rate_of_changeLibrary "rate_of_change"
// @description: Applies ROC algorithm to any pair of values.
// This library function is used to scale change of value (price, volume) to a percentage value, just as the ROC indicator would do. It is good practice to scale arbitrary ranges to set boundaries when you try to train statistical model.
rateOfChange(value, base, hardlimit)
This function is a helper to scale a value change to its percentage value.
Parameters:
value (float)
base (float)
hardlimit (int)
Returns: per: A float comprised between 0 and 100
Statistics
TradingView Financial Data ViewerTrading view provides request.security function to view the financial information of a script. The available sets of data is documented on below link
www.tradingview.com
The problem is there is no easy way to view this data as there are limitations to the # of unique requests that can be made. The limit is 40 for general paid accounts. So its makes it impossible to view the data in case you are looking to build a plugin related to some financial analysis.
So I came up with this trading view plugin which based on the documentation bifurcates the values available in the FQ, TTM and FY periods. Then you can select which period you would like to see. How many values you want to see at a time. And then next set of data can be viewed by increasing the Set # from 1 to which ever number keeps giving you the data.
Notes:
This is a data view only indicator and it will only display the latest data available for which quarter was there.
In case you want to view past data then you should go to replay mode and cut to the relative earning tags where you want to view the data
This is again for educational or study purpose only and is majorly helpful for those who want to create indicators based on Trading view supported financials and want to view what values are given for specific financial ids
The documentation reference and source of the plugin can be checked
Bayesian AverageThis indicator calculates a statistically informed average of the price data using the Bayesian update rule. It overlays directly on the price chart of the trading instrument.
Inputs:
* Length: An integer input (default is 20) that determines the period over which the rolling mean and variance of the closing prices are calculated. This essentially sets the lookback window for recent price action.
* Prior Mean: A floating-point number input (default is 0.0) representing the initial guess or prior belief about the average price of the asset before observing any price data within the specified Length.
* Prior Variance: A floating-point number input (default is 1.0) that quantifies the uncertainty associated with the Prior Mean. A higher value indicates less confidence in the initial guess.
Calculations:
* Rolling Mean and Variance: The script first computes the simple moving average (rollingMean) and the sample variance (rollingVariance) of the closing price using the ta.sma and ta.variance functions over the length period.
* Bayesian Update: The indicator then applies the Bayesian update formulas to combine the prior beliefs with the information extracted from the recent price data:
* Posterior Variance: This value represents the updated uncertainty about the average price after considering the recent price fluctuations. It is calculated by combining the inverse of the Prior Variance with the precision of the data (number of observations divided by the Rolling Variance).
* Posterior Mean (Bayesian Average): This is the main output of the indicator. It represents the refined estimate of the average price, taking into account both the initial Prior Mean and the information from the Rolling Mean and Rolling Variance. The formula weights the Prior Mean and the Rolling Mean based on their respective precisions (inverse of their variances).
Plotting:
* Bayesian Average (Blue Line): The indicator plots the calculated posteriorMean, which is the Bayesian average of the price, as a blue line on the chart.
* Rolling Mean (Gray Line - Optional): For comparison, the script optionally plots the traditional simple moving average (rollingMean) as a gray line.
* Prior Mean (Dotted Red Line - Optional): A horizontal line representing the initial priorMean is optionally drawn on the chart as a red dotted line, serving as a reference.
* Posterior Variance (Orange Line - Optional): The posteriorVariance, representing the uncertainty, is also optionally plotted as an orange line.
In essence, this indicator attempts to provide a more statistically sound and potentially smoother representation of the average price by blending an initial belief with observed market data. The Prior Mean and Prior Variance allow users to incorporate their existing knowledge or assumptions into the calculation, while the Bayesian update mechanism adjusts these beliefs based on the recent price action.
Avg.ROC TableThis indicator calculates the average Rate of Change (ROC) for up to 30 user-selected assets over a specified number of candles. It then ranks the assets—assigning rank 1 to the asset with the highest average ROC (strongest momentum) and rank 30 to the asset with the lowest. The results are displayed in a clean, easy-to-read table split into two stacks of 15 assets each, allowing you to quickly see which assets are performing best.
MonthlyReturnTableLibrary "MonthlyReturnTable"
TODO: The table displays monthly returns, profits, MDD, and number of trades.
get_table(mode, tablePosition, precision, textSize, marginTop, marginBottom, marginLeft, marginRight, colorHead, colorBull, colorBear, colorZero)
: get_table
Parameters:
mode (string)
tablePosition (string)
precision (int)
textSize (int)
marginTop (int)
marginBottom (int)
marginLeft (int)
marginRight (int)
colorHead (color)
colorBull (color)
colorBear (color)
colorZero (color)
Returns: : null, plot perfTable
Open Interest and Liquidity [by Alpha_Precision_Charts]Indicator Description: Open Interest and Liquidity
Introduction:
The "Open Interest and Liquidity" indicator is an advanced tool designed for traders seeking to analyze aggregated Open Interest (OI) flow and liquidity in the cryptocurrency market, with a special focus on Bitcoin. It combines high-quality Open Interest data, a detailed liquidity table, and a visual longs vs shorts gauge, providing a comprehensive real-time view of market dynamics. Ideal for scalpers, swing traders, and volume analysts, this indicator is highly customizable and optimized for 1-minute charts, though it works across other timeframes as well.
Key Features:
Aggregated Open Interest and Delta: Leverages Binance data for accuracy, allowing traders to switch between displaying absolute OI or OI Delta, with value conversion to base currency or USD.
Liquidity Table: Displays the analyzed period, active liquidity, shorts, and longs with visual proportion bars, functioning for various cryptocurrencies as long as Open Interest data is available.
Longs vs Shorts Gauge: A semicircle visual that shows real-time market sentiment, adjustable for chart positioning, helping identify imbalances, optimized and exclusive for Bitcoin on 1-minute charts.
Utilities:
Sentiment Analysis: Quickly detect whether the market is accumulating positions (longs/shorts) or liquidating (OI exits).
Pivot Identification: Highlight key moments of high buying or selling pressure, ideal for trade entries or exits.
Liquidity Monitoring: The table and gauge provide a clear view of active liquidity, helping assess a move’s strength.
Scalping and Day Trading: Perfect for short-term traders operating on 1-minute charts, offering fast and precise visual insights.
How to Use:
Initial Setup: Choose between "Open Interest" (candles) or "Open Interest Delta" (columns) in the "Display" field. The indicator defaults to Binance data for enhanced accuracy.
Customization: Enable/disable the table and gauge as needed and position them on the chart.
Interpretation: Combine OI Delta and gauge data with price movement to anticipate breakouts or reversals.
Technical Notes
The indicator uses a 500-period VWMA to calculate significant OI Delta thresholds and is optimized for Bitcoin (BTCUSDT.P) on high-liquidity charts.
Disclaimer
This indicator relies on the availability of Open Interest data on TradingView. For best results, use on Bitcoin charts with high liquidity, such as BTCUSDT.P. Accuracy may vary with lower-volume assets or exchanges.
