Candle Height & Trend Probability DashboardDescription and Guide
Description:
This Pine Script for TradingView displays a dashboard that calculates the probability of price increases or decreases based on past price movements. It analyzes the last 30 candles (by default) and shows the probabilities for different timeframes (from 1 minute to 1 week). Additionally, it checks volatility using the ATR indicator.
Script Features:
Calculates probabilities of an upward (Up %) or downward (Down %) price move based on past candles.
Displays a dashboard showing probabilities for multiple timeframes.
Color-coded probability display:
Green if the upward probability exceeds a set threshold.
Red if the downward probability exceeds the threshold.
Yellow if neither threshold is exceeded.
Considers volatility using the ATR indicator.
Triggers alerts when probabilities exceed specific values.
How to Use:
Insert the script into TradingView: Copy and paste the script into the Pine Script editor.
Adjust parameters:
lookback: Number of past candles used for calculation (default: 30).
alertThresholdUp & alertThresholdDown: Thresholds for probabilities (default: 51%).
volatilityLength & volatilityThreshold: ATR volatility settings.
dashboardPosition: Choose where the dashboard appears on the chart.
Enable visualization: The dashboard will be displayed over the chart.
Set alerts: The script triggers notifications when probabilities exceed set thresholds.
Statistics
Strategy Stats [presentTrading]Hello! it's another weekend. This tool is a strategy performance analysis tool. Looking at the TradingView community, it seems few creators focus on this aspect. I've intentionally created a shared version. Welcome to share your idea or question on this.
█ Introduction and How it is Different
Strategy Stats is a comprehensive performance analytics framework designed specifically for trading strategies. Unlike standard strategy backtesting tools that simply show cumulative profits, this analytics suite provides real-time, multi-timeframe statistical analysis of your trading performance.
Multi-timeframe analysis: Automatically tracks performance metrics across the most recent time periods (last 7 days, 30 days, 90 days, 1 year, and 4 years)
Advanced statistical measures: Goes beyond basic metrics to include Information Coefficient (IC) and Sortino Ratio
Real-time feedback: Updates performance statistics with each new trade
Visual analytics: Color-coded performance table provides instant visual feedback on strategy health
Integrated risk management: Implements sophisticated take profit mechanisms with 3-step ATR and percentage-based exits
BTCUSD Performance
The table in the upper right corner is a comprehensive performance dashboard showing trading strategy statistics.
Note: While this presentation uses Vegas SuperTrend as the underlying strategy, this is merely an example. The Stats framework can be applied to any trading strategy. The Vegas SuperTrend implementation is included solely to demonstrate how the analytics module integrates with a trading strategy.
⚠️ Timeframe Limitations
Important: TradingView's backtesting engine has a maximum storage limit of 10,000 bars. When using this strategy stats framework on smaller timeframes such as 1-hour or 2-hour charts, you may encounter errors if your backtesting period is too long.
Recommended Timeframe Usage:
Ideal for: 4H, 6H, 8H, Daily charts and above
May cause errors on: 1H, 2H charts spanning multiple years
Not recommended for: Timeframes below 1H with long history
█ Strategy, How it Works: Detailed Explanation
The Strategy Stats framework consists of three primary components: statistical data collection, performance analysis, and visualization.
🔶 Statistical Data Collection
The system maintains several critical data arrays:
equityHistory: Tracks equity curve over time
tradeHistory: Records profit/loss of each trade
predictionSignals: Stores trade direction signals (1 for long, -1 for short)
actualReturns: Records corresponding actual returns from each trade
For each closed trade, the system captures:
float tradePnL = strategy.closedtrades.profit(tradeIndex)
float tradeReturn = strategy.closedtrades.profit_percent(tradeIndex)
int tradeType = entryPrice < exitPrice ? 1 : -1 // Direction
🔶 Performance Metrics Calculation
The framework calculates several key performance metrics:
Information Coefficient (IC):
The correlation between prediction signals and actual returns, measuring forecast skill.
IC = Correlation(predictionSignals, actualReturns)
Where Correlation is the Pearson correlation coefficient:
Correlation(X,Y) = (nΣXY - ΣXY) / √
Sortino Ratio:
Measures risk-adjusted return focusing only on downside risk:
Sortino = (Avg_Return - Risk_Free_Rate) / Downside_Deviation
Where Downside Deviation is:
Downside_Deviation = √
R_i represents individual returns, T is the target return (typically the risk-free rate), and n is the number of observations.
Maximum Drawdown:
Tracks the largest percentage drop from peak to trough:
DD = (Peak_Equity - Trough_Equity) / Peak_Equity * 100
🔶 Time Period Calculation
The system automatically determines the appropriate number of bars to analyze for each timeframe based on the current chart timeframe:
bars_7d = math.max(1, math.round(7 * barsPerDay))
bars_30d = math.max(1, math.round(30 * barsPerDay))
bars_90d = math.max(1, math.round(90 * barsPerDay))
bars_365d = math.max(1, math.round(365 * barsPerDay))
bars_4y = math.max(1, math.round(365 * 4 * barsPerDay))
Where barsPerDay is calculated based on the chart timeframe:
barsPerDay = timeframe.isintraday ?
24 * 60 / math.max(1, (timeframe.in_seconds() / 60)) :
timeframe.isdaily ? 1 :
timeframe.isweekly ? 1/7 :
timeframe.ismonthly ? 1/30 : 0.01
🔶 Visual Representation
The system presents performance data in a color-coded table with intuitive visual indicators:
Green: Excellent performance
Lime: Good performance
Gray: Neutral performance
Orange: Mediocre performance
Red: Poor performance
█ Trade Direction
The Strategy Stats framework supports three trading directions:
Long Only: Only takes long positions when entry conditions are met
Short Only: Only takes short positions when entry conditions are met
Both: Takes both long and short positions depending on market conditions
█ Usage
To effectively use the Strategy Stats framework:
Apply to existing strategies: Add the performance tracking code to any strategy to gain advanced analytics
Monitor multiple timeframes: Use the multi-timeframe analysis to identify performance trends
Evaluate strategy health: Review IC and Sortino ratios to assess predictive power and risk-adjusted returns
Optimize parameters: Use performance data to refine strategy parameters
Compare strategies: Apply the framework to multiple strategies to identify the most effective approach
For best results, allow the strategy to generate sufficient trade history for meaningful statistical analysis (at least 20-30 trades).
█ Default Settings
The default settings have been carefully calibrated for cryptocurrency markets:
Performance Tracking:
Time periods: 7D, 30D, 90D, 1Y, 4Y
Statistical measures: Return, Win%, MaxDD, IC, Sortino Ratio
IC color thresholds: >0.3 (green), >0.1 (lime), <-0.1 (orange), <-0.3 (red)
Sortino color thresholds: >1.0 (green), >0.5 (lime), <0 (red)
Multi-Step Take Profit:
ATR multipliers: 2.618, 5.0, 10.0
Percentage levels: 3%, 8%, 17%
Short multiplier: 1.5x (makes short take profits more aggressive)
Stop loss: 20%
Backtesting Stats (Altrady)Track and analyze your backtesting results directly on your chart.
This indicator simplifies manual backtesting by summarizing your trades in a clear, structured table. Enter your R-values (one per line) in the text area, and instantly see:
✅ Trade list – All entries displayed with color-coded wins/losses.
