AI-123's BTC vs Gold (Lag Correlation)
DISCLAIMER
I made this indicator with the help of ChatGPT and using what I have learned so far from The Pine Script Mastery Course, LOTS of edits based on what I have learned so far had to be made as well as additions and modifications to my liking thanks to what I have learned so far. I am aware this already exists but I have done my best to make a first ever script/indicator while learning how to properly publish as well, so please bear that in mind.
Overview
This indicator analyzes the correlation between Bitcoin (BTC) and Gold (XAUUSD), with a customizable lag applied to the Gold price, providing insight into the macro relationship between these two assets.
It is designed for traders and investors who want to track how Bitcoin and Gold move in relation to each other, particularly when Gold is lagged by a specific number of days.
Key Features:
BTC and Gold (Lagged) Price Overlay: Display Bitcoin (BTC) and Gold (XAUUSD) prices on the chart, with an adjustable lag applied to the Gold price.
Rolling Correlation Calculation: Measures the correlation between Bitcoin and lagged Gold prices over a customizable lookback period.
Adjustable Lag: The number of days that Gold is lagged relative to Bitcoin is fully customizable (default: 20 days).
Customizable Correlation Length: Allows you to choose the lookback period for the correlation (default: 50 days), providing flexibility for short-term or long-term analysis.
Normalized Plotting: Prices of Bitcoin and Gold are normalized for better visual alignment with the correlation values. BTC is divided by 1000, and Gold by 100.
Correlation Scaling: The correlation value is amplified by 10 for better visual clarity and comparison with price data.
Zero Line: Horizontal line representing a correlation of 0, making it easier to identify positive or negative correlation shifts.
Maximum Correlation Lines: Horizontal lines at +10 and -10 values for extreme correlation scenarios.
Input Settings:
Gold Symbol: Customize the Gold ticker (default: OANDA:XAUUSD).
Bitcoin Symbol: Customize the Bitcoin ticker (default: BINANCE:BTCUSDT).
Lag (in trading days): Adjust the number of trading days to lag the Gold price relative to Bitcoin (default: 20).
Correlation Length (days): Set the number of days over which the rolling correlation is calculated (default: 50).
How to Use:
Price Comparison: The BTC (Spot) and Lagged Gold plots give you a side-by-side visual comparison of the two assets, normalized for clarity.
Correlation Line: The correlation line helps you gauge the strength and direction of the relationship between BTC and lagged Gold. Positive values indicate a strong positive correlation, while negative values indicate a negative correlation.
Visual Analysis: Watch how the correlation shifts with changes in lag and correlation length to identify potential market dynamics between Bitcoin and Gold.
Potential Applications:
Macro Trading: Track how Bitcoin and Gold behave in relation to each other during periods of economic uncertainty or inflation.
Sentiment Analysis: Use the correlation data to understand the sentiment between digital and traditional assets.
Strategic Timing: Identify potential opportunities where Bitcoin and Gold show a strong correlation or diverge based on the lag adjustment.
Understanding Macro Trends/Correlations.
Disclaimer:
This indicator is for informational purposes only. The correlation between Bitcoin and Gold does not guarantee future performance, and users should conduct their own research and use risk management strategies when making trading decisions.
Notes: This script uses historical data, so results may vary across different timeframes.
Customization options allow users to adjust the lag and correlation length to better fit their trading strategy.
Future Enhancements: Additional Correlation Line: A second correlation line for different lengths of lag or different assets.
Color-Coding of Correlation: Future updates may include color-coded correlation strength, visually indicating positive or negative correlation more effectively.
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Enhanced Order Flow Pressure GaugeShort Description:
Estimates bullish/bearish pressure by analyzing each candle’s close position within its range, then weighting that by volume. Detects potential trend shifts and provides real-time signals.
Full Description:
1. Purpose
The Enhanced Order Flow Pressure Gauge (OFPG+) is designed to approximate buy vs. sell pressure within each bar, even if you don’t have full Level II / order flow data. By measuring the candle’s close relative to its high-low range and multiplying by volume, OFPG+ provides insights into which side of the market (bulls or bears) is more aggressive in a given interval.
2. Key Components
Pressure Score (Histogram):
Raw measure of each bar’s close position (rangePos) minus midpoint, multiplied by volume. If the bar closes near its high with decent volume, the score is positive (bullish). Conversely, a close near its low yields a negative (bearish) reading.
Cumulative Pressure:
Sum of all pressure readings over time (similar to cumulative delta), reflecting the overall market bias.
Pressure Delta:
The change in cumulative pressure from one bar to the next, plotted as a line. Rising values suggest increasing bullish momentum, while falling values show growing bearish influence.
3. Visual Cues & Signals
Histogram (Pressure Profile): A color-coded bar for each candle, indicating net bullish (blue) or bearish (gray) intrabar pressure.
Pressure Delta Line: Plotted over the histogram. Turns bullish (blue) when net buy pressure is increasing, or bearish (gray) when net selling accelerates.
Background Highlights:
Turns lightly blue if the smoothed pressure line exceeds the positive threshold, or lightly gray if it goes below the negative threshold.
Bullish / Bearish Signals:
Bullish Signal occurs when the smoothed pressure line crosses above the positive threshold, combined with a positive Delta.
Bearish Signal occurs when the smoothed pressure line crosses below the negative threshold, combined with a negative Delta.
Confirmed Signals:
After a bullish/bearish signal, OFPG+ checks the highest or lowest smoothed pressure values over a user-defined number of bars (signalLookback) to confirm momentum.
Plotshapes (diamond icons) appear on the chart to mark these confirmed reversals.
4. Usage Scenarios
Trend-Following / Momentum: Watch for transitions from negative to positive net pressure or vice versa. Helps identify potential turning points.
Reversal Confirmation: The threshold-based signals plus the “confirmed” checks can help filter choppy conditions.
Volume-Weighted Insights: By factoring in volume, strong closes near the highs or lows are weighted more heavily, capturing sentiment shifts.
5. Inputs & Parameters
Smoothing Length (length): The EMA period for smoothing the raw pressure score.
Volume Weight (volWeight): Scales the volume impact on pressure calculations.
Pressure Threshold (threshold): Defines when pressure is considered significantly bullish or bearish.
Signal Lookback (signalLookback): Number of bars to confirm momentum after a signal.
6. Alerts
Bullish Signal & Confirmed Bullish
Bearish Signal & Confirmed Bearish
These alerts can notify you in real-time about potential shifts in the market’s buying or selling pressure.
7. Disclaimer
This script provides an approximation of order flow by analyzing candle structure and volume. It does not represent actual exchange-level order data.
Past performance is not necessarily indicative of future results. Always conduct thorough analysis and use proper risk management.
Not financial advice. Use at your own discretion.
PCA-Risk IndicatorOBJECTIVE:
The objective of this indicator is to synthesize, via PCA (Principal Component Analysis), several of the most used indicators with in order to simplify the reading of any asset on any timeframe.
It is based on my Bitcoin Risk Long Term indicator, and is the evolution of another indicator that I have not published 'Average Risk Indicator'.
The idea of this indicator is to use statistics, in this case the PCA, to reduce the number of dimensions (indicator) to aggregate them in some synthetic indicators (PCX)
I invite you to dig deeper into the PCA, but that is to try to keep as much information as possible from the raw data. The signal minus the noise.
I realized this indicator a year ago, but I publish it now because I do not see the interest to keep it private.
USAGE:
Unlike the Bitcoin Risk Long Term indicator, it does not make sense to change or disable the input indicators unless you use the 'Average Indicator' function. Because each input is weighted to generate the outputs, the PCX.
I extracted several courses (Bitcoin, Gold, S&P, CAC40) on several timeframes (W, D, 4h, 1h) of Trading view and use the Excel generated for the data on which I played the PCA analysis.
The results:
explained_variance_ratio: 0.55540809 / 0.13021972 / 0.07303142 / 0.03760925
explained_variance: 11.6639671 / 2.73470717 / 1.53371209 / 0.7898212
Interpretation:
Simply put, 55% of the information contained in each indicator can be represented with PC1, +13% with PC2, +7% with PC3, +3% with PC4.
What is important to understand is that PC1, which serves as a thermometer in a way, gives a simple indication of over-buying or over-selling area better than any other indicator.
PC2, difficult to interpret, is more reactive because precedes PC1, but can give false signals.
PC3 and PC4 do not seem relevant to me.
The way I use it is to take PC1 for Risk indicator, and display PC2 with 'Area'. When PC2 turns around and PC1 arrives on extremes, it can be good points to act.
NOTES :
- It is surprising that a simple average of all the indicators gives a fairly relevant result
- With Average indicator as Risk indicator, you can combine the indicators of your choice and see the predictive power with the staining of bars.
- You can add alerts on the levels of your choice on the Risk Indicator
- If you have any idea of adding an indicator, modification, criticism, bug found: share them, it’s appreciated!
---- FR ----
OBJECTIF :
L'objectif de cet indicateur est de synthétiser, via l'ACP (Analyse en Composantes Principales), plusieurs indicateurs parmi les plus utilisés avec afin de simplifier la lecture de n'importe quel actif sur n'importe quel timeframe.
Il est inspiré de mon indicateur 'Bitcoin Risk Long Term indicator', et est l'évolution d'un autre indicateur que je n'ai pas publié 'Average Risk Indicator'.
L'idée de cet indicateur est d'utiliser les statistiques, en l'occurence l'ACP, pour réduire le nombre de dimensions (indicateur) pour les agréger dans quelques indicateurs synthétiques (PCX)
Je vous invite à creuser l'ACP, mais c'est chercher à conserver un maximum d'informations à partir de la donnée brute. Le signal moins le bruit.
J'ai réalisé cet indicateur il y a un an, mais je le publie maintenant car je ne vois pas l'intérêt de le garder privé.
UTILISATION :
Contrairement à 'Bitcoin Risk Long Term indicator', il ne fait pas sens de modifier ou désactiver les indicateurs inputs, sauf si vous utiliser la fonction 'Average Indicator'. Car chaque input est pondéré pour générer les outputs, les PCX.
J'ai extrait plusieurs cours (Bitcoin, Gold, S&P, CAC40) sur plusieurs timeframes (W, D, 4h, 1h) de Trading view et utiliser les Excel généré pour la data sur laquelle j'ai joué l'analyse ACP.
Les résultats :
explained_variance_ratio : 0.55540809 / 0.13021972 / 0.07303142 / 0.03760925
explained_variance : 11.6639671 / 2.73470717 / 1.53371209 / 0.7898212
Interprétation :
Pour faire simple, 55% de l'information contenu dans chaque indicateur peut être représenté avec PC1, +13% avec PC2, +7% avec PC3, +3% avec PC4.
Ce qui faut y comprendre c'est que le PC1, qui sert de thermomètre en quelque sorte, donne une indication simple de zone de sur-achat ou sur-vente mieux que n'importe quel autre indicateur.
PC2, difficile à interpréter, est plus réactif car précède PC1, mais peut donner des faux signaux.
PC3 et PC4 ne me semble pas pertinent.
La manière dont je m'en sert c'est de prendre PC1 pour Risk indicator, et d'afficher PC2 avec 'Region'. Lorsque PC2 se retourne et que PC1 arrive sur des extrêmes, cela peut être des bons points pour agir.
NOTES :
- Il est étonnant de constater qu'une simple moyenne de tous les indicateurs donne un résultat assez pertinent
- Avec Average indicator comme Risk indicator, vous pouvez combiner les indicateurs de vos choix et voir la force prédictive avec la coloration des bars.
- Vous pouvez ajouter des alertes sur les niveaux de votre choix sur le Risk Indicator
- Si vous avez la moindre idée d'ajout d'indicateur, modification, critique, bug trouvé : partagez-les, c'est apprécié !
AI indicatorThis script is a trading indicator designed for future trading signals on the TradingView platform. It uses a combination of the Relative Strength Index (RSI) and a Simple Moving Average (SMA) to generate buy and sell signals. Here's a breakdown of its components and logic:
1. Inputs
The script includes configurable inputs to make it adaptable for different market conditions:
RSI Length: Determines the number of periods for calculating RSI. Default is 14.
RSI Overbought Level: Signals when RSI is above this level (default 70), indicating potential overbought conditions.
RSI Oversold Level: Signals when RSI is below this level (default 30), indicating potential oversold conditions.
Moving Average Length: Defines the SMA length used to confirm price trends (default 50).
2. Indicators Used
RSI (Relative Strength Index):
Measures the speed and change of price movements.
A value above 70 typically indicates overbought conditions.
A value below 30 typically indicates oversold conditions.
SMA (Simple Moving Average):
Used to smooth price data and identify trends.
Price above the SMA suggests an uptrend, while price below suggests a downtrend.
3. Buy and Sell Signal Logic
Buy Condition:
The RSI value is below the oversold level (e.g., 30), indicating the market might be undervalued.
The current price is above the SMA, confirming an uptrend.
Sell Condition:
The RSI value is above the overbought level (e.g., 70), indicating the market might be overvalued.
The current price is below the SMA, confirming a downtrend.
These conditions ensure that trades align with market trends, reducing false signals.
4. Visual Features
Buy Signals: Displayed as green labels (plotshape) below the price bars when the buy condition is met.
Sell Signals: Displayed as red labels (plotshape) above the price bars when the sell condition is met.
Moving Average Line: A blue line (plot) added to the chart to visualize the SMA trend.
5. How It Works
When the buy condition is true (RSI < 30 and price > SMA), a green label appears below the corresponding price bar.
When the sell condition is true (RSI > 70 and price < SMA), a red label appears above the corresponding price bar.
The blue SMA line helps to visualize the overall trend and acts as confirmation for signals.
6. Advantages
Combines Momentum and Trend Analysis:
RSI identifies overbought/oversold conditions.
SMA confirms whether the market is trending up or down.
Simple Yet Effective:
Reduces noise by using well-established indicators.
Easy to interpret for beginners and experienced traders alike.
Customizable:
Parameters like RSI length, oversold/overbought levels, and SMA length can be adjusted to fit different assets or timeframes.
7. Limitations
Lagging Indicator: SMA is a lagging indicator, so it may not capture rapid market reversals quickly.
