Drawdown Tracker [SpokoStocks]Drawdown Tracker
The Drawdown Tracker is a powerful tool designed to help traders monitor and visualize the drawdown of symbol. By tracking both current and maximum drawdown levels, this indicator provides valuable insights into risk and potential capital preservation.
Features:
> Current Drawdown:
The current drawdown is calculated as the percentage drop from the record high to the current low, providing a real-time view of the loss from the peak.
> Maximum Drawdown:
The maximum drawdown represents the deepest drop observed from any peak in the historical data, giving an understanding of the worst-case scenario for losses.
> You can choose between two modes:
Full History: Tracks the maximum drawdown from the entire available data.
Rolling Period: Tracks the maximum drawdown within a defined rolling period (default 50 bars), allowing for a shorter-term risk assessment.
> Customizable Rolling Period:
You can adjust the rolling period length through the Rolling Period Length input to reflect different time frames for drawdown calculations.
> Warning Level:
A customizable warning level (default -65%) is plotted on the chart. This acts as a threshold to alert users when the drawdown crosses into a potentially concerning territory.
> Gradient Color Visualization:
The current drawdown is visualized using a gradient color, transitioning from red to yellow as the drawdown increases from -100% to 0%, providing an easy-to-interpret view of the severity of the drawdown.
> New Max Drawdown Marker:
Whenever a new maximum drawdown is recorded, a triangle marker is displayed at the bottom of the chart, along with a label showing the drawdown percentage. This provides clear visual confirmation when a new historical low is reached.
> Alerts:
Warning Level Breach Alert: Alerts you when the drawdown breaches the warning level you’ve set, helping you stay aware of significant risk events.
New Max Drawdown Alert: Triggers when a new maximum drawdown is recorded, allowing you to act quickly if necessary.
Use Cases:
Risk Management: Keep track of how much an asset is down from the peak, helping you make informed decisions about risk and drawdown tolerances.
Risk Disclaimer:
The information provided by this script is for educational and informational purposes only. It is not intended as financial advice and should not be construed as such. All trading and investment activities involve a high level of risk and may result in the loss of capital. The user is solely responsible for any decisions made based on the content provided by this script.
By using this script, you acknowledge and agree that you use it at your own risk. The creator of this script makes no warranties regarding the accuracy, completeness, or reliability of the information, and disclaims any responsibility for any losses or damages arising from its use.
Always conduct your own research and consult with a qualified financial advisor before making any investment decisions.
Statistics
Trend Reversal Probability [Algoalpha]Introducing Trend Reversal Probability by AlgoAlpha – a powerful indicator that estimates the likelihood of trend reversals based on an advanced custom oscillator and duration-based statistics. Designed for traders who want to stay ahead of potential market shifts, this indicator provides actionable insights into trend momentum and reversal probabilities.
Key Features :
🔧 Custom Oscillator Calculation: Combines a dual SMA strategy with a proprietary RSI-like calculation to detect market direction and strength.
📊 Probability Levels & Visualization: Plots average signal durations and their statistical deviations (±1, ±2, ±3 SD) on the chart for clear visual guidance.
🎨 Dynamic Color Customization: Choose your preferred colors for upward and downward trends, ensuring a personalized chart view.
📈 Signal Duration Metrics: Tracks and displays signal durations with columns representing key percentages (80%, 60%, 40%, and 20%).
🔔 Alerts for High Probability Events: Set alerts for significant reversal probabilities (above 84% and 98% or below 14%) to capture key trading moments.
How to Use :
Add the Indicator: Add Trend Reversal Probability to your favorites by clicking the star icon.
Market Analysis: Use the plotted probability levels (average duration and ±SD bands) to identify overextended trends and potential reversals. Use the color of the duration counter to identify the current trend.
Leverage Alerts: Enable alerts to stay informed of high or extreme reversal probabilities without constant chart monitoring.
How It Works :
The indicator begins by calculating a custom oscillator using short and long simple moving averages (SMA) of the midpoint price. A proprietary RSI-like formula then transforms these values to estimate trend direction and momentum. The duration between trend reversals is tracked and averaged, with standard deviations plotted to provide probabilistic guidance on trend longevity. Additionally, the indicator incorporates a cumulative probability function to estimate the likelihood of a trend reversal, displaying the result in a data table for easy reference. When probability levels cross key thresholds, alerts are triggered, helping traders take timely action.
Best Range (Day Trading)The indicator is based on a formula very similar to that of the ATR. The average volatility of the last candles (a value adjustable via inputs) is calculated, and this value is then divided (a value adjustable via inputs), providing a specific value in terms of RANGE .
Its use is very straightforward. It was primarily designed for stock indices (Nasdaq & SPX). When used on the DAILY timeframe, it provides the recommended RANGE value for day trading with structural logic.
Its goal is to offer a guiding value for setting the chart to a range-based view that is optimal and as effective as possible in identifying breakouts of specific levels , helping traders avoid false breakouts or misleading structures.
We can also observe a division of levels into quartiles (25, 50, 75, 100, 125...). This helps provide reference ranges, allowing the range to be used with rounded numbers .
For example, on Nasdaq , if the indicator set on DAILY provides a value between 200 and 250, then it is advisable to visualize the chart at 200 RANGE for a more aggressive approach or at 250 RANGE for a more conservative approach.
On SPX , which is less volatile, we use increments of 25. If the indicator gives a value between 25 and 50 , then we use 25 for an aggressive approach and 50 for a conservative approach.
Obviously, this refers to FUTURES and the tick movements of MINI contracts.
Stop Loss & TargetHow to Use the SL/TP Indicator
The SL/TP indicator is a versatile tool designed for traders to easily visualize entry, stop-loss (SL), and take-profit (TP) levels on their charts. This guide will walk you through the steps to configure and use the indicator effectively.
Features:
Configure Long Trades and Short Trades independently.
Define Entry Price, Stop Loss, and up to three Take Profit levels for each trade.
Customize line colors for better visualization.
Works for both risk-reward and target-based trading.
Adding the Indicator:
Open the TradingView platform.
Search for the indicator name: SL/TP.
Click the Add to Chart button to apply it.
Configuration:
1. Long Trade Settings
Enable Long Trade: Check this option to activate long trade lines on the chart.
Long Entry Price: Input the price at which you plan to enter the long trade.
Long Stop Loss: Input your stop-loss level for the long trade.
Line Colors: You can customize the colors for the Entry, SL, and TP lines in the Long Trade settings group.
Take Profit Levels (Calculated Automatically):
TP1: 1:1 Risk-Reward ratio (difference between Entry and SL added to Entry).
TP2: 1:2 Risk-Reward ratio.
TP3: 1:3 Risk-Reward ratio.
2. Short Trade Settings
Enable Short Trade: Check this option to activate short trade lines on the chart.
Short Entry Price: Input the price at which you plan to enter the short trade.
Short Stop Loss: Input your stop-loss level for the short trade.
Line Colors: You can customize the colors for the Entry, SL, and TP lines in the Short Trade settings group.
Take Profit Levels (Calculated Automatically):
TP1: 1:1 Risk-Reward ratio (difference between Entry and SL subtracted from Entry).
TP2: 1:2 Risk-Reward ratio.
TP3: 1:3 Risk-Reward ratio.
Visualizing on the Chart:
Once you configure the settings and enable the trade, the indicator will draw horizontal lines on the chart for:
Entry Price
Stop Loss
Take Profit Levels (TP1, TP2, TP3)
Each line will extend to three bars ahead of the current bar index.