✅ Key stats – Total trades, win rate, and RR sum in the top row.
✅ Quick insights – Spot trends, refine your strategy, and track performance without spreadsheets.
How to Use
1️⃣ Open settings and enter R-values, one per line (e.g., 2.5, -1, 3.2) along with short comments (bad entry, counter trend, etc)
2️⃣ View the table in the top-right corner of your chart.
3️⃣ Analyze your results, adjust your strategy, and improve consistency.
Perfect for manual backtesters who want a fast, no-spreadsheet solution. 🚀
Spent Output Profit Ratio (SOPR) Z-Score | [DeV]SOPR Z-Score
The Spent Output Profit Ratio (SOPR) is an advanced on-chain metric designed to provide deep insights into Bitcoin market dynamics by measuring the ratio between the combined USD value of all Bitcoin outputs spent on a given day and their combined USD value at the time of creation (typically, their purchase price). As a member of the Realized Profit/Loss family of metrics, SOPR offers a window into aggregate seller behavior, effectively representing the USD amount received by sellers divided by the USD amount they originally paid. This indicator enhances this metric by normalizing it into a Z-Score, enabling a statistically robust analysis of market sentiment relative to historical trends, augmented by a suite of customizable features for precision and visualization.
SOPR Settings -
Lookback Length (Default: 150 days): Determines the historical window for calculating the Z-Score’s mean and standard deviation. A longer lookback captures broader market cycles, providing a stable baseline for identifying extreme deviations, which is particularly valuable for long-term strategic analysis.
Smoothing Period (Default: 100 days): Applies an EMA to the raw SOPR, balancing responsiveness to recent changes with noise reduction. This extended smoothing period ensures the indicator focuses on sustained shifts in seller behavior, ideal for institutional-grade trend analysis.
Moving Average Settings -
MA Lookback Length (Default: 90 days): Sets the period for the Z-Score’s moving average, offering a shorter-term trend signal relative to the 150-day Z-Score lookback. This contrast enhances the ability to detect momentum shifts within the broader context.
MA Type (Default: EMA): Provides six moving average types, from the simple SMA to the volume-weighted VWMA. The default EMA strikes an optimal balance between smoothness and responsiveness, while alternatives like HMA (Hull) or VWMA (volume-weighted) allow for specialized applications, such as emphasizing recent price action or incorporating volume dynamics.
Display Settings -
Show Moving Average (Default: True): Toggles the visibility of the Z-Score MA plot, enabling users to focus solely on the raw Z-Score when preferred.
Show Background Colors (Default: True): Activates dynamic background shading, enhancing visual interpretation of market regimes.
Background Color Source (Default: SOPR): Allows users to tie the background color to either the SOPR Z-Score’s midline (reflecting adjustedZScore > 0) or the MA’s trend direction (zScoreMA > zScoreMA ). This dual-source option provides flexibility to align the visual context with the primary analytical focus.
Analytical Applications -
Bear Market Resistance: When the Z-Score approaches or exceeds zero (raw SOPR near 1), it often signals resistance as sellers rush to exit at break-even, a pattern historically observed during downtrends. A rising Z-Score MA crossing zero can confirm this pressure.
Bull Market Support: Conversely, a Z-Score dropping below zero in uptrends indicates reluctance to sell at a loss, forming support as sell pressure diminishes. The MA’s bullish coloring reinforces confirmation of renewed buying interest.
Extreme Deviations: Values significantly above or below zero highlight overbought or oversold conditions, respectively, offering opportunities for contrarian positioning when paired with other on-chain or price-based metrics.
Econometrica by [SS]This is Econometrica, an indicator that aims to bridge a big gap between the resources available for analysis of fundamental data and its impact on tickers and price action.
I have noticed a general dearth of available indicators that offer insight into how fundamentals impact a ticker and provide guidance on how they these economic factors influence ticker behaviour.
Enter Econometrica. Econometrica is a math based indicator that aims to co-integrate and model indicator price action in relation to critical economic metrics.
Econometrica supports the following US based economic data:
CPI
Non-Farm Payroll
Core Inflation
US Money Supply
US Central Bank Balance Sheet
GDP
PCE
Let's go over the functions of Econometrica.
Creating a Regression Cointegrated Model
The first thing Econometrica does is creates a co-integrated regression, as you see in the main chart, predicting ticker value ranges from fundamental economic data.
You can visualize this in the main chart above, but here are some other examples:
SPY vs Core Inflation:
BA vs PCE:
QQQ vs US Balance Sheet:
The band represents the anticipated range the ticker should theoretically fall in based on the underlying economic value. The indicator will breakdown the relationship between the economic indicator and the ticker more precisely. In the images above, you can see how there are some metrics provided, including Stationairty, lagged correlation, Integrated Correlation and R2. Let's discuss these very briefly:
Stationarity: checks to ensure that the relationship between the economic indicator and ticker is stationary. Stationary data is important for making unbiased inferences and projections, so having data that is stationary is valuable.
Lagged Correlation: This is a very interesting metric. Lagged correlation means whether there is a delay in the economic indicator and the response of the ticker. Typically, you will observed a lagged correlation between an economic indicator and price of a ticker, as it can take some time for economic changes to reach the market. This lagged correlation will provide you with how long it takes for the economic indicator to catch up with the ticker in months.
Integrated Correlation: This metric tells you how good of a fit the regression bands are in relation to the ticker price. A higher correlation, means the model is better at consistent and accurate information about the anticipated range for the ticker in relation to the economic indicator.
R2: Provides information on the variance and degree of model fit. A high R2 value means that the model is capable of explaining a large amount of variance between the economic indicator and the ticker price action.
Explaining the Relationship
Owning to the fact that the indicator is a bit on the mathy side (it has to be to do this kind of task), I have included ability for the indicator to explain and make suggestions based on the underlying data. It can assess the model's fit and make suggestions for tweaking. It can also explain the implications of the data being presented in the model.
Here is an example with QQQ and the US Balance Sheet:
This helps to simplify and interpret the results you are looking at.
Forecasting the Economic Indicator
In addition to assessing the economic indicator's impact on the ticker, the indicator is also capable of forecasting out the economic indicator over the next 25 releases.
Here is an example of the CPI forecast:
Overall use of the indicator
The indicator is meant to bridge the gap between Technical Analysis and Fundamental Analysis.
Any trader who is attune to fundamentals would benefit from this, as this provides you with objective data on how and to what extent fundamental and economic data impacts tickers.
It can help affirm hypothesis and dispel myths objectively.
It also omits the need from having to perform these types of analyses outside of Tradingview (i.e. in excel, R or Python), as you can get the data in just a few licks of enabling the indicator.
Conclusion
I have tried to make this indicator as user friendly as possible. Though it uses a lot of math, it is fairly straight forward to interpret.
The band plotted can be considered the fair market value or FMV of the ticker based on the underlying economic data, provided the indicator tells you that the relationship is significant (and it will blatantly give you this information verbatim, you don't have to interpret the math stuff).
This is US economic data only. It does not pull economic data from other countries. You can absolutely see how US economic data impacts other markets like the TSX, BANKNIFTY, NIFTY, DAX etc. but the indicator is only pulling US economic data.
