_linebreak() function, which returns a tuple of OHLC values. And these series with the help of the plotcandle() annotation can be converted to the "Linear Breakthrough" chart. I also want to note that with a large number of candles on the chart, outrages about the buffer size uncertainty are heard from the TradingView black box. Because of this, in the annotation study() set the value to the max_bars_back parameter.
In general, use it (for example, to write strategies)!
在腳本中搜尋"algo"
REVEREVE is abbreviation from Range Extension Volume Expansion. This indicator shows these against a background of momentum. The histogram and columns for the range and volume rises ara calculated with the same algorithm as I use in the Volume Range Events indicator, which I published before. Because this algorithm uses the same special function to assess 'normal' levels for volume and range and uses the same calculation for depicting the rises on a scale of zero through 100, it becomes possible to compare volume and range rises in the same chart panel and come to meaningful conclusions. Different from VolumeRangeEvents is that I don't attempt to show direction of the bars and columns by actually pointing up or down. However I did color the bars for range events according to direction if Close jumps more than 20 percent of ATR up or down either blue or red. If the wider range leads to nothing, i.e. a smaller jump than 20 percent, the color is black. You can teak this in the inputs. The volume colums ar colored according to two criteria, resulting in four colors (orange, blue, maroon, green). The first criterium is whether the expansion is climactic (orange, blue) or moderate (maroon, green). I assume that climactic (i.e. more than twice as much) volume marks the beginning or end of a trend. The second criterium looks at the range event that goes together with the volume event. If lots of volume lead to little change in range (blue, green), I assume that this volume originates from institutional traders who are accumulating or distributing. If wild price jumps occur with comparatively little volume (orange, maroon, or even no volume event) I assume that opportunistic are active, some times attributing to more volume.
For the background I use the same colors calculated with the same algorithm as in the Hull Agreement Indicator, which I published before. This way I try to predict trend changes by observation of REVE.
T3 ICL MACD STRATEGY
Backtested manually and received approx 60% winrate. Tradingview strategy tester is skewed because this program does not specify when to sell at profit target or at a stop loss.
Uses 1 min for entry and a longer time frame for confirmation (5,10,15, etc..) (Not sure what the yellow arrows are in the picture but they can be ignored)
Ideal Long Entry - The algo uses T3 moving average (T3) and the Ichimoku Conversion Line (ICL) to determine when to enter a long or short position. In this case we are going to showcase what causes the algo to alert long. It first checks to see if the the ICL is greater than T3. Once that condition is met T3 must be green in order to enter long and finally the last closing price has to be greater than the ICL. You can use the MACD to further verify a long trend as well!
Ideal Short Entry - The algo uses T3 moving average (T3) and the Ichimoku Conversion Line (ICL) to determine when to enter a long or short position. In this case we are going to showcase what causes the algo to alert short. It first checks to see if the the ICL is less than T3. Once that condition is met T3 must be red in order to enter short and finally the last closing price has to be less than the ICL. You can use the MACD to further verify a long trend as well!
[PX] Moon PhaseHello guys,
while scrolling through the public library, I was surprised that there was no Open-Source version of the Moon Phase indicator. All moon phase indicators in the public library were either protected or not exactly what I was looking for. There is a built-in "Moon Phase" indicator, but even for this one, we can't access its source code.
Therefore, I started searching for an algorithm that I could implement into PineScript.
So here we go, an Open-Source Moon Phase indicator. It comes with the option to color the background based on the recent moon. Compared to the built-in indicator, the moon is slightly shifted, because it is centered on the candle and not plotted between two candles like the built-in indicator is doing it.
Feel free to use the indicator for your analysis or build on top of it in an open-source fashion.
Happy trading,
paaax :)
Reference: This indicator is a converted and simplified version of the original javascript algorithm, which can be found here .
SMU Quantum Thermo BallsThis script is the enhanced version of Market Thermometer with one difference. This one has Quantum Thermo balls shooting out of the thermometer tube when overheated. Quantum psychology, Quantum observation, call it what you like
My scripts are designed to beat ALGO, so the behavior of indicators is not like traditional indicators. Don't try to overthink it and compare it to other established functions.
If you knew ALGo as much as I do, then you would also ditch old indicators and design your own weird scripts to match the ALGO's personality. Oh yes, each AlGo for each stock has its own programming personality. Most my scripts are tuned to beat SPX ALGO meniac
Enjoy and think outside the box, the only way to beat the ALGO
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.
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
Adaptive Machine Learning Trading System [PhenLabs]📊Adaptive ML Trading System
Version: PineScript™v6
📌Description
The Adaptive ML Trading System is a sophisticated machine learning indicator that combines ensemble modeling with advanced technical analysis. This system uses XGBoost, Random Forest, and Neural Network algorithms to generate high-confidence trading signals while incorporating robust risk management features. Traders benefit from objective, data-driven decision-making that adapts to changing market conditions.