Normalized VolumeOVERVIEW
The Normalized Volume (NV) is an attempt at visualizing volume in a format that is more understandable by placing the values on a scale of 0 to 100. 0 in this case is the lowest volume candle available on the chart, and 100 being the highest. Calling a candle “high volume” can be misleading without having something to compare to. For example, in scaling the volume this way we can clearly see that a given candle had 80% of the peak volume or 20%, and gauge the validity of price moves more accurately.
FEATURES
NV by session
Allows user to filter the volume values across 4 different sessions. This can add context to the volume output, because what it high volume during London session may not be high volume relative to New York session.
Overlay plotting
When volume boxes are turned on, this will allow you to toggle how they are plotted.
Color theme
A standard color theme will color the NV based on if the respective candle closed green or red. Selecting variables will color the NV plot based on which range the value falls within.
Session inputs
Activated with the “By session?” Input. Allows user to break the day up into 4 sessions to more accurately gauge volume relative to time of day.
Show Box (X)
Toggles on chart boxes on and off.
Show historical boxes
Will plot prior occurrences of selected volume boxes, deleting them when price fully moves through them in the opposite direction of the initial candle.
Color inputs
Allows for intensive customization in how this tool appears visually.
INTERPRETATION
There are 6 pre-defined ranges that NV can fall within.
NV <= 10
Volume is insignificant
In this range, volume should not be a confirmation in your trading strategy.
NV > 10 and <= 20
Volume is low
In this range, volume should not be a confirmation in your trading strategy.
NV > 20 and <= 40
Volume is fair
In this range, volume should not be the primary confirmation in your trading strategy.
NV > 40 and <= 60
Volume is high
In this range, volume can be the primary confirmation in your trading strategy.
NV > 60 and <= 80
Volume is very high
In this range, volume can be the primary confirmation in your trading strategy.
NV > 80
Volume is extreme
In this range, volume is likely news driven and caution should be taken. High price volatility possible.
To utilize this tool in conjunction with your current strategy, follow the range explanations above section in this section. The higher the NV value, the stronger you can feel about your directional confirmation.
If NV = 100, this means that the highest volume candle occurred up to that point on your selected timeframe. All future data points will be weighed off of this value.
LIMITATIONS
This tool will not load on tickers that do not have volume data, such as VIX.
STRATEGY
The Normalized Volume plot can be used in exactly the same way as you would normally utilize volume in your trading strategy. All we are doing is weighing the volume relative to itself.
Volume boxes can be used as targets to be filled in a similar way to commonly used “fair value gap” strategies. To utilize this strategy, I recommend selecting “Plot to Wicks” in Overlay Plotting and toggling on Show Historical Boxes.
Volume boxes can be used as areas for entry in a similar way to commonly used “order block” strategies. To utilize this strategy, I recommend selecting “Open To Close” in Overlay Plotting.
NOTES
You are able to plot an info label on right side of NV plot using the "Toggle box label" input. When a box is toggled on this label will tell you when the most recent box of that intensity occurred.
This tool is deeply visually customizable, with the ability to adjust line width for plotted boxes, all colors on both box overlays, and all colors on NV panel. Customize it to your liking!
I have a handful of additional features that I plan on adding to this tool in future updates. If there is anything you would like to see added, any bugs you identify, or any strategies you encounter with this tool, I would love to hear from you!
Huge shoutout to @joebaus for assisting in bringing this tool to life, please check out his work here on TradingView!
Volume +OBV + ADXVolume + OBV + ADX Table
Optimized Buyer & Seller Volume with Trend Indications
Overview:
This indicator provides a comprehensive view of market participation and trend strength by integrating Volume, On Balance Volume (OBV) trends, and ADX (Average Directional Index) signals into a visually structured table. Designed for quick decision-making, it highlights buyer and seller dominance while comparing the selected stock with another custom symbol.
Features:
✅ Buyer & Seller Volume Analysis:
Computes buyer and seller volume percentages based on market movements.
Displays daily cumulative volume statistics to assess ongoing market participation.
✅ On Balance Volume (OBV) Trends:
Identifies positive, negative, or neutral OBV trends using an advanced smoothing mechanism.
Highlights accumulation or distribution phases with colored visual cues.
✅ ADX-Based Trend Confirmation:
Evaluates Directional Indicators (DI+ and DI-) to determine the trend direction.
Uses customizable ADX settings to filter out weak trends.
Provides uptrend, downtrend, or neutral signals based on strength conditions.
✅ Custom Symbol Comparison:
Allows users to compare two different assets (e.g., a stock vs. an index or ETF).
Displays a side-by-side comparison of volume dynamics and trend strength.
✅ User-Friendly Table Display:
Presents real-time calculations in a compact and structured table format.
Uses color-coded trend signals for easier interpretation.
Recommended Usage for Best Results:
📌 Pairing this indicator with Sri_Momentum and Sri(+) Pivot will enhance accuracy and provide better trade confirmations.
📌 Adding other major indicators like RSI, CCI, etc., will further increase the probability of winning trades.
How to Use:
Select a custom symbol for comparison.
Adjust ADX settings based on market conditions.
Analyze the table to identify buyer/seller dominance, OBV trends, and ADX trend strength.
Use the combined signals to confirm trade decisions and market direction.
Best Use Cases:
🔹 Trend Confirmation – Validate breakout or reversal signals.
🔹 Volume Strength Analysis – Assess buyer/seller participation before entering trades.
🔹 Multi-Asset Comparison – Compare the behavior of two related instruments.
This indicator is ideal for traders looking to combine volume dynamics with trend-following strategies. 🚀📈
Uptrick: Universal Market ValuationIntroduction
Uptrick: Universal Market Valuation is created for traders who seek an analytical tool that brings together multiple signals in one place. Whether you focus on intraday scalping or long-term portfolio management, the indicator merges various well-known technical indicators to help gauge potential overvaluation, undervaluation, and trend direction. It is engineered to highlight different market dimensions, from immediate price momentum to extended cyclical trends.
Overview
The indicator categorizes market conditions into short-term, long-term, or a classic Z-Score style reading. Additionally, it draws on a unified trend line for directional bias. By fusing elements from traditionally separate indicators, the indicator aims to reduce “false positives” while giving a multidimensional view of price behavior. The indicator works best on cryptocurrency markets while remaining a universal valuation indicator that performs well across all timeframes. However, on lower timeframes, the Long-Term Combo input may be too long-term, so it's recommended to select the Short-Term Combo in the inputs for better adaptability.
Originality and Value
The Uptrick: Universal Market Valuation indicator is not just a simple combination of existing technical indicators—it introduces a multi-layered, adaptive valuation model that enhances signal clarity, reduces false positives, and provides traders with a more refined assessment of market conditions.