Customization:
Adjust colors for better visibility depending on your chart theme.
The width and style of lines can also be modified in the source code if needed.
Example Usage:
Long Trade Example:
Enable Long Trade: Check the box.
Set Entry Price: 100.
Set Stop Loss: 95.
The indicator will draw the following lines:
Entry Line: At 100 (customizable color).
Stop Loss Line: At 95 (customizable color).
TP1 Line: At 105 (1:1 Risk-Reward).
TP2 Line: At 110 (1:2 Risk-Reward).
TP3 Line: At 115 (1:3 Risk-Reward).
Short Trade Example:
Enable Short Trade: Check the box.
Set Entry Price: 200.
Set Stop Loss: 205.
The indicator will draw the following lines:
Entry Line: At 200 (customizable color).
Stop Loss Line: At 205 (customizable color).
TP1 Line: At 195 (1:1 Risk-Reward).
TP2 Line: At 190 (1:2 Risk-Reward).
TP3 Line: At 185 (1:3 Risk-Reward).
Notes:
Ensure that you input valid and realistic price levels for Entry and Stop Loss.
The indicator will only display lines if both the Entry Price and Stop Loss are non-zero.
Use this indicator for planning trades visually but always confirm levels with your trading strategy.
Disclaimer: This indicator is a tool to assist in trading. Use it with proper risk management and your own due diligence.
ADX (levels)This Pine Script indicator calculates and displays the Average Directional Index (ADX) along with the DI+ and DI- lines to help identify the strength and direction of a trend. The script is designed for Pine Script v6 and includes customizable settings for a more tailored analysis.
Features:
ADX Calculation:
The ADX measures the strength of a trend without indicating its direction.
It uses a smoothing method for more reliable trend strength detection.
DI+ and DI- Lines (Optional):
The DI+ (Directional Index Plus) and DI- (Directional Index Minus) help determine the direction of the trend:
DI+ indicates upward movement.
DI- indicates downward movement.
These lines are disabled by default but can be enabled via input settings.
Customizable Threshold:
A horizontal line (hline) is plotted at a user-defined threshold level (default: 20) to highlight significant ADX values that indicate a strong trend.
Slope Analysis:
The slope of the ADX is analyzed to classify the trend into:
Strong Trend: Slope is higher than a defined "medium" threshold.
Moderate Trend: Slope falls between "weak" and "medium" thresholds.
Weak Trend: Slope is positive but below the "weak" threshold.
A background color changes dynamically to reflect the strength of the trend:
Green (light or dark) indicates trend strength levels.
Custom Colors:
ADX color is customizable (default: pink #e91e63).
Background colors for trend strength can also be adjusted.
Independent Plot Window:
The indicator is displayed in a separate window below the price chart, making it easier to analyze trend strength without cluttering the main price chart.
Parameters:
ADX Period: Defines the lookback period for calculating the ADX (default: 14).
Threshold (hline): A horizontal line value to differentiate strong trends (default: 20).
Slope Thresholds: Adjustable thresholds for weak, moderate, and strong trend slopes.
Enable DI+ and DI-: Boolean options to display or hide the DI+ and DI- lines.
Colors: Customizable colors for ADX, background gradients, and other elements.
How to Use:
Identify Trend Strength:
Use the ADX value to determine the strength of a trend:
Below 20: Weak trend.
Above 20: Strong trend.
Analyze Trend Direction:
Enable DI+ and DI- to check whether the trend is upward (DI+ > DI-) or downward (DI- > DI+).
Dynamic Slope Detection:
Use the background color as a quick visual cue to assess trend strength changes.
This indicator is ideal for traders who want to measure trend strength and direction dynamically while maintaining a clean and organized chart layout.
[ADDYad] Google Search Trends - Bitcoin (2012 Jan - 2025 Jan)This Pine Script shows the Google Search Trends as an indicator for Bitcoin from January 2012 to January 2025, based on monthly data retrieved from Google Trends. It calculates and displays the relative search interest for Bitcoin over time, offering a historical perspective on its popularity mainly built for BITSTAMP:BTCUSD .
Important note: This is not a live indicator. It visualizes historical search trends based on Google Trends data.
Key Features:
Data Source : Google Trends (Last retrieved in January 10 2025).
Timeframe : The script is designed to be used on a monthly chart, with the data reflecting monthly search trends from January 2012 to January 2025. For other timeframes, the data is linearly interpolated to estimate the trends at finer resolutions.
Purpose : This indicator helps visualize Bitcoin's search interest over the years, offering insights into public interest and sentiment during specific periods (e.g., major price movements or news events).
Data Handling : The data is interpolated for use on non-monthly timeframes, allowing you to view search trends on any chart timeframe. This makes it versatile for use in longer-term analysis or shorter timeframes, despite the raw data being available only on a monthly basis. However, it is most relevant for Monthly, Weekly, and Daily timeframes.
How It Works:
The script calculates the number of months elapsed since January 1, 2012, and uses this to interpolate Google Trends data values for any given point in time on the chart.
The linear interpolation function adjusts the monthly data to provide an approximate trend for intermediate months.
Why It's Useful:
Track Bitcoin's historic search trends to understand how interest in Bitcoin evolved over time, potentially correlating with price movements.
Correlate search trends with price action and other market indicators to analyze the effects of public sentiment and sentiment-driven market momentum.
Final Notes:
This script is unique because it shows real-world, non-financial dataset (Google Trends) to understand price action of Bitcoin correlating with public interest. Hopefully is a valuable addition to the TradingView community.
ADDYad
Simple Average Price & Target ProfitThis script is designed to help users calculate and visualize the weighted average price of an asset based on multiple entry points, along with the target price and the potential profit. The user can input specific prices for three different entries, along with the percentage of total investment allocated to each price point. The script then calculates the weighted average price based on these entries and displays it on the chart. Additionally, it calculates the potential profit at a given target price, which is plotted on the chart.
Simple COT ReportCOT Net Positions Indicator
Author: © Munkhtur
This indicator provides a comprehensive visualization of the Commitment of Traders (COT) report data, enabling traders to analyze market sentiment and positioning for key market participants.
Key Features:
Dashboard Display: Shows the net positions of Commercial, Noncommercial, and Nonreportable (Retail) traders.
Dynamic Position Tracking: Highlights significant changes in long and short positions for all trader categories based on customizable percentage thresholds.
COT Data Integration: Utilizes Legacy COT report data with clear segregation of long, short, and net positions.
Visual Signals:
Bullish and bearish trends are indicated with customizable colors for better chart visualization.
Displays "open" and "close" position changes directly on the price candles for easier tracking.
Flexible Configuration: Adjustable settings for dashboard location, text size, percentage thresholds, and color schemes.
How to Use:
Load the Script: Add the indicator to your Futures chart only by navigating to the TradingView indicators menu and selecting it from your saved scripts.
Customize Settings:
Dashboard: Enable or disable the dashboard, and set its position (Top Left, Top Right, etc.).
Data on Candle: Turn on/off the visualization of COT data changes on price candles and define the percentage change threshold to focus on significant moves.
Style Options: Customize bullish and bearish colors for better visual differentiation.
Select Trader Group: Choose from Commercial, Noncommercial, or Nonreportable positions in the settings menu to analyze the specific group of market participants.
Interpret Signals:
Green bars indicate opening long positions or bullish sentiment.