🚀Points of Innovation
• Machine Learning Ensemble - Three integrated models (XGBoost, Random Forest, Neural Network)
• Confidence-Based Trading - Only executes trades when ML confidence exceeds threshold
• Dynamic Risk Management - ATR-based stop loss and max drawdown protection
• Adaptive Position Sizing - Volatility-adjusted position sizing with confidence weighting
• Real-Time Performance Metrics - Live tracking of win rate, Sharpe ratio, and performance
• Multi-Timeframe Feature Analysis - Adaptive lookback periods for different market regimes
🔧Core Components
• ML Ensemble Engine - Weighted combination of XGBoost, Random Forest, and Neural Network outputs
• Feature Normalization System - Advanced preprocessing with custom tanh/sigmoid activation
• Risk Management Module - Dynamic position sizing and drawdown protection
• Performance Dashboard - Real-time metrics and risk status monitoring
• Alert System - Comprehensive alert conditions for entries, exits, and risk events
🔥Key Features
• High-confidence ML signals with customizable confidence thresholds
• Multiple trading modes (Conservative, Balanced, Aggressive) for different risk profiles
• Integrated stop loss and risk management with ATR-based calculations
• Real-time performance metrics including win rate and Sharpe ratio
• Comprehensive alert system with entry, exit, and risk management notifications
• Visual confidence bands and threshold indicators for easy signal interpretation
🎨Visualization
• ML Signal Line - Primary signal output ranging from -1 to +1
• Confidence Bands - Visual representation of model confidence levels
• Threshold Lines - Customizable buy/sell threshold levels
• Position Histogram - Current market position visualization
• Performance Tables - Real-time metrics display in customizable positions
📖Usage Guidelines
Model Configuration
• Confidence Threshold: Default 0.55, Range 0.5-0.95 - Minimum confidence for signals
• Model Sensitivity: Default 0.9, Range 0.1-2.0 - Adjusts signal sensitivity
• Ensemble Mode: Conservative/Balanced/Aggressive - Trading style preference
• Signal Threshold: Default 0.55, Range 0.3-0.9 - ML signal threshold for entries
Risk Management
• Position Size %: Default 10%, Range 1-50% - Portfolio percentage per trade
• Max Drawdown %: Default 15%, Range 5-30% - Maximum allowed drawdown
• Stop Loss ATR: Default 2.0, Range 0.5-5.0 - Stop loss in ATR multiples
• Dynamic Sizing: Default true - Volatility-based position adjustment
Display Settings
• Show Signals: Default true - Display entry/exit signals
• Show Threshold Signals: Default true - Display ±0.6 threshold crosses
• Show Confidence Bands: Default true - Display ML confidence levels
• Performance Dashboard: Default true - Show metrics table
✅Best Use Cases
• Swing trading with 1-5 day holding periods
• Trend-following strategies in established trends
• Volatility breakout trading during high-confidence periods
• Risk-adjusted position sizing for portfolio management
• Multi-timeframe confirmation for existing strategies
⚠️Limitations
• Requires sufficient historical data for accurate ML predictions
• May experience low confidence periods in choppy markets
• Performance varies across different asset classes and timeframes
• Not suitable for very short-term scalping strategies
• Requires understanding of basic risk management principles
💡What Makes This Unique
• True machine learning ensemble with multiple model types
• Confidence-based trading rather than simple signal generation
• Integrated risk management with dynamic position sizing
• Real-time performance tracking and metrics
• Adaptive parameters that adjust to market conditions
🔬How It Works
Feature Calculation: Computes 20+ technical features from price/volume data
Feature Normalization: Applies custom normalization for ML compatibility
Ensemble Prediction: Combines XGBoost, Random Forest, and Neural Network outputs
Signal Generation: Produces confidence-weighted trading signals
Risk Management: Applies position sizing and stop loss rules
Execution: Generates alerts and visual signals based on thresholds
💡Note:
This indicator works best on daily and 4-hour timeframes for most assets. Ensure you understand the risk management settings before live trading. The system includes automatic risk-off modes that halt trading during excessive drawdown periods.
Predicted Funding RatesOverview
The Predicted Funding Rates indicator calculates real-time funding rate estimates for perpetual futures contracts on Binance. It uses triangular weighting algorithms on multiple different timeframes to ensure an accurate prediction.
Funding rates are periodic payments between long and short position holders in perpetual futures markets
If positive, longs pay shorts (usually bullish)
If negative, shorts pay longs (usually bearish)
This is a prediction. Actual funding rates depend on the instantaneous premium index, derived from bid/ask impacts of futures. So whilst it may imitate it similarly, it won't be completely accurate.
This only applies currently to Binance funding rates, as HyperLiquid premium data isn't available. Other Exchanges may be added if their premium data is uploaded.
Methods
Method 1: Collects premium 1-minunute data using triangular weighing over 8 hours. This granular method fills in predicted funding for 4h and less recent data
Method 2: Multi-time frame approach. Daily uses 1 hour data in the calculation, 4h + timeframes use 15M data. This dynamic method fills in higher timeframes and parts where there's unavailable premium data on the 1min.
