Live Portfolio P<his script calculates live P&L (Profit & Loss) for up to 40 instruments — stocks, ETFs, options, futures, and Forex pairs supported by TradingView. Instead of juggling numerous inputs, you paste your portfolio in CSV format into a single text field, and the script handles the rest. It parses each position and displays a comprehensive table showing the symbol, current price, position value, total P&L, and today’s P&L—all updated in real time.
Key Features
CSV Portfolio Input – Effortlessly import all your positions at once without filling in multiple fields. You can export the position from your broker, save it in the required format, and paste it into this script.
Supports Various Asset Classes – Works with any instrument that TradingView provides data for, including futures, options, and Forex.
Up to 40 Instruments – Track a broad and diverse set of holdings in one place.
Real-Time Updates – Get immediate feedback on live price changes, total value, and current P&L.
Today’s P&L – Monitor your daily performance to gauge short-term trends.
CSV is consumed in the following format:
Symbol (supported TradingView instruments)
Entry Price
Quantity (negative for short position)
Lot Size (for futures/options, it might not be one)
For example:
AAPL,237,100,1
TSLA,400,-150,1
ESM2025,6000,5,50
Planned Enhancements
Multi-Currency Support – Automatically convert and display your positions’ values in different currencies.
Advanced Metrics – Get deeper insights with calculations for drawdown, Sharpe ratio, and more.
Risk Management Tools – Set stop-loss and take-profit levels and receive alerts when thresholds are hit.
Option Greeks & Margin Calculations – Manage complex option strategies and track margin requirements.
Questions for You
What additional features would you like to see?
Are there any specific metrics or analytics you’d find especially valuable?
How might this script fit into your current trading workflow?
Feel free to share your thoughts and suggestions. Your feedback will help shape future updates and make this tool even more helpful for traders like you!
Disclaimer
Please remember that past performance may not be indicative of future results.
Due to various factors, including changing market conditions, the strategy may no longer perform as well as in historical backtesting.
This post and the script don’t provide any financial advice.
在腳本中搜尋"THE SCRIPT"
Volume Weighted HMA Index | mad_tiger_slayerTitle: 🍉 Volume Weighted HMA Index | mad_tiger_slayer 🐯
Description:
The Volume Weighted HMA Index is a cutting-edge indicator designed to enhance the accuracy and responsiveness of trading signals by combining the power of volume with the Hull Moving Average (HMA). This indicator adjusts the HMA based on volume-weighted price changes, providing faster and more reliable entry and exit signals while reducing the likelihood of false signals.
Intended and Best Uses:
Used for Strategy Creation:
Extremely Quick Entries and Exits
Intended for Higher timeframe however can be used for scalping paired with additional scripts.
Can be paired to create profitable strategies
TREND FOLLOWING NOT MEAN REVERTING!!!!
[Key Features:
Volume Integration: Dynamically adjusts the HMA using volume data to prioritize higher-volume bars, ensuring that market activity plays a crucial role in signal generation.
Enhanced Signal Clarity: The indicator calculates precise long and short signals by detecting volume-weighted HMA crossovers.
Bar Coloring: Visually differentiate bullish and bearish conditions with customizable bar colors, making trends easier to identify.
Custom Signal Plotting: Optional long and short signal markers for a clear visual representation of potential trade opportunities.
Highly Configurable: Adjust parameters such as volume length and calculation source to tailor the indicator to your trading preferences and strategy.
How It Works:
Volume Weighting: The indicator calculates the HMA using a volume-weighted price change, amplifying the influence of high-volume periods on the moving average.
Trend Identification: Crossovers of the volume-weighted HMA with zero determine trend direction, where:
A bullish crossover signals a long condition.
A bearish crossunder signals a short condition.
Visual Feedback: Bar colors and optional signal markers provide real-time insights into trend direction and trading signals.
Use Cases:
Trend Following: Quickly identify emerging trends with volume-accelerated HMA calculations.
Trade Confirmation: Use the indicator to confirm the strength and validity of your trade setups.
Custom Signal Integration: Combine this indicator with your existing strategies to refine entries and exits.
Notes:
Ensure that your trading instrument provides volume data for accurate calculations. If no volume is available, the script will notify you.
This script works best when combined with other indicators or trading frameworks for a comprehensive market view.
Inspired by the community and designed for traders looking to stay ahead of the curve, the Volume Weighted HMA Index is a versatile tool for traders of all levels.
[blackat] L1 Funding Bottom Wave█ OVERVIEW
The script "Funding Bottom Wave" is an indicator designed to analyze market conditions based on multiple smoothed price calculations and specific thresholds. It calculates several values such as B-value, VAR2-value, and additional signals like SK and SD to identify buy/sell levels and reversals, aiding traders in making informed decisions.
█ LOGICAL FRAMEWORK
The script consists of several main components:
• Input parameters that allow customization of calculation periods and thresholds.
• A custom function funding_wave that computes various financial metrics and conditions.
• Plotting commands to visualize different aspects of those computations.
Data flows from input parameters into the funding_wave function where calculations are performed. These results are then plotted according to specified conditions. The script uses conditional expressions to define when certain plots should appear based on the computed values.
█ CUSTOM FUNCTIONS
funding_wave Function:
This function takes six arguments: close_price, high_price, low_price, open_price, period_b, and period_var2. It performs several calculations including:
• Price range percentage normalized between lowest and highest prices over 60 bars.
• SMA of this value over periods defined by period_b and period_var2.
• Several moving averages (MA), EMAs, and extreme point markers (highest/lowest).
• Multiple condition checks involving these metrics leading to buy/high signal flags.
Returns: An array containing B-value, VAR2-value, SK-value, SD-value, along with various conditional signal indicators.
█ KEY POINTS AND TECHNIQUES
• Utilizes built-in TA functions (ta.highest, ta.lowest, ta.sma, ta.ema) for smoothing and normalization purposes.
• Implements extensive use of ternary operators and boolean logic to determine plot visibility based on specific criteria.
• Employs column-style plotting which highlights significant transitions in calculated metric levels visually.
• No explicit loops; computations utilize vectorized operations inherent to Pine Script's nature.
█ EXTENDED KNOWLEDGE AND APPLICATIONS
Potential modifications/extensions include:
• Adding alerts for key threshold crossovers or meeting certain conditions.
• Customizing more sophisticated alert messages incorporating current time and symbol details.
• Incorporating stop-loss/take-profit strategies dynamically adjusted by indicator outputs.
Similar techniques can be applied in:
• Developing robust trend-following systems combining momentum oscillators.
• Enhancing basic price action rulesets with statistical filters derived from historical data behaviors.
• Exploring intraday breakout strategies predicated upon sudden changes in market sentiment captured via volatility spikes.
Related concepts/features:
• Using arrays to encapsulate complex return structures for reusability across scripts/functions.
• Leveraging na effectively within plotting constructs ensures cleaner chart presentation avoiding clutter from irrelevant points.
█ MARKET MEANING OF DIFFERENT COLORED COLUMNS
Red Columns ("B above Var2"):
• Market Interpretation: When the red columns appear, it indicates that the B-value is higher than the VAR2-value. This suggests a strengthening upward trend or consolidation phase where the market might be experiencing buying pressure relative to recent trends.
• Trading Implication: Traders may consider this as a potentially bullish sign, indicating strength in the underlying asset.
Green Columns ("B below Var2"):
• Market Interpretation: Green columns indicate that the B-value is lower than the VAR2-value. This could suggest downward trend acceleration or weakening buying pressure compared to recent trends.
• Trading Implication: Traders might interpret this as a bearish signal, suggesting a possible decline in the market.
Aqua Columns ("SK below SD"):
• Market Interpretation: Aqua columns show instances where the SK-value is below the SD-value. This typically signifies that the short-term stochastic oscillator (or similar measure) is signaling oversold conditions but not yet reaching extremes.
• Trading Implication: While not necessarily a strong sell signal, aqua columns might prompt traders to look for further confirmation before entering long positions.
Fuchsia Columns ("SK above SD"):
• Market Interpretation: Fuchsia columns represent situations where the SK-value exceeds the SD-value. This usually indicates overbought conditions in the near term.
• Trading Implication: Traders often view fuchsia columns as cautionary signs, possibly prompting them to exit existing long positions or refrain from adding new ones without further analysis.
Yellow Columns ("High Condition" and "High Condition Both"):
• Market Interpretation: Yellow columns occur when either the SK-value or B-value crosses above predefined high thresholds (e.g., 90). If both cross simultaneously, they form "High Condition Both."
• Trading Implication: Strongly bullish signals indicating overheated markets prone to corrections. Traders may see this as a good opportunity to take profits or prepare for a pullback/corrective move.
Blue Columns ("Low Condition" and "Low Condition Both"):
• Market Interpretation: Blue columns emerge when either the SK-value or B-value drops below predefined low thresholds (e.g., 10). Simultaneous crossing forms "Low Condition Both."
• Trading Implication: Potentially bullish reversal setups once the market starts showing signs of bottoming out after being significantly oversold. Traders might use blue columns as entry points for establishing long positions or hedging against anticipated rebounds.
Light Purple Columns ("Low Condition with Reversal" and "Low Condition Both with Reversal"):
• Market Interpretation: Light purple columns signify moments when the SK-value or B-value falls below their respective thresholds but has started reversing upwards immediately afterward. If both fall and reverse together, it's denoted as "Low Condition Both with Reversal."
• Trading Implication: Suggests a possible early-stage rebound from an extended downtrend or sideways movement. This could be seen as a highly reliable bulls' flag formation setup.
White Columns ("High Condition with Reversal" and "High Condition Both with Reversal"):
• Market Interpretation: White columns denote scenarios where the SK-value or B-value breaches high thresholds (e.g., 90) but begins descending shortly thereafter. Both simultaneously crossing leads to "High Condition Both with Reversal."
• Trading Implication: Indicative of peak overbought conditions followed quickly by exhaustion in buying interest. This warns traders about potential imminent retracements or pullbacks, prompting exits or short positions.
█ SUMMARY TABLE OF COLUMN COLORS AND THEIR MEANINGS
Color Type Market Interpretation Trading Implication
Red B above Var2 Strengthening upward trend/consolidation Bullish sign
Green B below Var2 Downward trend acceleration/weakening buying pressure Bearish sign
Aqua SK below SD Oversold conditions but not extreme Cautionary signal
Fuchsia SK above SD Overbought conditions Take profit/precaution
Yellow High Condition / High Condition Both Overheated market, likely correction coming Good time to exit/additional selling
Blue Low Condition / Low Condition Both Possible bull/rebound setup Entry point/hedging
Light Purple Low Condition with Reversal / Low Condition Both with Reversal Early-stage rebound from downtrend Reliable bulls' flag formation
White High Condition with Reversal / High Condition Both with Reversal Peak overbought with imminent retracement Exit positions/warning
Understanding these color-coded signals can help traders make more informed decisions, whether for entry, exit, or risk management in trading strategies. Each set of colors provides distinct insights into market dynamics and trends, aiding in effective execution of trade plans.