Rather than treating each included indicator as an independent signal, this script normalizes and synthesizes multiple indicators into a unified composite score, ensuring that short-term and long-term momentum, mean reversion, and trend strength are all dynamically weighted based on market behavior. It employs a proprietary weighting system that adjusts how each component contributes to the final valuation output. Instead of static threshold-based signals, the indicator integrates adaptive filtering mechanisms that account for volatility fluctuations, drawdowns, and momentum shifts, ensuring more reliable overbought/oversold readings.
Additionally, the script applies Z-Score-based deviation modeling, which refines price valuation by filtering out extreme readings that are statistically insignificant. This enhances the detection of true overvaluation and undervaluation points by comparing price behavior against a dynamically calculated standard deviation threshold rather than relying solely on traditional fixed oscillator bands. The MVRV-inspired ratio provides a unique valuation layer by incorporating historical fair-value estimations, offering deeper insight into market overextension.
The Universal Trend Line within the indicator is designed to smooth trend direction while maintaining responsiveness to market shifts. Unlike conventional trend indicators that may lag significantly or produce excessive false signals, this trend-following mechanism dynamically adjusts to changing price structures, helping traders confirm directional bias with reduced noise. This approach enables clearer trend recognition and assists in distinguishing between short-lived pullbacks and sustained market movements.
By merging momentum oscillators, trend strength indicators, volume-driven metrics, statistical deviation models, and long-term valuation principles into a single framework, this indicator eliminates the need for juggling multiple individual indicators, helping traders achieve a holistic market perspective while maintaining customization flexibility. The combination of real-time alerts, dynamic color-based valuation visualization, and customizable trend-following modes further enhances usability, making it a comprehensive tool for traders across different timeframes and asset classes.
Inputs and Features
• Calculation Window (Short-Term and Long-Term)
Defines how much historical data the indicator uses to evaluate the market. A smaller window makes the indicator more reactive, benefiting high-frequency traders. A larger window provides a steadier perspective for longer-term holders.
• Smoothing Period (Short-Term and Long-Term)
Controls how much the raw indicator outputs are “smoothed out.” Lower values reveal subtle intraday fluctuations, while higher values aim to present more robust, stable signals.
• Valuation Mechanism (Short Term Combo, Long Term Combo, Classic Z-Score)
Allows you to pick how the indicator evaluates overvaluation or undervaluation. Short Term Combo focuses on rapid oscillations, Long Term Combo assesses market health over more extended periods, and the Classic Z-Score approach highlights statistically unusual price levels.
Short-Term
• Determination Mechanism (Strict or Loose)
Governs the tolerance for labeling a market as overvalued or undervalued. Strict requires stronger confirmation; Loose begins labeling sooner, potentially catching moves earlier but risking more false signals.
Strict
Loose
• Select Color Scheme
Lets you choose the aesthetic style for your charts. Visual clarity can significantly improve reaction time, especially when multiple indicators are combined.
• Z-Score Coloring Mode (Heat or Slope)
Determines how the Classic Z-Score line and bars are colored. In Heat mode, the indicator intensifies color as readings move further from a baseline average. Slope mode changes color based on the direction of movement, making turning points more evident.
Classic Z-Score - Heat
Classic Z-Score - Slope
• Trend Following Mode (Short, Long, Extra Long, Filtered Long)
Offers various ways to compute and smooth the universal trend line. Short is more sensitive, Long and Extra Long are meant for extended time horizons, and Filtered Long applies an extra smoothing layer to help you see overarching trends rather than smaller fluctuations.
Short Term
Long Term
Extra Long Term
Filtered Long Term
• Table Display
An optional feature that places a concise summary table on the chart. It shows valuation states, trend direction, volatility condition, and other metrics, letting you observe multi-angle readings at a glance.
• Alerts
Multiple alert triggers can be set up—for crossing into overvaluation zones, for abrupt changes in trend, or for high volatility detection. Traders can stay informed without needing to watch charts continuously.
Why These Indicators Were Merged
• RSI (Relative Strength Index)
RSI is a cornerstone momentum oscillator that interprets speed and change of price movements. It has widespread recognition among traders for detecting potential overbought or oversold conditions. Including RSI provides a tried-and-tested layer of momentum insight.
• Stochastic Oscillator
This oscillator evaluates the closing price relative to its recent price range. Its responsiveness makes it valuable for pinpointing near-term price fluctuations. Where RSI offers a broader momentum picture, Stochastic adds fine-tuned detection of short-lived rallies or pullbacks.
• MFI (Money Flow Index)
MFI assesses buying and selling pressure by incorporating volume data. Many technical tools are purely price-based, but MFI’s volume component helps address questions of liquidity and actual money flow, offering a glimpse of how robust or weak a current move might be.
• CCI (Commodity Channel Index)
CCI shows how far price lies from its statistically “typical” trend. It can spot emerging trends or warn of overextension. Using CCI alongside RSI and Stochastic further refines the valuation layer by capturing price deviation from its underlying trajectory.
• ADX (Average Directional Index)
ADX reveals the strength of a trend but does not specify its direction. This is especially useful in combination with other oscillators that focus on bullish or bearish momentum. ADX can clarify whether a market is truly trending or just moving sideways, lending deeper context to the indicator's broader signals.
• MACD (Moving Average Convergence Divergence)
MACD is known for detecting momentum shifts via the interaction of two moving averages. Its inclusion ensures the indicator can capture transitional phases in market momentum. Where RSI and Stochastic concentrate on shorter-term changes, MACD has a slightly longer horizon for identifying robust directional changes.
• Momentum and ROC (Rate of Change)
Momentum and ROC specifically measure the velocity of price moves. By indicating how quickly (or slowly) price is changing compared to previous bars, they help confirm whether a trend is gathering steam, losing it, or is in a transitional stage.
• MVRV-Inspired Ratio
Drawn loosely from the concept of comparing market value to some underlying historical or fair-value metric, an MVRV-style ratio can help identify if an asset is trading above or below a considered norm. This additional viewpoint on valuation goes beyond simple price-based oscillations.
• Z-Score
Z-Score interprets how many standard deviations current prices deviate from a central mean. This statistical measure is often used to identify extreme conditions—either overly high or abnormally low. Z-Score helps highlight potential mean reversion setups by showing when price strays far from typical levels.
By merging these distinct viewpoints—momentum oscillators, trend strength gauges, volume flow, standard deviation extremes, and fundamental-style valuation measures—the indicator aims to create a well-rounded, carefully balanced final readout. Each component serves a specialized function, and together they can mitigate the weaknesses of a single metric acting alone.
Summary
This indicator simplifies multi-indicator analysis by fusing numerous popular technical signals into one tool. You can switch between short-term and long-term valuation perspectives or adopt a classic Z-Score approach for spotting price extremes. The universal trend line clarifies direction, while user-friendly color schemes, optional tabular summaries, and customizable alerts empower traders to maintain awareness without constantly monitoring every market tick.
Disclaimer
The indicator is made for educational and informational use only, with no claims of guaranteed profitability. Past data patterns, regardless of the indicators used, never ensure future results. Always maintain diligent risk management and consider the broader market context when making trading decisions. This indicator is not personal financial advice, and Uptrick disclaims responsibility for any trading outcomes arising from its use.
