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! 😉
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Happy Trading! May your charts be green and your stops be far away!
Daveatt
指標和策略
HTFCandlesLibLibrary "HTFCandlesLib"
Library to get detailed higher timeframe candle information
method tostring(this, delimeter)
Returns OHLC values, BarIndex of higher and lower timeframe candles in string format
Namespace types: Candle
Parameters:
this (Candle) : Current Candle object
delimeter (string) : delimeter to join the string components of the candle
Returns: String representation of the Candle
method draw(this, bullishColor, bearishColor, printDescription)
Draws the current candle using boxes and lines for body and wicks
Namespace types: Candle
Parameters:
this (Candle) : Current Candle object
bullishColor (color) : color for bullish representation
bearishColor (color) : color for bearish representation
printDescription (bool) : if set to true prints the description
Returns: Current candle object
getCurrentCandle(ltfCandles)
Gets the current candle along with reassigned ltf components. To be used with request.security to capture higher timeframe candle data
Parameters:
ltfCandles (array) : Lower timeframe Candles array
Returns: Candle object with embedded lower timeframe key candles in them
Candle
Candle represents the data related to a candle
Fields:
o (series float) : Open price of the candle
h (series float) : High price of the candle
l (series float) : Low price of the candle
c (series float) : Close price of the candle
lo (Candle) : Lower timeframe candle that records the open price of the current candle.
lh (Candle) : Lower timeframe candle that records the high price of the current candle.
ll (Candle) : Lower timeframe candle that records the low price of the current candle.
lc (Candle) : Lower timeframe candle that records the close price of the current candle.
barindex (series int) : Bar Index of the candle
bartime (series int) : Bar time of the candle
last (Candle) : Link to last candle of the series if any
Ehlers Loops [BigBeluga]The Ehlers Loops indicator is based on the concepts developed by John F. Ehlers, which provide a visual representation of the relationship between price and volume dynamics. This tool helps traders predict future market movements by observing how price and volume data interact within four distinct quadrants of the loop, each representing different combinations of price and volume directions. The unique structure of this indicator provides insights into the strength and direction of market trends, offering a clearer perspective on price behavior relative to volume.
🔵 KEY FEATURES & USAGE
● Four Price-Volume Quadrants:
The Ehlers Loops chart consists of four quadrants:
+Price & +Volume (top-right) – Typically indicates a bullish continuation in the market.
-Price & +Volume (bottom-right) – Generally shows a bearish continuation.
+Price & -Volume (top-left) – Typically indicates an exhaustion of demand with a potential reversal.
-Price & -Volume (bottom-left) – Indicates exhaustion of supply and near trend reversal.
By watching how symbols move through these quadrants over time, traders can assess shifts in momentum and volume flow.
● Price and Volume Scaling in Standard Deviations:
Both price and volume data are individually filtered using HighPass and SuperSmoother filters, which transform them into band-limited signals with zero mean. This scaling allows traders to view data in terms of its deviation from the average, making it easier to spot abnormal movements or trends in both price and volume.
● Loops Trajectories with Tails:
The loops draw a trail of price and volume dynamics over time, allowing traders to observe historical price-volume interactions and predict future movements based on the curvature and direction of the rotation.
● Price & Volume Histograms:
On the right side of the chart, histograms for each symbol provide a summary of the most recent price and volume values. These histograms allow traders to easily compare the strength and direction of multiple assets and evaluate market conditions at a glance.
● Flexible Symbol Display & Customization:
Traders can select up to five different symbols to be displayed within the Ehlers Loops. The settings also allow customization of symbol size, colors, and visibility of the histograms. Additionally, traders can adjust the LPPeriod and HPPeriod to change the smoothness and lag of the loops, with a shorter LPPeriod offering more responsiveness and a longer HPPeriod emphasizing longer-term trends.
🔵 USAGE
🔵 SETTINGS
Low pass Period: default is 10 to
obtain minimum lag with just a little smoothing.
High pass Period: default is 125 (half of the year if Daily timeframe) to capture the longer term moves.
🔵 CONCLUSION
The Ehlers Loops indicator offers a visually rich and highly customizable way to observe price and volume dynamics across multiple assets. By using band-limited signals and scaling data into standard deviations, traders gain a powerful tool for identifying market trends and predicting future movements. Whether you're tracking short-term fluctuations or long-term trends, Ehlers Loops can help you stay ahead of the market by offering key insights into the relationship between price and volume.
Industry Group StrengthThe Industry Group Strength indicator is designed to help traders identify the best-performing stocks within specific industry groups. The movement of individual stocks is often closely tied to the overall performance of their industry. By focusing on industry groups, this indicator allows you to find the top-performing stocks within an industry.
Thanks to a recent Pine Script update, an indicator like this is now possible. Special thanks to @PineCoders for introducing the dynamic requests feature.
How this indicator works:
The indicator contains predefined lists of stocks for each industry group. To be included in these lists, stocks must meet the following basic filters:
Market capitalization over 2B
Price greater than $10
Primary listing status
Once the relevant stocks are filtered, the indicator automatically recognizes the industry group of the current stock displayed on the chart. It then retrieves and displays data for that entire industry group.