How it works
1) Premium data is collected across multiple timeframes (depending on the timeframe)
2) Triangular weighing is applied to emphasize recent data points linearly
Tri_Weighing = (data *1 + data *2 + data *3 + data *4) / (1+2+3+4)
3) Finally, the funding rate is calculated
FundingRate = Premium + clamp(interest rate - Premium, -0.05, 0.05)
where the interest rate is 0.01% as per Binance
Triangular weighting is calculated on collected premium data, where recent data receives progressively higher weight (1, 2, 3, 4...). This linear weighting scheme provides responsiveness to recent market conditions while maintaining stability, similar to an exponential moving average but with predictable, linear characteristics
A visual representation:
Data points: ──────────────>
Weights: 1 2 3 4 5
Importance: ▂ ▃ ▅ ▆ █
How to use it
For futures traders:
If funding is trending up, the market can be interpreted as being in a bull market
If trending down, the market can be interpreted as being in a bear market
Even used simply, it allows you to gauge roughly how well the market is performing per funding. It can basically be gauged as a sentiment indicator too
For funding rate traders:
If funding is up, it can indicate a long on implied APR values
If funding is down, it can indicate a short on implied APR values
It also includes an underlying APR, which is the annualized funding rate. For Binance, it is current funding * (24/8) * 365
For Position Traders: Monitor predicted funding rates before entering large positions. Extremely high positive rates (>0.05% for 8-hour periods) suggest overleveraged longs and potential reversal risk. Conversely, extreme negative rates indicate shorts dominance
Table:
Funding rate: Gives the predicted funding rate as a percentage
Current premium: Displays the current premium (difference between perpetual futures price and the underlying spot) as a percentage
Funding period: You can choose between 1 hour funding (HyperLiquid usually) and 8 hour funding (Binance)
APR: Underlying annualized funding rate
What makes it original
Whilst some predicted funding scripts exist, some aren't as accurate or have gaps in data. And seeing as funding values are generally missing from TV tickers, this gives traders accessibility to the script when they would have to use other platforms
Notes
Currently only compatible with symbols that have Binance USDT premium indices
Optimal accuracy is found on timeframes that are 4H or less. On higher timeframes, the accuracy drops off
Actual funding rates may differ
Inputs
Funding Period: Choose between "8 Hour" (standard Binance cycle) or "1 Hour" (divides the 8-hour rate by 8 for granular comparison)
Plot Type: Display as "Funding Rate" (percentage per interval) or "APR" (annualized rate calculated as 8-hour rate × 3 × 365)
Table: Toggle the information table showing current funding rate, premium, funding period, and APR in the top-right corner
Positive Colour: Sets the colour for positive funding rates where longs pay shorts (default: #00ffbb turquoise)
Negative Colour: Sets the colour for negative funding rates where shorts pay longs (default: red)
Table Background: Controls the background colour and transparency of the information table (default: transparent dark blue)
Table Text Colour: Sets the colour for all text labels in the information table (default: white)
Table Text Size: Controls font size with options from Tiny to Huge, with Small as the default balance of readability and space
MACD Forecast [Titans_Invest]MACD Forecast — The Future of MACD in Trading
The MACD has always been one of the most powerful tools in technical analysis.
But what if you could see where it’s going, instead of just reacting to what has already happened?
Introducing MACD Forecast — the natural evolution of the MACD Full , now taken to the next level. It’s the world’s first MACD designed not only to analyze the present but also to predict the future behavior of momentum.
By combining the classic MACD structure with projections powered by Linear Regression, this indicator gives traders an anticipatory, predictive view, redefining what’s possible in technical analysis.
Forget lagging indicators.
This is the smartest, most advanced, and most accurate MACD ever created.
🍟 WHY MACD FORECAST IS REVOLUTIONARY
Unlike the traditional MACD, which only reflects current and past price dynamics, the MACD Forecast uses regression-based projection models to anticipate where the MACD line, signal line, and histogram are heading.
This means traders can:
• See MACD crossovers before they happen.
• Spot trend reversals earlier than most.
• Gain an unprecedented timing advantage in both discretionary and automated trading.
In other words: this indicator lets you trade ahead of time.
🔮 FORECAST ENGINE — POWERED BY LINEAR REGRESSION
At its core, the MACD Forecast integrates Linear Regression (ta.linreg) to project the MACD’s future behavior with exceptional accuracy.
Projection Modes:
• Flat Projection: Assumes trend continuity at the current level.
• LinReg Projection: Applies linear regression across N periods to mathematically forecast momentum shifts.
This dual system offers both a conservative and adaptive view of market direction.
📐 ACCURACY WITH FULL CUSTOMIZATION
Just like the MACD Full, this new version comes with 20 customizable buy-entry conditions and 20 sell-entry conditions — now enhanced with forecast-based rules that anticipate crossovers and trend reversals.
You’re not just reacting — you’re strategizing ahead of time.
⯁ HOW TO USE MACD FORECAST❓
The MACD Forecast is built on the same foundation as the classic MACD, but with predictive capabilities.
Step 1 — Spot Predicted Crossovers:
Watch for forecasted bullish or bearish crossovers. These signals anticipate when the MACD line will cross the signal line in the future, letting you prepare trades before the move.
Step 2 — Confirm with Histogram Projection:
Use the projected histogram to validate momentum direction. A rising histogram signals strengthening bullish momentum, while a falling projection points to weakening or bearish conditions.
Step 3 — Combine with Multi-Timeframe Analysis:
Use forecasts across multiple timeframes to confirm signal strength (e.g., a 1h forecast aligned with a 4h forecast).
Step 4 — Set Entry Conditions & Automation:
Customize your buy/sell rules with the 20 forecast-based conditions and enable automation for bots or alerts.
Step 5 — Trade Ahead of the Market:
By preparing for future momentum shifts instead of reacting to the past, you’ll always stay one step ahead of lagging traders.
🤖 BUILT FOR AUTOMATION AND BOTS 🤖
Whether for manual trading, quantitative strategies, or advanced algorithms, the MACD Forecast was designed to integrate seamlessly with automated systems.
With predictive logic at its core, your strategies can finally react to what’s coming, not just what already happened.
🥇 WHY THIS INDICATOR IS UNIQUE 🥇
• World’s first MACD with Linear Regression Forecasting
• Predictive Crossovers (before they appear on the chart)
• Maximum flexibility with Long & Short combinations — 20+ fully configurable conditions for tailor-made strategies
• Fully automatable for quantitative systems and advanced bots
This isn’t just an update.