That is it!
I hope you enjoy it and find this helpful!
Thanks everyone and safe trades as always 🚀🚀🚀
Trade Ladder Pro: Compounding & Risk ManagerTrade Ladder Pro: Compounding & Risk Manager
Inspired by the popular $20 to $52,000 trading challenge, this tool is designed to help you scale your trading account using systematic compounding and enhanced risk management techniques. Whether you’re aiming for disciplined growth or fine-tuning your risk/reward, Trade Ladder Pro offers a flexible approach to visualizing your trade levels.
How to Use:
Inputs:
Compounding Mode:
Set your starting balance, final balance goal, number of trades, and current trade level. You can move to the next trade after a successful trade in settings. The entries are not signals. They are there to help manage risk.
The script calculates the necessary compounding factor to grow your balance across the defined trades.
Risk Management Mode:
In addition to the above, specify a risk percentage and risk/reward ratio.
Input an entry price (or leave it at 0 to use the current price) to automatically compute the stop loss and take profit levels.
Display Options:
Choose the table’s position on the chart (e.g., Top Right, Top Left, Bottom Right, Bottom Left).
Pick between a vertical or horizontal layout for a display that suits your workflow.
Results:
The table will display the trade level, starting balance, risk amount, entry price, take profit, and (if in Risk Management mode) stop loss along with the projected ending balance.
Community & Feedback:
Your feedback is invaluable! Please share any tips or report any errors you encounter so we can continue to improve this tool. Happy trading!
Smart % Levels📈 Smart % Levels – Visualize Significant Percentage Moves
What it does:
This indicator plots horizontal levels based on a percentage change from the previous day's close (or open, if selected). It allows traders to visualize price movements relative to meaningful thresholds like ±1%, ±2%, etc.
What makes it different:
Unlike other level indicators, Smart % Levels only displays the relevant levels based on current price action. This avoids clutter by showing only the levels that are being approached or crossed by the current price. It's a clean and dynamic way to visualize key price zones for intraday analysis.
How it works:
- Select between using the previous day's Close or Open as the reference
- Choose the percentage spacing between levels (e.g., 1%, 0.5%, etc.)
- Enable optional labels to see the exact percentage of each level
- Automatically filters levels to only show those between yesterday's price and today's current price
- Includes customization for colors, line styles, widths, and opacity
Best for:
Day traders and scalpers who want a quick, clean view of how far the current price has moved from yesterday’s reference, without being overwhelmed by unnecessary lines.
Extra notes:
- The levels are recalculated each day at the market open
- All graphics reset at the start of each session to maintain clarity
- This script avoids repainting by only plotting levels relative to available historical data (no lookahead)
This tool is for informational purposes only and should not be considered as financial advice. Always do your own research before making trading decisions.
ATR & PTR TableThe ATR & PTR Table Indicator displays a dynamic table that provides Average True Range (measures market volatility over 1D, 1W, and 1M timeframes), Price trading range (difference between the high and low prices over the same periods) & percentage of the typical range that has been traded. This indicator will help traders identify potential breakout zones and assess volatility across multiple timeframes.
This had been optimized to show ATR and PTR on every time frame. The (1D) represents ATR on whatever timeframe you are currently on.
ML Deep Regression Pro (TechnoBlooms)ML Deep Regression Pro is a machine-learning-inspired trading indicator that integrates Polynomial Regression, Linear Regression and Statistical Deviation models to provide a powerful, data-driven approach to market trend analysis.
Designed for traders, quantitative analysts and developers, this tool transforms raw market data into predictive trend insights, allowing for better decision-making and trend validation.
By leveraging statistical regression techniques, ML Deep Regression Pro eliminates market noise and identifies key trend shifts, making it a valuable addition to both manual and algorithmic trading strategies.
REGRESSION ANALYSIS
Regression is a statistical modeling technique used in machine learning and data science to identify patterns and relationships between variables. In trading, it helps detect price trends, reversals and volatility changes by fitting price data into a predictive model.
1. Linear Regression -
The most widely used regression model in trading, providing a best-fit plotted line to track price trends.
2. Polynomial Regression -
A more advanced form of regression that fits curved price structures, capturing complex market cycles and improving trend forecasting accuracy.
3. Standard Deviation Bands -
Based on regression calculations, these bands measure price dispersion and identify overbought/ oversold conditions, similar to Bollinger Bands. By default, these lines are hidden and user can make it visible through Settings.
KEY FEATURES :-
✅ Hybrid Regression Engine – Combines Linear and Polynomial Regression to detect market trends with greater accuracy.
✅ Dynamic Trend Bias Analysis – Identifies bullish & bearish market conditions using real-time regression models.
✅ Standard Deviation Bands – Measures price volatility and potential reversals with an advanced deviation model.
✅ Adaptive EMA Crossover Signals – Generates buy/sell signals when price momentum shifts relative to the regression trend.
HBND ReferenceChart the HBND as an index based on weighting found on the HBND Etf website. For best results display the adjusted close since HBND is a high yielding fund. The weightings have to be updated manually.
There are three display options:
1. Normalize the index relative to the symbol on the chart (presumably HBND) and this is the default.
2. Percentage change relative to the first bar of the index
3. The raw value which will be the tlt price * tlt percentage weighting + vglt price * vglt percentage weighting + edv percentage weighting * edv price.
Buy on 5% dip strategy with time adjustment
This script is a strategy called "Buy on 5% Dip Strategy with Time Adjustment 📉💡," which detects a 5% drop in price and triggers a buy signal 🔔. It also automatically closes the position once the set profit target is reached 💰, and it has additional logic to close the position if the loss exceeds 14% after holding for 230 days ⏳.
Strategy Explanation
Buy Condition: A buy signal is triggered when the price drops 5% from the highest price reached 🔻.
Take Profit: The position is closed when the price hits a 1.22x target from the average entry price 📈.
Forced Sell Condition: If the position is held for more than 230 days and the loss exceeds 14%, the position is automatically closed 🚫.
Leverage & Capital Allocation: Leverage is adjustable ⚖️, and you can set the percentage of capital allocated to each trade 💸.
Time Limits: The strategy allows you to set a start and end time ⏰ for trading, making the strategy active only within that specific period.
Code Credits and References
Credits: This script utilizes ideas and code from @QuantNomad and jangdokang for the profit table and algorithm concepts 🔧.
Sources:
Monthly Performance Table Script by QuantNomad:
ZenAndTheArtOfTrading's Script:
Strategy Performance
This strategy provides risk management through take profit and forced sell conditions and includes a performance table 📊 to track monthly and yearly results. You can compare backtest results with real-time performance to evaluate the strategy's effectiveness.
The performance numbers shown in the backtest reflect what would have happened if you had used this strategy since the launch date of the SOXL (the Direxion Daily Semiconductor Bull 3x Shares ETF) 📅. These results are not hypothetical but based on actual performance from the day of the ETF’s launch 📈.
Caution ⚠️
No Guarantee of Future Results: The results are based on historical performance from the launch of the SOXL ETF, but past performance does not guarantee future results. It’s important to approach with caution when applying it to live trading 🔍.
Risk Management: Leverage and capital allocation settings are crucial for managing risk ⚠️. Make sure to adjust these according to your risk tolerance ⚖️.