[blackcat] L3 Counter Peacock Spread█ OVERVIEW
The script titled " L3 Counter Peacock Spread" is an indicator designed for use in TradingView. It calculates and plots various moving averages, K lines derived from these moving averages, additional simple moving averages (SMAs), weighted moving averages (WMAs), and other technical indicators like slope calculations. The primary function of the script is to provide a comprehensive set of visual tools that traders can use to identify trends, potential support/resistance levels, and crossover signals.
█ LOGICAL FRAMEWORK
Input Parameters:
There are no explicit input parameters defined; all variables are hardcoded or calculated within the script.
Calculations:
• Moving Averages: Calculates Simple Moving Averages (SMA) using ta.sma.
• Slope Calculation: Computes the slope of a given series over a specified period using linear regression (ta.linreg).
• K Lines: Defines multiple exponentially adjusted SMAs based on a 30-period MA and a 1-period MA.
• Weighted Moving Average (WMA): Custom function to compute WMAs by iterating through price data points.
• Other Indicators: Includes Exponential Moving Average (EMA) for momentum calculation.
Plotting:
Various elements such as MAs, K lines, conditional bands, additional SMAs, and WMAs are plotted on the chart overlaying the main price action.
No loops control the behavior beyond those used in custom functions for calculating WMAs. Conditional statements determine the coloring of certain plot lines based on specific criteria.
█ CUSTOM FUNCTIONS
calculate_slope(src, length) :
• Purpose: To calculate the slope of a time-series data point over a specified number of periods.
• Functionality: Uses linear regression to find the current and previous slopes and computes their difference scaled by the timeframe multiplier.
• Parameters:
– src: Source of the input data (e.g., closing prices).
– length: Periodicity of the linreg calculation.
• Return Value: Computed slope value.
calculate_ma(source, length) :
• Purpose: To calculate the Simple Moving Average (SMA) of a given source over a specified period.
• Functionality: Utilizes TradingView’s built-in ta.sma function.
• Parameters:
– source: Input data series (e.g., closing prices).
– length: Number of bars considered for the SMA calculation.
• Return Value: Calculated SMA value.
calculate_k_lines(ma30, ma1) :
• Purpose: Generates multiple exponentially adjusted versions of a 30-period MA relative to a 1-period MA.
• Functionality: Multiplies the 30-period MA by coefficients ranging from 1.1 to 3 and subtracts multiples of the 1-period MA accordingly.
• Parameters:
– ma30: 30-period Simple Moving Average.
– ma1: 1-period Simple Moving Average.
• Return Value: Returns an array containing ten different \u2003\u2022 "K line" values.
calculate_wma(source, length) :
• Purpose: Computes the Weighted Moving Average (WMA) of a provided series over a defined period.
• Functionality: Iterates backward through the last 'n' bars, weights each bar according to its position, sums them up, and divides by the total weight.
• Parameters:
– source: Price series to average.
– length: Length of the lookback window.
• Return Value: Calculated WMA value.
█ KEY POINTS AND TECHNIQUES
• Advanced Pine Script Features: Utilization of custom functions for encapsulating complex logic, leveraging TradingView’s library functions (ta.sma, ta.linreg, ta.ema) for efficient computations.
• Optimization Techniques: Efficient computation of K lines via pre-calculated components (multiples of MA30 and MA1). Use of arrays to store intermediate results which simplifies plotting.
• Best Practices: Clear separation between calculation and visualization sections enhances readability and maintainability. Usage of color.new() allows dynamic adjustments without hardcoding colors directly into plot commands.
• Unique Approaches: Introduction of K lines provides an alternative representation of trend strength compared to traditional MAs. Implementation of conditional band coloring adds real-time context to existing visual cues.
█ EXTENDED KNOWLEDGE AND APPLICATIONS
Potential Modifications/Extensions:
• Adding more user-defined inputs for lengths of MAs, K lines, etc., would make the script more flexible.
• Incorporating alert conditions based on crossovers between key lines could enhance automated trading strategies.
Application Scenarios:
• Useful for both intraday and swing trading due to the combination of short-term and long-term MAs along with trend analysis via slopes and K lines.
• Can be integrated into larger systems combining this indicator with others like oscillators or volume-based metrics.
Related Concepts:
• Understanding how linear regression works internally aids in grasping the slope calculation.
• Familiarity with WMA versus SMA helps appreciate why different types of averaging might be necessary depending on market dynamics.
• Knowledge of candlestick patterns can complement insights gained from this indicator.
Fibonacci Confluence Toolkit [LuxAlgo]The Fibonacci Confluence Toolkit is a technical analysis tool designed to help traders identify potential price reversal zones by combining key market signals and patterns. It highlights areas of interest where significant price action or reactions are anticipated, automatically applies Fibonacci retracement levels to outline potential pullback zones, and detects engulfing candle patterns.
Its unique strength lies in its reliance solely on price patterns, eliminating the need for user-defined inputs, ensuring a robust and objective analysis of market dynamics.
🔶 USAGE
The script begins by detecting CHoCH (Change of Character) points—key indicators of shifts in market direction. This script integrates the principles of pure price action as applied in Pure-Price-Action-Structures , where further details on the detection process can be found.
The detected CHoCH points serve as the foundation for defining an Area of Interest (AOI), a zone where significant price action or reactions are anticipated.
As new swing highs or lows emerge within the AOI, the tool automatically applies Fibonacci retracement levels to outline potential retracement zones. This setup enables traders to identify areas where price pullbacks may occur, offering actionable insights into potential entries or reversals.
Additionally, the toolkit highlights engulfing candle patterns within these zones, further refining entry points and enhancing confluence for better-informed trading decisions based on real-time trend dynamics and price behavior.
🔶 SETTINGS
🔹 Market Patterns
Bullish Structures: Enable or disable all bullish components of the indicator.
Bearish Structures: Enable or disable all bearish components of the indicator.
Highlight Area of Interest: Toggle the option to highlight the Areas of Interest (enabled or disabled).
CHoCH Line: Choose the line style for the CHoCH (Solid, Dashed, or Dotted).
Width: Adjust the width of the CHoCH line.
🔹 Retracement Levels
Choose which Fibonacci retracement levels to display (e.g., 0, 0.236, 0.382, etc.).
🔹 Swing Levels & Engulfing Patterns
Swing Levels: Select how swing levels are marked (symbols like ◉, △▽, or H/L).
Engulfing Candle Patterns: Choose which engulfing candle patterns to detect (All, Structure-Based, or Disabled).
🔶 RELATED SCRIPTS
Pure-Price-Action-Structures.
Crypto Wallets Profitability & Performance [LuxAlgo]The Crypto Wallets Profitability & Performance indicator provides a comprehensive view of the financial status of cryptocurrency wallets by leveraging on-chain data from IntoTheBlock. It measures the percentage of wallets profiting, losing, or breaking even based on current market prices.
Additionally, it offers performance metrics across different timeframes, enabling traders to better assess market conditions.
This information can be crucial for understanding market sentiment and making informed trading decisions.
🔶 USAGE
🔹 Wallets Profitability
This indicator is designed to help traders and analysts evaluate the profitability of cryptocurrency wallets in real-time. It aggregates data gathered from the blockchain on the number of wallets that are in profit, loss, or breaking even and presents it visually on the chart.
Breaking even line demonstrates how realized gains and losses have changed, while the profit and the loss monitor unrealized gains and losses.
The signal line helps traders by providing a smoothed average and highlighting areas relative to profiting and losing levels. This makes it easier to identify and confirm trading momentum, assess strength, and filter out market noise.
🔹 Profitability Meter
The Profitability Meter is an alternative display that visually represents the percentage of wallets that are profiting, losing, or breaking even.
🔹 Performance
The script provides a view of the financial health of cryptocurrency wallets, showing the percentage of wallets in profit, loss, or breaking even. By combining these metrics with performance data across various timeframes, traders can gain valuable insights into overall wallet performance, assess trend strength, and identify potential market reversals.
🔹 Dashboard
The dashboard presents a consolidated view of key statistics. It allows traders to quickly assess the overall financial health of wallets, monitor trend strength, and gauge market conditions.
🔶 DETAILS
🔹 The Chart Occupation Option
The chart occupation option adjusts the occupation percentage of the chart to balance the visibility of the indicator.
🔹 The Height in Performance Options
Crypto markets often experience significant volatility, leading to rapid and substantial gains or losses. Hence, plotting performance graphs on top of the chart alongside other indicators can result in a cluttered display. The height option allows you to adjust the plotting for balanced visibility, ensuring a clearer and more organized chart.
🔶 SETTINGS
The script offers a range of customizable settings to tailor the analysis to your trading needs.
Chart Occupation %: Adjust the occupation percentage of the chart to balance the visibility of the indicator.
🔹 Profiting Wallets
Profiting Percentage: Toggle to display the percentage of wallets in profit.
Smoothing: Adjust the smoothing period for the profiting percentage line.
Signal Line: Choose a signal line type (SMA, EMA, RMA, or None) to overlay on the profiting percentage.
🔹 Losing Wallets
Losing Percentage: Toggle to display the percentage of wallets in loss.
Smoothing: Adjust the smoothing period for the losing percentage line.
Signal Line: Choose a signal line type (SMA, EMA, RMA, or None) to overlay on the losing percentage.
🔹 Breaking Even Wallets
Breaking-Even Percentage: Toggle to display the percentage of wallets breaking even.
Smoothing: Adjust the smoothing period for the breaking-even percentage line.
🔹 Profitability Meter
Profitability Meter: Enable or disable the meter display, set its width, and adjust the offset.
🔹 Performance
Performance Metrics: Choose the timeframe for performance metrics (Day to Date, Week to Date, etc.).
Height: Adjust the height of the chart visuals to balance the visibility of the indicator.
🔹 Dashboard
Block Profitability Stats: Toggle the display of profitability stats.
Performance Stats: Toggle the display of performance stats.
Dashboard Size and Position: Customize the size and position of the performance dashboard on the chart.
🔶 RELATED SCRIPTS
Market-Sentiment-Technicals
Multi-Chart-Widget
Market Stats Panel [Daveatt]█ Introduction
I've created a script that brings TradingView's watchlist stats panel functionality directly to your charts. This isn't just another performance indicator - it's a pixel-perfect (kidding) recreation of TradingView's native stats panel.
Important Notes
You might need to adjust manually the scaling the firs time you're using this script to display nicely all the elements.
█ Core Features
Performance Metrics
The panel displays key performance metrics (1W, 1M, 3M, 6M, YTD, 1Y) in real-time, with color-coded boxes (green for positive, red for negative) for instant performance assessment.
Display Modes
Switch seamlessly between absolute prices and percentage returns, making it easy to compare assets across different price scales.
Absolute mode
Percent mode
Historical Comparison
View year-over-year performance with color-coded lines, allowing for quick historical pattern recognition and analysis.