All-Time High MarkerThis indicator automatically identifies and displays the All-Time High (ATH) price on a chart. When a new ATH is reached, a horizontal line is drawn, extending from a user-specified number of bars to the left of the ATH candle to the current bar, and continuing indefinitely to the right. An "ATH" label is placed at the beginning of the line. Key features:
Dynamic ATH Tracking: Automatically updates as new all-time highs are reached.
Customizable Line: Adjust the line color and width to match your chart theme.
Customizable Label: Change the label color, text color, and vertical offset.
Line Start Offset: Control how far back the ATH line starts from the ATH candle.
This tool helps traders quickly visualize and track ATH levels for potential breakouts or resistance zones.
Time of Day Background with Bar Count & TableDescription:
This indicator provides a comprehensive overview of market activity by dynamically displaying the time-of-day background and tracking bullish and bearish bar counts across different sessions. It also features a table summarizing the market performance for the last 7 days, segmented into four time-based sessions: Morning, Afternoon, Evening, and Night.
Key Features:
Time of Day Background:
The chart's background color changes based on the time of day:
Evening (12 AM - 6 AM) is shaded blue.
Morning (6 AM - 12 PM) is shaded aqua.
Afternoon (12 PM - 6 PM) is shaded yellow.
Night (6 PM - 12 AM) is shaded silver.
Bullish and Bearish Bar Counting:
It tracks the number of bullish (closing higher than opening) and bearish (closing lower than opening) candles.
The sum of the price differences (bullish minus bearish) for each session is displayed as a dynamic label, indicating overall market direction for each session.
Session Breakdown:
The chart is divided into four sessions, each lasting 6 hours (Morning, Afternoon, Evening, Night).
A new label is generated at the start of each session, indicating the bullish/bearish performance and the net difference in price movements for that session.
Historical Session Performance:
The indicator tracks and stores the performance for each session over the past 7 days.
A table is generated in the top-right corner of the chart, summarizing the performance for each session (Morning, Afternoon, Evening, Night) and the price changes for each of the past 7 days.
The values are color-coded to indicate positive (green) or negative (red) results.
Dynamic Table:
The table presents performance data for each time session over the past week with color-coded cells:
Green cells indicate positive performance.
Red cells indicate negative performance.
Empty cells represent no data for that session.
Use Case:
This indicator is useful for traders who want to track market activity and performance across different times of day and monitor how each session contributes to the overall market trend. It provides both visual insights (through background color) and numerical data (via the table) for better decision-making.
Settings:
The background color and session labels update automatically based on the time of day.
The table updates every day, tracking the performance of each session over the past week.
Vortex Candle MarkerVortex Candle Marker
The Vortex Candle Marker is a specialized TradingView indicator designed to identify and highlight **Vortex Candles**—candles that momentarily form without wicks on either the high or low. This unique price behavior can signal potential price retracements or reversals, aligning with the **Power of Three (PO3)** concept in price action theory.
Indicator Logic:
A candle is classified as a **Vortex Candle** if either of these conditions is met during its formation:
1. **Vortex Top:** The **high** equals either the **open** or **close**, indicating no upper wick.
2. **Vortex Bottom:** The **low** equals either the **open** or **close**, indicating no lower wick.
When a Vortex Candle is detected, the indicator changes the **candle border color** to **aqua**, making it easy to identify these significant price moments.
Market Insight & PO3 Interpretation:
In typical price behavior, most candles exhibit both upper and lower wicks, representing price exploration before settling at a closing value. A candle forming without a wick suggests **strong directional intent** at that moment. However, by the **Power of Three (PO3)** concept—Accumulation, Manipulation, and Distribution—such wickless formations often imply:
- **Price Reversion Likelihood:** When a candle temporarily forms without a wick, it suggests the market may **revisit the opening price** to establish a wick before the candle closes.
- **Liquidity Manipulation:** The absence of a wick may indicate a **stop-hunt** or liquidity grab, where the price manipulates one side before reversing.
- **Entry Triggers:** Identifying these moments can help traders anticipate potential **retracements** or **continuations** within the PO3 framework.
Practical Application
- **Early Reversal Detection:** Spot potential price reversals by observing wickless candles forming at key levels.
- **Breakout Validation:** Use Vortex Candles to confirm **true breakouts** or **false moves** before the price returns.
- **Liquidity Zones:** Identify areas where the market is likely to revisit to create a wick, signaling entry/exit points.
This indicator is a powerful tool for traders applying **Po3** methodologies and seeking to capture price manipulation patterns.
CAPM Alpha & BetaThe CAPM Alpha & Beta indicator is a crucial tool in finance and investment analysis derived from the Capital Asset Pricing Model (CAPM) . It provides insights into an asset's risk-adjusted performance (Alpha) and its relationship to broader market movements (Beta). Here’s a breakdown:
1. How Does It Work?
Alpha:
Definition: Alpha measures the portion of an investment's return that is not explained by market movements, i.e., the excess return over and above what the market is expected to deliver.
Purpose: It represents the value a fund manager or strategy adds (or subtracts) from an investment’s performance, adjusting for market risk.
Calculation:
Alpha is derived from comparing actual returns to expected returns predicted by CAPM:
Alpha = Actual Return − (Risk-Free Rate + β × (Market Return − Risk-Free Rate))
Alpha = Actual Return − (Risk-Free Rate + β × (Market Return − Risk-Free Rate))
Interpretation:
Positive Alpha: The investment outperformed its CAPM prediction (good performance for additional value/risk).
Negative Alpha: The investment underperformed its CAPM prediction.
Beta:
Definition: Beta measures the sensitivity of an asset's returns relative to the overall market's returns. It quantifies systematic risk.
Purpose: Indicates how volatile or correlated an investment is relative to the market benchmark (e.g., S&P 500).
Calculation:
Beta is computed as the ratio of the covariance of the asset and market returns to the variance of the market returns:
β = Covariance (Asset Return, Market Return) / Variance (Market Return)
β = Variance (Market Return) Covariance (Asset Return, Market Return)
Interpretation:
Beta = 1: The asset’s price moves in line with the market.
Beta > 1: The asset is more volatile than the market (higher risk/higher potential reward).
Beta < 1: The asset is less volatile than the market (lower risk/lower reward).
Beta < 0: The asset moves inversely to the market.
2. How to Use It?
Using Alpha:
Portfolio Evaluation: Investors use Alpha to gauge whether a portfolio manager or a strategy has successfully outperformed the market on a risk-adjusted basis.
If Alpha is consistently positive, the portfolio may deliver higher-than-expected returns for the given level of risk.
Stock/Asset Selection: Compare Alpha across multiple securities. Positive Alpha signals that the asset may be a good addition to your portfolio for excess returns.
Adjusting Investment Strategy: If Alpha is negative, reassess the asset's role in the portfolio and refine strategies.
Using Beta:
Risk Management:
A high Beta (e.g., 1.5) indicates higher sensitivity to market movements. Use such assets if you want to take on more risk during bullish market phases or expect higher returns.