VBSMI with Dynamic Bands and MTF Screener by QTX Algo SystemsVolatility Based SMI with Dynamic Bands & MTF Screener by QTX Algo Systems
Overview
This enhanced version of the Volatility Based SMI with Dynamic Bands (VBSMI) expands on the original design by integrating a Multi-Timeframe (MTF) Screener. It maintains the core momentum detection and volatility-responsive adjustments of the standard VBSMI while providing expanded multi-timeframe analysis across multiple assets in a tabular format.
By allowing users to track momentum shifts, reversals, and trend conditions across multiple timeframes and multiple assets, this version enhances market awareness and helps traders make more informed decisions.
How It Works
Enhanced SMI Calculation
The core SMI calculation uses double smoothing through Exponential Moving Averages (EMAs) to refine price movements.
Inputs for Smoothing K and Smoothing D control how much noise is filtered.
A final SMI EMA is applied to help confirm momentum direction.
Adaptive Volatility Scaling
A fixed Bollinger Band Width Percentile (BBWP) calculation is used to create an Adaptive Adjustment Factor for the SMI.
This ensures the oscillator adapts to current volatility levels, making signals more context-aware.
Dynamic Threshold Adjustment
The overbought and oversold thresholds (default 50 and -50) adjust in real time based on market conditions.
These adjustments use three proprietary factors:
Trend Lookback Period – Determines historical trend strength using a VWMA-based comparison.
Upper & Lower Band Tilt Strength – Controls how aggressively the bands shift in response to trends.
Opposite Band Compression – Adjusts the speed of threshold contraction when trends reverse, making it more responsive.
Multi-Timeframe and Multi-Asset Screener (MTF) – New Feature
The integrated MTF Screener provides a real-time overview of the VBSMI's conditions across multiple timeframes and assets.
It includes:
✅ User-selectable timeframes (Default: 1H, 4H, 1D, 3D, 1W, 1M).
✅ Up to 6 additional tickers for multi-asset analysis.
✅ Real-time VBSMI color-coded conditions for easier signal interpretation.
How to Read the MTF Screener Table
Each cell in the table provides a momentum reading based on VBSMI conditions in different timeframes:
🟢 Green Background → Oversold Condition (Potential Buy Zone)
🔴 Red Background → Overbought Condition (Potential Sell Zone)
📊 Label: "Up" or "Down" → Shows whether VBSMI is above or below its EMA.
🟠 Orange Background → VBSMI crossovers from oversold/overbought conditions
How to Use & Adjust Inputs
Momentum Confirmation & Reversals
Use the dynamically adjusting thresholds to confirm when momentum is overextended or entering a new trend phase.
Monitor crossovers between the SMI and its EMA—these can be potential reversal or trend continuation signals.
Multi-Timeframe Trend Confirmation
Look for alignment across multiple timeframes in the MTF Screener (e.g., if the 1H, 4H, and 1D all show green, it strengthens a bullish case).
Use the multi-ticker feature to see how different assets align with your primary asset’s momentum signals.
Fine-Tuning the Inputs
Smoothing K & D: Controls how much the SMI is smoothed. Lower values make the indicator respond faster but can introduce noise, while higher values produce smoother signals with a slight delay.
SMI EMA Length: Adjusts the sensitivity of the exponential moving average applied to the SMI. A lower value makes the EMA react more quickly, while a higher value slows it down for more stable signals.
Trend Lookback Period: Defines how far back the indicator looks to assess trend strength. A shorter lookback makes it more reactive to recent price movements, while a longer period smooths out fluctuations for a broader trend perspective.
Band Tilt Strengths: Determines how much the overbought and oversold levels shift in response to market trends. Increasing this value causes the thresholds to adjust more aggressively, making the indicator more sensitive to trend direction.
Opposite Band Compression: Controls how quickly the opposite band contracts when a trend reversal occurs. A higher value results in faster compression, making the indicator more responsive to sudden market shifts.
What Makes This Unique?
Unlike traditional Stochastic Momentum Index (SMI) indicators, which rely on fixed overbought/oversold levels, this version:
✔ Adjusts the SMI based on relevant volatility
✔ Adapts thresholds based on volatility & trend strength
✔ Incorporates multi-timeframe screening for trend confirmation
✔ Uses an MTF table for real-time, multi-asset tracking
Disclaimer
This indicator is for educational purposes only and is meant to support trading strategies—not replace independent analysis.
No financial guarantees are provided. Past performance does not guarantee future results. Always use proper risk management.
Enhanced Bar Count IndicatorThe Enhanced Bar Count Indicato r is a versatile tool designed for traders who follow price action methodologies, particularly those inspired by Al Brooks. Built for TradingView and optimized for 5-minute charts during Regular Trading Hours, this indicator combines bar counting with multiple analytical features to help traders identify key market moments, trends, and potential reversal points. While it excels on intraday timeframes, its customizable settings make it adaptable to various trading styles and timeframes.
Key Features
Bar Counting and Diamond Placement
At its core, the indicator numbers each bar starting from the beginning of the trading day, helping traders keep track of bar sequences without manual counting. It highlights specific bars—such as the 7th, 18th, 40th, 48th, 67th, and 73rd bars—with colored diamonds. These bars are significant in Al Brooks’ trading approach for identifying potential reversals or key price action setups:
Bar 7 (Purple Diamond): Occurring around 35 minutes into the session, this bar often marks the end of the initial market open phase, signaling potential opening reversals or the formation of double tops/bottoms.
Bar 18 (Green Diamond): Statistically significant for marking the high or low of the day, making it a critical point for assessing potential trend reversals.
Bar 40 (Red Diamond): Positioned around midday, this bar is often associated with reversal opportunities as the market shifts from morning to afternoon trading.
Bar 48 (Purple Diamond): Around 11:50 AM EST, this bar signals the start of the afternoon swing setup, offering opportunities for midday swing trades.
Bar 67 (Purple Diamond): Appearing in the last hour (around 2:35 PM EST), this bar is key for late-day swing setups, often used for end-of-day strategies like buy-the-close or sell-the-close.
Bar 73 (Purple Diamond): Tied to a 12:30 PM PDT (3:30 PM EST) setup, this bar is significant for US market traders as a late-session decision point for trend continuation or reversal.
This feature allows traders to spot these critical bars at a glance, aligning with Al Brooks’ methodology for intraday trading.
Customizable 10-Period EMA for Scalping
A customizable 10-period Exponential Moving Average (EMA) is included to help scalpers quickly assess short-term trends. By default, it’s set to 10 periods, but users can adjust both the period and color to suit their strategy. When the price is above the EMA, it suggests an uptrend; below it, a downtrend. Scalpers can use pullbacks to the EMA as potential entry points in the direction of the trend. While optimized for 2-minute charts, it also provides valuable context on 5-minute charts for intraday traders.
Multi-Timeframe 20-Period EMAs
To provide a broader trend perspective, the indicator plots 20-period EMAs from three different timeframes—5-minute, 15-minute, and 60-minute—directly on the chart. This allows traders to see how the trend aligns across multiple timeframes, which is crucial for confirming the strength and direction of a move. Each EMA is toggleable and color-coded:
Green for 5m
Orange for 15m
Red for 60m
For instance, if all three EMAs are sloping upwards, it reinforces a strong uptrend, increasing the probability of successful trades in that direction.