It’s the final evolution of the MACD.
______________________________________________________
🔹 CONDITIONS TO BUY 📈
______________________________________________________
• Signal Validity: The signal will remain valid for X bars .
• Signal Sequence: Configurable as AND or OR .
🔹 MACD > Signal Smoothing
🔹 MACD < Signal Smoothing
🔹 Histogram > 0
🔹 Histogram < 0
🔹 Histogram Positive
🔹 Histogram Negative
🔹 MACD > 0
🔹 MACD < 0
🔹 Signal > 0
🔹 Signal < 0
🔹 MACD > Histogram
🔹 MACD < Histogram
🔹 Signal > Histogram
🔹 Signal < Histogram
🔹 MACD (Crossover) Signal
🔹 MACD (Crossunder) Signal
🔹 MACD (Crossover) 0
🔹 MACD (Crossunder) 0
🔹 Signal (Crossover) 0
🔹 Signal (Crossunder) 0
🔮 MACD (Crossover) Signal Forecast
🔮 MACD (Crossunder) Signal Forecast
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______________________________________________________
🔸 CONDITIONS TO SELL 📉
______________________________________________________
• Signal Validity: The signal will remain valid for X bars .
• Signal Sequence: Configurable as AND or OR .
🔸 MACD > Signal Smoothing
🔸 MACD < Signal Smoothing
🔸 Histogram > 0
🔸 Histogram < 0
🔸 Histogram Positive
🔸 Histogram Negative
🔸 MACD > 0
🔸 MACD < 0
🔸 Signal > 0
🔸 Signal < 0
🔸 MACD > Histogram
🔸 MACD < Histogram
🔸 Signal > Histogram
🔸 Signal < Histogram
🔸 MACD (Crossover) Signal
🔸 MACD (Crossunder) Signal
🔸 MACD (Crossover) 0
🔸 MACD (Crossunder) 0
🔸 Signal (Crossover) 0
🔸 Signal (Crossunder) 0
🔮 MACD (Crossover) Signal Forecast
🔮 MACD (Crossunder) Signal Forecast
______________________________________________________
______________________________________________________
🔮 Linear Regression Function 🔮
______________________________________________________
• Our indicator includes MACD forecasts powered by linear regression.
Forecast Types:
• Flat: Assumes prices will stay the same.
• Linreg: Makes a 'Linear Regression' forecast for n periods.
Technical Information:
• Function: ta.linreg()
Parameters:
• source: Source price series.
• length: Number of bars (period).
• offset : Offset.
• return: Linear regression curve.
______________________________________________________
______________________________________________________
⯁ UNIQUE FEATURES
______________________________________________________
Linear Regression: (Forecast)
Signal Validity: The signal will remain valid for X bars
Signal Sequence: Configurable as AND/OR
Table of Conditions: BUY/SELL
Conditions Label: BUY/SELL
Plot Labels in the graph above: BUY/SELL
Automate & Monitor Signals/Alerts: BUY/SELL
Linear Regression (Forecast)
Signal Validity: The signal will remain valid for X bars
Signal Sequence: Configurable as AND/OR
Table of Conditions: BUY/SELL
Conditions Label: BUY/SELL
Plot Labels in the graph above: BUY/SELL
Automate & Monitor Signals/Alerts: BUY/SELL
______________________________________________________
📜 SCRIPT : MACD Forecast
🎴 Art by : @Titans_Invest & @DiFlip
👨💻 Dev by : @Titans_Invest & @DiFlip
🎑 Titans Invest — The Wizards Without Gloves 🧤
✨ Enjoy!
______________________________________________________
o Mission 🗺
• Inspire Traders to manifest Magic in the Market.
o Vision 𐓏
• To elevate collective Energy 𐓷𐓏
🎗️ In memory of João Guilherme — your light will live on forever.
Squeeze Momentum Pro + Divergencias RCTSqueeze Momentum Pro + Divergences RCT"
This indicator combines the core logic of the LazyBear Squeeze Momentum oscillator with divergence detection logic, as modified and integrated by Carlos Mauricio Vizcarra for the Rafael Cepeda Trader community. It displays the classic Squeeze Momentum histogram and zero-cross line, while simultaneously identifying potential regular and hidden bullish and bearish divergences based on the internal momentum oscillator (val) and price pivots.
This code is provided exclusively for demonstrative and academic purposes. It is intended for study, analysis, and educational use within the context of algorithmic trading indicator development. The code is subject to the Mozilla Public License 2.0 (MPL 2.0).
Fib Retracement ( AUTO)Key Features:
Automatic Pivot Detection:
Uses ZigZag algorithm to identify significant highs and lows
Configurable depth and deviation settings for pivot sensitivity
Automatically updates with new price data
Fibonacci Levels:
Standard retracement levels: 0%, 23.6%, 38.2%, 50%, 61.8%, 78.6%, 100%
Optional negative extension levels (-23.6%, -38.2%, -61.8%, -65%)
Clean visual presentation without extension levels beyond 100%
Customization Options:
Deviation: Controls sensitivity of pivot detection (higher values = fewer pivots)
Depth: Minimum bars between pivot points
Reverse: Switch between measuring from high-to-low or low-to-high
Extend Lines: Choose to extend lines left, right, both, or none
Display Format: Show levels as values or percentages
Label Position: Place labels on left or right side
Background Transparency: Adjust shading between levels
Visual Elements:
Colored horizontal lines at each Fibonacci level
Clear price labels aligned properly with levels
Optional background shading between levels
Dashed gray line connecting the pivot points
Alert System:
Automatic alerts when price crosses any Fibonacci level
Customizable alert messages with symbol and level information
Usage:
Traders use this indicator to identify potential support and resistance levels, entry/exit points, and to gauge the strength of price retracements within trends. The automatic nature eliminates subjective drawing and ensures consistent application of Fibonacci principles across different charts and timeframes.