Data Structure Innovation
Let's talk about one of the most interesting challenges I faced. PineScript has this quirky limitation where request.security() can only return 127 tuples at most. £To work around this, I implemented a dual-request system. The first request handles indices 0-63, while the second one takes care of indices 64-127.
This approach lets us maintain extensive historical data without compromising script stability.
And here's the cool part: if you need to handle even more years of historical data, you can simply extend this pattern by adding more request.security() calls.
Each additional call can fetch another batch of monthly open prices and timestamps, following the same structure I've used.
Think of it as building with LEGO blocks - you can keep adding more pieces to extend your historical reach.
Flexible Date Range
Unlike many scripts that box you into specific timeframes, I've designed this one to be completely flexible with your date selection. You can set any start year, any end year, and the script will dynamically scale everything to match. The visual presentation automatically adjusts to whatever range you choose, ensuring your data is always displayed optimally.
█ Customization Options
Visual Settings
The panel's visual elements are highly customizable. You can adjust the panel width to perfectly fit your workspace, fine-tune the line thickness to match your preferences, and enjoy the pre-defined year color scheme that makes tracking historical performance intuitive and visually appealing.
Box Dimensions
Every aspect of the performance boxes can be tailored to your needs. Adjust their height and width, fine-tune the spacing between them, and position the entire panel exactly where you want it on your chart. The goal is to make this tool feel like it's truly yours.
█ Technical Challenges Solved
Polyline Precision
Creating precise polylines was perhaps the most demanding aspect of this project.
The challenge was ensuring accurate positioning across both time and price axes, while handling percentage mode scaling with precision.
The script constantly updates the current year's data in real-time, seamlessly integrating new information as it comes in.
Axis Management
Getting the axes right was like solving a complex puzzle. The Y-axis needed to scale dynamically whether you're viewing absolute prices or percentages.
The X-axis required careful month labeling that stays clean and readable regardless of your selected timeframe.
Everything needed to align perfectly while maintaining proper spacing in all conditions.
█ Final Notes
This tool transforms complex market data into clear, actionable insights. Whether you're day trading or analyzing long-term trends, it provides the information you need to make informed decisions. And remember, while we can't predict the future, we can certainly be better prepared for it with the right tools at hand.
A word of warning though - seeing those red numbers in a beautifully formatted panel doesn't make them any less painful! 😉
---
Happy Trading! May your charts be green and your stops be far away!
Daveatt
Consecutive CandlesTrading as Easy as One, Two, and Three
Unlock the power of simplicity in trading with this innovative script inspired by KepalaBesi. Designed for traders of all levels, this script provides a user-friendly approach to market analysis, enabling you to make informed trading decisions effortlessly.
Key Features:
Simplified Signals: Receive clear buy and sell signals based on robust technical indicators. The script streamlines your trading process, allowing you to focus on execution rather than analysis.
Customizable Settings: Tailor the script to fit your trading style. Adjust parameters to suit your risk tolerance and market preferences, ensuring a personalized trading experience.
Visual Clarity: Benefit from intuitive visual cues on your chart, making it easy to identify optimal entry and exit points. The clean interface helps you make quick decisions without confusion.
Whether you’re a seasoned trader or just starting, "Trading as Easy as One, Two, and Three" simplifies your trading journey, turning complex strategies into straightforward actions. Embrace a more efficient way to trade and elevate your performance in the markets!
Get Started Today!
Join the community of traders who have discovered the ease of trading with KepalaBesi's inspired script. Elevate your trading experience and achieve your financial goals with confidence!
HTFMAs█ OVERVIEW
Contains a type HTFMA used to return data on six moving averages from a higher timeframe.
Several types of MA's are supported.
█ HOW TO USE
Please see instructions in the code (in library description). (Important: first fold all sections of the script: press Cmd + K then Cmd + - (for Windows Ctrl + K then Ctrl + -)
█ FULL LIST OF FUNCTIONS AND PARAMETERS
method getMaType(this)
Enumerator function, given a key returns `enum MaTypes` value
Namespace types: series string, simple string, input string, const string
Parameters:
this (string)
method init(this, enableAll, ma1Enabled, ma1MaType, ma1Src, ma1Prd, ma2Enabled, ma2MaType, ma2Src, ma2Prd, ma3Enabled, ma3MaType, ma3Src, ma3Prd, ma4Enabled, ma4MaType, ma4Src, ma4Prd, ma5Enabled, ma5MaType, ma5Src, ma5Prd, ma6Enabled, ma6MaType, ma6Src, ma6Prd)
Namespace types: RsParamsMAs
Parameters:
this (RsParamsMAs)
enableAll (simple MaEnable)
ma1Enabled (bool)
ma1MaType (series MaTypes)
ma1Src (string)
ma1Prd (int)
ma2Enabled (bool)
ma2MaType (series MaTypes)
ma2Src (string)
ma2Prd (int)
ma3Enabled (bool)
ma3MaType (series MaTypes)
ma3Src (string)
ma3Prd (int)
ma4Enabled (bool)
ma4MaType (series MaTypes)
ma4Src (string)
ma4Prd (int)
ma5Enabled (bool)
ma5MaType (series MaTypes)
ma5Src (string)
ma5Prd (int)
ma6Enabled (bool)
ma6MaType (series MaTypes)
ma6Src (string)
ma6Prd (int)
method init(this, enableAll, tf, rngAtrQ, showRecentBars, lblsOffset, lblsShow, lnOffset, lblSize, lblStyle, smoothen, ma1lnClr, ma1lnWidth, ma1lnStyle, ma2lnClr, ma2lnWidth, ma2lnStyle, ma3lnClr, ma3lnWidth, ma3lnStyle, ma4lnClr, ma4lnWidth, ma4lnStyle, ma5lnClr, ma5lnWidth, ma5lnStyle, ma6lnClr, ma6lnWidth, ma6lnStyle, ma1ShowHistory, ma2ShowHistory, ma3ShowHistory, ma4ShowHistory, ma5ShowHistory, ma6ShowHistory, ma1ShowLabel, ma2ShowLabel, ma3ShowLabel, ma4ShowLabel, ma5ShowLabel, ma6ShowLabel)
Namespace types: HTFMAs
Parameters:
this (HTFMAs)
enableAll (series MaEnable)
tf (string)
rngAtrQ (int)
showRecentBars (int)
lblsOffset (int)
lblsShow (bool)
lnOffset (int)
lblSize (string)
lblStyle (string)
smoothen (bool)
ma1lnClr (color)
ma1lnWidth (int)
ma1lnStyle (string)
ma2lnClr (color)
ma2lnWidth (int)
ma2lnStyle (string)
ma3lnClr (color)
ma3lnWidth (int)
ma3lnStyle (string)
ma4lnClr (color)
ma4lnWidth (int)
ma4lnStyle (string)
ma5lnClr (color)
ma5lnWidth (int)
ma5lnStyle (string)
ma6lnClr (color)
ma6lnWidth (int)
ma6lnStyle (string)
ma1ShowHistory (bool)
ma2ShowHistory (bool)
ma3ShowHistory (bool)
ma4ShowHistory (bool)
ma5ShowHistory (bool)
ma6ShowHistory (bool)
ma1ShowLabel (bool)
ma2ShowLabel (bool)
ma3ShowLabel (bool)
ma4ShowLabel (bool)
ma5ShowLabel (bool)
ma6ShowLabel (bool)
method get(this, id)
Namespace types: RsParamsMAs
Parameters:
this (RsParamsMAs)
id (int)
method set(this, id, prop, val)
Namespace types: RsParamsMAs
Parameters:
this (RsParamsMAs)
id (int)
prop (string)
val (string)
method set(this, id, prop, val)
Namespace types: HTFMAs
Parameters:
this (HTFMAs)
id (int)
prop (string)
val (string)
method htfUpdateTuple(rsParams, repaint)
Namespace types: RsParamsMAs
Parameters:
rsParams (RsParamsMAs)
repaint (bool)
method clear(this)
Namespace types: MaDrawing
Parameters:
this (MaDrawing)
method importRsRetTuple(this, htfBi, ma1, ma2, ma3, ma4, ma5, ma6)
Namespace types: HTFMAs
Parameters:
this (HTFMAs)
htfBi (int)
ma1 (float)
ma2 (float)
ma3 (float)
ma4 (float)
ma5 (float)
ma6 (float)
method getDrw(this, id)
Namespace types: HTFMAs
Parameters:
this (HTFMAs)
id (int)
method setDrwProp(this, id, prop, val)
Namespace types: HTFMAs
Parameters:
this (HTFMAs)
id (int)
prop (string)
val (string)
method initDrawings(this, rsPrms, dispBandWidth)
Namespace types: HTFMAs
Parameters:
this (HTFMAs)
rsPrms (RsParamsMAs)
dispBandWidth (float)
method updateDrawings(this, rsPrms, dispBandWidth)
Namespace types: HTFMAs
Parameters:
this (HTFMAs)
rsPrms (RsParamsMAs)
dispBandWidth (float)
method update(this)
Namespace types: HTFMAs
Parameters:
this (HTFMAs)
method importConfig(this, oCfg, maCount)
Imports HTF MAs settings from objProps (of any level) into `RsParamsMAs` child `RsMaCalcParams` objects (into the first first `maCount` of them)
Namespace types: RsParamsMAs
Parameters:
this (RsParamsMAs) : (RsParamsMAs) Target object to import prop values to.
oCfg (objProps type from moebius1977/CSVParser/1) : (CSVP.objProps) (one of objProps types) an objProps, ... opjProps8 containing properties' values in a child objProps objects
maCount (int) : (int) Number of tgtObj's RsMaCalcParams childs of tgtObj to set (1 to 6, starting from 1)
Returns: this
method importConfig(this, oCfg, maCount)
Imports HTF MAs settings from objProps (of any level) into `RsParamsMAs` child `RsMaCalcParams` objects (into the first first `maCount` of them)
Namespace types: RsParamsMAs
Parameters:
this (RsParamsMAs) : (RsParamsMAs) Target object to import prop values to.
oCfg (objProps0 type from moebius1977/CSVParser/1) : (CSVP.objProps) (one of objProps types) an objProps, ... opjProps8 containing properties' values in a child objProps objects
maCount (int) : (int) Number of tgtObj's RsMaCalcParams childs of tgtObj to set (1 to 6, starting from 1)
Returns: this
method importConfig(this, oCfg, maCount)
Imports HTF MAs settings from objProps (of any level) into `RsParamsMAs` child `RsMaCalcParams` objects (into the first first `maCount` of them)
Namespace types: RsParamsMAs
Parameters:
this (RsParamsMAs) : (RsParamsMAs) Target object to import prop values to.