Inside/Outside Bar Detection
The indicator automatically detects and marks inside bars with an 'i' and outside bars with an 'O' above the respective bars. Inside bars (where the high is lower than the previous high and the low is higher than the previous low) often signal consolidation and potential breakouts. Outside bars (where the high is higher and the low is lower than the previous bar) indicate increased volatility and possible trend reversals or continuations. These markers help traders quickly spot these patterns, which are essential for timing entries and exits in both range-bound and trending markets.
50% Pullback Retracement
Dynamic support and resistance levels are provided through the 50% retracement (midpoint) of the current and previous day’s price ranges. These levels are plotted as horizontal lines:
A solid line for the current day’s midpoint.
A dashed line for the previous day’s midpoint.
The lines are color-coded—green if below the current price and red if above—helping traders visualize potential reversal or continuation zones. This feature aligns with Fibonacci retracement principles and is particularly useful for intraday traders looking to identify areas where price might stall or reverse.
Customization and Usage
All features in the indicator are toggleable, allowing traders to enable or disable them based on their preferences. The settings are organized into groups—such as 'Bar Counting,' '10 EMA Scalp,' and 'Multi-Timeframe EMAs'—for easy navigation. This flexibility ensures that the indicator can be tailored to various trading styles, from scalping to swing trading. Traders can experiment with different combinations of features to find what works best for their strategy.
The Enhanced Bar Count Indicator is a comprehensive tool that brings together bar counting, trend analysis, pattern recognition, and dynamic support/resistance levels. Inspired by Al Brooks’ price action methodology, it offers traders a multifaceted approach to analyzing the markets. With its customizable and toggleable features, it adapts to different trading styles and timeframes, making it a valuable addition to any trader’s toolkit. Best of all, it’s available for free to the TradingView community—feel free to explore, customize, and integrate it into your trading strategy.
ADX BoxDescription:
The ADX Box indicator provides traders with a quick and intuitive way to monitor the current trend strength based on the Average Directional Index (ADX), calculated with a customisable period (default: 7 periods).
This compact indicator neatly displays the current ADX value rounded to one decimal place, along with a clear directional arrow:
Green upward triangle (▲): Indicates that ADX is rising above its moving average, signaling increasing trend strength.
Red downward triangle (▼): Indicates that ADX is declining below its moving average, signaling weakening trend strength.
Key Features:
Small and clean visual representation.
Dynamically updates in real-time directly on the chart.
Ideal for quick trend strength assessment without cluttering your workspace.
Recommended Usage:
Quickly identifying whether market trends are strengthening or weakening.
Enhancing decision-making for trend-following or breakout trading strategies.
Complementing other indicators such as ATR boxes for volatility measurement.
Feel free to use, share, and incorporate this indicator into your trading setups for clearer insights and more confident trading decisions!
Correlation TableThis indicator displays a vertical table that shows the correlation between the asset currently loaded on the chart and up to 32 selected trading pairs. It offers the following features:
Chart-Based Correlation: Correlations are calculated based on the asset you have loaded in your chart, providing relevant insights for your current market focus.
Configurable Pairs: Choose from a list of 32 symbols (e.g., AUDUSD, EURUSD, GBPUSD, etc.) with individual checkboxes to include or exclude each pair in the correlation analysis.
Custom Correlation Length: Adjust the lookback period for the correlation calculation to suit your analysis needs.
Optional EMA Smoothing: Enable an Exponential Moving Average (EMA) on the price data, with a configurable EMA length, to smooth the series before calculating correlations.
Color-Coded Output: The table cells change color based on the correlation strength and direction—neutral, bullish (green), or bearish (red)—making it easy to interpret at a glance.
Clear Table Layout: The indicator outputs a neatly organized vertical table with headers for "Pair" and "Correlation," ensuring the information is displayed cleanly and is easy to understand.
Ideal for traders who want a quick visual overview of how different instruments correlate with their current asset, this tool supports informed multi-asset analysis
ITALIANO:
Questo indicatore visualizza una tabella verticale che mostra la correlazione tra l'asset attualmente caricato sul grafico e fino a 32 coppie di trading selezionate. Offre le seguenti funzionalità:
Correlazione basata sul grafico: le correlazioni vengono calcolate in base all'asset caricato nel grafico, fornendo informazioni pertinenti per il tuo attuale focus di mercato.
Coppie configurabili: scegli da un elenco di 32 simboli (ad esempio, AUDUSD, EURUSD, GBPUSD, ecc.) con caselle di controllo individuali per includere o escludere ciascuna coppia nell'analisi della correlazione.
Lunghezza di correlazione personalizzata: regola il periodo di lookback per il calcolo della correlazione in base alle tue esigenze di analisi.
Smoothing EMA opzionale: abilita una media mobile esponenziale (EMA) sui dati dei prezzi, con una lunghezza EMA configurabile, per smussare la serie prima di calcolare le correlazioni.
Output codificato a colori: le celle della tabella cambiano colore in base alla forza e alla direzione della correlazione, neutra, rialzista (verde) o ribassista (rosso), rendendola facile da interpretare a colpo d'occhio.
Clear Table Layout: l'indicatore genera una tabella verticale ordinatamente organizzata con intestazioni per "Coppia" e "Correlazione", assicurando che le informazioni siano visualizzate in modo chiaro e siano facili da comprendere.
Ideale per i trader che desiderano una rapida panoramica visiva di come diversi strumenti siano correlati con il loro asset corrente, questo strumento supporta un'analisi multi-asset informata
Standard Deviation (fadi)The Standard Deviation indicator uses standard deviation to map out price movements. Standard deviation measures how much prices stray from their average—small values mean steady trends, large ones mean wild swings. Drawing from up to 20 years of data, it plots key levels using customizable Fibonacci lines tied to that standard deviation, giving traders a snapshot of typical price behavior.
These levels align with a bell curve: about 68% of price moves stay within 1 standard deviation, 95% within roughly 2, and 99.7% within roughly 3. When prices break past the 1 StDev line, they’re outliers—only 32% of moves go that far. Prices often snap back to these lines or the average, though the reversal might not happen the same day.
How Traders Use It
If prices surge past the 1 StDev line, traders might wait for momentum to fade, then trade the pullback to that line or the average, setting a target and stop.
If prices dip below, they might buy, anticipating a bounce—sometimes a day or two later. It’s a tool to spot overstretched prices likely to revert and/or measure the odds of continuation.
Settings
Higher Timeframe: Sets the Higher Timeframe to calculate the Standard Deviation for
Show Levels for the Last X Days: Displays levels for the specified number of days.
Based on X Period: Number of days to calculate standard deviation (e.g., 20 years ≈ 5,040 days). Larger periods smooth out daily level changes.
Mirror Levels on the Other Side: Plots symmetric positive and negative levels around the average.
Fibonacci Levels Settings: Defines which levels and line styles to show. With mirroring, negative values aren’t needed.
Background Transparency: Turn on Background color derived from the level colors with the specified transparency
Overrides: Lets advanced users input custom standard deviations for specific tickers (e.g., NQ1! at 0.01296).