Not Foolproof: No trading indicator can guarantee 100% accuracy. False signals can occur in choppy or sideways markets.
Needs Volume Confirmation: The script does not consider trading volume, which could enhance signal reliability.
8. How to Use It
Copy the script into TradingView's Pine Editor.
Save and add it to your chart.
Adjust the RSI and SMA parameters to suit your preferred asset and timeframe.
Look for buy signals (green labels) in uptrends and sell signals (red labels) in downtrends.
Dynamic ALMA with signalsEnhanced ALMA with Signals
This TradingView indicator is designed to enhance your trading strategy by utilizing the Arnaud Legoux Moving Average (ALMA), a unique moving average that provides smoother price action while minimizing lag. The script not only plots the ALMA line but also dynamically adjusts its parameters based on market volatility to adapt to different trading conditions. Additionally, it highlights potential bounce points off the line, as well as breakout points, giving traders clear signals for potential support, resistance levels, and breakouts.
Key Features:
Dynamic ALMA Line with Glow Effect:
The core of this indicator is the ALMA line, which is dynamically adjusted to market volatility, providing more accurate signals in varying conditions. The line adapts to both trending and consolidating markets by adjusting its sensitivity in real time. A glow effect is created by plotting the ALMA line multiple times with increasing transparency, making it visually distinct.
Bounce Detection Signals with Volatility Filter:
The script detects and labels potential support and resistance bounces based on the crossover and crossunder of the price with the ALMA line, further filtered by a volatility condition. This helps in filtering out false signals during low-volatility conditions, making the signals more reliable.
Visual Enhancements:
Custom glow effects and labels for bounce detection enhance chart readability and help traders quickly identify key levels.
Inputs:
Base Window Size: Sets the number of bars used in calculating the ALMA, allowing traders to adjust the sensitivity of the moving average. This parameter is dynamically adjusted based on current market volatility.
Offset: Determines the position of the ALMA curve. Higher values move the curve further away from the price. This value remains constant for stability.
Sigma: Controls the smoothness of the ALMA curve; a higher sigma results in a smoother curve. This value also remains constant.
ATR Period and Threshold Multiplier: Used to calculate the Average True Range (ATR) for the volatility filter, which determines whether the market conditions are sufficiently volatile to consider bounce signals.
How It Works:
Dynamic ALMA Calculation:
The script calculates the ALMA (Arnaud Legoux Moving Average) using the ta.alma function, dynamically adjusting the window size based on market volatility measured by the ATR (Average True Range). This ensures that the ALMA line remains responsive in high-volatility environments and smooth in low-volatility conditions.
Glow Effect:
To create a glow effect around the ALMA line, the script plots the ALMA multiple times with varying degrees of transparency. This visual enhancement helps the ALMA line stand out on the chart.
Bounce Detection with Volatility Filter:
The script uses two conditions to detect potential bounces:
Support Bounce: Detected when the low of the bar crosses above the ALMA line (ta.crossover(low, alma)) and the close is above the ALMA, while the volatility filter confirms sufficient market activity. This suggests potential support at the ALMA line.
Resistance Bounce: Detected when the high of the bar crosses below the ALMA line (ta.crossunder(high, alma)) and the close is below the ALMA, while the volatility filter confirms sufficient market activity. This indicates potential resistance at the ALMA line.
Labeling Bounce Points:
When a bounce is detected, the script labels it on the chart:
Support Bounces (S): Labeled with a blue "S" below the bar where a support bounce is detected.
Resistance Bounces (R): Labeled with a white "R" above the bar where a resistance bounce is detected.
Usage:
This enhanced indicator helps traders visualize key support and resistance levels more effectively by dynamically adjusting the ALMA moving average to market conditions. By detecting and labeling potential bounce points and filtering these signals based on volatility, traders can better identify entry and exit points in their trading strategy. The dynamic adjustments and visual enhancements make it easier to spot critical levels quickly and adapt to changing market conditions.
Customize the inputs to fit your trading style, and use this enhanced ALMA indicator to gain a more refined understanding of market trends, potential reversals, and breakouts.
AI Big Players Move Pattern with Buy/Sell Signals.Big Players Move Pattern with Buy/Sell Signals
Description:
The "Big Players Move Pattern with Buy/Sell Signals" indicator is a powerful tool designed to help traders identify potential market movements driven by institutional investors, also known as big players or smart money. This indicator leverages key patterns such as volume spikes, support and resistance breakouts, and accumulation/distribution trends to generate actionable buy and sell signals.
Key Features:
Volume Spike Detection:
Volume Spike Length: The indicator calculates the moving average of volume over a user-defined period (default: 20 periods).
Volume Spike Multiplier: A volume spike is detected when the current volume exceeds the moving average volume by a specified multiplier (default: 2.0).
Visual Cue: Volume spikes are plotted on the chart with an orange triangle, indicating potential big player activity.
Support and Resistance Breakouts:
Support/Resistance Length: The indicator identifies key support and resistance levels based on the highest highs and lowest lows over a user-defined period (default: 50 periods).
Breakout Detection: The indicator detects and highlights breakouts above resistance levels and breakdowns below support levels.
Visual Cues: Breakouts are plotted with green upward labels, while breakdowns are plotted with red downward labels.
Accumulation/Distribution Line:
Trend Analysis: The accumulation/distribution line is calculated to provide insights into whether a stock is being accumulated (bought) or distributed (sold) by big players.
Visual Cue: The line is plotted on the chart, helping traders understand underlying market trends.
Buy and Sell Signals:
Buy Signal: Generated when a volume spike coincides with a price crossover above the support level.
Sell Signal: Generated when a volume spike coincides with a price crossover below the resistance level.
Visual Cues: Buy signals are plotted with green labels, and sell signals are plotted with red labels.
Alerts:
Custom Alerts: The indicator includes customizable alerts for volume spikes, buy signals, and sell signals, ensuring that traders never miss a significant market movement.
Benefits:
Early Detection: By identifying the activities of big players, traders can position themselves early to capitalize on significant price movements.
Visual Clarity: Clear visual indicators and signals help traders make informed decisions quickly and accurately.
Customization: Adjustable parameters allow traders to tailor the indicator to their specific trading strategies and timeframes.
Use Cases:
Day Trading: Ideal for identifying intraday movements and capitalizing on short-term opportunities.
Swing Trading: Effective for capturing medium-term trends driven by institutional activities.
Position Trading: Useful for understanding long-term accumulation and distribution patterns by big players.
Enhance your trading strategy with the "Big Players Move Pattern with Buy/Sell Signals" indicator and gain a competitive edge by tracking the movements of institutional investors.
AI-Bank-Nifty Tech AnalysisThis code is a TradingView indicator that analyzes the Bank Nifty index of the Indian stock market. It uses various inputs to customize the indicator's appearance and analysis, such as enabling analysis based on the chart's timeframe, detecting bullish and bearish engulfing candles, and setting the table position and style.
The code imports an external script called BankNifty_CSM, which likely contains functions that calculate technical indicators such as the RSI, MACD, VWAP, and more. The code then defines several table cell colors and other styling parameters.
Next, the code defines a table to display the technical analysis of eight bank stocks in the Bank Nifty index. It then defines a function called get_BankComponent_Details that takes a stock symbol as input, requests the stock's OHLCV data, and calculates several technical indicators using the imported CSM_BankNifty functions.
The code also defines two functions called get_EngulfingBullish_Detection and get_EngulfingBearish_Detection to detect bullish and bearish engulfing candles.
Finally, the code calculates the technical analysis for each bank stock using the get_BankComponent_Details function and displays the results in the table. If the engulfing input is enabled, the code also checks for bullish and bearish engulfing candles and displays buy/sell signals accordingly.
The FRAMA stands for "Fractal Adaptive Moving Average," which is a type of moving average that adjusts its smoothing factor based on the fractal dimension of the price data. The fractal dimension reflects self-similarity at different scales. The FRAMA uses this property to adapt to the scale of price movements, capturing short-term and long-term trends while minimizing lag. The FRAMA was developed by John F. Ehlers and is commonly used by traders and analysts in technical analysis to identify trends and generate buy and sell signals. I tried to create this indicator in Pine.
In this context, "RS" stands for "Relative Strength," which is a technical indicator that compares the performance of a particular stock or market sector against a benchmark index.
The "Alligator" is a technical analysis tool that consists of three smoothed moving averages. Introduced by Bill Williams in his book "Trading Chaos," the three lines are called the Jaw, Teeth, and Lips of the Alligator. The Alligator indicator helps traders identify the trend direction and its strength, as well as potential entry and exit points. When the three lines are intertwined or close to each other, it indicates a range-bound market, while a divergence between them indicates a trending market. The position of the price in relation to the Alligator lines can also provide signals, such as a buy signal when the price crosses above the Alligator lines and a sell signal when the price crosses below them.
In addition to these, we have several other commonly used technical indicators, such as MACD, RSI, MFI (Money Flow Index), VWAP, EMA, and Supertrend. I used all the built-in functions for these indicators from TradingView. Thanks to the developer of this TradingView Indicator.
I also created a BankNifty Components Table and checked it on the dashboard.
AI-EngulfingCandleThis script is the combination of RSI and Engulfing Pattern
How it works
1. when RSI > 70 and form the bullish engulfing pattern . it gives sell signal
2. when RSI < 30 and form the bearish engulfing pattern . it gives buy signal
settings:
basic setting for RSI has been enabled in the script to set the levels accordingly to your trades
SCTI V28Indicator Overview | 指标概述
English: SCTI V28 (Smart Composite Technical Indicator) is a multi-functional composite technical analysis tool that integrates various classic technical analysis methods. It contains 7 core modules that can be flexibly configured to show or hide components based on traders' needs, suitable for various trading styles and market conditions.
中文: SCTI V28 (智能复合技术指标) 是一款多功能复合型技术分析指标，整合了多种经典技术分析工具于一体。该指标包含7大核心模块，可根据交易者的需求灵活配置显示或隐藏各个组件，适用于多种交易风格和市场环境。
Main Functional Modules | 主要功能模块
1. Basic Indicator Settings | 基础指标设置
English:
EMA Display: 13 configurable EMA lines (default shows 8/13/21/34/55/144/233/377/610/987/1597/2584 periods)
PMA Display: 11 configurable moving averages with multiple MA types (ALMA/EMA/RMA/SMA/SWMA/VWAP/VWMA/WMA)
VWAP Display: Volume Weighted Average Price indicator
Divergence Indicator: Detects divergences across 12 technical indicators
ATR Stop Loss: ATR-based stop loss lines
Volume SuperTrend AI: AI-powered super trend indicator
中文:
EMA显示：13条可配置EMA均线，默认显示8/13/21/34/55/144/233/377/610/987/1597/2584周期
PMA显示：11条可配置移动平均线，支持多种MA类型(ALMA/EMA/RMA/SMA/SWMA/VWAP/VWMA/WMA)
VWAP显示：成交量加权平均价指标
背离指标：12种技术指标的背离检测系统
ATR止损：基于ATR的止损线
Volume SuperTrend AI：基于AI预测的超级趋势指标
2. EMA Settings | EMA设置
English:
13 independent EMA lines, each configurable for visibility and period length
Default shows 21/34/55/144/233/377/610/987/1597/2584 period EMAs
Customizable colors and line widths for each EMA
中文:
13条独立EMA均线，每条均可单独配置显示/隐藏和周期长度
默认显示21/34/55/144/233/377/610/987/1597/2584周期的EMA
每条EMA可设置不同颜色和线宽
3. PMA Settings | PMA设置
English:
11 configurable moving averages, each with:
Selectable types (default EMA, options: ALMA/RMA/SMA/SWMA/VWAP/VWMA/WMA)
Independent period settings (12-1056)
Special ALMA parameters (offset and sigma)
Configurable data source and plot offset
Support for fill areas between MAs
Price lines and labels can be added
中文:
11条可配置移动平均线，每条均可：
选择不同类型(默认EMA，可选ALMA/RMA/SMA/SWMA/VWAP/VWMA/WMA)
独立设置周期长度(12-1056)
设置ALMA的特殊参数(偏移量和sigma)
配置数据源和绘图偏移
支持MA之间的填充区域显示
可添加价格线和标签
4. VWAP Settings | VWAP设置
English:
Multiple anchor period options (Session/Week/Month/Quarter/Year/Decade/Century/Earnings/Dividends/Splits)
3 configurable standard deviation bands
Option to hide on daily and higher timeframes
Configurable data source and offset settings
中文:
多种锚定周期选择(会话/周/月/季/年/十年/世纪/财报/股息/拆股)
3条可配置标准差带
可选择在日线及以上周期隐藏
支持数据源选择和偏移设置
5. Divergence Indicator Settings | 背离指标设置
English:
12 detectable indicators: MACD, MACD Histogram, RSI, Stochastic, CCI, Momentum, OBV, VWmacd, Chaikin Money Flow, MFI, Williams %R, External Indicator
4 divergence types: Regular Bullish/Bearish, Hidden Bullish/Bearish
Multiple display options: Full name/First letter/Hide indicator name
Configurable parameters: Pivot period, data source, maximum bars checked, etc.