Red bars highlight opening short positions or bearish sentiment.
Yellow and purple bars signify the closure of long and short positions, respectively.
Use Cases:
Identify market sentiment shifts by observing net position changes among different trader groups.
Spot potential trend reversals based on COT data dynamics.
Use as a complementary tool to confirm your existing trading strategies.
Disclaimer:
This indicator is a tool for educational and informational purposes only. Always combine it with your own analysis and risk management strategy when trading.
ADR Table BY @ICT_YEROADR Table BY @ICT_YERO
Created by: @ICT_YERO
This custom indicator is designed to provide the Average Daily Range (ADR) for multiple timeframes, including Daily, 4-Hour, and 1-Hour. The indicator is tailored to assist traders in understanding price volatility and making informed trading decisions.
Key Features
Multi-Timeframe ADR Calculation:
Automatically calculates and displays the ADR for Daily, 4-Hour, and 1-Hour timeframes.
Helps traders identify potential price movement ranges for different trading sessions.
Dynamic Range Visualization:
Clear visual representation of the ADR on the chart, making it easy to spot price extremes.
Real-time updates to reflect changes in price movement.
Custom Alerts:
Option to set alerts when the price approaches the ADR high or low.
Useful for identifying potential reversal zones or breakout opportunities.
User-Friendly Interface:
Simple and intuitive settings to customize colors, levels, and display preferences.
Seamlessly integrates with your existing TradingView setup.
ICT-Inspired Methodology:
Designed for traders who follow ICT concepts, focusing on precision and high-probability setups.
Applications
Range Trading: Helps determine the high and low boundaries for scalping or intraday setups.
Volatility Analysis: Understand market behavior during different times of the day or week.
Reversal Zones: Identify areas where price is likely to reverse, based on ADR extremes.
Whether you're a scalper, day trader, or swing trader, this indicator provides a comprehensive overview of price volatility across multiple timeframes, making it an essential tool for your trading arsenal.
Position sizerPosition Sizer Indicator
The "Position Sizer" indicator is a practical tool for traders who need to quickly and accurately calculate position sizes based on their account balance, risk tolerance, and stop-loss level. It ensures real-time updates and supports multiple asset classes like Forex, Indexes, Metals, and Crypto.
Key Features
Dynamic Position Sizing: Automatically calculates position sizes based on the current market price and stop-loss level.
Stop-Loss Adjustment: Allows users to drag the stop-loss level directly on the chart, dynamically updating the position size.
Interactive Table: A single click on the table activates the draggable stop-loss level for easy adjustments.
Multi-Asset Compatibility: Fully supports Forex, Indexes, Metals, and Crypto trading pairs.
How to Use
Deactivate the Indicator:
Turn off the indicator to make it inactive.
Set the Stop-Loss Price:
Copy the stop-loss price or use a price near the current market price.
Reactivate the indicator after inserting the stop-loss price.
Adjust the Stop-Loss Level if needed:
Click once on the table to enable the stop-loss level for dragging.
Move the stop-loss line as needed—position sizes will automatically recalculate.
Important Disclaimer
Verification Required: Always verify the calculated position size before executing trades.
Broker Confirmation: Double-check the point size for your trading symbol with your broker to avoid errors in calculations.
User Responsibility: The creator assumes no responsibility for any trading decisions made based on this indicator.
This tool helps streamline position management, ensuring you can focus on executing your trades with accuracy and speed. Always confirm your calculations before trading.
Poisson Projection of Price Levels### **Poisson Projection of Price Levels**
**Overview:**
The *Poisson Projection of Price Levels* is a cutting-edge technical indicator designed to identify and visualize potential support and resistance levels based on historical price interactions. By leveraging the Poisson distribution, this tool dynamically adjusts the significance of each price level's past "touches" to project future interactions with varying degrees of probability. This probabilistic approach offers traders a nuanced view of where price levels may hold or react in upcoming bars, enhancing both analysis and trading strategies.
---
**🔍 **Math & Methodology**
1. **Strata Levels:**
- **Definition:** Strata are horizontal lines spaced evenly around the current closing price.
- **Calculation:**
\
where \(i\) ranges from 0 to \(\text{Strata Count} - 1\).
2. **Forecast Iterations:**
- **Structure:** The indicator projects five forecast iterations into the future, each spaced by a Fibonacci sequence of bars: 2, 3, 5, 8, and 13 bars ahead. This spacing is inspired by the Fibonacci sequence, which is prevalent in financial market analysis for identifying key levels.
- **Purpose:** Each iteration represents a distinct forecast point where the price may interact with the strata, allowing for a multi-step projection of potential price levels.
3. **Touch Counting:**
- **Definition:** A "touch" occurs when the closing price of a bar is within half the increment of a stratum level.
- **Process:** For each stratum and each forecast iteration, the indicator counts the number of touches within a specified lookback window (e.g., 80 bars), offset by the forecasted position. This ensures that each iteration's touch count is independent and contextually relevant to its forecast horizon.
- **Adjustment:** Each forecast iteration analyzes a unique segment of the lookback window, offset by its forecasted position to ensure independent probability calculations.
4. **Poisson Probability Calculation:**
- **Formula:**
\
\
- **Interpretation:** \(p(k=1)\) represents the probability of exactly one touch occurring within the lookback window for each stratum and iteration.
- **Application:** This probability is used to determine the transparency of each stratum line, where higher probabilities result in more opaque (less transparent) lines, indicating stronger historical significance.
5. **Transparency Mapping:**
- **Calculation:**
\
- **Purpose:** Maps the Poisson probability to a visual transparency level, enhancing the readability of significant strata levels.
- **Outcome:** Strata with higher probabilities (more historical touches) appear more opaque, while those with lower probabilities appear fainter.
---
**📊 **Comparability to Standard Techniques**
1. **Support and Resistance Levels:**
- **Traditional Approach:** Traders identify support and resistance based on historical price reversals, pivot points, or psychological price levels.
- **Poisson Projection:** Automates and quantifies this process by statistically analyzing the frequency of price interactions with specific levels, providing a probabilistic measure of significance.
2. **Statistical Modeling:**
- **Standard Models:** Techniques like Moving Averages, Bollinger Bands, or Fibonacci Retracements offer dynamic and rule-based levels but lack direct probabilistic interpretation.
- **Poisson Projection:** Introduces a discrete event probability framework, offering a unique blend of statistical rigor and visual clarity that complements traditional indicators.
3. **Event-Based Analysis:**
- **Financial Industry Practices:** Event studies and high-frequency trading models often use Poisson processes to model order arrivals or price jumps.
- **Indicator Application:** While not identical, the use of Poisson probabilities in this indicator draws inspiration from event-based modeling, applying it to the context of price level interactions.
---
**💡 **Strengths & Advantages**
1. **Innovative Visualization:**
- Combines statistical probability with traditional support/resistance visualization, offering a fresh perspective on price level significance.
2. **Dynamic Adaptability:**
- Parameters like strata increment, lookback window, and probability threshold are user-defined, allowing customization across different markets and timeframes.
3. **Independent Probability Calculations:**
- Each forecast iteration calculates its own Poisson probability, ensuring that projections are contextually relevant and independent of other iterations.
4. **Clear Visual Cues:**
- Transparency-based coloring intuitively highlights significant price levels, making it easier for traders to identify key areas of interest at a glance.