StatPivot- Dynamic Range Analyzer - indicator [PresentTrading]Hello everyone! In the following few open scripts, I would like to share various statistical tools that benefit trading. For this time, it is a powerful indicator called StatPivot- Dynamic Range Analyzer that brings a whole new dimension to your technical analysis toolkit.
This tool goes beyond traditional pivot point analysis by providing comprehensive statistical insights about price movements, helping you identify high-probability trading opportunities based on historical data patterns rather than subjective interpretations. Whether you're a day trader, swing trader, or position trader, StatPivot's real-time percentile rankings give you a statistical edge in understanding exactly where current price action stands within historical contexts.
Welcome to share your opinions! Looking forward to sharing the next tool soon!
█ Introduction and How it is Different
StatPivot is an advanced technical analysis tool that revolutionizes retracement analysis. Unlike traditional pivot indicators that only show static support/resistance levels, StatPivot delivers dynamic statistical insights based on historical pivot patterns.
Its key innovation is real-time percentile calculation - while conventional tools require new pivot formations before updating (often too late for trading decisions), StatPivot continuously analyzes where current price stands within historical retracement distributions.
Furthermore, StatPivot provides comprehensive statistical metrics including mean, median, standard deviation, and percentile distributions of price movements, giving traders a probabilistic edge by revealing which price levels represent statistically significant zones for potential reversals or continuations. By transforming raw price data into statistical insights, StatPivot helps traders move beyond subjective price analysis to evidence-based decision making.
█ Strategy, How it Works: Detailed Explanation
🔶 Pivot Point Detection and Analysis
The core of StatPivot's functionality begins with identifying significant pivot points in the price structure. Using the parameters left and right, the indicator locates pivot highs and lows by examining a specified number of bars to the left and right of each potential pivot point:
Copyp_low = ta.pivotlow(low, left, right)
p_high = ta.pivothigh(high, left, right)
For a point to qualify as a pivot low, it must have left higher lows to its left and right higher lows to its right. Similarly, a pivot high must have left lower highs to its left and right lower highs to its right. This approach ensures that only significant turning points are recognized.
🔶 Percentage Change Calculation
Once pivot points are identified, StatPivot calculates the percentage changes between consecutive pivot points:
For drops (when a pivot low is lower than the previous pivot low):
CopydropPercent = (previous_pivot_low - current_pivot_low) / previous_pivot_low * 100
For rises (when a pivot high is higher than the previous pivot high):
CopyrisePercent = (current_pivot_high - previous_pivot_high) / previous_pivot_high * 100
These calculations quantify the magnitude of each market swing, allowing for statistical analysis of historical price movements.
🔶 Statistical Distribution Analysis
StatPivot computes comprehensive statistics on the historical distribution of drops and rises:
Average (Mean): The arithmetic mean of all recorded percentage changes
CopyavgDrop = array.avg(dropValues)
Median: The middle value when all percentage changes are arranged in order
CopymedianDrop = array.median(dropValues)
Standard Deviation: Measures the dispersion of percentage changes from the average
CopystdDevDrop = array.stdev(dropValues)
Percentiles (25th, 75th): Values below which 25% and 75% of observations fall
Copyq1 = array.get(sorted, math.floor(cnt * 0.25))
q3 = array.get(sorted, math.floor(cnt * 0.75))
VaR95: The maximum expected percentage drop with 95% confidence
Copyvar95D = array.get(sortedD, math.floor(nD * 0.95))
Coefficient of Variation (CV): Measures relative variability
CopycvD = stdDevDrop / avgDrop
These statistics provide a comprehensive view of market behavior, enabling traders to understand the typical ranges and extreme moves.
🔶 Real-time Percentile Ranking
StatPivot's most innovative feature is its real-time percentile calculation. For each current price, it calculates:
The percentage drop from the latest pivot high:
CopycurrentDropPct = (latestPivotHigh - close) / latestPivotHigh * 100
The percentage rise from the latest pivot low:
CopycurrentRisePct = (close - latestPivotLow) / latestPivotLow * 100
The percentile ranks of these values within the historical distribution:
CopyrealtimeDropRank = (count of historical drops <= currentDropPct) / total drops * 100
This calculation reveals exactly where the current price movement stands in relation to all historical movements, providing crucial context for decision-making.
🔶 Cluster Analysis
To identify the most common retracement zones, StatPivot performs a cluster analysis by dividing the range of historical drops into five equal intervals:
CopyrangeSize = maxVal - minVal
For each interval boundary:
Copyboundaries = minVal + rangeSize * i / 5
By counting the number of observations in each interval, the indicator identifies the most frequently occurring retracement zones, which often serve as significant support or resistance areas.
🔶 Expected Price Targets
Using the statistical data, StatPivot calculates expected price targets:
CopytargetBuyPrice = close * (1 - avgDrop / 100)
targetSellPrice = close * (1 + avgRise / 100)
These targets represent statistically probable price levels for potential entries and exits based on the average historical behavior of the market.
█ Trade Direction
StatPivot functions as an analytical tool rather than a direct trading signal generator, providing statistical insights that can be applied to various trading strategies. However, the data it generates can be interpreted for different trade directions:
For Long Trades:
Entry considerations: Look for price drops that reach the 70-80th percentile range in the historical distribution, suggesting a statistically significant retracement
Target setting: Use the Expected Sell price or consider the average rise percentage as a reasonable target
Risk management: Set stop losses below recent pivot lows or at a distance related to the statistical volatility (standard deviation)
For Short Trades:
Entry considerations: Look for price rises that reach the 70-80th percentile range, indicating an unusual extension
Target setting: Use the Expected Buy price or average drop percentage as a target
Risk management: Set stop losses above recent pivot highs or based on statistical measures of volatility
For Range Trading:
Use the most common drop and rise clusters to identify probable reversal zones
Trade bounces between these statistically significant levels
For Trend Following:
Confirm trend strength by analyzing consecutive higher pivot lows (uptrend) or lower pivot highs (downtrend)
Use lower percentile retracements (20-30th percentile) as entry opportunities in established trends
█ Usage
StatPivot offers multiple ways to integrate its statistical insights into your trading workflow:
Statistical Table Analysis: Review the comprehensive statistics displayed in the data table to understand the market's behavior. Pay particular attention to:
Average drop and rise percentages to set reasonable expectations
Standard deviation to gauge volatility
VaR95 for risk assessment
Real-time Percentile Monitoring: Watch the real-time percentile display to see where the current price movement stands within the historical distribution. This can help identify:
Extreme movements (90th+ percentile) that might indicate reversal opportunities
Typical retracements (40-60th percentile) that might continue further
Shallow pullbacks (10-30th percentile) that might represent continuation opportunities in trends
Support and Resistance Identification: Utilize the plotted pivot points as key support and resistance levels, especially when they align with statistically significant percentile ranges.
Target Price Setting: Use the expected buy and sell prices calculated from historical averages as initial targets for your trades.
Risk Management: Apply the statistical measurements like standard deviation and VaR95 to set appropriate stop loss levels that account for the market's historical volatility.
Pattern Recognition: Over time, learn to recognize when certain percentile levels consistently lead to reversals or continuations in your specific market, and develop personalized strategies based on these observations.