oCfg (objProps1 type from moebius1977/CSVParser/1) : (CSVP.objProps) (one of objProps types) an objProps, ... opjProps8 containing properties' values in a child objProps objects
maCount (int) : (int) Number of tgtObj's RsMaCalcParams childs of tgtObj to set (1 to 6, starting from 1)
Returns: this
method importConfig(this, oCfg, maCount)
Imports HTF MAs settings from objProps (of any level) into `RsParamsMAs` child `RsMaCalcParams` objects (into the first first `maCount` of them)
Namespace types: RsParamsMAs
Parameters:
this (RsParamsMAs) : (RsParamsMAs) Target object to import prop values to.
oCfg (objProps2 type from moebius1977/CSVParser/1) : (CSVP.objProps) (one of objProps types) an objProps, ... opjProps8 containing properties' values in a child objProps objects
maCount (int) : (int) Number of tgtObj's RsMaCalcParams childs of tgtObj to set (1 to 6, starting from 1)
Returns: this
method importConfig(this, oCfg, maCount)
Imports HTF MAs settings from objProps (of any level) into `RsParamsMAs` child `RsMaCalcParams` objects (into the first first `maCount` of them)
Namespace types: RsParamsMAs
Parameters:
this (RsParamsMAs) : (RsParamsMAs) Target object to import prop values to.
oCfg (objProps3 type from moebius1977/CSVParser/1) : (CSVP.objProps) (one of objProps types) an objProps, ... opjProps8 containing properties' values in a child objProps objects
maCount (int) : (int) Number of tgtObj's RsMaCalcParams childs of tgtObj to set (1 to 6, starting from 1)
Returns: this
method importConfig(this, oCfg, maCount)
Imports HTF MAs settings from objProps (of any level) into `RsParamsMAs` child `RsMaCalcParams` objects (into the first first `maCount` of them)
Namespace types: RsParamsMAs
Parameters:
this (RsParamsMAs) : (RsParamsMAs) Target object to import prop values to.
oCfg (objProps4 type from moebius1977/CSVParser/1) : (CSVP.objProps) (one of objProps types) an objProps, ... opjProps8 containing properties' values in a child objProps objects
maCount (int) : (int) Number of tgtObj's RsMaCalcParams childs of tgtObj to set (1 to 6, starting from 1)
Returns: this
method importConfig(this, oCfg, maCount)
Imports HTF MAs settings from objProps (of any level) into `RsParamsMAs` child `RsMaCalcParams` objects (into the first first `maCount` of them)
Namespace types: RsParamsMAs
Parameters:
this (RsParamsMAs) : (RsParamsMAs) Target object to import prop values to.
oCfg (objProps5 type from moebius1977/CSVParser/1) : (CSVP.objProps) (one of objProps types) an objProps, ... opjProps8 containing properties' values in a child objProps objects
maCount (int) : (int) Number of tgtObj's RsMaCalcParams childs of tgtObj to set (1 to 6, starting from 1)
Returns: this
method importConfig(this, oCfg, maCount)
Imports HTF MAs settings from objProps (of any level) into `RsParamsMAs` child `RsMaCalcParams` objects (into the first first `maCount` of them)
Namespace types: RsParamsMAs
Parameters:
this (RsParamsMAs) : (RsParamsMAs) Target object to import prop values to.
oCfg (objProps6 type from moebius1977/CSVParser/1) : (CSVP.objProps) (one of objProps types) an objProps, ... opjProps8 containing properties' values in a child objProps objects
maCount (int) : (int) Number of tgtObj's RsMaCalcParams childs of tgtObj to set (1 to 6, starting from 1)
Returns: this
method importConfig(this, oCfg, maCount)
Namespace types: RsParamsMAs
Parameters:
this (RsParamsMAs)
oCfg (objProps7 type from moebius1977/CSVParser/1)
maCount (int)
method importConfig(this, oCfg, maCount)
Imports HTF MAs settings from objProps (of any level) into `HTFMAs` child `MaDrawing` objects (into the first first `maCount` of them)
Namespace types: RsParamsMAs
Parameters:
this (RsParamsMAs) : (HTFMAs) Target object to import prop values to.
oCfg (objProps8 type from moebius1977/CSVParser/1) : (CSVP.objProps) (one of objProps types) an objProps, ... opjProps8 containing properties' values in a child objProps objects
maCount (int) : (int) Number of tgtObj's RsMaCalcParams childs of tgtObj to set (1 to 6, starting from 1)
Returns: this
method importConfig(this, oCfg, maCount)
Imports HTF MAs settings from objProps (of any level) into `HTFMAs` child `MaDrawing` objects (into the first first `maCount` of them)
Namespace types: HTFMAs
Parameters:
this (HTFMAs) : (HTFMAs) Target object to import prop values to.
oCfg (objProps type from moebius1977/CSVParser/1) : (CSVP.objProps) (one of objProps types) an objProps, ... opjProps8 containing properties' values in a child objProps objects
maCount (int) : (int) Number of tgtObj's RsMaCalcParams childs of tgtObj to set (1 to 6, starting from 1)
Returns: this
method importConfig(this, oCfg, maCount)
Imports HTF MAs settings from objProps (of any level) into `HTFMAs` child `MaDrawing` objects (into the first first `maCount` of them)
Namespace types: HTFMAs
Parameters:
this (HTFMAs) : (HTFMAs) Target object to import prop values to.
oCfg (objProps0 type from moebius1977/CSVParser/1) : (CSVP.objProps) (one of objProps types) an objProps, ... opjProps8 containing properties' values in a child objProps objects
maCount (int) : (int) Number of tgtObj's RsMaCalcParams childs of tgtObj to set (1 to 6, starting from 1)
Returns: this
method importConfig(this, oCfg, maCount)
Imports HTF MAs settings from objProps (of any level) into `HTFMAs` child `MaDrawing` objects (into the first first `maCount` of them)
Namespace types: HTFMAs
Parameters:
this (HTFMAs) : (HTFMAs) Target object to import prop values to.
oCfg (objProps1 type from moebius1977/CSVParser/1) : (CSVP.objProps) (one of objProps types) an objProps, ... opjProps8 containing properties' values in a child objProps objects
maCount (int) : (int) Number of tgtObj's RsMaCalcParams childs of tgtObj to set (1 to 6, starting from 1)
Returns: this
method importConfig(this, oCfg, maCount)
Imports HTF MAs settings from objProps (of any level) into `HTFMAs` child `MaDrawing` objects (into the first first `maCount` of them)
Namespace types: HTFMAs
Parameters:
this (HTFMAs) : (HTFMAs) Target object to import prop values to.
oCfg (objProps2 type from moebius1977/CSVParser/1) : (CSVP.objProps) (one of objProps types) an objProps, ... opjProps8 containing properties' values in a child objProps objects
maCount (int) : (int) Number of tgtObj's RsMaCalcParams childs of tgtObj to set (1 to 6, starting from 1)
Returns: this
method importConfig(this, oCfg, maCount)
Imports HTF MAs settings from objProps (of any level) into `HTFMAs` child `MaDrawing` objects (into the first first `maCount` of them)
Namespace types: HTFMAs
Parameters:
this (HTFMAs) : (HTFMAs) Target object to import prop values to.
oCfg (objProps3 type from moebius1977/CSVParser/1) : (CSVP.objProps) (one of objProps types) an objProps, ... opjProps8 containing properties' values in a child objProps objects
maCount (int) : (int) Number of tgtObj's RsMaCalcParams childs of tgtObj to set (1 to 6, starting from 1)
Returns: this
method importConfig(this, oCfg, maCount)
Imports HTF MAs settings from objProps (of any level) into `HTFMAs` child `MaDrawing` objects (into the first first `maCount` of them)
Namespace types: HTFMAs
Parameters:
this (HTFMAs) : (HTFMAs) Target object to import prop values to.
oCfg (objProps4 type from moebius1977/CSVParser/1) : (CSVP.objProps) (one of objProps types) an objProps, ... opjProps8 containing properties' values in a child objProps objects
maCount (int) : (int) Number of tgtObj's RsMaCalcParams childs of tgtObj to set (1 to 6, starting from 1)
Returns: this
method importConfig(this, oCfg, maCount)
Imports HTF MAs settings from objProps (of any level) into `HTFMAs` child `MaDrawing` objects (into the first first `maCount` of them)
Namespace types: HTFMAs
Parameters:
this (HTFMAs) : (HTFMAs) Target object to import prop values to.
oCfg (objProps5 type from moebius1977/CSVParser/1) : (CSVP.objProps) (one of objProps types) an objProps, ... opjProps8 containing properties' values in a child objProps objects
maCount (int) : (int) Number of tgtObj's RsMaCalcParams childs of tgtObj to set (1 to 6, starting from 1)
Returns: this
method importConfig(this, oCfg, maCount)
Imports HTF MAs settings from objProps (of any level) into `HTFMAs` child `MaDrawing` objects (into the first first `maCount` of them)
Namespace types: HTFMAs
Parameters:
this (HTFMAs) : (HTFMAs) Target object to import prop values to.
oCfg (objProps6 type from moebius1977/CSVParser/1) : (CSVP.objProps) (one of objProps types) an objProps, ... opjProps8 containing properties' values in a child objProps objects
maCount (int) : (int) Number of tgtObj's RsMaCalcParams childs of tgtObj to set (1 to 6, starting from 1)
Returns: this
method importConfig(this, oCfg, maCount)
Namespace types: HTFMAs
Parameters:
this (HTFMAs)
oCfg (objProps7 type from moebius1977/CSVParser/1)
maCount (int)
method importConfig(this, oCfg, maCount)
Namespace types: HTFMAs
Parameters:
this (HTFMAs)
oCfg (objProps8 type from moebius1977/CSVParser/1)
maCount (int)
method newRsParamsMAs(this)
Namespace types: LO
Parameters:
this (LO)
method newHTFMAs(this)
Namespace types: LO
Parameters:
this (LO)
RsMaCalcParams
Parameters of one MA (only calculation params needed within req.sec(), visual parameters are within htfMAs type)
Fields:
enabled (series bool)
maType (series MaTypes) : MA type options: SMA / EMA / WMA / ...
src (series string)
prd (series int) : MA period
RsParamsMAs
Collection of parameters of 6 MAs. Used to pass params to req.sec()
Fields:
ma1CalcParams (RsMaCalcParams)
ma2CalcParams (RsMaCalcParams)
ma3CalcParams (RsMaCalcParams)
ma4CalcParams (RsMaCalcParams)
ma5CalcParams (RsMaCalcParams)
ma6CalcParams (RsMaCalcParams)
RsReturnMAs
Used to return data from req.sec().
Fields:
htfBi (series int)
ma1 (series float)
ma2 (series float)
ma3 (series float)
ma4 (series float)
ma5 (series float)
ma6 (series float)
MaDrawing
MA's plot parameters plus drawing objects for MA's current level (line and label).