Ideal For:
Swing traders looking for retracement entries
Position traders identifying key levels
Technical analysts automating Fibonacci analysis
Any trader wanting objective Fibonacci level placement
The indicator works across all timeframes and markets, providing reliable Fibonacci retracement levels without manual intervention.
Volume Profile 3D (Zeiierman)█ Overview
Volume Profile 3D (Zeiierman) is a next-generation volume profile that renders market participation as a 3D-style profile directly on your chart. Instead of flat histograms, you get a depth-aware profile with parallax, gradient transparency, and bull/bear separation, so you can see where liquidity stacked up and how it shifted during the move.
Highlights:
3D visual effect with perspective and depth shading for clarity.
Bull/Bear separation to see whether up bars or down bars created the volume.
Flexible colors and gradients that highlight where the most significant trading activity took place.
This is a state-of-the-art volume profile — visually powerful, highly flexible, and unlike anything else available.
█ How It Works
⚪ Profile Construction
The price range (from highest to lowest) is divided into a number of levels (buckets). Each bar’s volume is added to the correct level, based on its average price. This builds a map of where trading volume was concentrated.
You can choose to:
Aggregate all volume at each level, or
Split bullish vs. bearish volume , slightly offset for clarity.
This creates a clear view of which price zones matter most to the market.
⚪ 3D Effect Creation
The unique part of this indicator is how the 3D projection is built. Each volume block’s width is scaled to its relative size, then tilted with a slope factor to create a depth effect.
maxVol = bins.bu.max() + bins.be.max()
width = math.max(1, math.floor(bucketVol / maxVol * ((bar_index - start) * mult)))
slope = -(step * dev) / ((bar_index - start) * (mult/2))
factor = math.pow(math.min(1.0, math.abs(slope) / step), .5)
width → determines how far the volume extends, based on relative strength.
slope → creates the angled projection for the 3D look.
factor → adjusts perspective to make deeper areas shrink naturally.
The result is a 3D-style volume profile where large areas pop forward and smaller areas fade back, giving you immediate visual context.
█ How to Use
⚪ Support & Resistance Zones (HVNs and Value Area)
Regions where a lot of volume traded tend to act like walls:
If price approaches a high-volume area from above, it may act as support.
From below, it may act as resistance.
Traders often enter or exit near these zones because they represent strong agreement among market participants.
⚪ POC Rejections & Mean Reversions
The Point of Control (POC) is the single price level with the highest volume in the profile.
When price returns to the POC and rejects it, that’s often a signal for reversal trades.
In ranging markets, price may bounce between edges of the Value Area and revert to POC.
⚪ Breakouts via Low-Volume Zones (LVNs)
Low volume areas (gaps in the profile) offer path of least resistance:
Price often moves quickly through these thin zones when momentum builds.
Use them to spot breakouts or continuation trades.
⚪ Directional Insight
Use the bull/bear separation to see whether buyers or sellers dominated at key levels.
█ Settings
Use Active Chart – Profile updates with visible candles.
Custom Period – Fixed number of bars.
Up/Down – Adjust tilt for the 3D angle.
Left/Right – Scale width of the profile.
Aggregated – Merge bull/bear volume.
Bull/Bear Shift – Separate bullish and bearish volume.
Buckets – Number of price levels.
Choose from templates or set custom colors.
POC Gradient option makes high volume bolder, low volume lighter.
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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.
Scalper - Pattern Recognition & Price Action with Divergence Scalper - Pattern Recognition & Price Action with Divergence
Overview
An educational indicator designed to demonstrate comprehensive technical analysis concepts through integrated pattern recognition, price action analysis, and divergence detection. This tool combines traditional candlestick patterns with modern institutional concepts and advanced divergence analysis for educational market study.