A low Beta (e.g., 0.7) indicates stability and is useful in diversifying risk in volatile or bearish markets.
Portfolio Diversification: Combine assets with varying Betas to achieve the desired level of market responsiveness and smooth out portfolio volatility.
Monitoring Systematic Risk: Beta helps identify whether an investment aligns with your risk tolerance. For example, high-Beta stocks may not be suitable for conservative investors.
Practical Application:
Use both Alpha and Beta together:
Assess performance with Alpha (excess returns).
Assess risk exposure with Beta (market sensitivity).
Example: A stock with a Beta of 1.2 and a highly positive Alpha might suggest a solid performer that is slightly more volatile than the market, making it a suitable pick for risk-tolerant, return-maximizing investors.
In conclusion, the CAPM Alpha & Beta indicator gives a comprehensive view of an asset's performance and risk. Alpha enables performance evaluation on a risk-adjusted basis, while Beta reveals the level of market risk. Together, they help investors make informed decisions, build optimal portfolios, and align investments with their risk-return preferences.
ATR Percentages BoxThis custom indicator provides a quick visual reference for volatility-based price ranges, directly on your TradingView charts. It calculates and displays three ranges derived from the Daily Average True Range (ATR) with a standard 14-period setting:
5 Min (3% ATR): Ideal for very short-term scalping and quick intraday moves.
1 Hour (5% ATR): Useful for hourly setups, short-term trades, and intraday volatility assessment.
Day (10% ATR): Perfect for daily volatility context, swing trades, or placing stops and targets.
The ranges are clearly shown in a compact box at the top-right corner, providing traders immediate insights into realistic price movements, helping to optimise entries, stops, and profit targets efficiently.
Massive Market Order Detector by GSK-VIZAG-AP-INDIA
Massive Market Order Detector by GSK-VIZAG-AP-INDIA
Purpose of the Indicator:
This indicator is designed to detect massive market orders (high-volume trades) in real-time, helping traders identify potential accumulation or distribution zones. It highlights sudden spikes in volume that exceed a calculated threshold, signaling strong buying or selling pressure.
Core Logic & Unique Aspects:
Volume Spike Detection: Compares the current volume to the average volume over a user-defined lookback period. If the volume exceeds the threshold (calculated using a multiplier), it is classified as a Massive Order.
Buy vs. Sell Order Identification: Determines whether the detected massive order is a buy (green marker) or a sell (red marker) based on candlestick price action.
Time Zone Adjustment: Allows traders to adjust the timestamp according to their local timezone, ensuring accurate interpretation of order timings.
Table Display of Recent Orders: A table is created within the chart to list the last 15 detected massive orders, showing key details such as time, volume, type (buy/sell), price, and volume percentage change.
How It Works:
The indicator calculates the average volume over a lookback period (default: 20 bars).
If the current volume exceeds the threshold (average volume × multiplier), it is marked as a Massive Order.
The order is classified as:
Massive Buy Order (MB) → If the closing price is higher than the opening price.
Massive Sell Order (MS) → If the closing price is lower than the opening price.
The detected orders are visually represented as green (MB) and red (MS) labels on the chart.
The most recent 15 massive orders are logged in a table for easy reference.
Intended Use Cases:
🔹 Scalping & Intraday Trading – Spot unusual market activity to enter or exit trades quickly.
🔹 Swing Trading – Identify strong buying or selling pressure at key support/resistance levels.
🔹 Breakout Confirmation – Validate if price breakouts are backed by significant volume.
🔹 Market Manipulation Detection – Recognize potential institutional buying/selling activity.
Input settings:
Lookback Period: Adjust the number of bars to calculate average volume.
Volume Multiplier: Set the threshold as 1/2/3 for defining a massive order.
Time Zone Offset: Modify timestamps to match your local market time.
Max Signals in Table: Control how many signals are displayed in the table.
Why Use This Indicator?
✅ Identifies smart money activity
✅ Works across multiple timeframes (5m, 15m, 1H, Daily, etc.)
✅ No repainting – Reliable real-time signals
✅ Easy-to-read visual cues & table logs
Disclaimer:
"This indicator is for educational and informational purposes only and should not be considered financial advice. Always do your own research (DYOR) and consult with a qualified financial professional before making investment decisions. Trading involves significant risk, and past performance does not guarantee future results. I am not a licensed financial advisor and hold no liability for any losses incurred. This indicator may not work in all market conditions, and results are based on backtesting or hypothetical scenarios. Use at your own discretion and ensure compliance with local regulations."
Extreme Areas with MTF Screener by QTX Algo SystemsStatistically Extreme Areas with MTF Screener by QTX Algo Systems
Overview
This indicator is designed to automatically highlight zones where prices become statistically overextended, signaling potential reversal opportunities. Enhanced with a Multi Time Frame (MTF) Screener, it verifies these extremes across several timeframes for a comprehensive, multi-dimensional view of market conditions.
How It Works
Baseline Statistical Analysis:
The indicator establishes a baseline price range using historical data through a statistical percentile approach. This baseline reflects typical price extremes over time.
Volatility and Momentum Filters:
It incorporates a Bollinger Band Width Percentile (BBWP) to measure real-time volatility and combines this with a double‐smoothed SMI and a Price – Moving Average Ratio (PMARP) to assess short-term momentum. This dual-filter system ensures that signals are generated only when both volatility and momentum conditions are satisfied.
Directional Oscillator (BBO) Analysis:
A Bollinger Band Oscillator (BBO) is used to evaluate the slopes of the upper and lower bands, adding an extra layer of confirmation for identifying true market extremes.
MTF Screener Integration:
The added MTF Screener scans multiple timeframes, confirming that the statistically extreme conditions are not isolated events. This cross-verification provides a more robust signal, ensuring that the identified reversal zones are consistent across the market.
Customizable Visual Alerts:
The indicator allows for customizable color coding for various conditions (e.g., extreme low warnings, extreme high warnings, and potential reversals), offering clear, visual guidance for traders.
Why It’s Different and Valuable
This tool is more than just a simple merger of common indicators—it’s a carefully integrated system that validates price extremes across several dimensions. By combining statistical analysis with real-time volatility, momentum verification, and multi-timeframe confirmation, it provides a dynamic framework that helps traders identify high-probability reversal zones while minimizing false signals. The added MTF Screener ensures that these signals are consistent and reliable across different market views, enhancing the overall decision-making process.
How to Use
Monitor Visual Cues: Look for the color-coded signals that indicate statistically extreme price levels.
Confirm Across Timeframes: Use the MTF Screener component to ensure that the extreme conditions appear consistently across various timeframes.
Integrate with Your Strategy: Use this indicator alongside other technical tools to refine entry, exit, and stop-loss decisions.
Disclaimer
This indicator is for educational purposes only and is intended to support your trading analysis. It does not guarantee performance, and past results are not indicative of future outcomes. Always use proper risk management and conduct your own analysis before trading.