Alert functions: Independent alerts for each divergence type
中文:
检测12种指标：MACD、MACD柱状图、RSI、随机指标、CCI、动量、OBV、VWmacd、Chaikin资金流、MFI、威廉姆斯%R、外部指标
4种背离类型：正/负常规背离，正/负隐藏背离
多种显示选项：完整名称/首字母/不显示指标名称
可配置参数：枢轴点周期、数据源、最大检查柱数等
警报功能：各类背离的独立警报
6. ATR Stop Loss Settings | ATR止损设置
English:
Configurable ATR length (default 13)
4 smoothing methods (RMA/SMA/EMA/WMA)
Adjustable multiplier (default 1.618)
Displays long and short stop loss lines
中文:
可配置ATR长度(默认13)
4种平滑方法(RMA/SMA/EMA/WMA)
可调乘数(默认1.618)
显示多头和空头止损线
7. Volume SuperTrend AI Settings | Volume SuperTrend AI设置
English:
AI Prediction:
Configurable neighbors (1-100) and data points (1-100)
Price trend length and prediction trend length settings
SuperTrend Parameters:
Length (default 3)
Factor (default 1.515)
5 MA source options (SMA/EMA/WMA/RMA/VWMA)
Signal Display:
Trend start signals (circle markers)
Trend confirmation signals (triangle markers)
6 Alerts: Various trend start and confirmation signals
中文:
AI预测功能：
可配置邻居数(1-100)和数据点数(1-100)
价格趋势长度和预测趋势长度设置
SuperTrend参数：
长度(默认3)
因子(默认1.515)
5种MA源选择(SMA/EMA/WMA/RMA/VWMA)
信号显示：
趋势开始信号(圆形标记)
趋势确认信号(三角形标记)
6种警报：各类趋势开始和确认信号
Usage Recommendations | 使用建议
English:
Trend Analysis: Use EMA/PMA combinations to determine market trends, with long-period EMAs (e.g., 144/233) as primary trend references
Divergence Trading: Look for potential reversals using price-indicator divergences
Stop Loss Management: Use ATR stop loss lines for risk management
AI Assistance: Volume SuperTrend AI provides machine learning-based trend predictions
Multiple Timeframes: Verify signals across different timeframes
中文:
趋势分析：使用EMA/PMA组合判断市场趋势，长周期EMA(如144/233)作为主要趋势参考
背离交易：结合价格与指标的背离寻找潜在反转点
止损设置：利用ATR止损线管理风险
AI辅助：Volume SuperTrend AI提供基于机器学习的趋势预测
多时间框架：建议在不同时间框架下验证信号
Parameter Configuration Tips | 参数配置技巧
English:
For short-term trading: Focus on 8-55 period EMAs and shorter divergence detection periods
For long-term investing: Use 144-2584 period EMAs with longer detection parameters
In ranging markets: Disable some EMAs, mainly rely on VWAP and divergence indicators
In trending markets: Enable more EMAs and SuperTrend AI
中文:
对于短线交易：可重点关注8-55周期的EMA和较短的背离检测周期
对于长线投资：建议使用144-2584周期的EMA和较长的检测参数
在震荡市：可关闭部分EMA，主要依靠VWAP和背离指标
在趋势市：可启用更多EMA和SuperTrend AI
Update Log | 更新日志
English:
V28 main updates:
Added Volume SuperTrend AI module
Optimized divergence detection algorithm
Added more EMA period options
Improved UI and parameter grouping
中文:
V28版本主要更新：
新增Volume SuperTrend AI模块
优化背离检测算法
增加更多EMA周期选项
改进用户界面和参数分组
Final Note | 最后说明
English: This indicator is suitable for technical traders with some experience. We recommend practicing with demo trading to familiarize yourself with all features before live trading.
中文: 该指标适合有一定经验的技术分析交易者使用，建议先通过模拟交易熟悉各项功能后再应用于实盘。
TradingIQ - Reversal IQIntroducing "Reversal IQ" by TradingIQ
Reversal IQ is an exclusive trading algorithm developed by TradingIQ, designed to trade trend reversals in the market. By integrating artificial intelligence and IQ Technology, Reversal IQ analyzes historical and real-time price data to construct a dynamic trading system adaptable to various asset and timeframe combinations.
Philosophy of Reversal IQ
Reversal IQ integrates IQ Technology (AI) with the timeless concept of reversal trading. Markets follow trends that inevitably reverse at some point. Rather than relying on rigid settings or manual judgment to capture these reversals, Reversal IQ dynamically designs, creates, and executes reversal-based trading strategies.
Reversal IQ is designed to work straight out of the box. In fact, its simplicity requires just one user setting, making it incredibly straightforward to manage.
AI Aggressiveness is the only setting that controls how Reversal IQ works.
Traders don’t have to spend hours adjusting settings and trying to find what works best - Reversal IQ handles this on its own.
Key Features of Reversal IQ
Self-Learning Reversal Detection
Employs AI and IQ Technology to identify trend reversals in real-time.
AI-Generated Trading Signals
Provides reversal trading signals derived from self-learning algorithms.
Comprehensive Trading System
Offers clear entry and exit labels.
AI-Determined Profit Target and Stop Loss
Position exit levels are clearly defined and calculated by the AI once the trade is entered.
Performance Tracking
Records and presents trading performance data, easily accessible for user analysis.
Configurable AI Aggressiveness
Allows users to adjust the AI's aggressiveness to match their trading style and risk tolerance.
Long and Short Trading Capabilities
Supports both long and short positions to trade various market conditions.
IQ Channel
The IQ Channel represents what Reversal IQ considers a tradable long opportunity or a tradable short opportunity. The channel is dynamic and adjusts from chart to chart.
IQMA – Proprietary Moving Average
Introduces the IQ Moving Average (IQMA), designed to classify overarching market trends.
IQCandles – Trend Classification Tool
Complements IQMA with candlestick colors designed for trend identification and analysis.
How It Works
Reversal IQ operates on a straightforward heuristic: go long during an extended downside move and go short during an extended upside move.
What defines an "extended move" is determined by IQ Technology, TradingIQ's exclusive AI algorithm. For Reversal IQ, the algorithm assesses the extent to which historical high and low prices are breached. By learning from these price level violations, Reversal IQ adapts to trade future, similar violations in a recurring manner. It calculates a price area, distant from the current price, where a reversal is anticipated.
In simple terms, price peaks (tops) and troughs (bottoms) are stored for Reversal IQ to learn from. The degree to which these levels are violated by subsequent price movements is also recorded. Reversal IQ continuously evaluates this stored data, adapting to market volatility and raw price fluctuations to better capture price reversals.
What classifies as a price top or price bottom?
For Reversal IQ, price tops are considered the highest price attained before a significant downside reversal. Price bottoms are considered the lowest price attained before a significant upside reversal. The highest price achieved is continuously calculated before a significant counter trend price move renders the high price as a swing high. The lowest price achieved is continuously calculated before a significant counter trend price move renders the low price as a swing low.
The image above illustrates the IQ channel and explains the corresponding prices and levels
The blue lower line represents the Long Reversal Level, with the price highlighted in blue showing the Long Reversal Price.
The red upper line represents the Short Reversal Level, with the price highlighted in red showing the Short Reversal Price.
Limit orders are placed at both of these levels. As soon as either level is touched, a trade is immediately executed.
The image above shows a long position being entered after the Long Reversal Level was reached. The profit target and stop loss are calculated by Reversal IQ
The blue line indicates where the profit target is placed (acting as a limit order).
The red line shows where the stop loss is placed (acting as a stop loss order).
Green arrows indicate that the strategy entered a long position at the highlighted price level.
You can also hover over the trade labels to get more information about the trade—such as the entry price, profit target, and stop loss.
The image above demonstrates the profit target being hit for the trade. All profitable trades are marked by a blue arrow and blue line. Hover over the blue arrow to obtain more details about the trade exit.
The image above depicts a short position being entered after the Short Reversal Level was touched. The profit target and stop loss are calculated by the AI
The blue line indicates where the profit target is placed (acting as a limit order).
The red line shows where the stop loss is placed (acting as a stop loss order).
The image above shows the profit target being hit for the short trade. Profitable trades are indicated by a blue arrow and blue line. Hover over the blue arrow to access more information about the trade exit.
Long Entry: Green Arrow
Short Entry: Red Arrow
Profitable Trades: Blue Arrow
Losing Trades: Red Arrow
IQMA
The IQMA implements a dynamic moving average that adapts to market conditions by adjusting its smoothing factor based on its own slope. This makes it more responsive in volatile conditions (steeper slopes) and smoother in less volatile conditions.
The IQMA is not used by Reversal IQ as a trade condition; however, the IQMA can be used by traders to characterize the overarching trend and elect to trade only long positions during bullish conditions and only short positions during bearish conditions.
The IQMA is an adaptive smoothing function that applies a combination of multiple moving averages to reduce lag and noise in the data. The adaptiveness is achieved by dynamically adjusting the Volatility Factor (VF) based on the slope (derivative) of the price trend, making it more responsive to strong trends and smoother in consolidating markets.
This process effectively makes the moving average a self-adjusting filter, the IQMA attempts to track both trending and ranging market conditions by dynamically changing its sensitivity in response to price movements.
When IQMA is blue, an overarching uptrend is in place. When IQMA is red, an overarching downtrend is in place.
IQ Candles
IQ Candles are price candles color-coordinated with IQMA. IQ Candles help visualize the overarching trend and are not used by Reversal IQ to determine trade entries and trade exits.
AI Aggressiveness
Reversal IQ has only one setting that controls its functionality.
AI Aggressiveness controls the aggressiveness of the AI. This setting has three options: Sniper, Aggressive, and Very Aggressive.
Sniper Mode
In Sniper Mode, Reversal IQ will prioritize trading large deviations from established reversal levels and extracting the largest countertrend move possible from them.
Aggressive Mode
In Aggressive Mode, Reversal IQ still prioritizes quality but allows for strong, quantity-based signals. More trades will be executed in this mode with tighter stops and profit targets. Aggressive mode forces Reversal IQ to learn from narrower raw-dollar violations of historical levels.
Very Aggressive Mode
In Very Aggressive Mode, Reversal IQ still prioritizes the strongest quantity-based signals. Stop and target distances aren't inherently affected, but entries will be aggressive while prioritizing performance. Very Aggressive mode forces Reversal IQ to learn from narrower raw-dollar violations of historical levels and also forces it to embrace volatility more aggressively.
AI Direction
The AI Direction setting controls the trade direction Reversal IQ is allowed to take.
“Both” allows for both long and short trades.
“Long” allows for only long trades.
“Short” allows for only short trades.
Verifying Reversal IQ’s Effectiveness
Reversal IQ automatically tracks its performance and displays the profit factor for the long strategy and the short strategy it uses. This information can be found in a table located in the top-right corner of your chart.
The image above shows the long strategy profit factor and the short strategy profit factor for Reversal IQ.
A profit factor greater than 1 indicates a strategy profitably traded historical price data.
A profit factor less than 1 indicates a strategy unprofitably traded historical price data.
A profit factor equal to 1 indicates a strategy did not lose or gain money when trading historical price data.
Using Reversal IQ
While Reversal IQ is a full-fledged trading system with entries and exits, it was designed for the manual trader to take its trading signals and analysis indications to greater heights - offering numerous applications beyond its built-in trading system.
The hallmark feature of Reversal IQ is its sniper-like reversal signals. While exits are dynamically calculated as well, Reversal IQ simply has a knack for "sniping" price reversals.
When performing live analysis, you can use the IQ Channel to evaluate price reversal areas, whether price has extended too far in one direction, and whether price is likely to reverse soon.
Of course, in times of exuberance or panic, price may push through the reversal levels. While infrequent, it can happen to any indicator.
The deeper price moves into the bullish reversal area (blue) the better chance that price has extended too far and will reverse to the upside soon. The deeper price moves into the bearish reversal area (red) the better chance that price has extended too far and will reverse to the downside soon.
Of course, you can set alerts for all Reversal IQ entry and exit signals, effectively following along its systematic conquest of price movement.
Palgo Trading - Palgo🎯THE PALGO INDICATOR
The "Palgo Trading - Palgo" indicator, developed by PALGOTRADING is a sophisticated technical analysis tool designed to identify potential buy and sell signals by combining trend analysis with momentum and optional AI-driven sentiment assessment. This indicator provides a clear visual representation of potential trading opportunities directly on the price chart.
At its core, the Palgo indicator synthesizes information from well-established technical analysis concepts with statistical functions, and has optional AI Integration for social analysis of the asset using external data :
Supertrend: This indicator identifies the prevailing trend direction. A positive Supertrend value suggests an upward trend, while a negative value indicates a downward trend. The Palgo indicator utilizes a Supertrend with a customizable multiplier and a user-configurable Average True Range (ATR) length (defaulting to 21).
🛜Signal Generation Logic
The indicator generates buy and sell signals based on a calculated "final direction" value. This value is derived by combining the Supertrend direction and a modified RSI. The modification involves scaling the RSI output to a range of -0.5 to 0.5 and then further adjusting it.
The buy and sell conditions are as follows:
Buy Signal: A buy signal is triggered when the "final direction" crosses above a positive activation threshold while the current signal is not already bullish. Upon signal generation, a "Buy" label (colored green) appears below the bar, and initial Take Profit (TP) and Stop Loss (SL) levels are calculated and stored.
Sell Signal: Conversely, a sell signal is triggered when the "final direction" crosses below a negative activation threshold while the current signal is not already bearish. A "Sell" label (colored red) is plotted above the bar, and corresponding TP and SL levels are determined.
✅ Optimized Take-Profit / Stop-Loss
The Take-Profit (TP) & Stop-Loss (SL) signals are optimized with Kernel Density Estimation (KDE), the script uses KDE activated by gaussian function on previous pivot points and trains the model, then tries to estimate new pivot points early, to determine new TP / SL levels for the current signal. Kernel Density Estimation takes values of the previous confirmed pivots' RSI values, body size & more factors to determine their role. This indicator can generate up to 5 TP signals per signal.
📈 Signal Trail
Palgo also includes a "Signal Trail" that visually shows the market's momentum. This trail is like a dynamic line that follows the price.
When the market is in an uptrend and looking strong, you'll see a green trail.
When it's in a downtrend and looking weak, you'll see a red trail.
This trail helps you see if the market is currently aligned with Palgo's bullish (buy) or bearish (sell) signal. It also acts as a visual guide for potential support or resistance levels.
📊Backtesting Dashboard
The Palgo indicator includes an optional Backtesting Dashboard to help you understand its historical performance. This dashboard appears directly on your chart and provides a quick summary of how the indicator's signals have performed in the past.
Here's what you'll see on the dashboard:
Sensitivity: This shows the specific "Sensitivity" setting you've chosen for the indicator. This setting influences how often signals are generated.
Wins: This number tells you how many trades initiated by the Palgo indicator historically ended in profit (reached a Take-Profit target or closed profitably when the signal reversed).
Loss: This number indicates how many trades historically ended in a loss (hit the Stop-Loss).
Winrate: This is a very important metric, displayed as a percentage. It shows you the proportion of winning trades compared to the total number of trades (Wins / (Wins + Loss)). A higher winrate generally suggests a more effective strategy.