Data Points Available:
The user can choose between three different data points to rank and compare stocks:
YTD (Year-To-Date) Return: Measures how much a stock has gained or lost since the start of the year.
RS Rating: A relative strength rating for a user-selected lookback period (explained below).
% Return: The percentage return over a user-selected lookback period.
Stock Ranking:
Stocks are ranked based on their performance within their respective industry groups, allowing users to easily identify which stocks are leading or lagging behind others in the same sector.
Visualization:
The indicator presents stocks in a table format, with performance metrics displayed both as text labels and color-coded lines. The color gradient represents the percentile rank, making it visually clear which stocks are outperforming or underperforming within their industry group.
Relative Strength (RS):
Relative Strength (RS) measures a stock’s performance relative to a benchmark, typically the S&P 500 (the default setting). It is calculated by dividing the closing price of the stock by the closing price of the S&P 500.
If the stock rises while the S&P 500 falls, or if the stock rises more sharply than the S&P 500, the RS value increases. Conversely, if the stock falls while the S&P 500 rises, the RS value decreases. This indicator normalizes the RS value into a range from 1 to 99, allowing for easier comparison across different stocks, regardless of their raw performance. This normalized RS value helps traders quickly assess how a stock is performing relative to others.
Periodic Linear Regressions [LuxAlgo]The Periodic Linear Regressions (PLR) indicator calculates linear regressions periodically (similar to the VWAP indicator) based on a user-set period (anchor).
This allows for estimating underlying trends in the price, as well as providing potential supports/resistances.
🔶 USAGE
The Periodic Linear Regressions indicator calculates a linear regression over a user-selected interval determined from the selected "Anchor Period".
The PLR can be visualized as a regular linear regression (Static), with a fit readjusting for new data points until the end of the selected period, or as a moving average (Rolling), with new values obtained from the last point of a linear regression fitted over the calculation interval. While the static method line is prone to repainting, it has value since it can further emphasize the linearity of an underlying trend, as well as suggest future trend directions by extrapolating the fit.
Extremities are included in the indicator, these are obtained from the root mean squared error (RMSE) between the price and calculated linear regression. The Multiple setting allows the users to control how far each extremity is from the other.
Periodic Linear Regressions can be helpful in finding support/resistance areas or even opportunities when ranging in a channel.
The anchor - where a new period starts - can be shown (in this case in the top right corner).
The shown bands can be visualized by enabling Show Extremities in settings ( Rolling or Static method).
The script includes a background gradient color option for the bands, which only applies when using the Rolling method.
The indicator colors can be suggestive of the detected trend and are determined as follows:
Method Rolling: a gradient color between red and green indicates the trend; more green if the output is rising, suggesting an uptrend, and more red if it is decreasing, suggesting a downtrend.
Method Static: green if the slope of the line is positive, suggesting an uptrend, red if negative, suggesting a downtrend.
🔶 DETAILS
🔹 Anchor Type
When the Anchor Type is set to Periodic , the indicator will be reset when the "Anchor Period" changes, after which calculations will start again.
An anchored rolling line set at First Bar won't reset at a new session; it will continue calculating the linear regression from the first bar to the last; in other words, every bar is included in the calculation. This can be useful to detect potential long-term tops/bottoms.
Note that a linear regression needs at least two values for its calculation, which explains why you won't see a static line at the first bar of the session. The rolling linear regression will only show from the 3rd bar of the session since it also needs a previous value.
🔹 Rolling/Static
When Anchor Type is set at Periodic , a linear regression is calculated between the first bar of the chosen session and the current bar, aiming to find the line that best fits the dataset.
The example above shows the lines drawn during the session. The offered script, though, shows the last calculated point connected to the previous point when the Rolling method is chosen, while the Static method shows the latest line.
Note that linear regression needs at least two values, which explains why you won't see a static line at the first bar of the session. The rolling line will only show from the 3rd bar of the session since it also needs a previous value.
🔶 SETTINGS
Method: Indicator method used, with options: "Static" (straight line) / "Rolling" (rolling linear regression).
Anchor Type: "Periodic / First Bar" (the latter works only when "Method" is set to "Rolling").
Anchor Period: Only applicable when "Anchor Type" is set at "Periodic".
Source: open, high, low, close, ...
Multiple: Alters the width of the bands when "Show Extremities" is enabled.
Show Extremities: Display one upper and one lower extremity.
🔹 Color Settings
Mono Color: color when "Bicolor" is disabled
Bicolor: Toggle on/off + Colors
Gradient: Background color when "Show extremities" is enabled + level of gradient
🔹 Dashboard
Show Dashboard
Location of dashboard
Text size
Custom Pattern DetectionOverview
Chart Patterns is a major tool for many traders. Pattern formation at specific location on the chart is used for investment/trading decisions.
This indicator is designed in a way to allow investors/traders to define patterns of their choice based on certain input parameters and then detect defined pattern on the chart.
Investors/traders can use their own creativity to create and detect patterns.