Continuation Opportunity with MTF Screener by QTX Algo SystemsContinuation Opportunity Indicator with MTF Screener by QTX Algo Systems
Overview
This enhanced indicator is designed to pinpoint key moments when an established trend is likely to continue. By combining traditional momentum analysis with dual volatility measures—and now integrating a powerful Multi Time Frame (MTF) Screener—it offers a multi-dimensional view of trend behavior. This tool not only detects when a pullback is simply a temporary consolidation (characterized by reduced volatility) but also confirms that the overall trend is poised to resume, validated across several timeframes.
How It Works
Core Methodology:
The base indicator uses a double‐smoothed Stochastic Momentum Index (SMI) combined with a Price – Moving Average Ratio (PMARP) to detect momentum crossovers that signal trend continuation. It also uses volatility filters to ensure that the signals occur only when market activity is strong.
Dual Volatility Analysis:
A Bollinger Band Width Percentile (BBWP) measure and historical volatility metrics work together to ensure that only meaningful pullbacks trigger signals—distinguishing between noise and genuine consolidation.
MTF Screener Integration:
The new MTF Screener feature extends the analysis beyond a single timeframe. It scans multiple assets and timeframes concurrently, confirming that a detected pullback or resumption signal appears consistently across the broader market view. This cross-verification minimizes false signals and provides traders with confidence that the trend continuation is robust.
Enhanced Visual Cues:
Color-coded backgrounds and well-defined signal triggers help traders quickly interpret when a pullback is likely just a consolidation phase and when increased volatility signals the trend’s resumption.
Why It’s Different and Valuable
Unlike a simple combination of separate indicators, this tool integrates each element in a systematic, layered approach. The MTF Screener adds an extra dimension by validating signals across different timeframes—ensuring that traders are not basing decisions on isolated, potentially misleading data. This cohesive design enhances overall accuracy and provides actionable insights that are more robust than what individual indicators would offer on their own.
How to Use
Monitor Visual Signals: Look for color-coded cues and momentum crossovers that appear after a pullback.
Validate Across Timeframes: Use the MTF Screener’s output to confirm that the continuation signal is consistent across various timeframes.
Integrate with Other Tools: Combine these signals with your existing technical analysis methods to refine your entry and exit points.
Disclaimer
This indicator is provided for educational purposes only and is intended to support your trading analysis. It does not guarantee performance, and past results are not indicative of future outcomes. Always use proper risk management and perform your own analysis before trading.
Simple APF Strategy Backtesting [The Quant Science]Simple backtesting strategy for the quantitative indicator Autocorrelation Price Forecasting. This is a Buy & Sell strategy that operates exclusively with long orders. It opens long positions and generates profit based on the future price forecast provided by the indicator. It's particularly suitable for trend-following trading strategies or directional markets with an established trend.
Main functions
1. Cycle Detection: Utilize autocorrelation to identify repetitive market behaviors and cycles.
2. Forecasting for Backtesting: Simulate trades and assess the profitability of various strategies based on future price predictions.
Logic
The strategy works as follow:
Entry Condition: Go long if the hypothetical gain exceeds the threshold gain (configurable by user interface).
Position Management: Sets a take-profit level based on the future price.
Position Sizing: Automatically calculates the order size as a percentage of the equity.
No Stop-Loss: this strategy doesn't includes any stop loss.
Example Use Case
A trader analyzes a dayli period using 7 historical bars for autocorrelation.
Sets a threshold gain of 20 points using a 5% of the equity for each trade.
Evaluates the effectiveness of a long-only strategy in this period to assess its profitability and risk-adjusted performance.
User Interface
Length: Set the length of the data used in the autocorrelation price forecasting model.
Thresold Gain: Minimum value to be considered for opening trades based on future price forecast.
Order Size: percentage size of the equity used for each single trade.
Strategy Limit
This strategy does not use a stop loss. If the price continues to drop and the future price forecast is incorrect, the trader may incur a loss or have their capital locked in the losing trade.
Disclaimer!
This is a simple template. Use the code as a starting point rather than a finished solution. The script does not include important parameters, so use it solely for educational purposes or as a boilerplate.
Multi-MA RibbonMulti-MA Ribbon is a dynamic and highly customizable indicator designed to visually compare and analyze up to 12 moving average bands simultaneously — across two different moving average (MA) types. This allows traders to study how various MAs behave relative to one another in real time, improving market analysis and trade precision.
The script supports EMA, SMA, HMA, RMA, WMA, VWMA, SWMA, and ALMA, with full user control over periods, ribbon thickness, color, and gradient direction.
Key Features:
Dual Moving Average Ribbon System — Compare two independent MA types side by side on the same price chart.
12 User-Defined Period Bands — Visualize short to long-term trend layers, fully adjustable.
Gradient Coloring with Direction Control — Choose whether fast or slow bands are brightest for quick visual focus.
Customizable Thickness and Colors — Adapt the visualization to fit any chart theme or preference.
Supports All Major MAs — Including EMA, SMA, HMA, RMA, WMA, VWMA, SWMA, ALMA.
Overlay-Friendly — Plots directly over price action for seamless market context.
Analytical and Statistical Value:
Visual Sensitivity Comparison: See how fast-reacting MAs (e.g., EMA, HMA) compare to slower, smoother MAs (e.g., SMA, ALMA) over the same periods — critical for understanding market momentum and lag.
Trend Strength and Consensus Detection: When two ribbons align tightly, the trend is strong and consistent; when they diverge, it signals potential reversal or market indecision.
Momentum Shift Identification: Fast MA ribbons breaking while slow MA ribbons hold indicate early momentum shifts or trap moves.
Trade Filtering and Confirmation: Only trade when both ribbons agree in direction, helping avoid false signals and improving entry/exit confidence.
Quantitative MA Efficiency Testing: Visually backtest and analyze which MA types work best for specific assets or strategies.
Use Cases:
Trend Following: Confirm trend strength by aligning both ribbons.
Reversal Anticipation: Spot divergence between ribbons as early reversal signals.
Momentum Trading: Use fast ribbons for early signals and slow ribbons for confirmation.
Breakout & Pullback Strategy: Analyze whether breakouts are sustained across different MA methodologies.
Backtesting and Optimization: Visually test combinations like EMA vs. HMA or VWMA vs. SMA to optimize strategies for specific assets.
Example MA Comparisons You Can Analyze:
Price Action vs. Volume-weighted: EMA vs. VWMA
Fast-reactive vs. Smooth: HMA vs. SMA
Minimal Lag vs. Standard: ALMA vs. EMA
Weighted vs. Wilder's (RMA): WMA vs. RMA
This is NOT:
A recommendation for what you should personally do.
Investment advice.
Intended solely for qualified investors.
Witchcraft or wizardry.
The only certainty is uncertainty
*Auto Backtest & Optimize EngineFull-featured Engine for Automatic Backtesting and parameter optimization. Allows you to test millions of different combinations of stop-loss and take profit parameters, including on any connected indicators.
⭕️ Key Futures
Quickly identify the optimal parameters for your strategy.