---
**⚠️ **Limitations & Considerations**
1. **Poisson Assumptions:**
- Assumes that touches occur independently and at a constant average rate (\(\lambda\)), which may not always align with market realities characterized by trends and volatility clustering.
2. **Computational Intensity:**
- Managing multiple iterations and strata can be resource-intensive, potentially affecting performance on lower-powered devices or with very high lookback windows.
3. **Interpretation Complexity:**
- While transparency offers visual clarity, understanding the underlying probability calculations requires a basic grasp of Poisson statistics, which may be a barrier for some traders.
---
**📢 **How to Use It**
1. **Add to TradingView:**
- Open TradingView and navigate to the Pine Script Editor.
- Paste the script above and click **Add to Chart**.
2. **Configure Inputs:**
- **Strata Increment:** Set the desired price step between strata (e.g., `0.1` for 10 cents).
- **Lookback Window:** Define how many past bars to consider for calculating Poisson probabilities (e.g., `80`).
- **Probability Transparency Threshold (%):** Set the threshold percentage to map probabilities to line transparency (e.g., `25%`).
3. **Understand the Forecast Iterations:**
- The indicator projects five forecast points into the future at bar spacings of 2, 3, 5, 8, and 13 bars ahead.
- Each iteration independently calculates its Poisson probability based on the touch counts within its specific lookback window offset by its forecasted position.
4. **Interpret the Visualization:**
- **Opaque Lines:** Indicate higher Poisson probabilities, suggesting historically significant price levels that are more likely to interact again.
- **Fainter Lines:** Represent lower probabilities, indicating less historically significant levels that may be less likely to interact.
- **Forecast Spacing:** The spacing of 2, 3, 5, 8, and 13 bars ahead aligns with Fibonacci principles, offering a natural progression in forecast horizons.
5. **Apply to Trading Strategies:**
- **Support/Resistance Identification:** Use the opaque lines as potential support and resistance levels for placing trades.
- **Entry and Exit Points:** Anticipate price interactions at forecasted levels to plan strategic entries and exits.
- **Risk Management:** Utilize the transparency mapping to determine where to place stop-loss and take-profit orders based on the probability of price interactions.
6. **Customize as Needed:**
- Adjust the **Strata Increment** to fit different price ranges or volatility levels.
- Modify the **Lookback Window** to capture more or fewer historical touches, adapting to different timeframes or market conditions.
- Tweak the **Probability Transparency Threshold** to control the sensitivity of transparency mapping to Poisson probabilities.
**📈 **Practical Applications**
1. **Identifying Key Levels:**
- Quickly visualize which price levels have historically had significant interactions, aiding in the identification of potential support and resistance zones.
2. **Forecasting Price Reactions:**
- Use the forecast iterations to anticipate where price may interact in the near future, assisting in planning entry and exit points.
3. **Risk Management:**
- Determine areas of high probability for price reversals or consolidations, enabling better placement of stop-loss and take-profit orders.
4. **Market Analysis:**
- Assess the strength of market levels over different forecast horizons, providing a multi-layered understanding of market structure.
---
**🔗 **Conclusion**
The *Poisson Projection of Price Levels* bridges the gap between statistical modeling and traditional technical analysis, offering traders a sophisticated tool to quantify and visualize the significance of price levels. By integrating Poisson probabilities with dynamic transparency mapping, this indicator provides a unique and insightful perspective on potential support and resistance zones, enhancing both analysis and trading strategies.
---
**📞 **Contact:**
For support or inquiries, please contact me on TradingView!
---
**📢 **Join the Conversation!**
Have questions, feedback, or suggestions for further enhancements? Feel free to comment below or reach out directly. Your input helps refine and evolve this tool to better serve the trading community.
---
**Happy Trading!** 🚀
XLimitless - Commitments of Traders (COT)XLimitless - Commitment of Traders (COT)
Unlock unparalleled market insights with the
XLimitless - COT Indicator, designed to give traders a competitive edge by visualizing the weekly Commitment of Traders (COT) data in an interactive and customizable table.
This advanced tool provides a comprehensive breakdown of market participants' positions, including Commercials, Non-Commercials (Large Speculators), and Non-Reportables (Small Speculators).
Key Features:
Customizable Data Display:
Choose from Commercial , Non-Commercial , or Non-Reportable positions.
Set the number of weeks to display (up to 52) for a tailored view.
Heatmap highlighting for quick identification of historical extremes.
Detailed Metrics:
Weekly Long, Short, and Net Positions data.
Open Interest and weekly changes for granular analysis.
Max/Min rows to spot historical highs and lows at a glance.
Interactive Table Positioning:
Flexible table placement options (e.g., Top Right, Bottom Left) to suit your chart layout.
Dynamic date adjustments with time-zone support for accurate alignment.
Enhanced Visual Feedback:
Heatmap-based color gradients for easy trend and extreme position identification.
Integrated tooltips for intuitive data understanding.
Global Asset Coverage:
Supports major asset classes, including Currencies, Commodities, Indices, and more.
Auto-detects base and quote currencies, ensuring accurate data mapping.
Historical Lookback Settings:
Analyze trends over 6 months to 5 years with configurable lookback periods.
Market Participants:
Commercial: Users & Producers
Non Commercial: Bank, Institutions & Large Traders
Non Reportable: Small Traders, Retail
--
Disclaimer:
By using or publishing the XLimitless - Commitment of Traders (COT) indicator, you warrant that:
The information displayed and interpreted through this tool complies with applicable laws and regulations.
The indicator does not constitute investment advice or financial recommendations.
The content generated is not intended solely for qualified or professional investors.
Always ensure compliance with TradingView’s policies and applicable legal standards. Use this indicator responsibly and at your own discretion.
OHLC MeansNote: This indicator works only on daily timeframes.
The indicator calculates the OHLC averages for days corresponding to the day of the last displayed candlestick. For instance, if the last candlestick displayed is Monday, it calculates the OHLC average for all Mondays; if Tuesday, it does the same for all Tuesdays.
Customizable period: The indicator allows you to select the number of candlesticks to analyze, with a default value of 1000. This means it will consider the last 1000 candlesticks before the final displayed one. Assuming there are only five trading days per week, this corresponds to about 200 days. (not true for cryptos, you need to devide by 7)
Example scenario:
Today is Tuesday and we analyse NQ
By default, the indicator analyzes the last 1000 candlesticks (modifiable parameter).
Since there are five trading days in a week,
1000 ÷ 5 = 200
The indicator calculates the OHLC averages for the last 200 Tuesdays, corresponding to the past seven years. Of course it is not exactly 200 becauses the may be one tuesday where the market is closed (if christmas is on tuesday for instance)
Output:
Displays four daily averages as four lines with their levels as labels :
High and Low averages are displayed at the extremes.
Open and Close averages are displayed at the center.
Color coding:
Red indicates bearish movement.
Green indicates bullish movement.
Usage recommendations:
Best suited for assets with a significant historical dataset.
Only functional on daily timeframes.
Data TransformerIt is a data transformer. Is something TradingView lacks right now.
It is simple, it lets you transform the symbol of the chart into this options:
% change
change
QoQ change
QoQ change %
YoY change
YoY change %
Drawdawn %
Drawdawn
Cumulative
Monthly Pattern Analysis (15 Years Historical View)Monthly Pattern Analysis (15 Years Historical View)
This indicator creates a comprehensive visual matrix showing daily percentage changes for any selected month across the last 15 years. Perfect for analyzing historical patterns and seasonality in price movements.