This indicator works in 2 modes
Create Pattern: One can define a pattern and verify sample pattern formation visually
Detect Pattern: Detect and mark patterns on the chart
Settings
Create Custom Pattern:
Show Custom Pattern – This will mark the pattern lines on the chart so that one can verify how pattern appears based on the input’s parameters provided for lines XA, AB, BC, CD, DE, EF
Offset – Used while pattern creation. Offset is horizonal distance between 2 lines.
XA Points – Used to draw XA line when sample pattern is drawn. XA points can be a negative or position number.
XA line is drawn based on Offset and XA Points. E.g. Offset = 5 and XA Points = -20. In this line would be drawn from last candle high to high – 20 (these are y1 and y2 points of a line). While drawing line distance of 5 candles would be placed between 2 line points (these are x1 and x2 points of a line). In XA line X forms start point and A forms end point of the line.
Line AB – Line AB is drawn from point X. To derive the end point of AB, average Fib% is derived based on From Fib% and To Fib% parameters. Finally end point is derived by applying Fib Retracement on Line XA based on average Fib%.
Line AB to Line EF – These points are derived as explained in Line AB.
The indicator can be used to define/create patterns up to 6 legs/lines. The line would be named as XA -> AB -> BC -> CD -> DE -> EF.
If one wish to create pattern consisting 3 legs then it can be achieved by unchecking/deselecting Line CD, DE and EF or by checking only Line AB and BC.
Based on the parameters above indicator draws a sample pattern after last candle/bar on the chart. Sample pattern helps to visually see how pattern will appear on the chart.
Pattern Identification
Indicator derive the swing high/low points based on the Pivot lookback and use as reference points while detecting patterns.
Use of From Fib% and To Fib% - While detecting pattern, retracement price points are derived for From Fib% and To Fib%. Price points between from Fib% and To Fib% are treated as valid retracement points.
How to configure and use indicator for detecting patterns
Sample Pattern 1
Sample Pattern 2
Sample Pattern 3
Sample Pattern 4
Volume Analysis - Heatmap and Volume ProfileHello All!
I have a new toy for you! Volume Analysis - Heatmap and Volume Profile . Honestly I started to work to develop Volume Heatmap then I decided to improve it and add more features such Volume profile, volume, difference in Buy/Sell volumes etc. I tried to put my abilities into this script and tried to use some new Pine Language™ features ( method, force_overlay, enum etc features ). I hope the usage of these new features would be an example for Pine Programmers.
Lets talk about how it works:
- It gets number of Rows/Columns from the user for each candle to create heatmap
- It calculates the number of the candles to analyze. Number of the candles may change by number of Rows/columns or if any volume / difference in volumes / volume profile is enabled
- It gets Closing/Opening price, Volume and Time info from lower time frame for each candle ( it can be up to 100K for each candle )
- After getting the data it calculates lower time frame to analyze
- Then it calculates how closing price moves, how much volume on each move and create boxes by the volume/move in each box
- The colors for each box calculated by volume info and closing price movements in the lower time frame
- It shows the boxes on Absolute places or Zero Line optionally
- it shows Volume, Cumulative volume, Difference between Buy/Sell volume for each column
- it changes empty box color by Chart background color, also you can change transparency
- At this time it creates Volume Profile with up to 25 rows
- As a new Pine Language™ feature, it can show Volume Profile in the indicator window or in Main chart, shows Value Area, Value Area High (VAH), Value Area Low (VAL), and draw it and POC (Point Of Control) in the indicator window and/or in the main chart
- Honestly the feature I like is that: For the markets that are not open 24/7, it combines the data from the lower time period without any gaps. For example, if you work for a market that is closed on Saturdays and Sundays, it ensures data integrity by omitting weekends and holidays. so for example if the data is like "ABC---DEF-X---YL-Z" then it makes this data like "ABCDEFXYLZ". In this way, there will be no data breaks in the displayed boxes, there will be no empty colons, and it will appear as if data is coming in at any time.
- Finally it shows Info Panel to give info, its background color automatically changes by the Chart background color
- Important! You should set your "Plan" accordingly, your plan is "Premium or Higher" or "Lower tier". so the script can understand the minimum time frame it can get data!!
I tried to share many screenshots below to explain it much better
How it looks?
it shows Highest Buy/Sell volumes brighter, move volume -> brighter
Volume Profile ( up to 25 row s) ( number of contained candles should be more than 1 )
Volume Profile can be shown in the main chart optionally
How the main chart looks:
Closing price shown and you can enable it, change colors & line width
Can include many candles according to Row&Column number you set
Optionally it can show cumulative volume for each candle
Closing prices from lower time frame
Shows Candle Body by changing background colors
It can shows all included candles on Zero line
You can change the colors of many things
You can set Empty box and border transparency
Table, Empty box Colors adjustment done automatically by chart background color
Sometimes we can not get data from some historical candles if time frame is high such 2days, 1 week etc, and it looks like:
It also checks if Chart time frame and Chart type is suitable
Enjoy!
Solar System in 3D [Astro Tool w/ Zodiac]Hello Traders and Developers,
I am excited to announce my latest Open Source indicator. At the core, this is a demonstration of PineScript’s capabilities in Rendering 3D Animations, while at the same time being a practical tool for Financial Astrologists.