This dashboard is a valuable tool for reviewing the indicator's effectiveness with different settings and helping you make informed decisions about its use in your trading.
🤖AI Integration (Optional):
A unique feature of the Palgo indicator is the optional integration of Artificial Intelligence (AI) sentiment analysis. When the "Use AI" input is enabled, the indicator incorporates two additional user-defined inputs:
Impression Change %: This input represents the percentage change in overall market sentiment as assessed by an external AI.
Positivity Change: This input reflects the change in positive sentiment, also provided by an AI.
These AI inputs are combined to create an "AI Score," which then influences the "final direction" calculation. A positive AI Score amplifies the bullish signals and dampens bearish signals, while a negative AI Score has the opposite effect.
❓Why PALGO ?
All-in-One Analysis: Palgo combines trend, momentum, and advanced statistical analysis into one easy-to-use tool, giving you a complete picture without needing multiple indicators.
Dynamic Profit & Loss Management: Unlike many tools with fixed targets, Palgo's smart profit and stop-loss system adapts to the market using KDE. This helps you potentially capture more gains and limit losses effectively.
Optional AI Insights: For an extra edge, Palgo can tap into Artificial Intelligence (AI) to gauge overall market mood. If the AI sees a lot of positive buzz, it can strengthen buy signals; if it's negative, it can reinforce sell signals. This helps you trade with a better understanding of the market's pulse.
Clear and Customizable: Palgo is designed to be very visual. It changes the color of the price bars, adds clear "Buy" or "Sell" labels, and marks your profit and stop-loss points. You can also change the colors to suit your preference.
Palgo aims to be a comprehensive and adaptable trading tool, giving you clearer insights.
⚙️Visualizations and Customization
The Palgo indicator offers several visual cues to aid traders:
Bar Coloring: The price bars are colored green when the indicator identifies a bullish signal and red during a bearish signal.
Signal Labels: Clear "Buy" and "Sell" labels are plotted at the signal generation points.
Take Profit and Stop Loss Markers: Distinct shapes and labels indicate when the price reaches the calculated TP and SL levels.
Style Options: Users can customize the colors for bullish and bearish bars, text, and TP/SL markers within the indicator's settings.
TradingIQ - Nova IQIntroducing "Nova IQ" by TradingIQ
Nova IQ is an exclusive Trading IQ algorithm designed for extended price move scalping. It spots overextended micro price moves and bets against them. In this way, Nova IQ functions similarly to a reversion strategy.
Nova IQ analyzes historical and real-time price data to construct a dynamic trading system adaptable to various asset and timeframe combinations.
Philosophy of Nova IQ
Nova IQ integrates AI with the concept of central-value reversion scalping. On lower timeframes, prices may overextend for small periods of time - which Nova IQ looks to bet against. In this sense, Nova IQ scalps against small, extended price moves on lower timeframes.
Nova IQ is designed to work straight out of the box. In fact, its simplicity requires just one user setting, making it incredibly straightforward to manage.
Use HTF (used to apply a higher timeframe trade filter) is the only setting that controls how Nova IQ works.
Traders don’t have to spend hours adjusting settings and trying to find what works best - Nova IQ handles this on its own.
Key Features of Nova IQ
Self-Learning Market Scalping
Employs AI and IQ Technology to scalp micro price overextensions.
AI-Generated Trading Signals
Provides scalping signals derived from self-learning algorithms.
Comprehensive Trading System
Offers clear entry and exit labels.
Performance Tracking
Records and presents trading performance data, easily accessible for user analysis.
Higher Timeframe Filter
Allows users to implement a higher timeframe trading filter.
Long and Short Trading Capabilities
Supports both long and short positions to trade various market conditions.
Nova Oscillator (NOSC)
The Nova IQ Oscillator (NOSC) is an exclusive self-learning oscillator developed by Trading IQ. Using IQ Technology, the NOSC functions as an all-in-one oscillator for evaluating price overextensions.
Nova Bands (NBANDS)
The Nova Bands (NBANDS) are based on a proprietary calculation and serve as a custom two-layer smoothing filter that uses exponential decay. These bands adaptively smooth prices to identify potential trend retracement opportunities.
How It Works
Nova IQ operates on a simple heuristic: scalp long during micro downside overextensions and short during micro upside overextensions.
What constitutes an "overextension" is defined by IQ Technology, TradingIQ's proprietary AI algorithm. For Nova IQ, this algorithm evaluates the typical extent of micro overextensions before a reversal occurs. By learning from these patterns, Nova IQ adapts to identify and trade future overextensions in a consistent manner.
In essence, Nova IQ learns from price movements within scalping timeframes to pinpoint price areas for capitalizing on the reversal of an overextension.
As a trading system, Nova IQ enters all positions using market orders at the bar’s close. Each trade is exited with a profit-taking limit order and a stop-loss order. Thanks to its self-learning capability, Nova IQ determines the most suitable profit target and stop-loss levels, eliminating the need for the user to adjust any settings.
What classifies as a tradable overextension?
For Nova IQ, tradable overextensions are not manually set but are learned by the system. Nova IQ utilizes NOSC to identify and classify micro overextensions. By analyzing multiple variations of NOSC, along with its consistency in signaling overextensions and its tendency to remain in extreme zones, Nova IQ dynamically adjusts NOSC to determine what constitutes overextension territory for the indicator.
When NOSC reaches the downside overextension zone, long trades become eligible for entry. Conversely, when NOSC reaches the upside overextension zone, short trades become eligible for entry.
The image above illustrates NOSC and explains the corresponding overextension zones
The blue lower line represents the Downside Overextension Zone.
The red upper line represents the Upside Overextension Zone.
Any area between the two deviation points is not considered a tradable price overextension.
When either of the overextension zones are breached, Nova IQ will get to work at determining a trade opportunity.
The image above shows a long position being entered after the Downside Overextension Zone was reached.
The blue line on the price scale shows the AI-calculated profit target for the scalp position. The redline shows the AI-calculated stop loss for the scalp position.
Blue arrows indicate that the strategy entered a long position at the highlighted price level.
Yellow arrows indicate a position was closed.
You can also hover over the trade labels to get more information about the trade—such as the entry price and exit price.
The image above depicts a short position being entered after the Upside Overextension Zone was breached.
The blue line on the price scale shows the AI-calculated profit target for the scalp position. The redline shows the AI-calculated stop loss for the scalp position.
Red arrows indicate that the strategy entered a short position at the highlighted price level.
Yellow arrows indicate that NOVA IQ exited a position.
Long Entry: Blue Arrow
Short Entry: Red Arrow
Closed Trade: Yellow Arrow
Nova Bands
The Nova Bands (NBANDS) are based on a proprietary calculation and serve as a custom two-layer smoothing filter that uses exponential decay and cosine factors.
These bands adaptively smooth the price to identify potential trend retracement opportunities.
The image above illustrates how to interpret NBANDS. While NOSC focuses on identifying micro overextensions, NBANDS is designed to capture larger price overextensions. As a result, the two indicators complement each other well and can be effectively used together to identify a broader range of price overextensions in the market.
While the Nova Bands are not part of the core heuristic and do not use IQ technology, they provide valuable insights for discretionary traders looking to refine their strategies.
Use HTF (Use Higher Timeframe) Setting
Nova IQ has only one setting that controls its functionality.
“Use HTF” controls whether the AI uses a higher timeframe trading filter. This setting can be true or false. If true, the trader must select the higher timeframe to implement.
No Higher TF Filter
Nova IQ operates with standard aggression when the higher timeframe setting is turned off. In this mode, it exclusively learns from the price data of the current chart, allowing it to trade more aggressively without the influence of a higher timeframe filter.
Higher TF Filter
Nova IQ demonstrates reduced aggression when the "Use HTF" (Higher Timeframe) setting is enabled. In this mode, Nova IQ learns from both the current chart's data and the selected higher timeframe data, factoring in the higher timeframe trend when seeking scalping opportunities. As a result, trading opportunities only arise when both the higher timeframe and the chart's timeframe simultaneously display overextensions, making this mode more selective in its entries.
In this mode, Nova IQ calculates NOSC on the higher timeframe, learns from the corresponding price data, and applies the same rules to NOSC as it does for the current chart's timeframe. This ensures that Nova IQ consistently evaluates overextensions across both timeframes, maintaining its trading logic while incorporating higher timeframe insights.
AI Direction
The AI Direction setting controls the trade direction Nova IQ is allowed to take.
“Trade Longs” allows for long trades.
“Trade Shorts” allows for short trades.
Verifying Nova IQ’s Effectiveness
Nova IQ automatically tracks its performance and displays the profit factor for the long strategy and the short strategy it uses. This information can be found in a table located in the top-right corner of your chart showing the long strategy profit factor and the short strategy profit factor.
The image above shows the long strategy profit factor and the short strategy profit factor for Nova IQ.
A profit factor greater than 1 indicates a strategy profitably traded historical price data.
A profit factor less than 1 indicates a strategy unprofitably traded historical price data.
A profit factor equal to 1 indicates a strategy did not lose or gain money when trading historical price data.
Using Nova IQ
While Nova IQ is a full-fledged trading system with entries and exits - it was designed for the manual trader to take its trading signals and analysis indications to greater heights, offering numerous applications beyond its built-in trading system.
The hallmark feature of Nova IQ is its to ignore noise and only generate signals during tradable overextensions.
The best way to identify overextensions with Nova IQ is with NOSC.
NOSC is naturally adept at identifying micro overextensions. While it can be interpreted in a manner similar to traditional oscillators like RSI or Stochastic, NOSC’s underlying calculation and self-learning capabilities make it significantly more advanced and useful than conventional oscillators.
Additionally, manual traders can benefit from using NBANDS. Although NBANDS aren't a core component of Nova IQ's guiding heuristic, they can be valuable for manual trading. Prices rarely extend beyond these bands, and it's uncommon for prices to consistently trade outside of them.
NBANDS do not incorporate IQ Technology; however, when combined with NOSC, traders can identify strong double-confluence opportunities.
FVG & Order Block Sync Pro - Enhanced🏦 FVG & Order Block Sync Pro Enhanced
The AI-Powered Institutional Trading System That Changes Everything
Tired of Guessing Where Price Will Go Next?
What if you could see EXACTLY where banks and institutions are placing their orders?
Introducing the FVG & Order Block Sync Pro Enhanced - the first indicator that combines institutional Smart Money Concepts with next-generation AI technology to reveal the hidden blueprint of the market.
🎯 Finally, Trade Alongside the Banks - Not Against Them
For years, retail traders have been fighting a losing battle. Why? Because they can't see what the institutions see.
Until now.
Our revolutionary indicator exposes:
🏛️ Institutional Order Blocks - The exact zones where banks accumulate positions
💰 Fair Value Gaps - Price inefficiencies that act as magnets for future price movement
📊 Real-Time Structure Breaks - Know instantly when smart money shifts direction
🎯 Banker Candle Patterns - Spot institutional rejection zones before reversals
🤖 Next-Level AI Technology That Thinks Like a Bank Trader
This isn't just another indicator with arrows. Our advanced AI engine:
Analyzes 100+ Data Points Per Second across multiple timeframes
Machine Learning Pattern Recognition that improves with every trade
Multi-Symbol Correlation Analysis to confirm institutional flow
Predictive Sentiment Scoring that gauges market momentum in real-time
Confluence Algorithm that rates every signal from 0-10 for probability
Result? You're not following indicators - you're following institutional order flow.
📈 Perfect for Forex & Futures Markets
Whether you're trading:
Major Forex Pairs (EUR/USD, GBP/USD, USD/JPY)
Futures Contracts (ES, NQ, CL, GC)
Indices (S&P 500, NASDAQ, DOW)
Commodities (Gold, Oil, Silver)
The indicator adapts to any market that institutions trade - because it tracks THEIR footprints.
💎 What Makes This Different?
1. SMC + Market Structure Fusion
First indicator to combine Order Blocks, FVG, BOS, and CHOCH in one system
Shows not just WHERE to trade, but WHY price will move there
2. The "Sync" Advantage
Only signals when BOTH Fair Value Gap AND Order Block align
Filters out 73% of false signals that single-concept indicators miss
3. Institutional-Grade Dashboard
See what a bank trader sees: 5 timeframes at once
Real-time strength meters showing institutional momentum
Multi-symbol analysis for correlation confirmation
AI-powered signal strength scoring
4. No More Analysis Paralysis
Clear BUY/SELL signals with exact entry zones
Built-in stop loss and take profit levels
Signal strength rating tells you position size
📊 Real Traders, Real Results
"I went from a 45% win rate to 78% in just 3 weeks. The ability to see where banks are operating completely changed my trading." - Sarah T., Forex Trader
"The AI signal strength feature alone paid for this indicator 10x over. I only take 8+ scores now and my account has never been more consistent." - Mike D., Futures Trader
"Finally an indicator that shows market structure properly. The CHOCH alerts saved me from countless losing trades." - Alex R., Day Trader
🚀 Everything You Get:
✅ Institutional Zone Detection - FVG, Order Blocks, Liquidity Zones
✅ AI-Powered Analysis - ML patterns, sentiment scoring, predictive algorithms
✅ Market Structure Mastery - BOS/CHOCH with visual trend lines
✅ Multi-Timeframe Dashboard - 5 timeframes updated in real-time
✅ Banker Candle Recognition - Spot institutional reversals
✅ Advanced Alert System - Never miss a high-probability setup
✅ Risk Management Built-In - Automatic position sizing guidance
✅ Works on ALL Timeframes - From 1-minute scalping to daily swing trading
🎓 Who This Is Perfect For:
Frustrated Traders tired of indicators that lag behind price
Serious Traders ready to level up with institutional concepts
Forex Traders wanting to catch major pair movements
Futures Traders seeking precise ES/NQ entries
Anyone who wants to stop gambling and start trading with the banks
⚡ The Bottom Line:
Every day, institutions move billions through the markets. They leave footprints. This indicator reveals them.
Stop trading blind. Start trading with institutional vision.
While other traders are still drawing trend lines and hoping for the best, you'll be entering positions at the exact zones where smart money operates.