Educational Purpose & Originality
Core Educational Concepts
This indicator serves as a learning platform for understanding:
- **Pattern Recognition Methodology**: Systematic identification of candlestick formations
- **Price Action Theory**: Modern institutional footprint analysis
- **Divergence Analysis**: Momentum divergence detection across multiple oscillators
- **Confluence Systems**: Multi-signal integration and validation techniques
Original Implementation Features
1. Enhanced Pattern Detection Library
- **Volatility-Filtered Patterns**: ATR-based validation for pattern significance
- **Volume-Confirmed Formations**: Integration of volume analysis with pattern detection
- **Multi-Candle Pattern Recognition**: Three-candle formations and complex patterns
- **Context-Aware Detection**: Patterns validated against market structure
2. Advanced Divergence System
- **Multi-Oscillator Analysis**: RSI, CCI, and MACD divergence detection
- **Four Divergence Types**: Regular bullish/bearish and hidden bullish/bearish
- **Pivot-Based Detection**: Systematic swing high/low identification
- **Weighted Signal Integration**: Divergences integrated into confluence scoring
3. Modern Price Action Concepts
- **Fair Value Gaps (FVG)**: Identification of institutional inefficiencies
- **Order Block Detection**: Volume-validated accumulation/distribution zones
- **Dynamic Support/Resistance**: Touch-count validated levels with ATR tolerance
- **Breakout Analysis**: Volume-confirmed price breakouts
4. Intelligent Confluence System
- **Multi-Signal Aggregation**: Combines patterns, oscillators, divergences, and breakouts
- **Weighted Scoring Algorithm**: Different signal types receive appropriate weighting
- **Visual Confluence Display**: Clear indication of high-probability setups
- **Reason Tracking**: Shows which signals contribute to confluence
How to Use
Initial Configuration
1. **Enable Desired Components**: Toggle individual analysis modules based on learning focus
2. **Adjust Sensitivity Settings**: Configure pattern detection parameters for your market
3. **Select Divergence Options**: Choose oscillators and divergence types to monitor
4. **Set Confluence Requirements**: Define minimum signals needed for confirmation
Component Settings
Moving Average Configuration
- Four customizable MA lines for multi-timeframe trend analysis
- Selectable MA types (SMA, EMA, WMA, VWMA, HMA)
- Independent timeframe settings for each MA
Pattern Recognition Settings
- **Engulfing Patterns**: Strong engulfing with ATR validation
- **Doji Variations**: Standard, gravestone, and dragonfly detection
- **Hammer/Hanging Man**: Context-validated reversal patterns
- **Star Formations**: Morning and evening star patterns
- **Three Soldiers/Crows**: Momentum continuation patterns
Divergence Detection Parameters
- **Lookback Period**: Adjustable swing detection range
- **Minimum Pivot Strength**: Percentage threshold for valid pivots
- **Oscillator Selection**: RSI, CCI, MACD, or combination
- **Divergence Types**: Regular and hidden divergences
Signal Interpretation
Visual Indicators
- **Pattern Labels**: Clear marking of detected formations
- **Divergence Lines**: Visual connection between price and oscillator pivots
- **Support/Resistance Levels**: Dynamic horizontal levels with validation
- **Confluence Signals**: Large "BULL" or "BEAR" labels for high-probability setups
Dashboard Information
- Real-time oscillator values (RSI, CCI, MACD)
- Current signal count for bulls and bears
- Active divergence status
- Confluence confirmation status
Important Educational Considerations
Learning Focus
- **Pattern Study**: Understand how traditional patterns form and their limitations
- **Divergence Concepts**: Learn to identify momentum shifts before price reversals
- **Confluence Theory**: Practice combining multiple analysis techniques
- **Risk Awareness**: No pattern or signal guarantees future price movement
Limitations for Learning
- **Historical Analysis**: Patterns are identified after formation
- **No Predictive Guarantee**: Educational tool for understanding concepts, not predictions
- **Market Context Required**: Patterns should be considered within broader market context
- **Practice Required**: Effective use requires study and practice
Educational Best Practices
1. **Start Simple**: Enable one component at a time to understand each concept
2. **Paper Trade**: Practice identifying signals without real money risk
3. **Study Failed Signals**: Learn why patterns fail to improve understanding
4. **Combine with Other Analysis**: Use alongside fundamental and sentiment analysis
5. **Document Observations**: Keep a journal of pattern occurrences and outcomes
Technical Components
Indicator Architecture
- **Modular Design**: Independent modules for different analysis types
- **Performance Optimization**: Efficient calculation methods for smooth operation
- **Visual Management**: Controlled use of Pine Script drawing objects
- **Array-Based Storage**: Efficient data management for historical analysis
Calculation Methods
- **ATR-Based Validation**: Volatility-adjusted pattern filtering
- **Volume Analysis**: Comparative volume assessment for confirmation
- **Pivot Detection**: Mathematical identification of swing points
- **Statistical Validation**: Touch-count and tolerance-based S/R levels
Divergence Detection Methodology
Regular Divergences (Reversal Signals)
- **Bullish**: Price lower low + Oscillator higher low
- **Bearish**: Price higher high + Oscillator lower high
Hidden Divergences (Continuation Signals)
- **Hidden Bullish**: Price higher low + Oscillator lower low
- **Hidden Bearish**: Price lower high + Oscillator higher high
Validation Criteria
- Minimum pivot strength requirement (percentage-based)
- Lookback period for swing detection
- Multiple oscillator confirmation option
Confluence Scoring System
Signal Categories
1. **Pattern Signals** (Weight: 1): Candlestick formations
2. **Oscillator Signals** (Weight: 1): RSI/CCI extremes
3. **Breakout Signals** (Weight: 1): Volume-confirmed breaks
4. **Regular Divergences** (Weight: 2): Higher probability reversals
5. **Hidden Divergences** (Weight: 1): Trend continuation signals
Confluence Thresholds
- Adjustable minimum signal requirement (2-6 signals)
- Visual indication when threshold is met
- Detailed reason display for educational understanding
Educational Dashboard
Real-Time Metrics
- Oscillator readings (RSI, CCI, MACD)
- ATR volatility measurement
- Bull/Bear signal counts
- Divergence status
- Confluence confirmation
Customization Options
- Position selection (6 screen locations)
- Color customization for all elements
- Enable/disable individual components
Version Information
- **Version 1.1**: Added comprehensive divergence detection system
- **Educational Focus**: Designed for learning technical analysis concepts
- **Integration**: All components work together in confluence system
Disclaimer
This indicator is designed exclusively for educational purposes to demonstrate technical analysis concepts. It is not financial advice and should not be used as the sole basis for trading decisions. Past patterns and signals do not guarantee future results. Trading involves substantial risk of loss. Users should conduct their own research, practice with demo accounts, and consider seeking advice from qualified professionals before making investment decisions.