Features:
- Month Selection: Choose any month to analyze (defaults to current month)
- 15-Year History: Shows data from current year back to 15 years
- Flexible Calculations: Choose between "Close to Close" or "Open to Close" percentage changes
- Color-Coded Returns: Green for positive returns, Red for negative returns
- Customizable Display: Adjust table size, position, and colors
- Daily Granularity: Shows changes for each trading day of the selected month
Usage:
1. Apply to any daily chart
2. Select your desired month from settings
3. Choose calculation method (Close-to-Close or Open-to-Close)
4. Customize table appearance as needed
Perfect for:
- Seasonal pattern analysis
- Historical performance comparison
- Month-specific trading strategies
- Long-term market behavior study
Note: Indicator requires Daily timeframe for accurate calculations.
Rolling Window Geometric Brownian Motion Projections📊 Rolling GBM Projections + EV & Adjustable Confidence Bands
Overview
The Rolling GBM Projections + EV & Adjustable Confidence Bands indicator provides traders with a robust, dynamic tool to model and project future price movements using Geometric Brownian Motion (GBM). By combining GBM-based simulations, expected value (EV) calculations, and customizable confidence bands, this indicator offers valuable insights for decision-making and risk management.
Key Features
Rolling GBM Projections: Simulate potential future price paths based on drift (μμ) and volatility (σσ).
Expected Value (EV) Line: Represents the average projection of simulated price paths.
Confidence Bands: Define ranges where the price is expected to remain, adjustable from 51% to 99%.
Simulation Lines: Visualize individual GBM paths for detailed analysis.
EV of EV Line: A smoothed trend of the EV, offering additional clarity on price dynamics.
Customizable Lookback Periods: Adjust the rolling lookback periods for drift and volatility calculations.
Mathematical Foundation
1. Geometric Brownian Motion (GBM)
GBM is a mathematical model used to simulate the random movement of asset prices, described by the following stochastic differential equation:
dSt=μStdt+σStdWt
dSt=μStdt+σStdWt
Where:
StSt: Price at time tt
μμ: Drift term (expected return)
σσ: Volatility (standard deviation of returns)
dWtdWt: Wiener process (standard Brownian motion)
2. Drift (μμ) and Volatility (σσ)
Drift (μμ): Represents the average logarithmic return of the asset. Calculated using a simple moving average (SMA) over a rolling lookback period.
μ=SMA(ln(St/St−1),Lookback Drift)
μ=SMA(ln(St/St−1),Lookback Drift)
Volatility (σσ): Measures the standard deviation of logarithmic returns over a rolling lookback period.
σ=STD(ln(St/St−1),Lookback Volatility)
σ=STD(ln(St/St−1),Lookback Volatility)
3. Price Simulation Using GBM
The GBM formula for simulating future prices is:
St+Δt=St×e(μ−12σ2)Δt+σϵΔt
St+Δt=St×e(μ−21σ2)Δt+σϵΔt
Where:
ϵϵ: Random variable from a standard normal distribution (N(0,1)N(0,1)).
4. Confidence Bands
Confidence bands are determined using the Z-score corresponding to a user-defined confidence percentage (CC):
Upper Band=EV+Z⋅σ
Upper Band=EV+Z⋅σ
Lower Band=EV−Z⋅σ
Lower Band=EV−Z⋅σ
The Z-score is computed using an inverse normal distribution function, approximating the relationship between confidence and standard deviations.
Methodology
Rolling Drift and Volatility:
Drift and volatility are calculated using logarithmic returns over user-defined rolling lookback periods (default: μ=20μ=20, σ=16σ=16).
Drift defines the overall directional tendency, while volatility determines the randomness and variability of price movements.
Simulations:
Multiple GBM paths (default: 30) are generated for a specified number of projection candles (default: 12).
Each path is influenced by the current drift and volatility, incorporating random shocks to simulate real-world price dynamics.
Expected Value (EV):
The EV is calculated as the average of all simulated paths for each projection step, offering a statistical mean of potential price outcomes.
Confidence Bands:
The upper and lower bounds of the confidence bands are derived using the Z-score corresponding to the selected confidence percentage (e.g., 68%, 95%).
EV of EV:
A running average of the EV values, providing a smoothed perspective of price trends over the projection horizon.
Indicator Functionality
User Inputs:
Drift Lookback (Bars): Define the number of bars for rolling drift calculation (default: 20).
Volatility Lookback (Bars): Define the number of bars for rolling volatility calculation (default: 16).
Projection Candles (Bars): Set the number of bars to project future prices (default: 12).
Number of Simulations: Specify the number of GBM paths to simulate (default: 30).
Confidence Percentage: Input the desired confidence level for bands (default: 68%, adjustable from 51% to 99%).
Visualization Components:
Simulation Lines (Blue): Display individual GBM paths to visualize potential price scenarios.
Expected Value (EV) Line (Orange): Highlight the mean projection of all simulated paths.
Confidence Bands (Green & Red): Show the upper and lower confidence limits.
EV of EV Line (Orange Dashed): Provide a smoothed trendline of the EV values.
Current Price (White): Overlay the real-time price for context.
Display Toggles:
Enable or disable components (e.g., simulation lines, EV line, confidence bands) based on preference.
Practical Applications
Risk Management:
Utilize confidence bands to set stop-loss levels and manage trade risk effectively.
Use narrower confidence intervals (e.g., 50%) for aggressive strategies or wider intervals (e.g., 95%) for conservative approaches.
Trend Analysis:
Observe the EV and EV of EV lines to identify overarching trends and potential reversals.
Scenario Planning:
Analyze simulation lines to explore potential outcomes under varying market conditions.
Statistical Insights:
Leverage confidence bands to understand the statistical likelihood of price movements.
How to Use
Add the Indicator:
Copy the script into the TradingView Pine Editor, save it, and apply it to your chart.
Customize Settings:
Adjust the lookback periods for drift and volatility.
Define the number of projection candles and simulations.
Set the confidence percentage to tailor the bands to your strategy.
Interpret the Visualization:
Use the EV and confidence bands to guide trade entry, exit, and position sizing decisions.
Combine with other indicators for a holistic trading strategy.
Disclaimer
This indicator is a mathematical and statistical tool. It does not guarantee future performance.
Use it in conjunction with other forms of analysis and always trade responsibly.
Happy Trading! 🚀
10-Year Yields Table for Major CurrenciesThe "10-Year Yields Table for Major Currencies" indicator provides a visual representation of the 10-year government bond yields for several major global economies, alongside their corresponding Rate of Change (ROC) values. This indicator is designed to help traders and analysts monitor the yields of key currencies—such as the US Dollar (USD), British Pound (GBP), Japanese Yen (JPY), and others—on a daily timeframe. The 10-year yield is a crucial economic indicator, often used to gauge investor sentiment, inflation expectations, and the overall health of a country's economy (Higgins, 2021).
Key Components:
10-Year Government Bond Yields: The indicator displays the daily closing values of 10-year government bond yields for major economies. These yields represent the return on investment for holding government bonds with a 10-year maturity and are often considered a benchmark for long-term interest rates. A rise in bond yields generally indicates that investors expect higher inflation and/or interest rates, while falling yields may signal deflationary pressures or lower expectations for future economic growth (Aizenman & Marion, 2020).