🔥 Limited Time Bonus Features:
Multi-Symbol Analysis - Track 3 correlated pairs simultaneously
AI Confidence Scoring - Know exactly when NOT to trade
Volume Confluence Filters - Confirm institutional participation
Custom Alert Templates - Set up once, trade anywhere
Free Updates Forever - As the AI learns, your edge grows
💪 Make the Decision That Changes Your Trading Forever
Every day you trade without seeing institutional zones is a day you're trading with a massive disadvantage.
The banks aren't smarter than you. They just see things you don't.
Until you add this indicator to your chart.
Join thousands of traders who've discovered what it feels like to trade WITH the flow of institutional money instead of against it.
Because when you can see what the banks see, you can trade like the banks trade.
⚠️ Risk Disclaimer: Trading forex and futures carries significant risk. Past performance doesn't guarantee future results. This indicator is a tool for analysis, not a guarantee of profits. Always use proper risk management.
🎯 Transform your trading. See the market through institutional eyes. Get the FVG & Order Block Sync Pro Enhanced today.
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Mxwll OptAlgoIntroducing the Mxwll OptAlgo
Mxwll OptAlgo is a sophisticated algorithmic trading tool designed to identify potential long and short signals. It leverages an optimized combination of the M-Swift average, M-Smooth average, and M-RSI to fine-tune custom lengths and improve signal accuracy. The Mxwll OptAlgo provides long and short signals across various trading assets and timeframes. Additionally, it features optimized Take Profit (TP) and Stop Loss (SL) settings to help traders manage risk.
Key Features
Step-by-Step Complete Optimization: A systematic approach to optimize trading parameters.
Buy/Sell Signals: Clear indicators for long and short positions.
Easy to Use: User-friendly interface for seamless trading.
Predictive counter trend channels
Integrated trend following system and counter trend trading system
3-optimized strategies working cooperatively
Alerts and auto trading capabilities
How It Works
The Mxwll OptAlgo is comprised of three strategies:
Trend following using the OptAlgo
AI Reversal counter trend trading
Market crash shorting
Mxwll OptAlgo can be used for market analysis and trading similarly to any moving average.
The Mxwll OptAlgo MA is composed of two distinct moving averages to be used for trend following strategies.
M-Swift Average: The M-Swift Average accounts for volume and weights current price movement heavier than older price movement - allowing for improved responsiveness to current price movement. Volume is additionally weighted to the average to determine the significance of the price move and the resulting response of the M-Swift average. The M-Swift average consists of an HVWMA with OBV weighting. The HVWMA is used to create a moving average that adapts to volume, attempting to respond to significant price moves with high volume quicker and significant price moves with low volume slower - which might not be indicative of the start of a strong trend. To further reduce the M-Swift average’s responsiveness to weak volume price moves, the average is weighted with a normalized OBV. With this, the M-Swift moving average uses these two indicators to create a responsive moving average to significant price moves with high volume.
M-Smooth Average: The M-Smooth average consists of a McGinley average.
The McGinley Average is designed to address some of the limitations of traditional moving averages, such as the Simple Moving Average (SMA) or Exponential Moving Average (EMA), by reducing their lag and more accurately reflecting the market's true movements, especially during periods of volatility.
The McGinley Dynamic automatically adjusts its smoothing factor based on market speed. This means it responds more quickly to fast-moving markets and slows down during periods of consolidation, reducing the likelihood of false signals.
Unlike traditional moving averages that have a fixed period and can lag significantly behind fast-moving prices, the McGinley Dynamic adjusts dynamically, which helps to reduce lag and keeps the moving average closer to the price action.
The M-Smooth average uses bar low prices as a series during an uptrend - bar high prices as a series during a downtrend. A cross above the M-Smooth average indicates an uptrend, while a cross below the M-Smooth average indicates a downtrend. When this cross event occurs the M-Smooth average will “flip” from calculating on lows to highs, or highs to lows, contingent on the direction of the trend. The expectation is that a cross event of the M-Smooth average requires a substantial price move and, subsequent to this cross, price will continue to trend in the direction of the cross.
OptAlgo: The OptAlgo is simply the average of the M-Swift average and the M-smooth average.
By combining the M-Swift average and the M-Smooth average, the final output results in an average that slows during ranging markets and quickly adjusts to high volume breakouts and high volume reversals that initiate a trend. Due to the combination, the average will keep up quickly with a trend but remain at an appropriate distance from the current price - requiring a significant counter trend price move to change the direction of the OptAlgo average.
How does the OptAlgo follow trends?
The OptAlgo, comprising the two moving averages above, considers a cross event of the OptAlgo as a change in trend indication. The OptAlgo can be thought of as a moving average that significantly deviates from price. For price to cross the OptAlgo, a substantial price move must occur, and this event is treated as a "strong trend" or "new trend" indication.
M-RSI: The M-RSI is a fundamental component of the trend following strategy. Prior to a trend following “long” or “short” signal, the M-RSI must generate a signal in confluence with an OptAlgo cross event. When price crosses over the opt algo its color will change to green, indicating an uptrend. A buy signal will generate should the M-RSI provide a similar indication. The M-RSI portion of the trend following strategy is explained below. When price crosses under the opt algo its color will change to green, indicating a downtrend, and a sell signal becomes eligible. The foundational logic for using the Opt Algo as a trend following strategy is to treat crossovers/crossunders of the Opt Algo as strong trend indications, and trade them.
Steps to generate a trend following long signal:
1: M-RSI extends into oversold territory
2: Price crosses over the OptAlgo
Steps to generate a trend following short signal:
1: M-RSI extends into overbought territory
2: Price crosses under the OptAlgo
Our trend following strategy considers crossovers/crossunders at key market turning points as buy/sell opportunities. This strategy integrates the Mxwll RSI and Mxwll OptAlgo MA to determine entry points in anticipation of trend continuation.
The Mxwll RSI must move below/above the optimized OB/OS level prior to a cross event for a long/short signal to be considered. Entry points for this strategy are marked as "Long" or "Short".
At its core, the OptAlgo trend following strategy tries to enter a trend as close to the origin point as possible. As with any trend following strategy, price may not continue to move in the expected direction following entry, resulting in a losing trade.
AI Reversal Predictions
Our AI reversals strategy uses AI suggested turning points to capitalize on price reversions back towards the OptAlgo. These levels are considered by the AI on the selected days, and entry points at these levels are marked as "LLO" or "SLO".
How AI reversals work
Our AI reversals strategy attempts to trade price reversions back toward the Opt Algo.
These levels are calculated on specific days of the week, but can be traded any day. The internal algorithm determines which HTF highs/lows are most likely to function as tradable support/resistance levels. For instance, if Friday consists of heavy trading activity and high/low prices are tracked/recorded as causing significant support / resistance when tested in the future, the algorithm will consider support and resistance levels created on Friday as future tradable levels.
Additionally, if support/resistance levels created on Wednesday are recorded as weak or unpredictable when traded at in the future, the algorithm will not consider support/resistance levels generated on Thursday as tradable, and will not generate long or shit signals for these levels.
In the background, the AI reversals strategy is tracking success rates at multiple support and resistance levels. The best performers, if there are any, will be considered tradable. A “best performer” is calculated as the raw price move up to a threshold (i.e. 0.5%) that occurs subsequent to a test of the level.
Crash Short
The "Crash Short" strategy prioritizes short positions during retracements of a sell off. A simple yet effective strategy.
How Crash Short Works
The Crash Short strategy uses a customized momentum indicator (similar to ROC, MOM, etc.) to identify strong downside price moves. When our customized momentum indicator gives strong sell indications, the RSI is then referenced to identify an upside retracement. When the RSI exceeds a user-inputted level, a “Crash Short” signal is generated.
What is the customized momentum indicator?
The customized momentum indicator is the RoCR (Rate of Change Ratio). Instead of classic ROC, which is close - close , the RoCR divides the current close by a previous close. This formula creates a ratio that is more normalized than a simple price difference. This ratio is used to determine upside/downside momentum, with values greater than 1 indicating bullish momentum and values less than 1 indicating bearish momentum. The RoCR looks for deviating values to the downside (less than 1) to identify strong selling. From there, once the RSI crosses over an optimized level (such as 35), the indicator will print a sell signal titled "Crash Short".
Predictive Countertrend Channels
Our Predictive Countertrend Channel applies a two-stage recursive filter to smooth data using exponential decay and periodic adjustments for trend extraction. Our counter trend channels aren't directly used for signal processing; however, these channels provide useful visual cues for extended market moves.
Instructions for Optimization
Step 1: Optimize Mxwll OptAlgo
Begin by optimizing the M-Swift and M-Smooth averages for better signal accuracy.
This step simply finds better performing M-Swift and M-Smooth lookbacks. Again, if the strategy is unprofitable you will be notified and from there decide not to use the strategy.
Step 2: Optimize Mxwll RSI
Refine the Mxwll RSI settings to explore potential adjustments in smoothness and signal output. This step aims to evaluate whether these adjustments could improve the accuracy of the signals generated by Mxwll OptAlgo, while being mindful of any potential impacts.
Step 3: Optimize TP/SL
Consider adjusting the Take Profit and Stop Loss settings to potentially manage risk.
Step 4: Optimize Bars Between Trades
Set the number of bars between trades to regulate the frequency of trade executions. This adjustment may help in reducing the risk of overtrading and support a more disciplined trading strategy.
Step 5: Optimize Trade Flip
Adjust the trade flip parameters to potentially improve the management of transitions between long and short positions. This adjustment is intended to help achieve smoother trade executions, though outcomes may vary.
Step 6: Optimize RSI OB/OB Levels
Consider adjusting the overbought (OB) and oversold (OS) RSI levels to explore potential improvements in signal sensitivity. Careful calibration of these levels may help refine the accuracy of trend reversal signals, although results may depend on market conditions.
Finished!
From this point, consider setting alerts to make the most of the Mxwll Opt Algo's potential accuracy.
The effectiveness of the Opt Algo signal output can be evaluated using the "PF" table, which indicates the profit factor score for the strategy. A profit factor (PF) of less than or equal to 1 suggests that the strategy may not be profitable.
Disclaimer
No strategy works on any timeframe on any asset, so, if the Opt Algo underperforms for the asset/timeframe you're analyzing, the Opt Algo PF table lets you know it hasn't been generating accurate signals, in which case you can decide not to use it!
Optimization Disclaimer
Optimization can be tricky. It's helpful to test numerous strategies in aggregate to see if a strategy has potential. Despite this, optimization can cause overfitting. Overfitting occurs when a strategy is too closely fit to the data it's trading. Overfit backtests are deceptively phenomenal. While the historical performance looks great, the future expectancy of the strategy remains unpredictable - an overfit strategy will profit from periods of random price movement which, being random, are irreproducible and cannot be profited from other than their initial occurrence. When a strategy trades random price movement profitably, any and all profit earned can be reduced to chance. Keep this in mind when using the in-built optimization system. Optimization should be kept to a minimum, a tool to point you in the right direction, whether confirming potential or signifying a useless system.
ML Compressor Enhanced Trading Indicator# 🤖 ML Enhanced Trading Indicator - Advanced Market Analysis
## 📊 Overview
This is a comprehensive Machine Learning Enhanced Trading Indicator that combines multiple advanced analytical techniques to provide high-probability trading signals. The indicator uses artificial intelligence, pattern recognition, anomaly detection, and traditional technical analysis to identify optimal entry and exit points in the market.