This 3D Engine dynamically renders all the major celestial bodies with their individual orbits, rotation speeds, polar inclinations and astrological aspects, all while maintaining accurate spatial relationships and perspective.
This is a Geocentric model of the solar system (viewed from the perspective of Earth), since that is what most Astrologists use. Thanks to the AstroLib Library created by @BarefootJoey, this model uses the real coordinates of cosmic bodies for every timestamp.
This script truly comes to life when using the “Bar Replay” mode in TradingView, as you can observe the relationships between planets and price action as time progresses, with the full animation capabilities as mentioned above.
In addition to what I have described, this indicator also displays the orbital trajectories for each cosmic body, and has labels for everything. I have also added the ability to hover on all the labels, and see a short description of what they imply in Astrology.
Optional Planetary Aspect Computation
This indicator supports all the Major Planetary Aspects, with an accuracy defined by the user (1° by default).
Conjunction: 0° Alignment. This draws a RED line starting from the center, and going through both planets.
Sextile: 60° Alignment. This draws three YELLOW lines, connecting the planets to each other and to the center.
Square: 90° Alignment. This draws three BLUE lines, connecting the planets to each other and to the center.
Trine: 120° Alignment. This draws three PURPLE lines, connecting the planets to each other and to the center.
Opposition: 180° Alignment. This draws a GREEN line starting from one planet, passing through the center and ending on the second planet.
The below image depicts a Top-Down view of the system, with the Moon in Opposition to Venus and with Mars in Square with Neptune .
Retrograde Computation
This indicator also displays when a planet enters Retrograde (Apparent Backward Motion) by making its orbital trajectory dashed and the planet name getting a red background.
The image below displays an example of Jupiter, Saturn, Neptune and Pluto in Retrograde Motion, from the camera perspective of a 65 degree inclination.
Optional Zodiac Computation (Tropical and Sidereal)
Zodiac represents the relatively stationary star formations that rest along the ecliptic plane, with planets transitioning from one to the next, each with a 30° separation (making 12 in total). I have implemented the option to switch between Tropical mode (where these stars were 2,000 years ago) and Sidereal (where these stars are today).
The image below displays the Zodiac labels with clear lines denoting where each planet falls into.
While this indicator is deployed in a separate pane, it is trivial to transfer it onto your price chart, just by clicking and dragging the graphics. After that, you can adjust the visuals by dragging the scale on the side, or optimizing model settings. You can also drag the model above or below the price, as shown in the following image:
Of course, there are a lot of options to customize this planetary model to your tastes and analytical needs. Aside from visual changes for the labels, colors or resolution you can also disable certain planets that don’t meet your needs as shown below:
Once can also infer the current lunar phases using the Aspects between the Sun and Moon. When the Moon is Opposite the Sun that is a Full Moon, while when they are Conjunct that is a New Moon (and sometimes Eclipse).
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I have made this indicator open source to help PineScript programmers understand how to approach 3D graphics rendering, enabling them to develop ever more capable scripts and continuously push the boundaries of what's possible on TradingView.
The code is well documented with comments and has a clear naming convention for functions and variables, to aid developers understand how everything operates.
For financial astrologists, this indicator offers a new way to visualize and correlate planetary movements, adding depth and ease to astrological market analysis.
Regards,
Hawk
Machine Learning Adaptive SuperTrend [AlgoAlpha]📈🤖 Machine Learning Adaptive SuperTrend - Take Your Trading to the Next Level! 🚀✨
Introducing the Machine Learning Adaptive SuperTrend , an advanced trading indicator designed to adapt to market volatility dynamically using machine learning techniques. This indicator employs k-means clustering to categorize market volatility into high, medium, and low levels, enhancing the traditional SuperTrend strategy. Perfect for traders who want an edge in identifying trend shifts and market conditions.
What is K-Means Clustering and How It Works
K-means clustering is a machine learning algorithm that partitions data into distinct groups based on similarity. In this indicator, the algorithm analyzes ATR (Average True Range) values to classify volatility into three clusters: high, medium, and low. The algorithm iterates to optimize the centroids of these clusters, ensuring accurate volatility classification.
Key Features
🎨 Customizable Appearance: Adjust colors for bullish and bearish trends.
🔧 Flexible Settings: Configure ATR length, SuperTrend factor, and initial volatility guesses.
📊 Volatility Classification: Uses k-means clustering to adapt to market conditions.
📈 Dynamic SuperTrend Calculation: Applies the classified volatility level to the SuperTrend calculation.
🔔 Alerts: Set alerts for trend shifts and volatility changes.
📋 Data Table Display: View cluster details and current volatility on the chart.
Quick Guide to Using the Machine Learning Adaptive SuperTrend Indicator
🛠 Add the Indicator: Add the indicator to favorites by pressing the star icon. Customize settings like ATR length, SuperTrend factor, and volatility percentiles to fit your trading style.
📊 Market Analysis: Observe the color changes and SuperTrend line for trend reversals. Use the data table to monitor volatility clusters.