█ Default Settings
The default settings of StatPivot have been carefully calibrated to provide reliable statistical analysis across a variety of markets and timeframes, but understanding their effects allows for optimal customization:
Left Bars (30) and Right Bars (30): These parameters determine how pivot points are identified. With both set to 30 by default:
A pivot low must be the lowest point among 30 bars to its left and 30 bars to its right
A pivot high must be the highest point among 30 bars to its left and 30 bars to its right
Effect on performance: Larger values create fewer but more significant pivot points, reducing noise but potentially missing important market structures. Smaller values generate more pivot points, capturing more nuanced movements but potentially including noise.
Table Position (Top Right): Determines where the statistical data table appears on the chart.
Effect on performance: No impact on analytical performance, purely a visual preference.
Show Distribution Histogram (False): Controls whether the distribution histogram of drop percentages is displayed.
Effect on performance: Enabling this provides visual insight into the distribution of retracements but can clutter the chart.
Show Real-time Percentile (True): Toggles the display of real-time percentile rankings.
Effect on performance: A critical setting that enables the dynamic analysis of current price movements. Disabling this removes one of the key advantages of the indicator.
Real-time Percentile Display Mode (Label): Chooses between label display or indicator line for percentile rankings.
Effect on performance: Labels provide precise information at the current price point, while indicator lines show the evolution of percentile rankings over time.
Advanced Considerations for Settings Optimization:
Timeframe Adjustment: Higher timeframes generally benefit from larger Left/Right values to identify truly significant pivots, while lower timeframes may require smaller values to capture shorter-term swings.
Volatility-Based Tuning: In highly volatile markets, consider increasing the Left/Right values to filter out noise. In less volatile conditions, lower values can help identify more potential entry and exit points.
Market-Specific Optimization: Different markets (forex, stocks, commodities) display different retracement patterns. Monitor the statistics table to see if your market typically shows larger or smaller retracements than the current settings are optimized for.
Trading Style Alignment: Adjust the settings to match your trading timeframe. Day traders might prefer settings that identify shorter-term pivots (smaller Left/Right values), while swing traders benefit from more significant pivots (larger Left/Right values).
By understanding how these settings affect the analysis and customizing them to your specific market and trading style, you can maximize the effectiveness of StatPivot as a powerful statistical tool for identifying high-probability trading opportunities.
Time Marker Pro: Vertical Line at Key Times)Smart Vertical Line at Specific Time (with Timezone, Color, and Width Controls)
This script draws a vertical line on your chart at a user-defined time once per day, based on the selected timezone.
🕒 Key Features:
Set your target hour and minute
Choose from a list of common timezones (Tehran, UTC, New York, etc.)
Customize the line color and thickness
Works across all intraday timeframes (1min, 5min, 15min, etc.)
Adjusts automatically to bar intervals — no need for exact time matching
This is perfect for traders who want to:
Highlight the start of a session
Mark specific news times, breakouts, or routine entries
Visualize key time-based levels on the chart
Stocks Goats Ticker DisplayThis indicator displays a dynamic, customizable information panel overlay on your TradingView chart, providing at-a-glance details about the current asset. It’s perfect for traders who want quick access to essential stock fundamentals and real-time data without cluttering the chart.
🧩 What It Shows
✅ Company Name (with optional Market Cap)
✅ Ticker Symbol and Time Frame
✅ Industry & Sector
✅ Live Price
✅ Current Volume and 30-Day Average Volume
✅ ATR (14) Value with a Volatility Indicator (🔴 🟡 🟢)
⚙️ Customizable Options
You can tailor the display to your preferences using the settings panel:
📍 Positioning — Choose horizontal & vertical placement (left/middle/right, top/middle/bottom)
🎨 Text Appearance — Control text size, color, and background opacity
🏢 Toggle Display Elements:
Show/hide company name
Show/hide sector/industry
Show/hide symbol + time frame
Show/hide volume and price
Show/hide market cap
📈 ATR Volatility Emoji — Set custom thresholds for:
🔴 High volatility
🟡 Medium volatility
🟢 Low volatility Based on the percentage of ATR relative to price.
📌 Notes
Market Cap is calculated using shares_outstanding_total * close price
ATR is calculated using the standard 14-day average true range
Works best on stocks and ETFs with fundamental data available
Standard Deviation Lines v1.0Overview
The Standard Deviation Lines v1.0 indicator is designed to provide a statistical approach to market volatility by plotting multiple standard deviation levels based on price action. This tool helps traders identify key price levels where the market may experience significant reactions, making it useful for trend analysis, support/resistance identification, and volatility-based trading strategies.
Key Features
✅ Dynamic Standard Deviation Levels: Calculates and plots up to ±3 standard deviation levels, giving traders a clear view of price dispersion and potential overbought/oversold areas.
✅ Quadrant-Based Deviation Zones: Divides standard deviation ranges into smaller, meaningful levels (e.g., 0.214, 0.382, 0.50, 0.618, 0.786) for a granular analysis of price movements.
✅ VIX Integration for Volatility Adjustment: Incorporates CBOE:VIX to dynamically adjust standard deviation levels based on market volatility.
✅ Weekly vs. Daily Mode: Users can toggle between weekly and daily standard deviation calculations to adapt to different trading strategies.
✅ Auto-Updating Levels: The indicator refreshes at market close (17:00), ensuring traders work with the latest price data.
✅ Customizable Display: Uses color-coded lines to differentiate between positive and negative deviations, with dashed lines for mid-levels and key support/resistance areas.
How to Use
📌 Trend & Volatility Analysis – Higher standard deviation levels indicate strong price movements, helping traders assess trend strength and market volatility.
📌 Reversal & Continuation Signals – Prices reaching extreme standard deviation levels (±2 or ±3) may suggest potential reversals or breakouts.
📌 Support & Resistance Zones – The quadrant-based deviation zones help identify hidden support/resistance areas where price may react.
📌 Risk Management – Traders can use standard deviation bands to set stop-loss and take-profit levels based on statistical price dispersion.
Best For
🔹 Day traders & swing traders looking to incorporate volatility-based strategies.
🔹 Mean reversion traders who capitalize on price returning to statistical averages.
🔹 Momentum traders who want to confirm trend strength and continuation.
Try the Standard Deviation Lines v1.0 now and enhance your market analysis with a statistical edge!
Correlation X macroeconomicsFind the correlation between financial assets and the main Brazilian macroeconomic variables:
SELIC rate (Red)
PIB (Green)
Inflation (Blue)
Employment and income (Yellow)
Unlike other indicators that measure the correlation between two assets, the indicator "Correlation X macroeconomics" measures, for example, the correlation that the VALE3 asset has with the SELIC rate.
The correlation is obtained by calculating the variation suffered by a given asset on the day a given Brazilian macroeconomic variable is released.
This indicator can be used on any financial asset.
Use time frame chart = 1 day.
To calculate the correlation, data published by IBGE and the Central Bank of Brazil over a period of time are used. This time period is different depending on the selected macroeconomic variable. Namely:
16 PIB disclosures (4 years)
24 SELIC rate disclosures (3 years)
24 disclosures of IPCA and employment and income data (2 years)
You can select one or more macroeconomic variables to check the effect of correlation separately on each of them.