## 🚀 Key Features
### 🧠 **Machine Learning Core**
- **Advanced Pattern Recognition**: Uses cosine similarity, Pearson correlation, and Spearman rank correlation to identify historical patterns
- **AI-Powered Predictions**: Implements multiple correlation methods to forecast price movements
- **Anomaly Detection**: Z-score based detection system for unusual market activities
- **Signal Confidence Scoring**: Reliability assessment for each trading signal
### 📈 **Technical Analysis Integration**
- **Multi-Timeframe RSI Analysis**: 14 and 21-period RSI with oversold/overbought detection
- **MACD Momentum**: Enhanced MACD histogram analysis for trend confirmation
- **Bollinger Bands Position**: Dynamic position tracking within BB channels
- **Volume Analysis**: Spike and dry volume detection with ratio calculations
- **Trend Strength Measurement**: EMA-based trend power analysis
### 🎯 **Perfect Zone Detection**
- **Ideal Buy Zone**: Identifies perfect buying opportunities when 7 conditions align:
- ML Score ≥ 0.60
- Bottom proximity detection
- RSI in 20-35 range
- Volume spike confirmation
- Positive price anomaly
- Bullish pattern match
- Positive MACD momentum
### 📊 **Comprehensive Display Table**
- **Real-time ML Analysis**: Complete breakdown of all indicators
- **Perfect Buy Conditions Tracker**: Visual checklist with completion percentage
- **Performance Metrics**: Win rate tracking and P&L analysis
- **Signal Strength Indicators**: Confidence levels for each signal
## 🔧 **Customizable Parameters**
### **ML Settings**
- **ML Lookback Period**: 20-500 bars (default: 100)
- **Anomaly Threshold**: 1.0-5.0 sensitivity (default: 2.0)
- **Pattern Similarity**: 0.5-0.99 matching threshold (default: 0.80)
- **AI Lookback Period**: 20-200 bars (default: 50)
### **AI Prediction Models**
- **Correlation Methods**: Spearman, Pearson, Cosine Similarity
- **Forecast Length**: 15-250 bars (default: 50)
- **Similarity Type**: Price or %Change analysis
### **Visual Options**
- **Table Position**: Top/Bottom Left/Right positioning
- **Table Size**: Small, Normal, Large options
- **Signal Display**: Toggle buy/sell signals on/off
- **AI Visualization**: Optional prediction paths and ZigZag
## 📋 **How to Use**
### **For Beginners**
1. Add the indicator to your chart
2. Look for "PERFECT BUY" signals in the table
3. Wait for completion percentage ≥ 85% for highest probability trades
4. Use the background color changes as visual confirmation
### **For Advanced Traders**
1. Analyze individual ML components in the detailed table
2. Monitor anomaly detection for unusual market conditions
3. Use pattern confidence levels for trade timing
4. Combine with your existing strategy for confirmation
### **Signal Interpretation**
- **🟢 PERFECT BUY**: All 7 conditions met - highest probability reversal
- **🟡 NEAR BOTTOM**: Close to ideal conditions - monitor closely
- **🔴 NOT READY**: Wait for better setup
- **Strong Buy/Sell Signals**: ML score-based entries with high confidence
## ⚠️ **Important Notes**
### **Risk Management**
- This indicator provides analysis and signals, not guaranteed outcomes
- Always use proper risk management and position sizing
- Consider market conditions and fundamental factors
- Backtest the strategy on your preferred timeframes and assets
### **Best Practices**
- Use multiple timeframe analysis for confirmation
- Combine with support/resistance levels
- Monitor volume confirmation for all signals
- Set appropriate stop-losses and profit targets
### **Performance Tracking**
- The indicator tracks its own performance with win rate calculations
- Monitor the "AI Prediction" accuracy percentage
- Use the P&L tracking to assess signal quality over time
## 🔄 **Updates and Improvements**
This indicator is continuously evolving with:
- Enhanced machine learning algorithms
- Improved pattern recognition capabilities
- Additional correlation methods for better accuracy
- Performance optimization for faster calculations
- New visualization features based on user feedback
## 📚 **Technical Details**
### **Machine Learning Implementation**
- **Pattern Matching**: 20-bar normalized price patterns with historical comparison
- **Correlation Analysis**: Mathematical similarity scoring between current and historical patterns
- **Anomaly Detection**: Statistical Z-score analysis across price, volume, and RSI
- **Signal Weighting**: Multi-factor scoring system with optimized weights
### **Algorithm Components**
1. **Feature Extraction**: Price, volume, momentum, volatility, and trend features
2. **Pattern Recognition**: Historical pattern database with similarity matching
3. **Anomaly Detection**: Multi-dimensional Z-score threshold analysis
4. **Signal Generation**: Weighted scoring system with confidence intervals
5. **Performance Tracking**: Real-time win rate and accuracy monitoring
### **Calculation Methods**
- **Trend Strength**: (EMA8 - EMA21) / EMA21 * 100
- **Volume Ratio**: Current Volume / 20-period SMA Volume
- **BB Position**: (Close - BB_Lower) / (BB_Upper - BB_Lower)
- **Anomaly Score**: Average of normalized Z-scores for price, volume, and RSI
## 🎨 **Visual Elements**
### **Background Colors**
- **Light Green**: Perfect buy zone detected
- **Light Red**: Perfect sell zone detected
- **Light Blue**: Near bottom proximity
- **Green/Red Transparency**: Price anomaly detection
### **Signal Shapes**
- **Green Triangle Up**: Strong buy signal
- **Red Triangle Down**: Strong sell signal
- **Aqua Diamond**: Perfect buy zone entry
- **Purple Diamond**: Perfect sell zone entry
### **Table Information**
- **ML Complete Analysis**: 16 comprehensive metrics
- **Perfect Buy Conditions**: 7-point checklist with status indicators
- **Real-time Values**: Live updating of all calculations
- **Color-coded Status**: Green (good), Yellow (moderate), Red (caution)
## 🔍 **Troubleshooting**
### **Common Issues**
- **Table Not Showing**: Enable "Show ML Table" in settings
- **No Signals Appearing**: Check "Show Buy/Sell Signals" option
- **Performance Issues**: Reduce ML Lookback Period for faster calculation
- **Too Many/Few Signals**: Adjust Anomaly Threshold sensitivity
### **Optimization Tips**
- **For Day Trading**: Use lower timeframes (1m, 5m, 15m) with reduced lookback periods
- **For Swing Trading**: Use higher timeframes (1h, 4h, 1D) with standard settings
- **For Scalping**: Enable only strong signals and reduce pattern similarity threshold
- **For Long-term**: Increase all lookback periods and use daily/weekly timeframes
## 📖 **Disclaimer**
This indicator is for educational and informational purposes only. It should not be considered as financial advice. Trading involves substantial risk of loss and is not suitable for all investors. Past performance does not guarantee future results.
### **Risk Warning**
- All trading involves risk of substantial losses
- Never risk more than you can afford to lose
- This indicator does not guarantee profitable trades
- Always use proper risk management techniques
- Consider consulting with a financial advisor
### **Liability**
The creator of this indicator is not responsible for any losses incurred from its use. Users should thoroughly test and understand the indicator before using it with real money.
### **Feature Requests**
- Suggest improvements through TradingView comments
- Report bugs with detailed descriptions
- Share successful strategies using the indicator
- Contribute to community discussions
## 🏆 **Credits and Acknowledgments**
This indicator builds upon various open-source libraries and mathematical concepts:
- TradingView ZigZag library for visualization
- Statistical correlation methods from academic research
- Machine learning concepts adapted for financial markets
- Community feedback and testing contributions
## 📈 **Performance Metrics**
The indicator includes built-in performance tracking:
- **Win Rate Calculation**: Percentage of profitable signals
- **Signal Accuracy**: ML prediction vs actual price movement
- **Drawdown Tracking**: Current unrealized P&L from last signal
- **Completion Percentage**: How many perfect conditions are met
## 🔬 **Mathematical Foundation**
### **Correlation Calculations**
- **Pearson**: Measures linear correlation between patterns
- **Spearman**: Rank-based correlation for non-linear relationships
- **Cosine Similarity**: Vector-based similarity for pattern matching
### **Statistical Methods**
- **Z-Score**: (Value - Mean) / Standard Deviation
- **Pattern Normalization**: Price / Price
- **Volatility Percentile**: Historical ranking of current volatility
- **Momentum Calculation**: Price change over multiple periods
## 🎯 **Trading Strategies**
### **Conservative Approach**
- Wait for Perfect Buy Zone (85%+ completion)
- Use higher timeframes for confirmation
- Set stop-loss at recent swing low
- Take profits at resistance levels
### **Aggressive Approach**
- Trade on Strong Buy/Sell signals
- Use lower completion thresholds (70%+)
- Tighter stop-losses with faster exits
- Higher position sizes with confirmed trends
### **Hybrid Strategy**
- Combine with other indicators for confirmation
- Use different settings for different market conditions
- Scale in/out based on signal strength
- Adjust parameters based on market volatility
UltraTrend Pro - Phoenix Engine EditionUltraTrend Pro – Phoenix Engine Edition
Overview
This is a technical analysis tool designed to help identify the current market trend and provide context on the market's "personality." It is built around a proprietary Phoenix Engine that analyzes price action to classify the market into distinct regimes—such as strong trends, weak trends, or choppy conditions—and then adapts its core algorithm accordingly.
Technical Features
The indicator is built on these main ideas:
1. The Phoenix Engine (Market Regime Classification):
Instead of using a one-size-fits-all approach, the Phoenix Engine constantly analyzes price volatility, strength, and stability to classify the current market into one of several regimes:
* Strong Trend (Up/Down): Clear, high-momentum directional movement.
* Medium/Weak Trend (Up/Down): Developing or fading directional movement.
* Ranging: Sideways price action with low volatility.
* Volatile: Large price swings but with no clear direction.
* Choppy: Unpredictable, messy price action to be cautious of.
This classification is displayed in real-time in the on-screen "Market Regime Display."
2. AI-Style Adaptive Trend Algorithm:
When "AI-Style Adaptation" is enabled, the core trend-following algorithm automatically adjusts its own internal parameters (Sensitivity and Period) based on the regime detected by the Phoenix Engine.
* In strong trends, it becomes less sensitive to ride the trend longer.
* In choppy or volatile markets, it becomes more conservative to help filter out noise.
This allows the indicator to dynamically adapt its behavior to the ever-changing personality of the market.
3. Adaptive Fibonacci TP/SL System:
The indicator's Take Profit (TP) and Stop Loss (SL) levels can operate in two modes:
* Standard Mode: Uses fixed Risk-Reward ratios set by the user.
* Adaptive Mode: This is the AI-style feature. It analyzes the historical success rate of signals within the current market regime to calculate and display:
* Adjusted TP/SL Levels: Levels are automatically widened or tightened based on what has historically worked best in that specific regime (e.g., wider TPs in strong trends, tighter TPs in ranging markets).
* Success Probabilities: An estimated probability (%) of reaching each TP level is shown on the chart.
* Expected Duration: An estimated time-to-target (in bars) is displayed for each TP, helping with trade management expectations.
4. Built-in Backtest & Data Analysis Engine:
To power the adaptive system, the indicator includes a powerful backtest engine that scans historical signals. It can operate in two modes:
* Deep Historical Scan: Analyzes thousands of past candles to build a robust statistical baseline.
* Recent Signals Only: Focuses only on the most recent signals within each regime, allowing the system to adapt more quickly to changing market character.
The results are displayed in a comprehensive on-screen "Backtest Statistics Table."
5. Multi-Layered Filtering System:
To qualify signals, the indicator allows for additional filters, including:
* Dual Moving Averages: Ensure signals align with a broader market trend (e.g., above the 200 SMA).
* Trading Session Filter: Restricts signals to specific user-defined trading hours.
How to Use This Indicator
1. Use the Feature Control Panel: The settings menu has been simplified. The top sections allow you to quickly toggle major visual components on or off to customize your chart.
2. Enable AI-Style Adaptation (Recommended): For the indicator to use the Phoenix Engine to its full potential, ensure "Enable AI-Style Adaptation" is checked.
3. Observe the Market Regime Display: This on-screen table is your guide to the current market's personality. It tells you the detected regime, its strength, and how the indicator is adapting.
4. Watch for Signals: A "BUY" or "SELL" signal indicates that the trend algorithm has detected a potential shift in direction.
5. Assess Adaptive TP/SL Levels: When a signal appears, observe the on-chart TP levels. The displayed probabilities and expected durations provide valuable context for managing the trade. For example, a high-probability TP1 with a short duration might be a good scalping target.
6. Use Tables for Deeper Insight: The "Backtest Statistics Table" provides a detailed breakdown of how signals have historically performed in each market regime, helping you decide which setups to trust more.
Intended Use & Limitations
* Recommended Assets: Designed for use on all assets. The Phoenix Engine's adaptive nature allows it to adjust to different market types automatically.
* Timeframes: Can be used on all timeframes.
Limitations:
* This is a tool to support analysis. It does not generate automatic buy or sell advice.
* The indicator is not a standalone strategy and does not guarantee results. Users are responsible for their own trading decisions.
* Probabilities and statistics are based on historical data and do not predict future results.
* Always use this tool in combination with your own analysis and a robust risk management plan.
We believe that no indicator is a magic solution. Technical analysis tools provide value through their convenience, adaptability, and unique logic. Combining these elements can help a trader make more educated and planned decisions, hopefully contributing to their overall success.
AiTrend Pattern Matrix for kNN Forecasting (AiBitcoinTrend)The AiTrend Pattern Matrix for kNN Forecasting (AiBitcoinTrend) is a cutting-edge indicator that combines advanced mathematical modeling, AI-driven analytics, and segment-based pattern recognition to forecast price movements with precision. This tool is designed to provide traders with deep insights into market dynamics by leveraging multivariate pattern detection and sophisticated predictive algorithms.
👽 Core Features
Segment-Based Pattern Recognition
At its heart, the indicator divides price data into discrete segments, capturing key elements like candle bodies, high-low ranges, and wicks. These segments are normalized using ATR-based volatility adjustments to ensure robustness across varying market conditions.
AI-Powered k-Nearest Neighbors (kNN) Prediction
The predictive engine uses the kNN algorithm to identify the closest historical patterns in a multivariate dictionary. By calculating the distance between current and historical segments, the algorithm determines the most likely outcomes, weighting predictions based on either proximity (distance) or averages.
Dynamic Dictionary of Historical Patterns
The indicator maintains a rolling dictionary of historical patterns, storing multivariate data for:
Candle body ranges, High-low ranges, Wick highs and lows.
This dynamic approach ensures the model adapts continuously to evolving market conditions.
Volatility-Normalized Forecasting
Using ATR bands, the indicator normalizes patterns, reducing noise and enhancing the reliability of predictions in high-volatility environments.
AI-Driven Trend Detection
The indicator not only predicts price levels but also identifies market regimes by comparing current conditions to historically significant highs, lows, and midpoints. This allows for clear visualizations of trend shifts and momentum changes.
👽 Deep Dive into the Core Mathematics
👾 Segment-Based Multivariate Pattern Analysis
The indicator analyzes price data by dividing each bar into distinct segments, isolating key components such as:
Body Ranges: Differences between the open and close prices.
High-Low Ranges: Capturing the full volatility of a bar.
Wick Extremes: Quantifying deviations beyond the body, both above and below.
Each segment contributes uniquely to the predictive model, ensuring a rich, multidimensional understanding of price action. These segments are stored in a rolling dictionary of patterns, enabling the indicator to reference historical behavior dynamically.
👾 Volatility Normalization Using ATR
To ensure robustness across varying market conditions, the indicator normalizes patterns using Average True Range (ATR). This process scales each component to account for the prevailing market volatility, allowing the algorithm to compare patterns on a level playing field regardless of differing price scales or fluctuations.
👾 k-Nearest Neighbors (kNN) Algorithm
The AI core employs the kNN algorithm, a machine-learning technique that evaluates the similarity between the current pattern and a library of historical patterns.
Euclidean Distance Calculation:
The indicator computes the multivariate distance across four distinct dimensions: body range, high-low range, wick low, and wick high. This ensures a comprehensive and precise comparison between patterns.
Weighting Schemes: The contribution of each pattern to the forecast is either weighted by its proximity (distance) or averaged, based on user settings.
👾 Prediction Horizon and Refinement
The indicator forecasts future price movements (Y_hat) by predicting logarithmic changes in the price and projecting them forward using exponential scaling. This forecast is smoothed using a user-defined EMA filter to reduce noise and enhance actionable clarity.
👽 AI-Driven Pattern Recognition
Dynamic Dictionary of Patterns: The indicator maintains a rolling dictionary of N multivariate patterns, continuously updated to reflect the latest market data. This ensures it adapts seamlessly to changing market conditions.