🔔 Alerts: Enable notifications for trend shifts and volatility changes to seize trading opportunities without constant chart monitoring.
How It Works
The indicator begins by calculating the ATR values over a specified training period to assess market volatility. Initial guesses for high, medium, and low volatility percentiles are inputted. The k-means clustering algorithm then iterates to classify the ATR values into three clusters. This classification helps in determining the appropriate volatility level to apply to the SuperTrend calculation. As the market evolves, the indicator dynamically adjusts, providing real-time trend and volatility insights. The indicator also incorporates a data table displaying cluster centroids, sizes, and the current volatility level, aiding traders in making informed decisions.
Add the Machine Learning Adaptive SuperTrend to your TradingView charts today and experience a smarter way to trade! 🌟📊
D-Shape Breakout Signals [LuxAlgo]The D-Shape Breakout Signals indicator uses a unique and novel technique to provide support/resistance curves, a trailing stop loss line, and visual breakout signals from semi-circular shapes.
🔶 USAGE
D-shape is a new concept where the distance between two Swing points is used to create a semi-circle/arc, where the width is expressed as a user-defined percentage of the radius. The resulting arc can be used as a potential support/resistance as well as a source of breakouts.
Users can adjust this percentage (width of the D-shape) in the settings ( "D-Width" ), which will influence breakouts and the Stop-Loss line.
🔹 Breakouts of D-Shape
The arc of this D-shape is used for detecting breakout signals between the price and the curve. Only one breakout per D-shape can occur.
A breakout is highlighted with a colored dot, signifying its location, with a green dot being used when the top part of the arc is exceeded, and red when the bottom part of the arc is surpassed.
When the price reaches the right side of the arc without breaking the arc top/bottom, a blue-colored dot is highlighted, signaling a "Neutral Breakout".
🔹 Trailing Stop-Loss Line
The script includes a Trailing Stop-Loss line (TSL), which is only updated when a breakout of the D-Shape occurs. The TSL will return the midline of the D-Shape subject to a breakout.
The TSL can be used as a stop-loss or entry-level but can also act as a potential support/resistance level or trend visualization.
🔶 DETAILS
A D-shape will initially be colored green when a Swing Low is followed by a Swing High, and red when a Swing Low is followed by a Swing High.
A breakout of the upper side of the D-shape will always update the color to green or to red when the breakout occurs in the lower part. A Neutral Breakout will result in a blue-colored D-shape. The transparency is lowered in the event of a breakout.
In the event of a D-shape breakout, the shape will be removed when the total number of visible D-Shapes exceeds the user set "Minimum Patterns" setting. Any D-shape whose boundaries have not been exceeded (and therefore still active) will remain visible.
🔹 Trailing Stop-Loss Line
Only when a breakout occurs will the midline of the D-shape closest to the closing price potentially become the new Trailing Stop value.
The script will only consider middle lines below the closing price on an upward breakout or middle lines above the closing price when it concerns a downward breakout.
In an uptrend, with an already available green TSL, the potential new Stop-Loss value must be higher than the previous TSL value; while in a downtrend, the new TSL value must be lower.
The Stop-Loss line won't be updated when a "Neutral Breakout" occurs.
🔶 SETTINGS
Swing Length: Period used for the swing detection, with higher values returning longer-term Swing Levels.
🔹 D-Patterns
Minimum Patterns: Minimum amount of visible D-Shape patterns.
D-Width: Width of the D-Shape as a percentage of the distance between both Swing Points.
Included Swings: Include "Swing High" (followed by a Swing Low), "Swing Low" (followed by a Swing High), or "Both"
Style Historical Patterns: Show the "Arc", "Midline" or "Both" of historical patterns.
🔹 Style
Label Size/Colors
Connecting Swing Level: Shows a line connecting the first Swing Point.
Color Fill: colorfill of Trailing Stop-Loss
Monte Carlo (Polyline Traceback) [Kioseff Trading]Hello!
This script "Monte Carlo (Polyline Traceback) " performs a Monte Carlo simulation using polylines!
By using polylines, and tracing back the initial simulation to its origin point, we can better replicate the ideal output of a Monte Carlo simulation!
Such as:
The image above shows the output of a simulation (image sourced outside TV).
With this script, and polyline capabilities, we can come quite close on TradingView.
The image above shows the indicator in action! Not bad considering the ideal output.
Of course, the script is quite heavy and tries its best to circumvent limitations :D
You might run into load time errors, in which case you might try applying the built-in setting "Force Script Load". This setting will cut-off the visuals for some simulations, but has a higher chance of passing load-time limitations!
As shown in the image above, you can select to only show worst-case and best-case simulations. Using this option will reduce chart lag and improve load times.
Features
Monte Carlo Simulation: Performs Monte Carlo simulation to generate multiple future paths.
Asset Price: Can simulate future asset prices based on historical log returns.
Statistical Methods: Offers two simulation methods—Gaussian (Normal) distribution and Bootstrapping.
Adjustable Parameters: Offers numerous user-adjustable settings like number of simulations, forecast length, and more.