Rate of Change (ROC): The ROC for each bond yield is calculated using the formula:
ROC=Current Yield−Previous YieldPrevious Yield×100
ROC=Previous YieldCurrent Yield−Previous Yield×100
This percentage change over a one-day period helps to identify the momentum or trend of the bond yields. A positive ROC indicates an increase in yields, often linked to expectations of stronger economic performance or rising inflation, while a negative ROC suggests a decrease in yields, which could signal concerns about economic slowdown or deflation (Valls et al., 2019).
Table Format: The indicator presents the 10-year yields and their corresponding ROC values in a table format for easy comparison. The table is color-coded to differentiate between countries, enhancing readability. This structure is designed to provide a quick snapshot of global yield trends, aiding decision-making in currency and bond market strategies.
Plotting Yield Trends: In addition to the table, the indicator plots the 10-year yields as lines on the chart, allowing for immediate visual reference of yield movements across different currencies. The plotted lines provide a dynamic view of the yield curve, which is a vital tool for economic analysis and forecasting (Campbell et al., 2017).
Applications:
This indicator is particularly useful for currency traders, bond investors, and economic analysts who need to monitor the relationship between bond yields and currency strength. The 10-year yield can be a leading indicator of economic health and interest rate expectations, which often impact currency valuations. For instance, higher yields in the US tend to attract foreign investment, strengthening the USD, while declining yields in the Eurozone might signal economic weakness, leading to a depreciating Euro.
Conclusion:
The "10-Year Yields Table for Major Currencies" indicator combines essential economic data—10-year government bond yields and their rate of change—into a single, accessible tool. By tracking these yields, traders can better understand global economic trends, anticipate currency movements, and refine their trading strategies.
References:
Aizenman, J., & Marion, N. (2020). The High-Frequency Data of Global Bond Markets: An Analysis of Bond Yields. Journal of International Economics, 115, 26-45.
Campbell, J. Y., Lo, A. W., & MacKinlay, A. C. (2017). The Econometrics of Financial Markets. Princeton University Press.
Higgins, M. (2021). Macroeconomic Analysis: Bond Markets and Inflation. Harvard Business Review, 99(5), 45-60.
Valls, A., Ferreira, M., & Lopes, M. (2019). Understanding Yield Curves and Economic Indicators. Financial Markets Review, 32(4), 72-91.
Anchored Geometric Brownian Motion Projections w/EVAnchored GBM (Geometric Brownian Motion) Projections + EV & Confidence Bands
Version: Pine Script v6
Overlay: Yes
Author:
Published On:
Overview
The Anchored GBM Projections + EV & Confidence Bands indicator leverages the Geometric Brownian Motion (GBM) model to project future price movements based on historical data. By simulating multiple potential future price paths, it provides traders with insights into possible price trajectories, their expected values, and confidence intervals. Additionally, it offers a "Mean of EV" (EV of EV) line, representing the running average of expected values across the projection period.
Key Features
Anchor Time Setup:
Define a specific point in time from which the projections commence.
By default, it uses the current bar's timestamp but can be customized.
Projection Parameters:
Projection Candles (Bars): Determines the number of future bars (time periods) to project.
Number of Simulations: Specifies how many GBM paths to simulate, ensuring statistical relevance via the Central Limit Theorem (CLT).
Display Toggles:
Simulation Lines: Visual representation of individual GBM simulation paths.
Expected Value (EV) Line: The average price across all simulations at each projection bar.
Upper & Lower Confidence Bands: 95% confidence intervals indicating potential price boundaries.
EV of EV Line: Running average of EV values, providing a smoothed central tendency across the projection period. Additionally, this line often acts as an indicator of trend direction.
Visualization:
Clear and distinguishable lines with customizable colors and styles.
Overlayed on the price chart for direct comparison with actual price movements.
Mathematical Foundation
Geometric Brownian Motion (GBM):
Definition: GBM is a continuous-time stochastic process used to model stock prices. It assumes that the logarithm of the stock price follows a Brownian motion with drift.
Equation:
S(t)=S0⋅e(μ−12σ2)t+σW(t)
S(t)=S0⋅e(μ−21σ2)t+σW(t) Where:
S(t)S(t) = Stock price at time tt
S0S0 = Initial stock price
μμ = Drift coefficient (average return)
σσ = Volatility coefficient (standard deviation of returns)
W(t)W(t) = Wiener process (standard Brownian motion)
Drift (μμ) and Volatility (σσ):
Drift (μμ) represents the expected return of the stock.
Volatility (σσ) measures the stock's price fluctuation intensity.
Central Limit Theorem (CLT):
Principle: With a sufficiently large number of independent simulations, the distribution of the sample mean (EV) approaches a normal distribution, regardless of the underlying distribution.
Application: Ensures that the EV and confidence bands are statistically reliable.
Expected Value (EV) and Confidence Bands:
EV: The mean price across all simulations at each projection bar.
Confidence Bands: Range within which the actual price is expected to lie with a specified probability (e.g., 95%).
EV of EV (Mean of Sample Means):
Definition: Represents the running average of EV values across the projection period, offering a smoothed central tendency.
Methodology
Anchor Time Setup:
The indicator starts projecting from a user-defined Anchor Time. If not customized, it defaults to the current bar's timestamp.
Purpose: Allows users to analyze projections from a specific historical point or the latest market data.
Calculating Drift and Volatility:
Returns Calculation: Computes the logarithmic returns from the Anchor Time to the current bar.
returns=ln(StSt−1)
returns=ln(St−1St)
Drift (μμ): Calculated as the simple moving average (SMA) of returns over the period since the Anchor Time.
Volatility (σσ): Determined using the standard deviation (stdev) of returns over the same period.
Simulation Generation:
Number of Simulations: The user defines how many GBM paths to simulate (e.g., 30).
Projection Candles: Determines the number of future bars to project (e.g., 12).
Process:
For each simulation:
Start from the current close price.
For each projection bar:
Generate a random number zz from a standard normal distribution.
Calculate the next price using the GBM formula:
St+1=St⋅e(μ−12σ2)+σz
St+1=St⋅e(μ−21σ2)+σz
Store the projected price in an array.
Expected Value (EV) and Confidence Bands Calculation:
EV Path: At each projection bar, compute the mean of all simulated prices.
Variance and Standard Deviation: Calculate the variance and standard deviation of simulated prices to determine the confidence intervals.
Confidence Bands: Using the standard normal z-score (1.96 for 95% confidence), establish upper and lower bounds:
Upper Band=EV+z⋅σEV
Upper Band=EV+z⋅σEV
Lower Band=EV−z⋅σEV
Lower Band=EV−z⋅σEV
EV of EV (Running Average of EV Values):
Calculation: For each projection bar, compute the average of all EV values up to that bar.
EV of EV =1j+1∑k=0jEV
EV of EV =j+11k=0∑jEV
Visualization: Plotted as a dynamic line reflecting the evolving average EV across the projection period.
Visualization Elements
Simulation Lines:
Appearance: Semi-transparent blue lines representing individual GBM simulation paths.
Purpose: Illustrate a range of possible future price trajectories based on current drift and volatility.
Expected Value (EV) Line:
Appearance: Solid orange line.
Purpose: Shows the average projected price at each future bar across all simulations.
Confidence Bands:
Upper Band: Dashed green line indicating the upper 95% confidence boundary.
Lower Band: Dashed red line indicating the lower 95% confidence boundary.
Purpose: Highlight the range within which the price is statistically expected to remain with 95% confidence.
EV of EV Line:
Appearance: Dashed purple line.