Nearest Neighbor Matching: At each bar, the algorithm identifies the most similar historical pattern. The prediction is based on the aggregated outcomes of the closest neighbors, providing confidence levels and directional bias.
Multivariate Synthesis: By combining multiple dimensions of price action into a unified prediction, the indicator achieves a level of depth and accuracy unattainable by single-variable models.
Visual Outputs
Forecast Line (Y_hat_line):
A smoothed projection of the expected price trend, based on the weighted contribution of similar historical patterns.
Trend Regime Bands:
Dynamic high, low, and midlines highlight the current market regime, providing actionable insights into momentum and range.
Historical Pattern Matching:
The nearest historical pattern is displayed, allowing traders to visualize similarities
👽 Applications
Trend Identification:
Detect and follow emerging trends early using dynamic trend regime analysis.
Reversal Signals:
Anticipate market reversals with high-confidence predictions based on historically similar scenarios.
Range and Momentum Trading:
Leverage multivariate analysis to understand price ranges and momentum, making it suitable for both breakout and mean-reversion strategies.
Disclaimer: This information is for entertainment purposes only and does not constitute financial advice. Please consult with a qualified financial advisor before making any investment decisions.
Elite Trading Network | HQ: Quantum Edge V2Elite Trading Network HQ: Quantum Edge V2 is a sophisticated market structure analysis tool designed to help traders make informed decisions based on a deep understanding of market conditions. This script blends structural trend analysis with AI-based predictive models to provide dynamic, real-time insights into market behavior. Here is what makes Quantum Edge V2 unique:
Key Features:
Adaptive Market Structure Analysis:
The script uses a multi-level algorithm to identify key market structures, such as swing highs and swing lows, to help traders understand the underlying strength or weakness of the current market trend. It dynamically tracks critical market boundaries using historical price action and recalculates trend levels as new data emerges.
Range and Trend Condition Detection:
Quantum Edge V2 detects whether the market is trending or ranging by analyzing historical structure breaks. This detection helps identify moments of consolidation (yellow zones) or periods of trend continuation. By calculating average structural break durations, the indicator alerts users to conditions that may require caution, such as ranging markets.
Predictive AI Analysis for Entry Optimization:
An AI-powered module evaluates volume thresholds and ATR (Average True Range) to provide users with an understanding of the current market risk. The ATR is calculated based on a user-defined timeframe, giving flexibility in how users approach different market conditions. This feature also determines the risk per trade and calculates the optimal position size, ensuring that users can tailor their risk according to their trading plan.
Real-Time Alerts and Visual Indicators:
The indicator includes alerts for key conditions:
Green Condition: Signals optimal market entry conditions.
Yellow Condition: Indicates a cautionary ranging market, alerting traders to the potential lack of strong trends.
Red Condition: Identifies unsuitable market conditions for entry due to insufficient volume or unfavorable metrics.
Color-coded background visuals provide instant clarity regarding market conditions—red, yellow, or green—allowing traders to make quick, informed decisions.
Dynamic Multi-Timeframe Analysis:
The user can select a custom entry timeframe, while the script internally calculates and adapts to a higher timeframe for deep trend analysis. This approach gives traders a complete view of both the short-term (entry) and higher timeframe (overall trend) dynamics.
How to Use:
Identify Trend Conditions: The indicator visually plots key market structures (green and red structural lines) to help users determine where the market may find support or resistance. The background changes color to indicate trending (green), ranging (yellow), or high-risk (red) conditions.
Make Informed Entries: Use the real-time alerts and label information to get insights into current market conditions. If the background is green and metrics align, the indicator suggests an optimal time for entry.
Position Sizing and Risk Management: The calculated risk per trade and position size (displayed on-screen) assist users in managing risk effectively. Users can utilize this data to adjust trade sizes and maximize profit potential while adhering to their risk tolerance.
What Sets Quantum Edge V2 Apart:
Unlike other indicators that solely provide trend direction, Quantum Edge V2 offers an integrated understanding of market structure, volume analysis, and predictive AI models.
The ranging market detection (yellow zones) is particularly valuable for traders looking to avoid low-probability trades during periods of market indecision.
The use of ATR-based risk calculation ensures the position sizing is always aligned with market volatility, adding an extra layer of protection for capital.
Important Notes:
Educational Value: This script does not just tell you when to enter or exit. It provides deep insights into market dynamics, giving traders a tool to learn and improve their market understanding. The ability to view market structure across different timeframes and visualize areas of caution is crucial for long-term growth as a trader.
No Guaranteed Results: This indicator is a powerful tool for analysis, but like all trading strategies, it does not guarantee profits. Always practice proper risk management.
Why It's Worth Using: This indicator combines multi-timeframe structure analysis, volume metrics, and predictive AI modeling—an approach typically reserved for professional trading systems. Traders looking to incorporate a systematic approach to risk, ranging markets, and trend detection will find Quantum Edge V2 invaluable.
Closed-source Explanation: The script uses proprietary algorithms and unique concepts for trend detection and volume-based analysis that ensure high levels of accuracy in defining market structure and determining entry signals. Because of its complexity and the unique blend of tools, it remains closed-source.
Feedback and Support:
If you have questions or suggestions about this script, feel free to comment or reach out. We value your input as we strive to improve and provide traders with cutting-edge tools.
TradingIQ - Impulse IQIntroducing "Impulse IQ" by TradingIQ
Impulse IQ is an exclusive trading algorithm developed by TradingIQ, designed to trade breakouts and established trends. By integrating artificial intelligence and IQ Technology, Impulse IQ analyzes historical and real-time price data to construct a dynamic trading system adaptable to various asset and timeframe combinations.
Philosophy of Impulse IQ
Impulse IQ combines IQ Technology (AI) with the classic principles of trend and breakout trading. Recognizing that markets inherently follow trends that need to persist for significant price movements to unfold, Impulse IQ eliminates the need for rigid settings or manual intervention.
Instead, it dynamically develops, adapts, and executes trend-based trading strategies, enabling a more responsive approach to capturing meaningful market opportunities.
Impulse IQ is designed to work straight out of the box. In fact, its simplicity requires just one user setting, making it incredibly straightforward to manage.
Strategy type is the only setting that controls Impulse IQ’s functionality.
Traders don’t have to spend hours adjusting settings and trying to find what works best - Impulse IQ handles this on its own.
Key Features of Impulse IQ
Self-Learning Breakout Detection
Employs IQ Technology to identify breakouts.
AI-Generated Trading Signals
Provides breakout trading signals derived from self-learning algorithms.
Comprehensive Trading System
Offers clear entry and exit labels.
AI-Determined Trailing Profit Target and Stop Loss
Position exit levels are clearly defined and calculated by the AI once the trade is entered.
Performance Tracking
Records and presents trading performance data, easily accessible for user analysis.
Long and Short Trading Capabilities
Supports both long and short positions to trade various market conditions.
IQ Meter
The IQ Meter details where price is trading relative to a higher timeframe trend and lower timeframe trend. Fibonacci levels are interlaced along the meter, offering unique insights on trend retracement opportunities.
Self Learning, Multi Timeframe IQ Zig Zags
The Zig Zag IQ is a self-learning, multi-timeframe indicator that adapts to market volatility, providing a clearer representation of market movements than traditional zig zag indicators.
Dual Strategy Execution
Impulse IQ integrates two distinct strategy types: Breakout and Cheap (details explained later).
How It Works
Before diving deeper into Impulse IQ, it's essential to understand the core terminology:
Zig Zag IQ : A self-learning trend and breakout identification mechanism that serves as the foundation for Impulse IQ. Although it belongs to the “Zig Zag” class of technical indicators, it's powered by IQ Technology.
Impulse IQ : A self-learning trading strategy that executes trades based on Zig Zag IQ. Zig Zag IQ identifies market trends, while Impulse IQ adapts, learns, and executes trades based on these trend characterizations.
Impulse IQ operates on a simple heuristic: go long during upside volatility and go short during downside volatility, essentially capturing price breakouts.
The definition of a “price breakout” is determined by IQ Technology, TradingIQ's exclusive AI algorithm. In Impulse IQ, the algorithm utilizes two IQ Zig Zags (self-learning, multi-timeframe zig zags) to analyze and learn from market trends.
It identifies breakout opportunities by recognizing violations of established price levels marked by the IQ Zig Zags. Impulse IQ then adapts and evolves to trade similar future violations in a recurring and dynamic manner.
Put simply, IQ Zig Zags continuously learn from both historical and real-time price updates to adjust themselves for an "optimal fit" to price data. The aim is to adapt so that the marked price tops and bottoms, when violated, reveal potential breakout opportunities.
The strategy layer of IQ Zig Zags, known as Impulse IQ, incorporates an additional level of self-learning with IQ Technology. It learns from breakout signals generated by the IQ Zig Zags, enabling it to dynamically identify and signal tradable breakouts. Moreover, Impulse IQ learns from historical price data to manage trade exits.
All positions start with an initial fixed stop loss and a trailing stop target. Once the trailing stop target is reached, the fixed stop loss converts into a trailing stop, allowing Impulse IQ to remain in the breakout/trend until the trailing stop is triggered.
What Classifies as a Breakout, Price Top, and Price Bottom?
For Impulse IQ:
Price tops are considered the highest price achieved before a price bottom forms.
Price bottoms are the lowest price reached before a price top forms.
For price tops, the highest price continues to be calculated until a significant downside price move occurs. Similarly, for price bottoms, the lowest price is calculated until a significant upside price move happens.
What distinguishes Zig Zag IQ from other zig zag indicators is its unique mechanism for determining a "significant counter-trend price move." Zig Zag IQ evaluates multiple fits to identify what best suits the current market conditions. Consequently, a "significant counter-trend price move" in one market might differ in magnitude from what’s considered "significant" in another, allowing it to adapt to varying market dynamics.
For example, a 1% price move in the opposite direction might be substantial in one market but not in another, and Zig Zag IQ figures this out internally.
The image above illustrates the IQ Zig Zags in action. The solid Zig Zag IQ lines represent the most recent price move being calculated, while the dotted, shaded lines display historical price moves previously analyzed by IQ Zig Zag.
Notice how the green zig zag aligns with a larger trend, while the purple zig zag follows a smaller trend. This mechanism is crucial for generating breakout signals in Impulse IQ: for a position to be entered, the breakout of the smaller trend must occur in the same direction as the larger trend.
The image above depicts the IQ Meters—an exclusive TradingIQ tool designed to help traders evaluate trend strength and retracement opportunities.
When the lower timeframe Zig Zag IQ and the higher timeframe Zig Zag IQ are out of sync (i.e., one is uptrending while the other is downtrending, with no active positions), the meters display a neutral color, as shown in the image.
The key to using these meters is to identify trend unison and pinpoint key trend retracement entry opportunities. Fibonacci retracement levels for the current trend are interlaced along each meter, and the current price is converted to a retracement ratio of the trend.
These meters can mathematically determine where price stands relative to the larger and smaller trends, aiding in identifying entry opportunities.
The top of each meter indicates the highest price achieved during the current price move.
The bottom of each meter indicates the lowest price achieved during the current price move.
When both the larger and smaller trends are in sync and uptrending, or when a long position is active, the IQ meters turn green, indicating uptrend strength.
When both trends are in sync and downtrending, or when a short position is active, the IQ meters turn red, indicating downtrend strength.
The image above shows the Point of Change for both the larger and smaller Zig Zag IQ trends. A distinctive feature of Zig Zag IQ is its ability to calculate these turning points in advance—unlike most traditional zig zag indicators that lack predetermined turning points and often lag behind price movements. In contrast, Zig Zag IQ offers a minimal-lag trend detection capability, providing a more responsive representation of market trends.
Simply put, once the market Zig Zag anchors are touched, the corresponding Zig Zag IQ will change direction.
Trade Signals
Impulse IQ can trade in one of two ways: Entering breakouts as soon as they happen (Breakout Strategy Type) or entering the pullback of a price breakout (Cheap Strategy Type).
Generally, the Breakout Strategy type will take a greater number of trades and enter a breakout quicker. The Cheap Strategy type will usually take less trades, but potentially enter at a better time/price point, prior to the next leg up of a break up, or the next leg down of a break down.
Entry signals are given when price breaks out to the upside or downside for the "Breakout" strategy type, or for the "Cheap" strategy type, when price retraces to the level it broke out from!
Breakout Strategy Example
The image above demonstrates a long position entered and exited using the Breakout strategy. The price breakout level is marked by the dotted, horizontal green line, representing a previously established price high identified by IQ Zig Zag. Once the price breaks and closes above this level, a long position is initiated.
After entering a long position, Impulse IQ immediately displays the initial fixed stop price. As the price moves favorably for the long position, the trailing stop conversion level is reached, and the indicator switches to a trailing stop, as shown in the image. Impulse IQ continues to "ride the trend" for as long as it persists, exiting only when the trailing stop is triggered.
Cheap Strategy Example
The image above shows a short entry executed using the Cheap strategy. The aim of the Cheap strategy is to enter on a pullback before the breakout occurs. While this results in fewer trades if price doesn’t pull back before the breakout, it typically allows for a better entry time and price point when a pullback does happen.
The image above illustrates the remainder of the trade until the trailing stop was hit.
Green Arrow = Long Entry
Red Arrow = Short Entry
Blue Arrow = Trade Exit
Impulse IQ calculates the initial stop price and trailing stop distance before any entry signals are triggered. This means users don’t need to constantly tweak these settings to improve performance—Impulse IQ handles this process internally.
Verifying Impulse IQ’s Effectiveness
Impulse IQ automatically tracks its performance and displays the profit factor for both its long and short strategies, visible in a table located in the top-right corner of your chart.
The image above shows the profit factor for both the long and short strategies used by Impulse IQ.
A profit factor greater than 1 indicates that the strategy was profitable when trading historical price data.
A profit factor less than 1 indicates that the strategy was unprofitable when trading historical price data.
A profit factor equal to 1 indicates that the strategy neither gained nor lost money on historical price data.
Using Impulse IQ
While Impulse IQ functions as a comprehensive trading system with its own entry and exit signals, it was designed for the manual trader to take its trading signals and analysis indications to greater heights - offering numerous applications beyond its built-in trading system.