Automatically generate and test thousands of parameter combinations.
A simple Genetic Algorithm for result selection.
Saves time on manual testing of multiple parameters.
Detailed analysis, sorting, filtering and statistics of results.
Detailed control panel with many tooltips.
Display of key metrics: Profit, Win Rate, etc..
Comprehensive Strategy Score calculation.
In-depth analysis of the performance of different types of stop-losses.
Possibility to use to calculate the best Stop-Take parameters for your position.
Ability to test your own functions and signals.
Customizable visualization of results.
Flexible Stop-Loss Settings:
• Auto ━ Allows you to test all types of Stop Losses at once(listed below).
• S.VOLATY ━ Static stop based on volatility (Fixed, ATR, STDEV).
• Trailing ━ Classic trailing stop following the price.
• Fast Trail ━ Accelerated trailing stop that reacts faster to price movements.
• Volatility ━ Dynamic stop based on volatility indicators.
• Chandelier ━ Stop based on price extremes.
• Activator ━ Dynamic stop based on SAR.
• MA ━ Stop based on moving averages (9 different types).
• SAR ━ Parabolic SAR (Stop and Reverse).
Advanced Take-Profit Options:
• R:R: Risk/Reward ━ sets TP based on SL size.
• T.VOLATY ━ Calculation based on volatility indicators (Fixed, ATR, STDEV).
Testing Modes:
• Stops ━ Cyclical stop-loss testing
• Pivot Point Example ━ Example of using pivot points
• External Example ━ Built-in example how test functions with different parameters
• External Signal ━ Using external signals
⭕️ Usage
━ First Steps:
When opening, select any point on the chart. It will not affect anything until you turn on Manual Start mode (more on this below).
The chart will immediately show the best results of the default Auto mode. You can switch Part's to try to find even better results in the table.
Now you can display any result from the table on the chart by entering its ID in the settings.
Repeat steps 3-4 until you determine which type of Stop Loss you like best. Then set it in the settings instead of Auto mode.
* Example: I flipped through 14 parts before I liked the first result and entered its ID so I could visually evaluate it on the chart.
Then select the stop loss type, choose it in place of Auto mode and repeat steps 3-4 or immediately follow the recommendations of the algorithm.
Now the Genetic Algorithm at the bottom right will prompt you to enter the Parameters you need to search for and select even better results.
Parameters must be entered All at once before they are updated. Enter recommendations strictly in fields with the same names.
Repeat steps 5-6 until there are approximately 10 Part's left or as you like. And after that, easily pour through the remaining Parts and select the best parameters.
━ Example of the finished result.
━ Example of use with Takes
You can also test at the same time along with Take Profit. In this example, I simply enabled Risk/Reward mode and immediately specified in the TP field Maximum RR, Minimum RR and Step. So in this example I can test (3-1) / 0.1 = 20 Takes of different sizes. There are additional tips in the settings.
━
* Soon you will start to understand how the system works and things will become much easier.
* If something doesn't work, just reset the engine settings and start over again.
* Use the tips I have left in the settings and on the Panel.
━ Details:
Sort ━ Sorting results by Score, Profit, Trades, etc..
Filter ━ Filtring results by Score, Profit, Trades, etc..
Trade Type ━ Ability to disable Long\Short but only from statistics.
BackWin ━ Backtest Window Number of Candle the script can test.
Manual Start ━ Enabling it will allow you to call a Stop from a selected point. which you selected when you started the engine.
* If you have a real open position then this mode can help to save good Stop\Take for it.
1 - 9 Сheckboxs ━ Allow you to disable any stop from Auto mode.
Ex Source - Allow you to test Stops/Takes from connected indicators.
Connection guide:
//@version=6
indicator("My script")
rsi = ta.rsi(close, 14)
buy = not na(rsi) and ta.crossover (rsi, 40) // OS = 40
sell = not na(rsi) and ta.crossunder(rsi, 60) // OB = 60
Signal = buy ? +1 : sell ? -1 : 0
plot(Signal, "🔌Connector🔌", display = display.none)
* Format the signal for your indicator in a similar style and then select it in Ex Source.
⭕️ How it Works
Hypothesis of Uniform Distribution of Rare Elements After Mixing.
'This hypothesis states that if an array of N elements contains K valid elements, then after mixing, these valid elements will be approximately uniformly distributed.'
'This means that in a random sample of k elements, the proportion of valid elements should closely match their proportion in the original array, with some random variation.'
'According to the central limit theorem, repeated sampling will result in an average count of valid elements following a normal distribution.'
'This supports the assumption that the valid elements are evenly spread across the array.'
'To test this hypothesis, we can conduct an experiment:'
'Create an array of 1,000,000 elements.'
'Select 1,000 random elements (1%) for validation.'
'Shuffle the array and divide it into groups of 1,000 elements.'
'If the hypothesis holds, each group should contain, on average, 1~ valid element, with minor variations.'
* I'd like to attach more details to My hypothesis but it won't be very relevant here. Since this is a whole separate topic, I will leave the minimum part for understanding the engine.
Practical Application
To apply this hypothesis, I needed a way to generate and thoroughly mix numerous possible combinations. Within Pine, generating over 100,000 combinations presents significant challenges, and storing millions of combinations requires excessive resources.
I developed an efficient mechanism that generates combinations in random order to address these limitations. While conventional methods often produce duplicates or require generating a complete list first, my approach guarantees that the first 10% of possible combinations are both unique and well-distributed. Based on my hypothesis, this sampling is sufficient to determine optimal testing parameters.
Most generators and randomizers fail to accommodate both my hypothesis and Pine's constraints. My solution utilizes a simple Linear Congruential Generator (LCG) for pseudo-randomization, enhanced with prime numbers to increase entropy during generation. I pre-generate the entire parameter range and then apply systematic mixing. This approach, combined with a hybrid combinatorial array-filling technique with linear distribution, delivers excellent generation quality.
My engine can efficiently generate and verify 300 unique combinations per batch. Based on the above, to determine optimal values, only 10-20 Parts need to be manually scrolled through to find the appropriate value or range, eliminating the need for exhaustive testing of millions of parameter combinations.
For the Score statistic I applied all the same, generated a range of Weights, distributed them randomly for each type of statistic to avoid manual distribution.
Score ━ based on Trade, Profit, WinRate, Profit Factor, Drawdown, Sharpe & Sortino & Omega & Calmar Ratio.
⭕️ Notes
For attentive users, a little tricks :)
To save time, switch parts every 3 seconds without waiting for it to load. After 10-20 parts, stop and wait for loading. If the pause is correct, you can switch between the rest of the parts without loading, as they will be cached. This used to work without having to wait for a pause, but now it does slower. This will save a lot of time if you are going to do a deeper backtest.
Sometimes you'll get the error “The scripts take too long to execute.”
For a quick fix you just need to switch the TF or Ticker back and forth and most likely everything will load.
The error appears because of problems on the side of the site because the engine is very heavy. It can also appear if you set too long a period for testing in BackWin or use a heavy indicator for testing.