Learning Resources
The indicator includes extensive inline comments explaining each calculation and concept. Users are encouraged to study the source code to understand the methodology behind each component. This transparency aids in learning how technical indicators work and their limitations.
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**Note**: This is an educational tool meant to help traders learn pattern recognition and technical analysis concepts. Success requires practice, additional analysis, and proper risk management.
Advanced Market Structure [OmegaTools]📌 Market Structure
Advanced Market Structure is a next–generation indicator designed to decode price structure in real time by combining classical swing–based analysis with modern quantitative confirmation techniques. Built for traders who demand both precision and adaptability, it provides a robust multi–layered framework to identify structural shifts, trend continuations, and potential reversals across any asset class or timeframe.
Unlike traditional structure indicators that rely solely on visual swing identification, Market Structure introduces an integrated methodology: pivot detection, Donchian trend modeling, statistical confirmation via Z–Score, and volume–based validation. Each element contributes to a comprehensive, systematic representation of the underlying market dynamics.
🔑 Core Features
1. Five Distinct Market Structure Modes
Standard Mode:
Captures structural breaks through classical swing high/low pivots. Ideal for discretionary traders looking for clarity in directional bias.
Confirmed Breakout Mode:
Requires validation beyond the initial pivot break, filtering out noise and reducing false positives.
Donchian Trend HL (High/Low):
Establishes structure based on absolute highs and lows over rolling lookback windows. This approach highlights broader momentum shifts and trend–defining extremes.
Donchian Trend CC (Close/Close):
Similar to HL mode, but calculated using closing prices, enabling more precise bias identification where close–to–close structure carries stronger statistical weight.
Average Mode:
A composite methodology that synthesizes the four models into a weighted signal, producing a balanced structural bias designed to minimize model–specific weaknesses.
2. Dynamic Pivot Recognition with Auto–Updating Levels
Swing highs and lows are automatically detected and plotted with adaptive horizontal levels. These dynamic support/resistance markers continuously extend into the future, ensuring that historically significant levels remain visible and actionable.
3. Color–Adaptive Candlesticks
Price bars are dynamically recolored to reflect the prevailing structural regime: bullish (default blue), bearish (default red), or neutral (gray). This enables instant visual recognition of regime changes without requiring external confirmation.
4. Statistical Reversal Triggers
The script integrates a 21–period Z–Score calculation applied to closing prices, combined with multi–layered volume confirmation (SMA and EMA convergence).
Bullish trigger: Z–Score < –2 with structural confirmation and volume support.
Bearish trigger: Z–Score > +2 with structural confirmation and volume support.
Signals are plotted as diamond markers above or below the bars, identifying potential high–probability reversal setups in real time.
5. Integrated Alpha Backtesting Engine
Each market structure mode is evaluated through a built–in backtesting routine, tracking hit ratios and consistency across the most recent ~2000 structural events.
Performance metrics (“Alpha”) are displayed directly on–chart via a dedicated Performance Dashboard Table, allowing side–by–side comparison of Standard, Confirmed Breakout, Donchian HL, Donchian CC, and Average models.
Traders can instantly evaluate which structural methodology best adapts to the current market conditions.
🎯 Practical Advantages
Systematic Clarity: Eliminates subjectivity in defining structural bias, offering a rules–based framework.
Statistical Transparency: Built–in performance metrics validate each mode in real time, allowing informed decision–making.
Noise Reduction: Confirmed Breakouts and Donchian modes filter out common traps in structural trading.
Multi–Asset Adaptability: Optimized for scalping, intraday, swing, and multi–day strategies across FX, equities, futures, commodities, and crypto.
Complementary Usage: Works as a stand–alone structure identifier or as a quantitative filter in larger algorithmic/trading frameworks.
⚙️ Ideal Users
Discretionary traders seeking an objective reference for structural bias.
Quantitative/systematic traders requiring on–chart statistical validation of structural regimes.
Technical analysts leveraging pivots, Donchian channels, and price action as part of broader frameworks.
Portfolio traders integrating structure into multi–factor models.
💡 Why This Tool?
Market Structure is not a static indicator — it is an adaptive framework. By merging classical pivot theory with Donchian–style momentum analysis, and reinforcing both with statistical backtesting and volume confirmation, it provides traders with a unique ability:
To see the structure,
To measure its reliability,
And to act with confidence on quantifiably validated signals.
SCTI - D14SCTI - D14 Comprehensive Technical Analysis Suite
English Description
SCTI D14 is an advanced multi-component technical analysis indicator designed for professional traders and analysts. This comprehensive suite combines multiple analytical tools into a single, powerful indicator that provides deep market insights across various timeframes and methodologies.