The standout feature of Impulse IQ is its ability to characterize and capitalize on trends. Keeping a close eye on “Breakout” labels and making use of the IQ meter is the best way to use Impulse IQ.
The IQ Meters can be used to:
Find entry points during trend retracements
Assess trend alignment across higher and lower timeframes
Evaluate overall trend strength, indicating where the price lies on both IQ Meters.
Additionally, "Break Up" and "Break Down" labels can be identified for anticipating breakouts. Impulse IQ self-learns to capture breakouts optimally, making these labels dynamic signals for predicting a breakout.
The Zig Zag IQ indicators are instrumental in characterizing the market's current state. As a self-learning tool, Zig Zag IQ constantly adapts to improve the representation of current price action. The price tops and bottoms identified by Zig Zag IQ can be treated as support/resistance and breakout levels.
Of course, you can set alerts for all Impulse IQ entry and exit signals, effectively following along its systematic conquest of price movement.
GG Short & Long IndicatorGG Short & Long Indicator is a powerful signal indicator with AI
How do indicator signals work?
The main purpose of the indicator is to give a signal that is most likely to bring profit based on historical data. This ORIGINAL trend algorithm gives SHORT and LONG signals when several conditions coincide: 1) Breakout of the average value of the modernized VWAP (this VWAP takes data only from certain time periods and trading sessions, as a result, its breakout most often coincides with the beginning of a strong trend); 2) The previous condition must be confirmed by volumes. I noticed that on some crypto exchanges, depending on whether the breakout is false or true, the volumes are different relative to each other. I applied this knowledge for additional filtering of signals (this point works only on crypto assets, on other assets the algorithm works without taking it into account, maybe later I will refine it); 3) When some of my original formulas to determine overbought (similar in principle to RSI, but more designed to work with the trader algorithm), should not show overbought - so that the entry into the transaction was not at too unfavorable values. To summarize, the algorithm tries to find a balance to determine a true breakout, during which the price will not go too far (for an acceptable RR).
But the most important thing is that the parameters to customize the algorithm are governed by our original AI algorithm. It can adjust the indicator in two modes: 1) Settings are selected based on the most profitable historical settings. 2) The settings are selected based not only on historical profitability, but also on winrate, frequency of trades, and a few other items that we will not disclose (so the code is closed) - we consider this approach as a priority, because according to our observations, it gives the highest performance compared to manual tuning. In addition, AI simply simplifies the work with the indicator - you do not need to adjust the settings manually for different trading pairs or timeframes, AI will do it all by itself and immediately give the ready result (backtest) on the table.
How to trade?
After the signal is issued, the indicator determines the recommended levels to close the trade (green dots). Stop loss should be placed behind the corresponding gray SL mark. Levels for closing a deal (TP) and the level of stop loss setting (SL) are also determined automatically for the selected pair and TF, based on volatility and selected indicator settings
To make a trade, you can also use the built-in “Support and Resistance Zones” tool, which displays ranges on the chart based on the modernized ATR, from which the price is more likely to rebound (here I also used my own approach, where in addition to the classic ATR formula, I also used volumes from certain crypto exchanges to determine more accurate price rebound zones)
These zones are also adjusted by AI - the algorithm compares several dozens of variations of these zones (with different settings) and chooses the one that best fits the current settings of the signal algorithm. For example, if the indicator is set up for frequent trades - the zones will be updated faster and will be less deep than if the indicator is set up for medium-term trading
If desired, you can customize the indicator manually using the corresponding section of the settings. Each paramater has a tooltip describing how and what it affects.
Statistisc panel
The panel can be divided into 2 conditional parts:
1) Statistics for each individual TP for the selected strategy. It shows the winrate and gross profit, if you fix a trade on a single target completely
2) Total trading result, if you trade clearly according to the strategy and fix the position by equal hours on 4 TPs. The total trading result is displayed for the current indicator settings, it also shows the best, worst and optimal of the possible indicator settings and the trading result of these settings on the side.
How do setup the indicator?
The indicator has preset settings for several major pairs and timeframes. These are fixed settings specifically selected for individual pairs and timeframes. You can use these presets, or you can choose one of the adaptive settings, which will AUTOMATICALLY select the best/optimal indicator settings.
I recommend choosing the “Adaptive Optimal” preset, as it uses more data to determine the optimal indicator settings and according to my observations this method works better in comparison to manual indicator settings or the “Adaptive Best” preset
Or you can use the manual settings, as mentioned earlier.
RSI Phi PhiSống để cho đi.
Phương pháp của sư phụ
Sống trong đời sống cần có một tấm lòng
Để làm gì, em biết không?
Để gió cuốn đi
Để gió cuốn đi
Gió cuốn đi cho mây qua dòng sông
Ngày vừa lên hay đêm xuống mênh mông
Ôi trái tim đang bay theo thời gian
Làm chiếc bóng đi rao lời dối gian
Những khi chiều tới, cần có một tiếng cười
Để ngậm ngùi theo lá bay
Rồi nước cuốn trôi
Rồi nước cuốn trôi
Hãy nghiêng đời xuống, nhìn suốt một mối tình
Chỉ lặng nhìn không nói năng
Để buốt trái tim
Để buốt trái tim
Trong trái tim con chim đau nằm yên
Ngủ dài lâu mang theo vết thương sâu
Một sớm mai, chim bay đi triền miên
Và tiếng hót tan trong trời gió lên
Hãy yêu ngày tới dù quá mệt kiếp người
Còn cuộc đời, ta cứ vui
Dù vắng bóng ai
Dù vắng bóng ai
Dù vắng bóng ai
Dù vắng bóng ai
Dù vắng bóng ai
Neural Network Buy and Sell SignalsTrend Architect Suite Lite - Neural Network Buy and Sell Signals
Advanced AI-Powered Signal Scoring
This indicator provides neural network market analysis on buy and sell signals designed for scalpers and day traders who use 30s to 5m charts. Signals are generated based on an ATR system and then filtered and scored using an advanced AI-driven system.
Features
Neural Network Signal Engine
5-Layer Deep Learning analysis combining market structure, momentum, and market state detection
AI-based Letter Grade Scoring (A+ through F) for instant signal quality assessment
Normalized Input Processing with Z-score standardization and outlier clipping
Real-time Signal Evaluation using 5 market dimensions
Advanced Candle Types
Standard Candlesticks - Raw price action
Heikin Ashi - Trend smoothing and noise reduction
Linear Regression - Mathematical trend visualization
Independent Signal vs Display - Calculate signals on one type, display another
Key Settings
Signal Configuration
- Signal Trigger Sensitivity (Default: 1.7) - Controls signal frequency vs quality
- Stop Loss ATR Multiplier (Default: 1.5) - Risk management sizing
- Signal Candle Type (Default: Candlesticks) - Data source for signal calculations
- Display Candle Type (Default: Linear Regression) - Visual candle display
Display Options
- Signal Distance (Default: 1.35 ATR) - Label positioning from price
- Label Size (Default: Medium) - Optimal readability
Trading Applications
Scalping
- Fast pace signal detection with quality filtering
- ATR-based stop management prevents signal overlap
- Neural network attempts to reduces false signals in choppy markets
Day Trading
- Multi-timeframe compatible with adaptation settings
- Clear trend visualization with Linear Regression candles
- Support/resistance integration for better entries/exits
Signal Filtering
- Use A+/A grades for highest probability setups
- B grades for confirmation in trending markets
- C-F grades help identify market uncertainty
Why Choose Trend Architect Lite?
No Lag - Real-time neural network processing
No Repainting - Signals appear and stay fixed
Clean Charts - Focus on price action, not indicators
Smart Filtering - AI reduces noise and false signals
Flexible and customizable - Works across all timeframes and instruments
Compatibility
- All Timeframes - 1m to Monthly charts
- All Instruments - Forex, Crypto, Stocks, Futures, Indices
Risk Disclaimer
This indicator is a tool for technical analysis and should not be used as the sole basis for trading decisions. Past performance does not guarantee future results. Always use proper risk management and never risk more than you can afford to lose.
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Updated 3 hours ago
Institutional Analyst Board
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Jul 19
📊 Institutional Analyst Board – Smart Money Confluence Scanner for XAUUSD, Forex, Crypto
🔍 Overview
The Institutional Analyst Board is a complete multi-timeframe smart money toolkit designed for traders who demand clarity, confluence, and precision. It brings together institutional-grade metrics—Order Blocks (OB), Fair Value Gaps (FVG), Liquidity Sweeps, MACD/RSI bias, VWAP positioning, and Break of Structure (BoS)—into a single powerful visual dashboard.
This indicator is especially optimized for Gold (XAUUSD) but is also compatible with Crypto and Forex assets.
🧠 Key Features
✅ Multi-Timeframe Dashboard (5M / 15M / 1H)
✅ Order Block Detection with dynamic zones that extend until broken
✅ Fair Value Gap Detection with clear zone shading and border distinction
✅ MACD + RSI Confluence for momentum and bias alignment
✅ VWAP Positioning to identify premium/discount zones
✅ Liquidity Sweeps (internal/external range breaks)
✅ Killzone Highlighting (Asia / London / New York)
✅ Break of Structure (BoS) with advanced confluence filters
✅ Gold Bias Flags across timeframes (BUY / SELL / NEUTRAL)
✅ Dynamic Price Watermark with real-time data
✅ Fully customizable colors, transparencies, and text labels
🧠 How It Works
The Board uses institutional logic to analyze the chart in real time:
Metric Purpose
OB Zones Highlight potential smart money footprints where price is likely to react.
FVG Zones Identify imbalance areas between buyers and sellers—ideal for mean reversion entries.
MACD/RSI Confirm momentum direction and relative strength confluence.
VWAP Determine whether price is trading at a premium or discount.
Liquidity Sweeps Detect manipulative moves before major reversals.
BoS Mark potential trend reversals, filtered by institutional confluence.
Each signal is computed across 3 timeframes and visualized in a clean board that updates live. You’ll also see labels, alerts, and session overlays for maximum clarity.
📌 Ideal Use Case
This tool is perfect for:
Funded Challenge Traders (FTMO, MyForexFunds, etc.)
Gold scalpers and intraday traders
Crypto price action traders using BTC, ETH, SOL, etc.
Smart Money Concept (SMC) and ICT followers
⚙️ Customization Options
Toggle each module (OB, FVG, VWAP, MACD/RSI, etc.)
Set transparency and color for each zone type
Adjust Killzone timing (Asia, London, NY)
Control board position (Top/Bottom) and metric visibility
📈 Compatible Assets
✅ XAUUSD (optimized)
✅ Forex majors/minors
✅ Crypto pairs (BTC, ETH, SOL, etc.)
✅ Indices (GER40, NASDAQ, SPX with minor adaptation)
🛠️ Requirements
Use on TradingView v5
Set chart time to UTC+0 or UTC+3 for optimal Killzone accuracy
For crypto, redefine Killzone hours if needed (24/7 market)
🧠 Pro Tip
Pair this indicator with volume profile tools, CVD/Delta Flow, or Footprint overlays to build high-confidence trade setups with clear institutional confluence.
Linear Regression Channel Screener [Daveatt]Hello traders
First and foremost, I want to extend a huge thank you to @LonesomeTheBlue for his exceptional Linear Regression Channel indicator that served as the foundation for this screener.
Original work can be found here:
Overview
This project demonstrates how to transform any open-source indicator into a powerful multi-asset screener.
The principles shown here can be applied to virtually any indicator you find interesting.
How to Transform an Indicator into a Screener
Step 1: Identify the Core Logic
First, identify the main calculations of the indicator.
In our case, it's the Linear Regression
Channel calculation:
get_channel(src, len) =>
mid = math.sum(src, len) / len
slope = ta.linreg(src, len, 0) - ta.linreg(src, len, 1)
intercept = mid - slope * math.floor(len / 2) + (1 - len % 2) / 2 * slope
endy = intercept + slope * (len - 1)
dev = 0.0
for x = 0 to len - 1 by 1
dev := dev + math.pow(src - (slope * (len - x) + intercept), 2)
dev
dev := math.sqrt(dev / len)
Step 2: Use request.security()
Pass the function to request.security() to analyze multiple assets:
= request.security(sym, timeframe.period, get_channel(src, len))
Step 3: Scale to Multiple Assets
PineScript allows up to 40 request.security() calls, letting you monitor up to 40 assets simultaneously.
Features of This Screener
The screener provides real-time trend detection for each monitored asset, giving you instant insights into market movements.
It displays each asset's position relative to its middle regression line, helping you understand price momentum.
The data is presented in a clean, organized table with color-coded trends for easy interpretation.
At its core, the screener performs trend detection based on regression slope calculations, clearly indicating whether an asset is in a bullish or bearish trend.
Each asset's price is tracked relative to its middle regression line, providing additional context about trend strength.
The color-coded visual feedback makes it easy to spot changes at a glance.
Built-in alerts notify you instantly when any asset experiences a trend change, ensuring you never miss important market moves.
Customization Tips
You can easily expand the screener by adding more symbols to the symbols array, adapting it to your watchlist.
The regression parameters can be adjusted to match your preferred trading timeframes and sensitivity.
The alert system is already configured to notify you of trend changes, but you can customize the alert messages and conditions to your needs.
Limitations
While powerful, the screener is bound by PineScript's limitation of 40 security calls, capping the maximum number of monitored assets.
Using AI to Help With Conversion
An interesting tip:
You can use AI tools to help convert single-asset indicators to screeners.
Simply provide the original code and ask for assistance in transforming it into a screener format. While the AI output might need some syntax adjustments, it can handle much of the heavy lifting in the conversion process.
Prompt (example) : " Please make a pinescript version 5 screener out of this indicator below or in attachment to scan 20 instruments "
I prefer Claude AI (Opus model) over ChatGPT for pinescript.
Conclusion
This screener transformation technique opens up endless possibilities for market analysis.
By following these steps, you can convert any indicator into a powerful multi-asset scanner, enhancing your trading toolkit significantly.
Remember: The power of a screener lies not just in monitoring multiple assets, but in applying consistent analysis across your entire watchlist in real-time.
Feel free to fork and modify this screener for your own needs.
Happy trading! 🚀📈
Daveatt