Fields:
lnClr (series color) : (color) MA plot line color (like in plot())
lnWidth (series int) : (int) MA plot line width (like in plot())
lnStyle (series string) : (string) MA plot line style (like in plot())
showHistory (series bool) : (bool) Whether to plot the MA on historical bars or only show current level to the right of the latest bar.
showLabel (series bool) : (bool) Whether to show the name of the MA to the right of the MA's level
ln (series line) : (line) line to show MA"s current level
lbl (series label) : (label) label showing MA's name
HTFMAs
Contains data and drawing parameters for MA's of one timeframe (MA calculation parameters for MA's of one timeframe are in a separate object RsParamsMAs)
Fields:
rsRet (RsReturnMAs) : (RsReturnMAs) Contains data returned from req.sec(). Is set to na in between HTF bar changes if smoothing is enabled.
rsRetLast (RsReturnMAs) : (RsReturnMAs) Contains a copy of data returned from req.sec() in case rsRet is set to na for smoothing.
rsRetNaObj (RsReturnMAs) : (RsReturnMAs) An empty object as `na` placeholder
ma1Drawing (MaDrawing) : (MaDrawing) MA drawing properties
ma2Drawing (MaDrawing) : (MaDrawing) MA drawing properties
ma3Drawing (MaDrawing) : (MaDrawing) MA drawing properties
ma4Drawing (MaDrawing) : (MaDrawing) MA drawing properties
ma5Drawing (MaDrawing) : (MaDrawing) MA drawing properties
ma6Drawing (MaDrawing) : (MaDrawing) MA drawing properties
enabled (series bool) : (bool ) Enables/disables all of the MAs of one timeframe.
tf (series string) : (string) Timeframe
showHistory (series bool) : (bool ) Plot MA line on historical bars
rngAtrQ (series int) : (int ) A multiplier for atr(14). Determines a range within which the MA's will be plotted. MA's too far away will not be plotted.
showRecentBars (series int) : (int ) Only plot MA on these recent bars
smoothen (series bool) : (bool ) Smoothen MA plot. If false the same HTF value is returned on all chart bars within a HTF bar (intrabars), so the plot looks like steps.
lblsOffset (series int) : (int ) Show MA name this number of bars to the right off last bar.
lblsShow (series bool) : (bool ) Show MA name
lnOffset (series int) : (int ) Start line showing current level of the MA this number of bars to the right off the last bar.
lblSize (series string) : (string) Label size
lblStyle (series string) : (string) Label style
lblTxtAlign (series string) : (string) Label text align
bPopupLabel (series bool) : (bool ) Show current MA value as a tooltip to MA's name.
LO
LO Library object, whose only purpose is to serve as a shorthand for library name in script code.
Fields:
dummy (series string)
N Bar Reversal Detector [LuxAlgo]The N Bar Reversal Detector is designed to detect and highlight N-bar reversal patterns in user charts, where N represents the length of the candle sequence used to detect the patterns. The script incorporates various trend indicators to filter out detected signals and offers a range of customizable settings to fit different trading strategies.
🔶 USAGE
The N-bar reversal pattern extends the popular 3-bar reversal pattern. While the 3-bar reversal pattern involves identifying a sequence of three bars signaling a potential trend reversal, the N-bar reversal pattern builds on this concept by incorporating additional bars based on user settings. This provides a more comprehensive indication of potential trend reversals. The script automates the identification of these patterns and generates clear, visually distinct signals to highlight potential trend changes.
When a reversal chart pattern is confirmed and aligns with the price action, the pattern's boundaries are extended to create levels. The upper boundary serves as resistance, while the lower boundary acts as support.
The script allows users to filter patterns based on the trend direction identified by various trend indicators. Users can choose to view patterns that align with the detected trend or those that are contrary to it.
🔶 DETAILS
🔹 The N-bar Reversal Pattern
The N-bar reversal pattern is a technical analysis tool designed to signal potential trend reversals in the market. It consists of N consecutive bars, with the first N-1 bars used to identify the prevailing trend and the Nth bar confirming the reversal. Here’s a detailed look at the pattern:
Bullish Reversal : In a bullish reversal setup, the first bar is the highest among the first N-1 bars, indicating a prevailing downtrend. Most of the remaining bars in this sequence should be bearish (closing lower than where they opened), reinforcing the existing downward momentum. The Nth (most recent) bar confirms a bullish reversal if its high price is higher than the high of the first bar in the sequence (standard pattern). For a stronger signal, the closing price of the Nth bar should also be higher than the high of the first bar.
Bearish Reversal : In a bearish reversal setup, the first bar is the lowest among the first N-1 bars, indicating a prevailing uptrend. Most of the remaining bars in this sequence should be bullish (closing higher than where they opened), reinforcing the existing upward momentum. The Nth bar confirms a bearish reversal if its low price is lower than the low of the first bar in the sequence (standard pattern). For a stronger signal, the closing price of the Nth bar should also be lower than the low of the first bar.
🔹 Min Percentage of Required Candles
This parameter specifies the minimum percentage of candles that must be bullish (for a bearish reversal) or bearish (for a bullish reversal) among the first N-1 candles in a pattern. For higher values of N, it becomes more challenging for all of the first N-1 candles to be consistently bullish or bearish. By setting a percentage value, P, users can adjust the requirement so that only a minimum of P percent of the first N-1 candles need to meet the bullish or bearish condition. This allows for greater flexibility in pattern recognition, accommodating variations in market conditions.
🔶 SETTINGS
Pattern Type: Users can choose the type of the N-bar reversal patterns to detect: Normal, Enhanced, or All. "Normal" detects patterns that do not necessarily surpass the high/low of the first bar. "Enhanced" detects patterns where the last bar surpasses the high/low of the first bar. "All" detects both Normal and Enhanced patterns.
Reversal Pattern Sequence Length: Specifies the number of candles (N) in the sequence used to identify a reversal pattern.
Min Percentage of Required Candles: Sets the minimum percentage of the first N-1 candles that must be bullish (for a bearish reversal) or bearish (for a bullish reversal) to qualify as a valid reversal pattern.
Derived Support and Resistance: Toggles the visibility of the support and resistance levels/zones.
🔹 Trend Filtering
Filtering: Allows users to filter patterns based on the trend indicators: Moving Average Cloud, Supertrend, and Donchian Channels. The "Aligned" option only detects patterns that align with the trend and conversely, the "Opposite" option detects patterns that go against the trend.
🔹 Trend Indicator Settings
Moving Average Cloud: Allows traders to choose the type of moving averages (SMA, EMA, HMA, etc.) and set the lengths for fast and slow moving averages.
Supertrend: Options to set the ATR length and factor for Supertrend.
Donchian Channels: Option to set the length for the channel calculation.
🔶 RELATED SCRIPTS
Reversal-Candlestick-Structure.
Reversal-Signals.
Prometheus Black-Scholes Option PricesThe Black-Scholes Model is an option pricing model developed my Fischer Black and Myron Scholes in 1973 at MIT. This is regarded as the most accurate pricing model and is still used today all over the world. This script is a simulated Black-Scholes model pricing model, I will get into why I say simulated.
What is an option?
An option is the right, but not the obligation, to buy or sell 100 shares of a certain stock, for calls or puts respective, at a certain price, on a certain date (assuming European style options, American options can be exercised early). The reason these agreements, these contracts exist is to provide traders with leverage. Buying 1 contract to represent 100 shares of the underlying, more often than not, at a cheaper price. That is why the price of the option, the premium , is a small number. If an option costs $1.00 we pay $100.00 for it because 100 shares * 1 dollar per share = 100 dollars for all the shares. When a trader purchases a call on stock XYZ with a strike of $105 while XYZ stock is trading at $100, if XYZ stock moves up to $110 dollars before expiration the option has $5 of intrinsic value. You have the right to buy something at $105 when it is trading at $110. That agreement is way more valuable now, as a result the options premium would increase. That is a quick overview about how options are traded, let's get into calculating them.
Inputs for the Black-Scholes model
To calculate the price of an option we need to know 5 things:
Current Price of the asset
Strike Price of the option
Time Till Expiration
Risk-Free Interest rate
Volatility
The price of a European call option 𝐶 is given by:
𝐶 = 𝑆0 * Φ(𝑑1) − 𝐾 * 𝑒^(−𝑟 * 𝑇) * Φ(𝑑2)
where:
𝑆0 is the current price of the underlying asset.
𝐾 is the strike price of the option.
𝑟 is the risk-free interest rate.
𝑇 is the time to expiration.
Φ is the cumulative distribution function of the standard normal distribution.
𝑑1 and 𝑑2 are calculated as:
𝑑1 = (ln(𝑆0 / 𝐾) + (𝑟 + (𝜎^2 / 2)) * 𝑇) / (𝜎 * sqrt(𝑇))
𝑑2= 𝑑1 - (𝜎 * sqrt(𝑇))
𝜎 is the volatility of the underlying asset.
The price of a European put option 𝑃 is given by:
𝑃 = 𝐾 * 𝑒^(−𝑟 * 𝑇) * Φ(−𝑑2) − 𝑆0 * Φ(−𝑑1)
where 𝑑1 and 𝑑2 are as defined above.
Key Assumptions of the Black-Scholes Model
The price of the underlying asset follows a lognormal distribution.
There are no transaction costs or taxes.
The risk-free interest rate and volatility of the underlying asset are constant.
The underlying asset does not pay dividends during the life of the option.
The markets are efficient, meaning that all known information is already reflected in the prices.
Options can only be exercised at expiration (European-style options).
Understanding the Script
Here I have arrows pointing to specific spots on the table. They point to Historical Volatility and Inputted DTE . Inputted DTE is a value the user may input to calculate premium for options that expire in that many days. Historical Volatility , is the value calculated by this code.
length = 252 // One year of trading days
hv = ta.stdev(math.log(close / close ), length) * math.sqrt(365)
And then made daily like the Black-Scholes model needs from this step in the code.
hv_daily = request.security(syminfo.tickerid, "1D", hv)
The user has the option to input their own volatility to the Script. I will get into why that may be advantageous in a moment. If the user chooses to do so the Script will change which value it is using as so.
hv_in_use = which_sig == false ? hv_daily : sig
There is a lot going on in this image but bare with me, it will all make sense by the end. The column to the far left of both the green and maroon colored columns represent the strike price of the contract, if the numbers are white that means the contract is out of the money, gray means in the money. If you remember from the calculation this represents the price to buy or sell shares at, for calls or puts respective. The column second from the left shows a value for Simulated Market Price . This is a necessary part of this script so we can show changes in implied volatility. See, when we go to our brokerages and look at options prices, sure the price was calculated by a pricing model, but that is rarely the true price of the model. Market participant sentiment affects this value as their estimates for future volatility, Implied Volatility changes.
For example, if a call option is supposed to be worth $1.00 from the pricing model, however everyone is bullish on the stock and wants to buy calls, the premium may go to $1.20 from $1.00 because participants juice up the Implied Volatility . Higher Implied Volatility generally means higher premium, given enough time to expiration. Buying an option at $0.80 when it should be worth $1.00 due to changes in sentiment is a big part of the Quant Trading industry.