Core Components:
1. EMA System (Exponential Moving Averages)
13 customizable EMA lines with periods ranging from 8 to 2584
Fibonacci-based periods (8, 13, 21, 34, 55, 89, 144, 233, 377, 610, 987, 1597, 2584)
Color-coded visualization for easy trend identification
Individual toggle controls for each EMA line
2. TFMA (Multi-Timeframe Moving Averages)
Cross-timeframe analysis with 3 independent EMA calculations
Real-time labels showing trend direction and price relationships
Customizable timeframes for each moving average
Percentage deviation display from current price
3. PMA (Precision Moving Average Cloud)
7-layer moving average system with customizable periods
Fill areas between moving averages for trend visualization
Support and resistance zone identification
Dynamic color-coded trend clouds
4. VWAP (Volume Weighted Average Price)
Multiple anchor points (Session, Week, Month, Quarter, Year, Earnings, Dividends, Splits)
Standard deviation bands for volatility analysis
Automatic session detection and anchoring
Statistical price level identification
5. Advanced Divergence Detector
12 technical indicators for divergence analysis (MACD, RSI, Stochastic, CCI, Williams %R, Bias, Momentum, OBV, VW-MACD, CMF, MFI, External)
Regular and hidden divergences detection
Bullish and bearish signals with visual confirmation
Customizable sensitivity and filtering options
Real-time alerts for divergence formations
6. Volume Profile & Node Analysis
Comprehensive volume distribution analysis
Point of Control (POC) identification
Value Area High/Low (VAH/VAL) calculations
Volume peaks and troughs detection
Support and resistance levels based on volume
7. Smart Money Concepts
Market structure analysis with Break of Structure (BOS) and Change of Character (CHoCH)
Internal and swing structure detection
Equal highs and lows identification
Fair Value Gaps (FVG) detection and visualization
Liquidity zones and institutional flow analysis
8. Trading Sessions
9 major trading sessions (Asia, Sydney, Tokyo, Shanghai, Hong Kong, Europe, London, New York, NYSE)
Real-time session status and countdown timers
Session volume and performance tracking
Customizable session boxes and labels
Statistical session analysis table
Key Features:
Modular Design: Enable/disable any component independently
Real-time Analysis: Live updates with market data
Multi-timeframe Support: Works across all chart timeframes
Customizable Alerts: Set alerts for any detected pattern or signal
Professional Visualization: Clean, organized display with customizable colors
Performance Optimized: Efficient code for smooth chart performance
Use Cases:
Trend Analysis: Identify market direction using multiple EMA systems
Entry/Exit Points: Use divergences and structure breaks for timing
Risk Management: Utilize volume profiles and session analysis for better positioning
Multi-timeframe Analysis: Confirm signals across different timeframes
Institutional Analysis: Track smart money flows and market structure
Perfect For:
Day traders seeking comprehensive market analysis
Swing traders needing multi-timeframe confirmation
Professional analysts requiring detailed market structure insights
Algorithmic traders looking for systematic signal generation
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中文描述
SCTI - D14是一个先进的多组件技术分析指标，专为专业交易者和分析师设计。这个综合套件将多种分析工具整合到一个强大的指标中，在各种时间框架和方法论中提供深度市场洞察。
核心组件：
1. EMA系统（指数移动平均线）
13条可定制EMA线，周期从8到2584
基于斐波那契的周期（8, 13, 21, 34, 55, 89, 144, 233, 377, 610, 987, 1597, 2584）
颜色编码可视化，便于趋势识别
每条EMA线的独立切换控制
2. TFMA（多时间框架移动平均线）
跨时间框架分析，包含3个独立的EMA计算
实时标签显示趋势方向和价格关系
每个移动平均线的可定制时间框架
显示与当前价格的百分比偏差
3. PMA（精密移动平均云）
7层移动平均系统，周期可定制
移动平均线间填充区域用于趋势可视化
支撑阻力区域识别
动态颜色编码趋势云
4. VWAP（成交量加权平均价格）
多个锚点（交易时段、周、月、季、年、财报、分红、拆股）
标准差带用于波动性分析
自动时段检测和锚定
统计价格水平识别
5. 高级背离检测器
12个技术指标用于背离分析（MACD、RSI、随机指标、CCI、威廉姆斯%R、Bias、动量、OBV、VW-MACD、CMF、MFI、外部指标）
常规和隐藏背离检测
看涨看跌信号配视觉确认
可定制敏感度和过滤选项
背离形成的实时警报
6. 成交量分布与节点分析
全面的成交量分布分析
控制点（POC）识别
价值区域高/低点（VAH/VAL）计算
成交量峰值和低谷检测
基于成交量的支撑阻力水平
7. 聪明钱概念
市场结构分析，包括结构突破（BOS）和结构转变（CHoCH）
内部和摆动结构检测
等高等低识别
公允价值缺口（FVG）检测和可视化
流动性区域和机构资金流分析
8. 交易时区
9个主要交易时段（亚洲、悉尼、东京、上海、香港、欧洲、伦敦、纽约、纽交所）
实时时段状态和倒计时器
时段成交量和表现跟踪
可定制时段框和标签
统计时段分析表格
主要特性：
模块化设计：可独立启用/禁用任何组件
实时分析：随市场数据实时更新
多时间框架支持：适用于所有图表时间框架
可定制警报：为任何检测到的模式或信号设置警报
专业可视化：清洁、有序的显示界面，颜色可定制
性能优化：高效代码确保图表流畅运行
使用场景：
趋势分析：使用多重EMA系统识别市场方向
入场/出场点：利用背离和结构突破进行时机选择
风险管理：利用成交量分布和时段分析进行更好定位
多时间框架分析：在不同时间框架间确认信号
机构分析：跟踪聪明钱流向和市场结构
适用于：
寻求全面市场分析的日内交易者
需要多时间框架确认的摆动交易者
需要详细市场结构洞察的专业分析师
寻求系统化信号生成的算法交易者