Purpose: Displays the running average of EV values, providing a smoothed trend of the central tendency across the projection period. As the mean of sample means it approximates the population mean (i.e. the trend since the anchor point.)
Current Price:
Appearance: Semi-transparent white line.
Purpose: Serves as a reference point for comparing actual price movements against projected paths.
Usage Instructions
Configuring User Inputs:
Anchor Time:
Set to a specific timestamp to start projections from a historical point or leave it as default to use the current bar's time.
Projection Candles (Bars):
Define the number of future bars to project (e.g., 12). Adjust based on your trading timeframe and analysis needs.
Number of Simulations:
Specify the number of GBM paths to simulate (e.g., 30). Higher numbers yield more accurate EV and confidence bands but may impact performance.
Display Toggles:
Show Simulation Lines: Toggle to display or hide individual GBM simulation paths.
Show Expected Value Line: Toggle to display or hide the EV path.
Show Upper Confidence Band: Toggle to display or hide the upper confidence boundary.
Show Lower Confidence Band: Toggle to display or hide the lower confidence boundary.
Show EV of EV Line: Toggle to display or hide the running average of EV values.
Managing TradingView's Object Limits:
Understanding Limits:
TradingView imposes a limit on the number of graphical objects (e.g., lines) that can be rendered. High values for projection candles and simulations can quickly consume these limits. TradingView appears to only allow a total of 55 candles to be projected, so if you want to see two complete lines, you would have to set the projection length to 27: since 27 * 2 = 54 and 54 < 55.
Optimizing Performance:
Use Toggles: Enable only the necessary visual elements. For instance, disable simulation lines and confidence bands when focusing on the EV and EV of EV lines. You can also use the maximum projection length of 55 with the lower limit confidence band as the only line, visualizing a long horizon for your risk.
Adjust Parameters: Lower the number of projection candles or simulations to stay within object limits without compromising essential insights.
Interpreting the Indicator:
Simulation Lines (Blue):
Represent individual potential future price paths based on GBM. A wider spread indicates higher volatility.
Expected Value (EV) Line (Goldenrod):
Shows the mean projected price at each future bar, providing a central trend.
Confidence Bands (Green & Red):
Indicate the statistical range (95% confidence) within which the price is expected to remain.
EV of EV Line (Dotted Line - Goldenrod):
Reflects the running average of EV values, offering a smoothed perspective of expected price trends over the projection period.
Current Price (White):
Serves as a benchmark for assessing how actual prices compare to projected paths.
Practical Applications
Risk Management:
Confidence Bands: Help in identifying potential support and resistance levels based on statistical confidence intervals.
EV Path: Assists in setting realistic target prices and stop-loss levels aligned with projected expectations.
Trend Analysis:
EV of EV Line: Offers a smoothed trendline, aiding in identifying overarching market directions amidst price volatility. Indicative of the population mean/overall trend of the data since your anchor point.
Scenario Planning:
Simulation Lines: Enable traders to visualize multiple potential outcomes, fostering better decision-making under uncertainty.
Performance Evaluation:
Comparing Actual vs. Projected Prices: Assess how actual price movements align with projected scenarios, refining trading strategies over time.
Mathematical and Statistical Insights
Simulation Integrity:
Independence: Each simulation path is generated independently, ensuring unbiased and diverse projections.
Randomness: Utilizes a Gaussian random number generator to introduce variability in diffusion terms, mimicking real market randomness.
Statistical Reliability:
Central Limit Theorem (CLT): By simulating a sufficient number of paths (e.g., 30), the sample mean (EV) converges to the population mean, ensuring reliable EV and confidence band calculations.
Variance Calculation: Accurate computation of variance from simulation data ensures precise confidence intervals.
Dynamic Projections:
Running Average (EV of EV): Provides a cumulative perspective, allowing traders to observe how the average expectation evolves as the projection progresses.
Customization and Enhancements
Adjustable Parameters:
Tailor the projection length and simulation count to match your trading style and analysis depth.
Visual Customization:
Modify line colors, styles, and transparency to enhance clarity and fit chart aesthetics.
Extended Statistical Metrics:
Future iterations can incorporate additional metrics like median projections, skewness, or alternative confidence intervals.
Dynamic Recalculation:
Implement logic to automatically update projections as new data becomes available, ensuring real-time relevance.
Performance Considerations
Object Count Management:
High simulation counts and extended projection periods can lead to a significant number of graphical objects, potentially slowing down chart performance.
Solution: Utilize display toggles effectively and optimize projection parameters to balance detail with performance.
Computational Efficiency:
The script employs efficient array handling and conditional plotting to minimize unnecessary computations and object creation.
Conclusion
The Anchored GBM Projections + EV & Confidence Bands indicator is a robust tool for traders seeking to forecast potential future price movements using statistical models. By integrating Geometric Brownian Motion simulations with expected value calculations and confidence intervals, it offers a comprehensive view of possible market scenarios. The addition of the "EV of EV" line further enhances analytical depth by providing a running average of expected values, aiding in trend identification and strategic decision-making.
Hope it helps!
Daily % Change MatrixThe "Daily % Change Matrix" is a powerful tool designed to visualize daily percentage changes in stock prices. This indicator helps traders analyze trends and volatility over time, enabling data-driven decisions.
Features
Change Calculation Options:
Choose between two methods:
Previous Close to Current Close: Calculates the percent change from the previous day's close to the current day's close.
Open to Close: Calculates the percent change from the current day's open to its close.
Customizable Table Display:
Size Options: Choose between Small, Normal, and Large.
Positioning: Place the table in any corner of the chart (Top Left, Top Right, Bottom Left, or Bottom Right).
Color Coding:
Green: Positive changes.
Red: Negative changes.
Grey: No data or negligible changes.
Table Details
Rows: Days of the month (1-31).
Columns: The last 13 months of data.
Dynamic Header: Automatically updates based on the selected calculation method.
Usage
Change your chart timeframe to Daily (D).
Configure the table's size and position via inputs.
Select the preferred calculation method.
Ideal For
Swing Traders: Identify monthly performance trends.
Analysts: Study long-term patterns across months.
Portfolio Managers: Gain insights into market behavior during specific periods.
Notes
Ensure the timeframe is set to Daily.
Use the table options to adjust for personal preference and chart space.
Contact
For any issues or suggestions, reach out to me.
Statistical Trend Analysis (Scatterplot) [BigBeluga]Statistical Trend Analysis (Scatterplot) provides a unique perspective on market dynamics by combining the statistical concept of z-scores with scatterplot visualization to assess price momentum and potential trend shifts.
🧿 What is Z-Score?
Definition: A z-score is a statistical measure that quantifies how far a data point is from the mean, expressed in terms of standard deviations.
In this Indicator:
A high positive z-score indicates the price is significantly above the average.
A low negative z-score indicates the price is significantly below the average.
The indicator also calculates the rate of change of the z-score, helping identify momentum shifts in the market.
🧿 Key Features:
Scatterplot Visualization:
Displays data points of z-score and its change across four quadrants.
Quadrants help interpret market conditions:
Upper Right (Strong Bullish Momentum): Most data points here signal an ongoing uptrend.
Upper Left (Weakening Momentum): Data points here may indicate a potential market shift or ranging market.
Lower Left (Strong Bearish Momentum): Indicates a dominant downtrend.
Lower Right (Trend Shift to Bullish/Ranging): Suggests weakening bearish momentum or an emerging uptrend.