Of course I don't have access to an actual exchange so get prices, so I modeled participant decisions by adding or subtracting a small random value on the "perfect premium" from the Black-Scholes model, and solving for implied volatility using the Newton-Raphson method.
It is like when we have speed = distance / time if we know speed and time , we can solve for distance .
This is what models the changing Implied Volatility in the table. The other column in the table, 3rd from the left, is the Black-Scholes model price without the changes of a random number. Finally, the 4th column from the left is that Implied Volatility value we calculated with the modified option price.
More on Implied Volatility
Implied Volatility represents the future expected volatility of an asset. As it is the value in the future it is not know like Historical Volatility, only projected. We provide the user with the option to enter their own Implied Volatility to start with for better modeling of options close to expiration. If you want to model options 1 day from expiration you will probably have to enter a higher Implied Volatility so that way the prices will be higher. Since the underlying is so close to expiration they are traded so much and traders manipulate their Implied Volatility , increasing their value. Be safe while trading these!
Thank you all for clicking on my indicator and reading this description! Happy coding, Happy trading, Be safe!
Good reference: www.investopedia.com
Fibonacci Period Range [UkutaLabs]█ OVERVIEW
The Fibonacci Period Range Indicator is a powerful trading tool that draws levels of support and resistance that are based on key Fibonacci levels. The script will identify the high and low of a range that is specified by the user, then draw several levels of support and resistance based on Fibonacci levels.
The script will also draw extension levels outside of the specified range that are also based on Fibonacci levels. These extension levels can be turned off in the indicator settings.
Each level is also labelled to help traders understand what each line represents. These labels can be turned off in the indicator settings.
The purpose of this script is to simplify the trading experience of users by giving them the ability to customize the time period that is identified, then draw levels of support and resistance that are based on the price action during this time.
█ USAGE
In the indicator settings, the user has access to a setting called Session Range. This gives users control over the range that will be used.
The script will then identify the high and low of the range that was specified and draw several levels of support and resistance based on Fibonacci levels between this range. The user can also choose to have extension levels that display more levels outside of the range.
These lines will extend until the end of the current trading day at 5:00 pm EST.
█ SETTINGS
Configuration
• Display Mode: Determines the number of days that will be displayed by the script.
• Show Labels: Determines whether or not identifying labels will be displayed on each line.
• Font Size: Determines the text size of labels.
• Label Position: Determines the justification of labels.
• Extension Levels: Determines whether or not extension levels will be drawn outside of the high and low of the specified range.
Session
• Session Range: Determines the time period that will be used for calculations.
• Timezone Offset (+/-): Determines how many hours the session should be offset by.
Speedometer RevisitedSpeedometer Revisited is a new way to draw custom metric speedometers and is intended to be a utility for other coders to use.
@rumpypumpydumpy originally introduced the Speedometer Toolkit in version 4 of Pine Script. Since then, Pine Script has been updated to version 5, introducing some amazing new features such as polylines and chart.points. This indicator is an example of what can be done with these newer features.
The indicator starts off with a handful of functions that will be used to create the drawings. Notes are left throughout the code explaining what each line of the functions does. My goal was to make these functions user-friendly and somewhat easy to understand. I then demonstrate two examples: one speedometer with five segments and another with three.
The first example demonstrates how to visually represent the analysts' ratings for a stock using the built-in syminfo.recommendations. The speedometer is divided into five segments, each representing a different level of analyst recommendation: strong sell, sell, hold, buy, and strong buy.
Each segment is drawn using a polyline from the createSeg function, with colors assigned as follows:
Red for 'Strong Sell'
Maroon for 'Sell'
Yellow for 'Hold'
Green for 'Buy'
Lime for 'Strong Buy'
The script identifies the maximum value among the analyst ratings, calculates the midpoint of the corresponding segment, and draws a needle pointing to this midpoint.
The second example employs the speedometer design to display market sentiment through the put-call ratio. The put-call ratio is a gauge of investor sentiment, where values above 1 indicate a bearish sentiment (more puts being bought relative to calls), and values below 1 suggest a bullish outlook (more calls being bought relative to puts).
The speedometer is divided into three segments, reflecting different ranges of the put-call ratio:
Red for a ratio greater than 1 (bearish sentiment)
Yellow for a ratio between 0.8 and 1 (neutral to bearish sentiment)
Lime for a ratio less than 0.8 (bullish sentiment)
Depending on the value of the put-call ratio, the script calculates which segment the current value falls into and determines the appropriate segment number. The script calculates the midpoint of the selected segment and draws a needle pointing to this value.
Both examples show how the speedometer can be used as a visual indicator of certain market conditions, helping traders quickly recognize trends and adjust their strategies accordingly.
A big thanks to @rumpypumpydumpy for his original Speedometer Toolbox. I hope this take on it can be useful for other coders.
Volume Candles By Anil ChawraHow Users Can Make Profit Using This Script:
1. Volume Representation : Each candle on the chart represents a specific time period (e.g., 1 minute, 1 hour, 1 day) and includes information about both price movement and trading volume during that period.
2. Candlestick Anatomy : A volume candle has the same components as a regular candlestick: the body (which represents the opening and closing prices) and the wicks or shadows (which indicate the highest and lowest prices reached during the period).
3. Volume Bars : Instead of just the candlestick itself, volume candles also include a bar or histogram representing the trading volume during that period. The height or length of the volume bar indicates the amount of trading activity.
4. Interpreting Volume : High volume candles typically indicate increased market interest or activity during that period. This could be due to significant buying or selling pressure.
5. Confirmation : Traders often look for confirmation from other technical indicators or price action to validate the significance of a high volume candle. For example, a high volume candle breaking through a key support or resistance level may signal a strong market move.
6. Trend Strength : Volume candles can provide insights into the strength of a trend. A series of high volume candles in the direction of the trend suggests strong momentum, while decreasing volume may indicate weakening momentum or a potential reversal.
7. Volume Patterns : Traders also analyze volume patterns, such as volume spikes or divergences, to identify potential trading opportunities or reversals.
8. Combination with Price Action: Volume analysis is often used in conjunction with price action analysis and other technical indicators to make more informed trading decisions.
9. Confirmation and Validation: It's important to confirm the significance of volume candles with other indicators or price action signals to avoid false signals.
10. Risk Management : As with any trading strategy, proper risk management is crucial when using volume candles to make trading decisions. Set stop-loss orders and adhere to risk management principles to protect your capital.
How the Script Works:
1. Volume Representation : Each candle on the chart represents a specific time period (e.g., 1 minute, 1 hour, 1 day) and includes information about both price movement and trading volume during that period.
2. Candlestick Anatomy : A volume candle has the same components as a regular candlestick: the body (which represents the opening and closing prices) and the wicks or shadows (which indicate the highest and lowest prices reached during the period).
3. Volume Bars : Instead of just the candlestick itself, volume candles also include a bar or histogram representing the trading volume during that period. The height or length of the volume bar indicates the amount of trading activity.
4. Interpreting Volume : High volume candles typically indicate increased market interest or activity during that period. This could be due to significant buying or selling pressure.
5. Confirmation : Traders often look for confirmation from other technical indicators or price action to validate the significance of a high volume candle. For example, a high volume candle breaking through a key support or resistance level may signal a strong market move.
6. Trend Strength : Volume candles can provide insights into the strength of a trend. A series of high volume candles in the direction of the trend suggests strong momentum, while decreasing volume may indicate weakening momentum or a potential reversal.
7. Volume Patterns : Traders also analyze volume patterns, such as volume spikes or divergences, to identify potential trading opportunities or reversals.
8. Combination with Price Action : Volume analysis is often used in conjunction with price action analysis and other technical indicators to make more informed trading decisions.
9. Confirmation and Validation : It's important to confirm the significance of volume candles with other indicators or price action signals to avoid false signals.
10. Risk Management : As with any trading strategy, proper risk management is crucial when using volume candles to make trading decisions. Set stop-loss orders and adhere to risk management principles to protect your capital.
Understanding volume candles can provide valuable insights into market dynamics and help traders make more informed decisions. However, like any technical tool, it's essential to use volume analysis in conjunction with other forms of analysis for comprehensive market assessment.
Understanding volume candles can provide valuable insights into market dynamics and help traders make more informed decisions. However, like any technical tool, it's essential to use volume analysis in conjunction with other forms of analysis for comprehensive market assessment.
Squeeze & Release [AlgoAlpha]Introduction:
💡The Squeeze & Release by AlgoAlpha is an innovative tool designed to capture price volatility dynamics using a combination of EMA-based calculations and ATR principles. This script aims to provide traders with clear visual cues to spot potential market squeezes and release scenarios. Hence it is important to note that this indicator shows information on volatility, not direction.
Core Logic and Components:
🔶EMA Calculations: The script utilizes the Exponential Moving Average (EMA) in multiple ways to smooth out the data and provide indicator direction. There are specific lengths for the EMAs that users can modify as per their preference.
🔶ATR Dynamics: Average True Range (ATR) is a core component of the script. The differential between the smoothed ATR and its EMA is used to plot the main line. This differential, when represented as a percentage of the high-low range, provides insights into volatility.
🔶Squeeze and Release Detection: The script identifies and highlights squeeze and release scenarios based on the crossover and cross-under events between our main line and its smoothed version. Squeezes are potential setups where the market may be consolidating, and releases indicate a potential breakout or breakdown.
🔶Hyper Squeeze Detection: A unique feature that detects instances when the main line is rising consistently over a user-defined period. Hyper squeeze marks areas of extremely low volatility.
Visual Components:
The main line (ATR-based) changes color depending on its position relative to its EMA.
A middle line plotted at zero level which provides a quick visual cue about the main line's position. If the main line is above the zero level, it indicates that the price is squeezing on a longer time horizon, even if the indicator indicates a shorter-term release.
"𝓢" and "𝓡" characters are plotted to represent 'Squeeze' and 'Release' scenarios respectively.
Standard Deviation Bands are plotted to help users gauge the extremity and significance of the signal from the indicator, if the indicator is closer to either the upper or lower deviation bands, this means that statistically, the current value is considered to be more extreme and as it is further away from the mean where the indicator is oscillating at for the majority of the time. Thus indicating that the price has experienced an unusual amount or squeeze or release depending on the value of the indicator.
Usage Guidelines:
☝️Traders can use the script to:
Identify potential consolidation (squeeze) zones.
Gauge potential breakout or breakdown scenarios (release).
Fine-tune their entries and exits based on volatility.
Adjust the various lengths provided in the input for better customization based on individual trading styles and the asset being traded.
Liquidation Estimates (Real-Time) [LuxAlgo]The Liquidation Estimates (Real-Time) experimental indicator attempts to highlight real-time long and short liquidations on all timeframes. Here with liquidations, we refer to the process of forcibly closing a trader's position in the market.
By analyzing liquidation data, traders can gauge market sentiment, identify potential support and resistance levels, identify potential trend reversals, and make informed decisions about entry and exit points.