Historical Data Points: Option to specify the amount of historical data to be used in the simulation (price).
Best/Worst Case: Allows you to show only the best case / worst case outcome (range) for all simulations!
Thank you!
LOWESS (Locally Weighted Scatterplot Smoothing) [ChartPrime]LOWESS (Locally Weighted Scatterplot Smoothing)
⯁ OVERVIEW
The LOWESS (Locally Weighted Scatterplot Smoothing) [ ChartPrime ] indicator is an advanced technical analysis tool that combines LOWESS smoothing with a Modified Adaptive Gaussian Moving Average. This indicator provides traders with a sophisticated method for trend analysis, pivot point identification, and breakout detection.
◆ KEY FEATURES
LOWESS Smoothing: Implements Locally Weighted Scatterplot Smoothing for trend analysis.
Modified Adaptive Gaussian Moving Average: Incorporates a volatility-adapted Gaussian MA for enhanced trend detection.
Pivot Point Identification: Detects and visualizes significant pivot highs and lows.
Breakout Detection: Tracks and optionally displays the count of consecutive breakouts.
Gaussian Scatterplot: Offers a unique visualization of price movements using randomly colored points.
Customizable Parameters: Allows users to adjust calculation length, pivot detection, and visualization options.
◆ FUNCTIONALITY DETAILS
⬥ LOWESS Calculation:
Utilizes a weighted local regression to smooth price data.
Adapts to local trends, reducing noise while preserving important price movements.
⬥ Modified Adaptive Gaussian Moving Average:
Combines Gaussian weighting with volatility adaptation using ATR and standard deviation.
Smooths the Gaussian MA using LOWESS for enhanced trend visualization.
⬥ Pivot Point Detection and Visualization:
Identifies pivot highs and lows using customizable left and right bar counts.
Draws lines and labels to mark broke pivot points on the chart.
⬥ Breakout Tracking:
Monitors price crossovers of pivot lines to detect breakouts.
Optionally displays and updates the count of consecutive breakouts.
◆ USAGE
Trend Analysis: Use the color and direction of the smoothed Gaussian MA line to identify overall trend direction.
Breakout Trading: Monitor breakouts from pivot levels and their persistence using the breakout count feature.
Volatility Assessment: The spread of the Gaussian scatterplot can provide insights into market volatility.
⯁ USER INPUTS
Length: Sets the lookback period for LOWESS and Gaussian MA calculations (default: 30).
Pivot Length: Determines the number of bars to the left for pivot calculation (default: 5).
Count Breaks: Toggle to show the count of consecutive breakouts (default: false).
Gaussian Scatterplot: Toggle to display the Gaussian MA as a scatterplot (default: true).
⯁ TECHNICAL NOTES
Implements a custom LOWESS function for efficient local regression smoothing.
Uses a modified Gaussian MA calculation that adapts to market volatility.
Employs Pine Script's line and label drawing capabilities for clear pivot point visualization.
Utilizes random color generation for the Gaussian scatterplot to enhance visual distinction between different time periods.
The LOWESS (Locally Weighted Scatterplot Smoothing) indicator offers traders a sophisticated tool for trend analysis and breakout detection. By combining advanced smoothing techniques with pivot point analysis, it provides a comprehensive view of market dynamics. The indicator's adaptability to different market conditions and its customizable nature make it suitable for various trading styles and timeframes.
Adaptive Trend Finder (log)In the dynamic landscape of financial markets, the Adaptive Trend Finder (log) stands out as an example of precision and professionalism. This advanced tool, equipped with a unique feature, offers traders a sophisticated approach to market trend analysis: the choice between automatic detection of the long-term or short-term trend channel.
Key Features:
1. Choice Between Long-Term or Short-Term Trend Channel Detection: Positioned first, this distinctive feature of the Adaptive Trend Finder (log) allows traders to customize their analysis by choosing between the automatic detection of the long-term or short-term trend channel. This increased flexibility adapts to individual trading preferences and changing market conditions.
2. Autonomous Trend Channel Detection: Leveraging the robust statistical measure of the Pearson coefficient, the Adaptive Trend Finder (log) excels in autonomously locating the optimal trend channel. This data-driven approach ensures objective trend analysis, reducing subjective biases, and enhancing overall precision.
3. Precision of Logarithmic Scale: A distinctive characteristic of our indicator is its strategic use of the logarithmic scale for regression channels. This approach enables nuanced analysis of linear regression channels, capturing the subtleties of trends while accommodating variations in the amplitude of price movements.
4. Length and Strength Visualization: Traders gain a comprehensive view of the selected trend channel, with the revelation of its length and quantification of trend strength. These dual pieces of information empower traders to make informed decisions, providing insights into both the direction and intensity of the prevailing trend.
In the demanding universe of financial markets, the Adaptive Trend Finder (log) asserts itself as an essential tool for traders, offering an unparalleled combination of precision, professionalism, and customization. Highlighting the choice between automatic detection of the long-term or short-term trend channel in the first position, this indicator uniquely caters to the specific needs of each trader, ensuring informed decision-making in an ever-evolving financial environment.