This indicator "Correlation X macroeconomics" will be updated monthly, as detailed below:
At the end of the day on which the PIB is released
At the end of the day on which employment and income data are released
At the end of the day following the day on which the SELIC rate is published
On the last business day of the month if none of the aforementioned disclosures occur
Invictus📝 Invictus – Probabilistic Trading Indicator
🔍 1. General Introduction
Invictus is a technical trading indicator designed to support traders by identifying potential buy and sell signals through a probabilistic and adaptive analytical approach. It aims to enhance the analytical process rather than provide explicit trading recommendations. The indicator integrates multiple analytical components—price pattern detection, momentum analysis (RSI), dynamic trend lines (Kalman Line), and volatility bands (ATR)—to offer traders a structured and contextual framework for making informed decisions.
Invictus does not guarantee profitable outcomes but seeks to enhance analytical clarity and support cautious decision-making through multiple validation layers.
⚙️ 2. Main Components
🌊 2.1. Price Pattern Detection
Invictus identifies potential market shifts by analyzing specific candlestick sequences:
Bearish Patterns (Sell): Detected when consecutive candles close below their openings, indicating increased selling pressure.
Bullish Patterns (Buy): Detected when consecutive candles close above their openings, suggesting increased buying interest.
These patterns provide historical insights rather than absolute predictions for market movements.
⚡ 2.2. Momentum Confirmation (RSI)
To improve signal clarity, Invictus employs the Relative Strength Index (RSI):
Buy Signal: RSI below a predefined threshold (e.g., 30), signaling potential oversold conditions.
Sell Signal: RSI above a threshold (e.g., 70), signaling potential overbought conditions.
RSI acts exclusively as an additional validation filter to reduce, though not eliminate, false signals derived solely from price patterns.
🌀 2.3. Kalman Dynamic Line
The Kalman Dynamic Line smooths price action and dynamically tracks trends using a Kalman filter algorithm:
Noise Reduction: Minimizes minor price fluctuations.
Trend Direction Indicator: Line slope visually represents bullish or bearish market bias.
Adaptive Support/Resistance: Adjusts continuously to market conditions.
Volatility Sensitivity: Adjustments use ATR to scale proportionally with market volatility.
This adaptive dynamic line provides clear context, aiding traders by filtering short-term volatility.
📊 2.4. Volatility Bands (ATR-based)
ATR-based volatility bands define potential breakout zones and market extremes dynamically:
Upper/Lower Bands: Positioned relative to the Kalman Line based on ATR (volatility multiplier).
Volatility Zones: Highlight potential areas of trend continuation or reversal due to significant price movements.
These bands assist traders in visually assessing significant market movements and reducing the focus on minor fluctuations.
🧠 3. Component Interaction and Validation Logic
Invictus is designed to enhance analytical clarity by integrating multiple technical components, requiring independent confirmations before signals may be considered as potentially actionable
🔗 Step 1: Pattern + RSI Validation
Initial identification of price patterns.
Signal validation through RSI conditions (oversold/overbought).
🔗 Step 2: Trend Alignment (Kalman Line)
Validated signals undergo further assessment with respect to the Kalman Dynamic Line.
Buy signals require price action above the Kalman Line; sell signals require price action below.
🔗 Step 3: Volatility Confirmation (ATR Bands)
Price action must penetrate and close beyond the corresponding volatility band.
Ensures signals align with adequate market volatility and momentum.
🔄 4. Comprehensive Decision-Making Flow
Identify price patterns (initial indication).
Confirm momentum via RSI.
Verify trend alignment using the Kalman Line.
Confirm adequate volatility via ATR bands.
💡 5. Practical Example (Buy Scenario)
Invictus signals a potential buy scenario.
Trader waits for the price to cross above the Kalman Line.
Entry consideration occurs only after a confirmed close above the upper ATR volatility band.
⚠️ 6. Important Limitations
Do not rely solely on Invictus signals; always perform broader market analysis.
Invictus performs optimally in trending markets; exercise caution in sideways or range-bound markets.
Always evaluate broader market context and the dominant trend before making decisions.
📝 7. Risk Management & Responsible Trading
Invictus serves as an analytical support tool, not a guarantee of market outcomes:
Set prudent stop-loss levels.
Apply conservative leverage, especially in volatile conditions.
Conduct thorough backtesting and practice on a demo account before live trading.
⚠️ Disclaimer: Trading involves significant risks. Invictus generates signals based on historical and technical analysis. Past performance is not indicative of future results. Responsible trading practices are strongly advised.
💡 8. Final Considerations
Invictus provides an analytical framework integrating various supportive technical methodologies designed to enhance decision-making and comprehensive analysis. Its multi-layered validation process encourages disciplined analysis and informed decision-making without implying any guarantees of profitability.
Traders should incorporate Invictus within broader strategic frameworks, consistently applying disciplined risk management and thorough market analysis.
BTC Dominance PercentageThis BTC Dominance Percentage indicator calculates Bitcoin's dominance relative to altcoins, excluding stablecoins.
🔹 Unlike the standard BTC.D metric, which includes all cryptocurrencies (including stablecoins like USDT, USDC, and DAI), this version focuses only on Bitcoin’s market share compared to altcoins.
🔹 It calculates BTC dominance relative to major altcoins (ETH, BNB, ADA, XRP, SOL) and the OTHERS.D index, which represents smaller-cap altcoins.
🔹 Stablecoins are excluded, providing a clearer view of Bitcoin’s actual strength against the altcoin market, without distortion from fiat-pegged assets.
🚀 This is a true BTC dominance metric for tracking Bitcoin’s market position against altcoins!
Multi-Faceted Analysis ToolHere’s a detailed description for the **Multi-Faceted Analysis Tool** TradingView indicator:
---
## Multi-Faceted Analysis Tool
### Overview
The **Multi-Faceted Analysis Tool** is a powerful TradingView indicator designed to enhance your technical analysis by combining several popular indicators: Simple Moving Average (SMA), Relative Strength Index (RSI), and Moving Average Convergence Divergence (MACD). This indicator provides traders with insightful market signals that can be tailored to fit various trading strategies and timeframes.
### Key Features
1. **Simple Moving Average (SMA)**:
- Plots a customizable SMA on the price chart. The length of the SMA can be adjusted to suit your analysis needs (default is set to 50). The SMA helps identify the overall trend direction.
2. **Relative Strength Index (RSI)**:
- Calculates and plots RSI values, providing insights into potential overbought or oversold market conditions. The user can customize the length of the RSI calculation (default is 14).
- Overbought (70) and oversold (30) levels are visually marked, helping traders identify potential reversal points.
3. **MACD**:
- Computes MACD values with customizable parameters for fast length, slow length, and signal length (defaults are 12, 26, and 9 respectively).
- The MACD histogram is displayed, highlighting the difference between the MACD line and the signal line, which can help traders visualize momentum shifts.
4. **Buy and Sell Signals**:
- Generates clear buy and sell signals based on RSI crossover with established thresholds (buy when RSI crosses above 30, sell when RSI crosses below 70). These signals are visually represented on the chart for easy decision-making.
5. **User-Friendly Customization**:
- All parameters are adjustable, allowing traders to set their preferred values based on individual strategies or market conditions. This flexibility ensures that the tool can cater to a wide range of trading styles.