🔶 USAGE
Liquidation refers to the process of forcibly closing a trader's position. It occurs when a trader's margin account can no longer support their open positions due to significant losses or a lack of sufficient margin to meet the maintenance requirements.
Liquidations can be categorized as either a long liquidation or a short liquidation. A long liquidation is a situation where long positions are being liquidated, while short liquidation is a situation where short positions are being liquidated.
The green bars indicate long liquidations – meaning the number of long positions liquidated in the market. Typically, long liquidations occur when there is a sudden drop in the asset price that is being traded. This is because traders who were bullish on the asset and had opened long positions on the same will now face losses since the market has moved against them.
Similarly, the red bars indicate short liquidations – meaning the number of short positions liquidated in the futures market. Short liquidations occur when there is a sudden spike in the price of the asset that is being traded. This is because traders who were bearish on the asset and had opened short positions will now face losses since the market has moved against them.
Liquidation patterns or clusters of liquidations could indicate potential trend reversals.
🔹 Dominance
Liquidation dominance (Difference) displays the difference between long and short liquidations, aiming to help identify the dominant side.
🔹 Total Liquidations
Total liquidations display the sum of long and short liquidations.
🔹 Cumulative Liquidations
Cumulative liquidations are essentially the cumulative sum of the difference between short and long liquidations aiming to confirm the trend and the strength of the trend.
🔶 DETAILS
It's important to note that liquidation data is not provided on the Trading View's platform or can not be fetched from anywhere else.
Yet we know that the liquidation data is closely tied in with trading volumes in the market and the movement in the underlying asset’s price. As a result, this script analyzes available data sources extracts the required information, and presents an educated estimate of the liquidation data.
The data presented does not reflect the actual individual quantitative value of the liquidation data, traders and analysts shall look to the changes over time and the correlation between liquidation data and price movements.
The script's output with the default option values has been visually checked/compared with the liquidation chart presented on coinglass.com.
🔶 SETTINGS
🔹Liquidations Input
Mode: defines the presentation of the liquidations chart. Details are given in the tooltip of the option.
Longs Reference Price: defines the base price in calculating long liquidations.
Shorts Reference Price: defines the base price in calculating short liquidations.
🔶 RELATED SCRIPTS
Liquidation-Levels
Liquidity-Sentiment-Profile
Buyside-Sellside-Liquidity
Liquidation Levels [LuxAlgo]The Liquidation Levels indicator aims at detecting and estimating potential price levels where large liquidation events may occur.
By analyzing liquidation Levels, traders can identify potential support & resistance levels, identify stop-loss levels, and gauge market sentiment and potential areas of price volatility.
🔶 USAGE
Liquidation refers to the process of forcibly closing a trader's leveraged positions in the market. It occurs when a trader's margin account can no longer support their open positions due to significant losses or a lack of sufficient margin to meet the maintenance margin requirements.
Liquidation events happen at all times and the script focuses on detecting the most significant ones. Bubbles will appear on the relevant price bar when larger trading activity has been detected. Larger bubbles represent more significant potential liquidation levels. The lines attached to the bubbles represent the liquidation zones at that price.
These liquidation levels are based on clusters of price points where highly leveraged traders open long or short positions. High leverage is identified as 100x, 50x, and 25x leverages used for both long and short positions. The script allows users to either remove or customize leverage levels.
Price generally heads towards zones or clusters of liquidity.
🔶 SETTINGS
🔹Liquidation Levels
Reference Price: defines the base price in calculating liquidation levels.
Volume Threshold: The volume threshold is the primary factor in detecting the significant trading activities that could potentially lead to liquidating leveraged positions.
Volatility Threshold: The volatility threshold option is the secondary factor that aims at detecting significant movement in the underlying asset’s price with relatively lower trading activities that could potentially also lead to liquidating high-leveraged positions.
Leverage Options: The leverage options are where the trader will set the desired leverage value and customize the potential liquidation level colors.
Hide Liquidation Bubbles: Toggles the visibility of the bubbles.
Hide Liquidation Levels: Toggles the visibility of the lines.
🔶 RELATED SCRIPTS
Liquidity-Sentiment-Profile
Buyside-Sellside-Liquidity
Supply Demand Profiles [LuxAlgo]The Supply Demand Profiles is a charting tool that measures the traded volume at all price levels on the market over a specified time period and highlights the relationship between the price of a given asset and the willingness of traders to either buy or sell it, in other words, highlights key concepts as significant supply & demand zones, the distribution of the traded volume, and market sentiment at specific price levels within a specified time period, allowing traders to reveal dominant and/or significant price levels and to analyze the trading activity of a particular user-selected range.
In other words, this tool highlights key concepts as significant supply & demand zones, the distribution of the traded volume, and market sentiment at specific price levels within a specified time period, allowing traders to reveal dominant and/or significant price levels and to analyze the trading activity of a particular user-selected range.
Besides having the tool as a combo tool, the uniqueness of this version of the tool compared to its early versions is its ability to benefit from different volume data sources and its ability to use a variety of different polarity methods, where polarity is a measure used to divide the total volume into either up volume (trades that moved the price up) or down volume (trades that moved the price down).
🔶 USAGE
Supply & demand zones are presented as horizontal zones across the selected range, hence adding the ability to visualize the price interaction with them
By default, the right side of the profile is the volume profile which highlights the distribution of the traded activity at different price levels, emphasizing the value area, the range of price levels in which the specified percentage of all volume was traded during the time period, and levels of significance, such as developing point of control line, value area high/low lines, and profile high/low labels
The left side of the profile is the sentiment profile which highlights the market sentiment at specific price levels
🔶 DETAILS
🔹 Volume data sources
The users have the option to select volume data sources as either 'volume' (regular volume) or 'volume delta', where volume represents all the recorded trades that occur at a given bar and volume delta is the difference between the buying and the selling volume, that is, the net demand at a given bar
🔹 Polarity methods
The users are able to choose the methods of how the tool to take into consideration the polarity of the bar (the direction of a bar, green (bullish) or red (bearish) bar) among a variety of different options, such as 'bar polarity', 'bar buying/selling pressure', 'intrabar (chart bars at a lower timeframe than the chart's) polarity', 'intrabar buying/selling pressure', and 'heikin ashi bar polarity'.
Finally, the interactive mode of the tool is activated, as such users can easily modify the intervals of their interest just by selecting the indicator and moving the points on the chart
🔶 SETTINGS
The script takes into account user-defined parameters and plots the profiles and zones
🔹 Calculation Settings
Volume Data Source and Polarity: This option is to set the desired volume data source and polarity method
Lower Timeframe Precision: This option is applicable in case any of the 'Intrabar (LTF)' options are selected, please check the tooltip for further details
Value Area Volume %: Specifies the percentage for the value area calculation
🔹 Presentation Settings
Supply & Demand Zones: Toggles the visibility of the supply & demand zones
Volume Profile: Toggles the visibility of the volume profile
Sentiment Profile: Toggles the visibility of the sentiment profile
🔹 Presentation, Others
Value Area High (VAH): Toggles the visibility of the VAH line and color customization option
Point of Control (POC): Toggles the visibility of the developing POC line and color customization option
Value Area Low (VAL): Toggles the visibility of the VAL line and color customization option
🔹 Supply & Demand, Others
Supply & Demand Threshold %: This option is used to set the threshold value to determine supply & demand zones
Supply/Demand Zones: Color customization option
🔹 Volume Profile, Others
Profile, Up/Down Volume: Color customization option
Value Area, Up/Down Volume: Color customization option
🔹 Sentiment Profile, Others
Sentiment, Bullish/Bearish: Color customization option
Value Area, Bullish/Bearish: Color customization option
🔹 Others
Number of Rows: Specify how many rows the profile will have
Placment: Specify where to display the profile
Profile Width %: Alters the width of the rows in the profile, relative to the profile range
Profile Price Levels: Toggles the visibility of the profile price levels
Profile Background, Color: Fills the background of the profile range
Value Area Background, Color: Fills the background of the value area range
Start Calculation/End Calculation: The tool is interactive, where the user may modify the range by selecting the indicator and moving the points on the chart or can set the start/end time using these options
🔶 RELATED SCRIPTS
Volume-Profile
Volume-Profile-Maps
Volume-Delta
Liquidity Sentiment Profile (Auto-Anchored) [LuxAlgo]
The Liquidity Sentiment Profile (Auto-Anchored) is an advanced charting tool that measures by combining PRICE and VOLUME data over specified anchored periods and highlights the distribution of the liquidity and the market sentiment at specific price levels. This version is a variation of the previously published Liquidity Sentiment Profile , wherewith this version allows users to select a variety of different anchoring periods, such as 'Auto', 'Fixed Range', 'Swing High', 'Swing Low', 'Session', 'Day', 'Week', 'Month', 'Quarter', and 'Year'
Liquidity refers to the availability of orders at specific price levels in the market, allowing transactions to occur smoothly.
🔶 USAGE
A Liquidity Sentiment Profile (Auto-Anchored) is a combination of liquidity and a sentiment profile, where the right side of the profile highlights the distribution of the traded activity at different price levels, and the left side of the profile highlights the market sentiment at those price levels
The liquidity profile is categorized by assigning different colors based on the significance of the traded activity of the specific price levels, allowing traders to reveal significant price levels, such as support and resistance levels, supply and demand zones, liquidity gaps, consolidation zones, etc
The Liquidity Sentiment Profiles aim to present Value Areas based on the significance of price levels, thus allowing users to identify value areas that can be formed more than once within the range of a single profile
Level of Significance Line - displays the changes in the price levels with the highest traded activity (developing POC)
Buyside & Sellside Liquidity Zones - displays Liquidity Levels, also known as Supply and Demand Zones
🔶 SETTINGS
The script takes into account user-defined parameters and plots the profiles, where detailed usage for each user-defined input parameter in indicator settings is provided with the related input's tooltip.
🔹 Liquidity Sentiment Profile
Anchor Period: The indicator resolution is set by the input of the Anchor Period.