Oscillator Scatterplot Analysis [Trendoscope®]In this indicator, we demonstrate how to plot oscillator behavior of oversold-overbought against price movements in the form of scatterplots and perform analysis. Scatterplots are drawn on a graph containing x and y-axis, where x represent one measure whereas y represents another. We use the library Graph to collect the data and plot it as scatterplot.
Pictorial explanation of components is defined in the chart below.
🎲 This indicator performs following tasks
Calculate and plot oscillator
Identify oversold and overbought areas based on various methods
Measure the price and bar movement from overbought to oversold and vice versa and plot them on the chart.
In our example,
The x-axis represents price movement. The plots found on the right side of the graph has positive price movements, whereas the plots found on the left side of the graph has negative price movements.
The y-axis represents the number of bars it took for reaching overbought to oversold and/or oversold to overbought. Positive bars mean we are measuring oversold to overbought, whereas negative bars are a measure of overbought to oversold.
🎲 Graph is divided into 4 equal quadrants
Quadrant 1 is the top right portion of the graph. Plots in this quadrant represent the instances where positive price movement is observed when the oscillator moved from oversold to overbought
Quadrant 2 is the top left portion of the graph. Plots in this quadrant represent the instances where negative price movement is observed when the oscillator moved from oversold to overbought.
Quadrant 3 is the bottom left portion of the chart. Plots in this quadrant represent the instances where negative price movement is observed when the oscillator moved from overbought to oversold.
Quadrant 4 is the bottom right portion of the chart. Plots in this quadrant represent the instances where positive price movement is observed when the oscillator moved from overbought to oversold.
🎲 Indicator components in Detail
Let's dive deep into the indicator.
🎯 Oscillator Selection
Select the Oscillator and define the overbought oversold conditions through input settings
Indicator - Oscillator base used for performing analysis
Length - Loopback length on which the oscillator is calculated
OB/OS Method - We use Bollinger Bands, Keltener Channel and Donchian channel to calculate dynamic overbought and oversold levels instead of static 80-10. This is also useful as other type of indicators may not be within 0-100 range.
Length and Multiplier are used for the bands for calculating Overbought/Oversold boundaries.
🎯 Define Graph Properties
Select different graph properties from the input settings that will instruct how to display the scatterplot.
Type - this can be either scatterplot or heatmap. Scatterplot will display plots with specific transparency to indicate the data, whereas heatmap will display background with different transparencies.
Plot Color - this is the color in which the scatterplot or heatmap is drawn
Plot Size - applicable mainly for scatterplot. Since the character we use for scatterplot is very tiny, the large at present looks optimal. But, based on the user's screen size, we may need to select different sizes so that it will render properly.
Rows and Columns - Number of rows and columns allocated per quadrant. This means, the total size of the chart is 2X rows and 2X columns. Data sets are divided into buckets based on the number of available rows and columns. Hence, changing this can change the appearance of the overall chart, even though they are representing the same data. Also, please note that tables can have max 10000 cells. If we increase the rows and columns by too much, we may get runtime errors.
Outliers - this is used to exclude the extreme data. 20% outlier means, the chart will ignore bottom 20% and top 20% when defining the chart boundaries. However, the extreme data is still added to the boundaries.
[Pandora] Vast Volatility Treasure TroveINTRODUCTION:
Volatility enthusiasts, prepare for VICTORY on this day of July 4th, 2024! This is my "Vast Volatility Treasure Trove," intended mostly for educational purposes, yet these functions will also exhibit versatility when combined with other algorithms to garner statistical excellence. Once again, I am now ripping the lid off of Pandora's box... of volatility. Inside this script is a 'vast' collection of volatility estimators, reflecting the indicators name. Whether you are a seasoned trader destined to navigate financial strife or an eagerly curious learner, this script offers a comprehensive toolkit for a broad spectrum of volatility analysis. Enjoy your journey through the realm of market volatility with this code!
WHAT IS MARKET VOLATILITY?:
Market volatility refers to various fluctuations in the value of a financial market or asset over a period of time, often characterized by occasional rapid and significant deviations in price. During periods of greater market volatility, evolving conditions of prices can move rapidly in either direction, creating uncertainty for investors with results of sharp declines as well as rapid gains. However, market volatility is a typical aspect expected in financial markets that can also present opportunities for informed decision-making and potential benefits from the price flux.
SCRIPT INTENTION:
Volatility is assuredly omnipresent, waxing and waning in magnitude, and some readers have every intention of studying and/or measuring it. This script serves as an all-in-one armada of volatility estimators for TradingView members. I set out to provide a diverse set of tools to analyze and interpret market volatility, offering volatile insights, and aid with the development of robust trading indicators and strategies.
In today's fast-paced financial markets, understanding and quantifying volatility is informative for both seasoned traders and novice investors. This script is designed to empower users by equipping them with a comprehensive suite of volatility estimators. Each function within this script has been meticulously crafted to address various aspects of volatility, from traditional methods like Garman-Klass and Parkinson to more advanced techniques like Yang-Zhang and my custom experimental algorithms.