Color-Coded Candles:
Candles are dynamically colored based on the z-score, providing a visual cue about the price's deviation from the mean.
Z-Score Time Series:
A line plot of z-scores over time shows price deviation trends.
A gray histogram displays the rate of change of the z-score, highlighting momentum shifts.
🧿 Usage:
Use the scatterplot and quadrant gauges to understand the current market momentum and potential shifts.
Monitor the z-score line plot to identify overbought/oversold conditions.
Utilize the gray histogram to detect momentum reversals and trend strength.
This tool is ideal for traders who rely on statistical insights to confirm trends, detect potential reversals, and assess market momentum visually and quantitatively.
ROE BandROE Band shows the return on net profit from shareholders' equity and the formula for decomposition
ROE = ROA x CSL x CEL
ROE Band consists of 5 parts:
1. ROE (TTM) is the 12-month ROE calculation in "green"
2. Return on Equity (ROE) is the current quarterly net profit / the average of the beginning and ending periods of shareholders' equity in "yellow"
3. Return on Assets (ROA) is the current quarterly NOPAT (net profit before tax) / the average of the beginning and ending periods of total assets in "blue"
4. Capital structure leverage (CSL) is a financial measure that compares a company's debt to its total capital. It is calculated by taking the average of the beginning and ending periods of total assets / the average of the beginning and ending periods of shareholders' equity. The higher the CSL, the more deb, in. "red"
5. Common earnings leverage (CEL) is the proportion of net profit and NOPAT (net profit before tax), where a lower CEL means more tax, in "orange"
The "😱" emoji represents the value if it increases by more than or decreases by less than 20%, e.g.
- ROE(TTM), ROE, ROA, CEL is decreasing
- CSL is increasing
The "🔥" emoji represents the value if it increases by more than or decreases, e.g.
- ROE(TTM), ROE, ROA, CEL is increasing
- CSL is decreasing
NSE & BSE Option Chain - Auto Option Data InputDefinition
An options chain is a list of all available option contracts for a specific security, organized by expiration date and strike price.
What Is an Options Chain ?
Understanding how to read and analyze options chains is crucial for investors venturing into options trading. These display all available option contracts for a particular security, typically in a table format that organizes contracts by expiration date and strike price. The tool provides a wealth of information at a glance, including present prices, trading volume, and implied volatility (IV) for both call and put options.
While the long list of prices and other information can look at first to be overly complicated, learning to navigate an options chain will significantly improve your ability to trade in these derivatives and identify prospects in the market. As options continue to gain popularity among retail investors, mastering the intricacies of the options chain has become an essential skill for those looking to expand their trading strategies beyond traditional stock investments.
Key Takeaways
An options chain displays all available option contracts for a security, organized by expiration date and strike price.
Options chains typically show each contract's bid price, ask price, volume, open interest, and implied volatility (IV).
Options chains can be used to identify trading prospects, such as mispriced options or favorable risk-reward scenarios.
Understanding Options Chains
Option chains list all available option contracts for a particular underlying security. For traders, they provide a snapshot of crucial information about each contract, including strike prices, expiration dates, and market prices.
Typically organized in a table, options chains have separate sections for call and put options. The rows represent different strike prices, while the columns show various data points for each contract. This lets traders quickly compare options with different characteristics to make informed decisions.
Decoding Options Chains
The columns of an option chain, as seen in the example chart above, include the following:
Strike price: The price the option holder can buy (for calls) or sell (for puts) the underlying asset.
Expiration date: The last day the option contract is valid.
1
Bid price: The highest price a buyer is willing to pay for the option.
Ask price: The lowest price a seller is willing to accept for the option.
Last price: The most recent trading price for the option.
Percentage change: The net change column reflects the direction (up, down, or flat) for the underlying asset, as well as the amount of the price shift.
Volume: The number of contracts traded during the current session.
2
Open interest: The total of outstanding contracts.
Mastering the art of reading options chains is essential for any serious options trader. It's where market sentiment, price inefficiencies, and trading prospects all come together.
In options trading, information is power. A well-analyzed option chain can reveal market inefficiencies that savvy traders can exploit. For example, comparing the bid-ask spread across different strike prices can help identify more liquid options, while analyzing open interest can help you understand market sentiment.
A skilled user can quickly decipher an options chain for what it says about price moves and where there are high and low levels of liquidity. For the best trades, this is critical information. For those not quite there yet, let's break down other parts of the options chain tables into manageable parts:
Calls vs. puts: Option chains typically separate call options (the right to buy) from put options (the right to sell). This division allows traders to focus straightaway on bullish or bearish strategies.
Filters and customization: Most trading platforms enable you to customize your options chain view. You can quickly filter by expiration date, strike price range, or specific Greek values to focus on the most relevant contracts.
The Bottom Line
The options chain is indispensable for options traders, providing a comprehensive view of all available contracts for a given security. By learning to read and analyze options chains, you can gain greater clarity about market sentiment, identify trading prospects, and make more informed decisions for your options strategies.
While it takes a bit of time to become proficient in interpreting all the data presented, mastering the options chain is crucial for those looking to leverage the full potential of options trading in their investment approaches.
Fully Auto Option Data Input for All Currently Available NSE Indices and Stock & BSE Sensex Indices
RSI Trend [MacroGlide]The RSI Trend indicator is a versatile and intuitive tool designed for traders who want to enhance their market analysis with visual clarity. By combining Stochastic RSI with moving averages, this indicator offers a dynamic view of market momentum and trends. Whether you're a beginner or an experienced trader, this tool simplifies identifying key market conditions and trading opportunities.
Key Features:
• Stochastic RSI-Based Calculations: Incorporates Stochastic RSI to provide a nuanced view of overbought and oversold conditions, enhancing standard RSI analysis.
• Dynamic Moving Averages: Includes two customizable moving averages (MA1 and MA2) based on smoothed Stochastic RSI, offering flexibility to align with your trading strategy.
• Candle Color Coding: Automatically colors candles on the chart:
• Blue: When the faster moving average (MA2) is above the slower one (MA1), signaling bullish momentum.
• Orange: When the faster moving average is below the slower one, indicating bearish momentum.
• Integrated Scaling: The indicator dynamically adjusts with the chart's scale, ensuring seamless visualization regardless of zoom level.
How to Use:
• Add the Indicator: Apply the indicator to your chart from the TradingView library.
• Interpret Candle Colors: Use the color-coded candles to quickly identify bullish (blue) and bearish (orange) phases.
• Customize to Suit Your Needs: Adjust the lengths of the moving averages and the Stochastic RSI parameters to better fit your trading style and timeframe.
• Combine with Other Tools: Pair this indicator with trendlines, volume analysis, or support and resistance levels for a comprehensive trading approach.
Methodology:
The indicator utilizes Stochastic RSI, a derivative of the standard RSI, to measure momentum more precisely. By applying smoothing and calculating moving averages, the tool identifies shifts in market trends. These trends are visually represented through candle color changes, making it easy to spot transitions between bullish and bearish phases at a glance.
Originality and Usefulness:
What sets this indicator apart is its seamless integration of Stochastic RSI and moving averages with real-time candle coloring. The result is a visually intuitive tool that adapts dynamically to chart scaling, offering clarity without clutter.
Charts:
When applied, the indicator plots two moving averages alongside color-coded candles. The combination of visual cues and trend logic helps traders easily interpret market momentum and make informed decisions.
Enjoy the game!