Fixed Period: Applicable if the Anchor Period is set to 'Fixed Range' then the period of the profile is defined with this option
Swing Detection Length: Applicable if the Anchor Period is set to 'Swing High' or 'Swing Low' then the length required to detect the Swing Levels is defined with this option which is then used to determine the period of the profile
🔹 Liquidity Profile
Liquidity Profile: Toggles the visibility of the Liquidity Profiles
High Traded Nodes: Threshold and Color option for High Traded Nodes
Average Traded Nodes: Color option for Average Traded Nodes
Low Traded Nodes: Threshold and Color option for Low Traded Nodes
🔹 Sentiment Profile
Sentiment Profile: Toggles the visibility of the Sentiment Profiles
Bullish Nodes: Color option for Bullish Nodes
Bearish Nodes: Color option for Bearish Nodes
🔹 Buyside & Sellside Liquidity Zones
Buyside & Sellside Liquidity Zones: Toggles the visibility of the Liquidity Levels
Buyside Liquidity Nodes: Color option for Buyside Liquidity Nodes
Sellside Liquidity Nodes: Color option for Sellside Liquidity Nodes
🔹 Other Settings
Level of Significance: Toggles the visibility of the Level of Significance Line
Price Levels, Color: Toggles the visibility of the Profile Price Levels
Number of Rows: Specify how many rows each profile histogram will have. Caution, having it set to high values will quickly hit Pine Script™ drawing objects limit and fewer historical profiles will be displayed
Profile Width %: Alters the width of the rows in the histogram, relative to the profile length
Profile Range Background Fill: Toggles the visibility of the Profiles Range
🔶 RELATED SCRIPTS
Liquidity-Sentiment-Profile
Buyside-Sellside-Liquidity
ICT-Concepts
Candle Close AlertCandle Close Alert (CCA) :
The "Candle Close Alert" (CCA) is a custom technical analysis tool. It operates as an overlay on price charts and serves to detect and notify users about significant changes in consecutive candle closes. The script calculates the difference between the closing price of the current candle and the previous candle, referred to as the "close difference." It then compares this close difference against a user-specified threshold value.
When the close difference exceeds the threshold, the script triggers an alert, notifying users of a potential noteworthy event. This alert can serve as a prompt for traders and investors to investigate the current price action further or to consider possible trading decisions .
Additionally, the script enhances visualization by plotting the close differences on the price chart. Positive close differences exceeding the threshold are plotted in green, while negative close differences exceeding the threshold in magnitude are plotted in red. This color-coded visualization helps users quickly identify periods of significant price movement and potential market trends.
However, it's important to note that the CCA script is a standalone tool and should be used in conjunction with comprehensive market analysis. Trading decisions should not be solely based on the alerts and visualizations provided by this script. Instead, they should be considered within the broader context of other technical indicators, fundamental analysis, and risk management strategies. Enjoy it!
Liquidity Levels/Voids (VP) [LuxAlgo]The Liquidity Levels/Voids (VP) is a script designed to detect liquidity voids & levels by measuring traded volume at all price levels on the market between two swing points and highlighting the distribution of the liquidity voids & levels at specific price levels.
🔶 USAGE
Liquidity is a fundamental market force that shapes the trajectory of assets.
The creation of a liquidity level comes as a result of an initial imbalance of supply/demand, which forms what we know as a swing high or swing low. As more players take positions in the market, these are levels that market participants will use as a historical reference to place their stops. When the levels are then re-tested, a decision will be made. The binary outcome here can be a breakout of the level or a reversal back to the mean.
Liquidity voids are sudden price changes that occur in the market when the price jumps from one level to another with little trading activity (low volume), creating an imbalance in price. The price tends to fill or retest the liquidity voids area, and traders understand at which price level institutional players have been active.
Liquidity voids are a valuable concept in trading, as they provide insights about where many orders were injected, creating this inefficiency in the market. The price tends to restore the balance.
🔶 SETTINGS
The script takes into account user-defined parameters and detects the liquidity voids based on them, where detailed usage for each user-defined input parameter in indicator settings is provided with the related input's tooltip.
🔹 Liquidity Levels / Voids
Liquidity Levels/Voids: Color customization option for Unfilled Liquidity Levels/Voids.
Detection Length: Lookback period used for the calculation of Swing Levels.
Threshold %: Threshold used for the calculation of the Liquidity Levels & Voids.
Sensitivity: Adjusts the number of levels between two swing points, as a result, the height of a level is determined, and then based on the above-given threshold the level is checked if it matches the liquidity level/void conditions.
Filled Liquidity Levels/Voids: Toggles the visibility of the Filled Liquidity Levels/Voids and color customization option for Filled Liquidity Levels/Voids.
🔹 Other Features
Swing Highs/Lows: Toggles the visibility of the Swing Levels, where tooltips present statistical information, such as price, price change, and cumulative volume between the two swing levels detected based on the detection length specified above, Coloring options to customize swing low and swing high label colors, and Size option to adjust the size of the labels.
🔹 Display Options
Mode: Controls the lookback length of detection and visualization.
# Bars: Lookback length customization, in case Mode is set to Present.
🔶 RELATED SCRIPTS
Liquidity-Voids-FVG
Buyside-Sellside-Liquidity
Swing-Volume-Profiles
AI SuperTrend Clustering Oscillator [LuxAlgo]The AI SuperTrend Clustering Oscillator is an oscillator returning the most bullish/average/bearish centroids given by multiple instances of the difference between SuperTrend indicators.
This script is an extension of our previously posted SuperTrend AI indicator that makes use of k-means clustering. If you want to learn more about it see:
🔶 USAGE
The AI SuperTrend Clustering Oscillator is made of 3 distinct components, a bullish output (always the highest), a bearish output (always the lowest), and a "consensus" output always within the two others.
The general trend is given by the consensus output, with a value above 0 indicating an uptrend and under 0 indicating a downtrend. Using a higher minimum factor will weigh results toward longer-term trends, while lowering the maximum factor will weigh results toward shorter-term trends.
Strong trends are indicated when the bullish/bearish outputs are indicating an opposite sentiment. A strong bullish trend would for example be indicated when the bearish output is above 0, while a strong bearish trend would be indicated when the bullish output is below 0.
When the consensus output is indicating a specific trend direction, an opposite indication from the bullish/bearish output can highlight a potential reversal or retracement.
🔶 DETAILS
The indicator construction is based on finding three clusters from the difference between the closing price and various SuperTrend using different factors. The centroid of each cluster is then returned. This operation is done over all historical bars.
The highest cluster will be composed of the differences between the price and SuperTrends that are the highest, thus creating a more bullish group. The lowest cluster will be composed of the differences between the price and SuperTrends that are the lowest, thus creating a more bearish group.
The consensus cluster is composed of the differences between the price and SuperTrends that are not significant enough to be part of the other clusters.
🔶 SETTINGS
ATR Length: ATR period used for the calculation of the SuperTrends.
Factor Range: Determine the minimum and maximum factor values for the calculation of the SuperTrends.
Step: Increments of the factor range.
Smooth: Degree of smoothness of each output from the indicator.
🔹 Optimization
This group of settings affects the runtime performances of the script.
Maximum Iteration Steps: Maximum number of iterations allowed for finding centroids. Excessively low values can return a better script load time but poor clustering.
Historical Bars Calculation: Calculation window of the script (in bars).
SuperTrend AI (Clustering) [LuxAlgo]The SuperTrend AI indicator is a novel take on bridging the gap between the K-means clustering machine learning method & technical indicators. In this case, we apply K-Means clustering to the famous SuperTrend indicator.
🔶 USAGE
Users can interpret the SuperTrend AI trailing stop similarly to the regular SuperTrend indicator. Using higher minimum/maximum factors will return longer-term signals.
The displayed performance metrics displayed on each signal allow for a deeper interpretation of the indicator. Whereas higher values could indicate a higher potential for the market to be heading in the direction of the trend when compared to signals with lower values such as 1 or 0 potentially indicating retracements.
In the image above, we can notice more clear examples of the performance metrics on signals indicating trends, however, these performance metrics cannot perform or predict every signal reliably.
We can see in the image above that the trailing stop and its adaptive moving average can also act as support & resistance. Using higher values of the performance memory setting allows users to obtain a longer-term adaptive moving average of the returned trailing stop.
🔶 DETAILS
🔹 K-Means Clustering
When observing data points within a specific space, we can sometimes observe that some are closer to each other, forming groups, or "Clusters". At first sight, identifying those clusters and finding their associated data points can seem easy but doing so mathematically can be more challenging. This is where cluster analysis comes into play, where we seek to group data points into various clusters such that data points within one cluster are closer to each other. This is a common branch of AI/machine learning.
Various methods exist to find clusters within data, with the one used in this script being K-Means Clustering , a simple iterative unsupervised clustering method that finds a user-set amount of clusters.
A naive form of the K-Means algorithm would perform the following steps in order to find K clusters:
(1) Determine the amount (K) of clusters to detect.
(2) Initiate our K centroids (cluster centers) with random values.
(3) Loop over the data points, and determine which is the closest centroid from each data point, then associate that data point with the centroid.
(4) Update centroids by taking the average of the data points associated with a specific centroid.
Repeat steps 3 to 4 until convergence, that is until the centroids no longer change.
To explain how K-Means works graphically let's take the example of a one-dimensional dataset (which is the dimension used in our script) with two apparent clusters:
This is of course a simple scenario, as K will generally be higher, as well the amount of data points. Do note that this method can be very sensitive to the initialization of the centroids, this is why it is generally run multiple times, keeping the run returning the best centroids.
🔹 Adaptive SuperTrend Factor Using K-Means
The proposed indicator rationale is based on the following hypothesis:
Given multiple instances of an indicator using different settings, the optimal setting choice at time t is given by the best-performing instance with setting s(t) .
Performing the calculation of the indicator using the best setting at time t would return an indicator whose characteristics adapt based on its performance. However, what if the setting of the best-performing instance and second best-performing instance of the indicator have a high degree of disparity without a high difference in performance?
Even though this specific case is rare its however not uncommon to see that performance can be similar for a group of specific settings (this could be observed in a parameter optimization heatmap), then filtering out desirable settings to only use the best-performing one can seem too strict. We can as such reformulate our first hypothesis:
Given multiple instances of an indicator using different settings, an optimal setting choice at time t is given by the average of the best-performing instances with settings s(t) .
Finding this group of best-performing instances could be done using the previously described K-Means clustering method, assuming three groups of interest (K = 3) defined as worst performing, average performing, and best performing.
We first obtain an analog of performance P(t, factor) described as:
P(t, factor) = P(t-1, factor) + α * (∆C(t) × S(t-1, factor) - P(t-1, factor))
where 1 > α > 0, which is the performance memory determining the degree to which older inputs affect the current output. C(t) is the closing price, and S(t, factor) is the SuperTrend signal generating function with multiplicative factor factor .
We run this performance function for multiple factor settings and perform K-Means clustering on the multiple obtained performances to obtain the best-performing cluster. We initiate our centroids using quartiles of the obtained performances for faster centroids convergence.
The average of the factors associated with the best-performing cluster is then used to obtain the final factor setting, which is used to compute the final SuperTrend output.
Do note that we give the liberty for the user to get the final factor from the best, average, or worst cluster for experimental purposes.
🔶 SETTINGS
ATR Length: ATR period used for the calculation of the SuperTrends.
Factor Range: Determine the minimum and maximum factor values for the calculation of the SuperTrends.
Step: Increments of the factor range.
Performance Memory: Determine the degree to which older inputs affect the current output, with higher values returning longer-term performance measurements.
From Cluster: Determine which cluster is used to obtain the final factor.
🔹 Optimization
This group of settings affects the runtime performances of the script.
Maximum Iteration Steps: Maximum number of iterations allowed for finding centroids. Excessively low values can return a better script load time but poor clustering.
Historical Bars Calculation: Calculation window of the script (in bars).