Manual Start - Allow you to Start you Result from any point. Which in turn can help you choose a good stop-stick for your real position.
* It took me half a year from idea to current realization. This seems to be one of the few ways to build something automatic in backtest format and in this particular Pine environment. There are already better projects in other languages, and they are created much easier and faster because there are no limitations except for personal PC. If you see solutions to improve this system I would be glad if you share the code. At the moment I am tired and will continue him not soon.
Also You can use my previosly big Backtest project with more manual settings(updated soon)
Clustering Volatility (ATR-ADR-ChaikinVol) [Sam SDF-Solutions]The Clustering Volatility indicator is designed to evaluate market volatility by combining three widely used measures: Average True Range (ATR), Average Daily Range (ADR), and the Chaikin Oscillator.
Each indicator is normalized using one of the available methods (MinMax, Rank, or Z-score) to create a unified metric called the Score. This Score is further smoothed with an Exponential Moving Average (EMA) to reduce noise and provide a clearer view of market conditions.
Key Features:
Multi-Indicator Integration: Combines ATR, ADR, and the Chaikin Oscillator into a single Score that reflects overall market volatility.
Flexible Normalization: (Supports three normalization methods)
MinMax: Scales values between the observed minimum and maximum.
Rank: Normalizes based on the relative rank within a moving window.
Z-score: Standardizes values using mean and standard deviation.
Dynamic Window Selection: Offers an automatic window selection option based on a specified lookback period, or a fixed window size can be used.
Customizable Weights: Allows the user to assign individual weights to ATR, ADR, and the Chaikin Oscillator. Optionally, weights can be normalized to sum to 1.
Score Smoothing: Applies an EMA to the computed Score to smooth out short-term fluctuations and reduce market noise.
Cluster Visualization: Divides the smoothed Score into a number of clusters, each represented by a distinct color. These colors can be applied to the price bars (if enabled) for an immediate visual indication of the current volatility regime.
How It Works:
Input & Window Setup: Users set parameters for indicator periods, normalization methods, weights, and window size. The indicator can automatically determine the analysis window based on the number of lookback days.
Calculation of Metrics: The indicator computes the ATR, ADR (as the average of bar ranges), and the Chaikin Oscillator (based on the difference between short and long EMAs of the Accumulation/Distribution line).
Normalization & Scoring: Each indicator’s value is normalized and then weighted to form a raw Score. This raw Score is scaled to a range using statistics from the chosen window.
Smoothing & Clustering: The raw Score is smoothed using an EMA. The resulting smoothed Score is then multiplied by the number of clusters to assign a cluster index, which is used to choose a color for visual signals.
Visualization: The smoothed Score is plotted on the chart with a color that changes based on its value (e.g., lime for low, red for high, yellow for intermediate values). Optionally, the price bars are colored according to the assigned cluster.
_____________
This indicator is ideal for traders seeking a quick and clear assessment of market volatility. By integrating multiple volatility measures into one comprehensive Score, it simplifies analysis and aids in making more informed trading decisions.
For more detailed instructions, please refer to the guide here:
Statistically Extreme Areas by QTX Algo SystemsStatistically Extreme Areas by QTX Algo Systems
Overview
This indicator helps traders pinpoint potential reversal zones by detecting when prices become statistically overextended. By combining advanced statistical analysis with volatility and momentum metrics—including BBWP, SMI, PMARP, and Bollinger Band Oscillator (BBO) slope analysis—it provides clear visual cues for identifying market extremes and managing risk.
How It Works
Baseline Statistical Calculation:
The indicator starts by establishing a baseline price range using historical data through a statistical percentile approach. This captures the typical extremes over a significant period and forms the foundation for further analysis.
Volatility Adjustment:
A Bollinger Band Width Percentile (BBWP) measure is used to assess recent price variability. This dynamic volatility factor adjusts the baseline, ensuring that signals are only generated when overall market volatility exceeds a minimum threshold.
Momentum and Trend Verification:
A double‐smoothed Stochastic Momentum Index (SMI) captures short-term momentum, while a Price – Moving Average Ratio (PMARP) confirms the prevailing trend's strength. Additionally, a Bollinger Band Oscillator (BBO) calculates the slopes of the upper and lower bands to further refine the detection of extreme conditions without relying solely on a simple mashup of standard indicators.
Why It's Different
Rather than merely merging common indicators, this tool integrates distinct layers of analysis to produce a cohesive and dynamic framework. The synthesis of statistical extremes, real-time volatility adjustments, and momentum/trend verification helps filter out noise and false signals, offering traders a robust method to identify reversal zones and set precise stop-loss levels. This multi-dimensional approach delivers actionable insights that go beyond what traditional support/resistance or momentum indicators can offer on their own.
How to Use
Interpret the Visual Cues:
Watch for the color-coded background changes that signal statistically extreme conditions.
Integrate with Your Analysis:
Use these visual alerts alongside other technical tools to refine your entry and exit decisions and to enhance your overall risk management.
Disclaimer
This indicator is for educational purposes only and is intended to support your trading analysis. It does not guarantee performance, and past results are not indicative of future outcomes. Always use proper risk management and perform your own analysis before trading.
Statistical Price Bands with Trend Filtering by QTX Algo SystemsStatistical Price Bands with Trend Filtering by QTX Algo Systems
Overview
This indicator generates adaptive support and resistance bands by fusing statistical analysis with real-time volatility and trend measurements. It highlights areas where prices appear overextended, providing traders with clear visual cues for potential reversals or risk management adjustments.
How It Works
Baseline Statistical Calculation:
The indicator begins by deriving a baseline price range from historical data using a statistical percentile approach. This percentile reflects the typical extremes observed over a significant period, forming the foundation for the bands.
Volatility Adjustment:
A dynamic volatility factor is then calculated by comparing the moving standard deviation of price to its moving average. This factor adjusts the baseline, ensuring that the bands reflect current market variability. The use of both a long-term dispersion measure and a short-term percentile-based volatility metric helps confirm that overall market volatility remains above a minimum threshold.
Trend Filtering:
In parallel, the indicator assesses trend direction by comparing the current price to a volume-weighted moving average (VWMA). This trend component shifts the bands in the direction of the prevailing market bias—moving the bands upward during uptrends and downward during downtrends.
Why It’s Different
Unlike traditional static support/resistance tools, this indicator integrates multiple layers of analysis—statistical extremes, real-time volatility, and trend direction—to create bands that continuously adapt to market conditions. This synthesis produces a dynamic framework that not only identifies potential overextended price areas but also provides practical stop loss levels, setting it apart from other basic band or moving average models.
How to Use
Customize the baseline statistical setting to match your trading style. Use the dynamically adjusted bands as visual cues for potential reversal zones or as guides for setting stop losses. Combine these insights with other technical tools to refine your entry and exit decisions.
Disclaimer
This indicator is for educational purposes only and is intended to support your trading strategy. It does not guarantee performance, and past results are not indicative of future outcomes. Always use proper risk management and perform your own analysis before trading.