Ultimately, this script is more than just a collection of functions. It is a gateway to a deeper understanding of market volatility and a valuable resource for anyone committed to mastering the complexities of financial markets.
SCRIPT CONTENTS:
This script includes a variety of functions designed to measure and analyze market volatility. Where applicable, an input checkbox option provides an unbiased/biased estimate. Below is a brief description of each function in the original order they appear as code upon first publish:
Parkinson Volatility - Estimates volatility emphasizing the high and low range movements.
Alternate Parkinson Volatility - Simpler version of the original Parkinson Volatility that I realized.
Garman-Klass Volatility - Estimates volatility based on high, low, open, and close prices using a formula that adjusts for biases in price dynamics.
Rogers-Satchell-Yoon Volatility #1 - Estimates volatility based on logarithmic differences between high, low, open, and close values.
Rogers-Satchell-Yoon Volatility #2 - Similar estimate to Rogers-Satchell with the same result via an alternate formulation of volatility.
Yang-Zhang Volatility - An advanced volatility estimate combining both strengths of the Garman-Klass and Rogers-Satchell estimators, with weights determined by an alpha parameter.
Yang-Zhang (Modified) Volatility - My experimental modification slightly different from the Yang-Zhang formula with improved computational efficiency.
Selectable Volatility - Basic customizable volatility calculation based on the logarithmic difference between selected numerator and denominator prices (e.g., open, high, low, close).
Close-to-Close Volatility - Estimates volatility using the logarithmic difference between consecutive closing prices. Specifically applicable to data sources without open, high, and low prices.
Open-to-Close Volatility - (Overnight Volatility): Estimates volatility based on the logarithmic difference between the opening price and the last closing price emphasizing overnight gaps.
Hilo Volatility - Estimates volatility using a method similar to Parkinson's method, which considers the logarithm of the high and low prices.
Vantage Volatility - My experimental custom 'vantage' method to estimate volatility similar to Yang-Zhang, which incorporates various factors (Alpha, Beta, Gamma) to generate a weighted logarithmic calculation. This may be a volatility advantage or disadvantage, hence it's name.
Schwert Volatility - Estimates volatility based on arithmetic returns.
Historical Volatility - Estimates volatility considering logarithmic returns.
Annualized Historical Volatility - Estimates annualized volatility using logarithmic returns, adjusted for the number of trading days in a year.
If I omitted any other known varieties, detailed requests for future consideration can be made below for their inclusion into this script within future versions...
BONUS ALGORITHMS:
This script also includes several experimental and bonus functions that push the boundaries of volatility analysis as I understand it. These functions are designed to provide additional insights and also are my ideal notions for traders looking to explore other methods of volatility measurement.
VOLATILITY APPLICATIONS:
Volatility estimators serve a common role across various facets of trading and financial analysis, offering insights into market behavior. These tools are already in instrumental with enhancing risk management practices by providing a deeper understanding of market dynamics and the inherent uncertainty in asset prices. With volatility estimators, traders can effectively quantifying market risk and adjust their strategies accordingly, optimizing portfolio performance and mitigating potential losses. Additionally, volatility estimations may serve as indication for detecting overbought or oversold market conditions, offering probabilistic insights that could inform strategic decisions at turning points. This script
distinctly offers a variety of volatility estimators to navigate intricate financial terrains with informed judgment to address challenges of strategic planning.
CODE REUSE:
You don't have to ask for my permission to use/reuse these functions in your published scripts, simply because I have better things to do than answer requests for the reuse of these functions.
Notice: Unfortunately, I will not provide any integration support into member's projects at all. I have my own projects that require way too much of my day already.
Linear Regression Oscillator [ChartPrime]Linear Regression Oscillator Indicator
Overview:
The Linear Regression Oscillator is a custom TradingView indicator designed to provide insights into potential mean reversion and trend conditions. By calculating a linear regression on the closing prices over a user-defined period, this oscillator helps identify overbought and oversold levels and highlights trend changes. The indicator also offers visual cues and color-coded price bars to aid in quick decision-making.
Key Features:
◆ Customizable Look-Back Period:
Input: Length
Default: 20
Description: Determines the period over which the linear regression is calculated. A longer period smooths the oscillator but may lag, while a shorter period is more responsive but may be noisier.
◆ Overbought and Oversold Thresholds:
Inputs: Upper Threshold and Lower Threshold
Default: 1.5 and -1.5 respectively
Description: Define the upper and lower bounds for identifying overbought and oversold conditions. Values outside these thresholds suggest potential reversals.
◆ Candlestick Color Plotting:
Input: Plot Bar Color
Default: false
Description: Option to color the price bars based on the oscillator's value, providing a visual representation of market conditions. Bars turn cyan for positive oscillator values and blue for negative.
◆ Mean Reversion and Trend Signals:
Visual markers and labels indicate when the oscillator suggests mean reversion or trend changes, aiding in identifying key market turning points.
◆ Invalidation Levels:
Tracks the highest and lowest prices over a recent period to set levels where the current trend signal would be considered invalidated.
◆ Gradient Color Coding:
Utilizes gradient color coding to enhance the visualization of oscillator values, making it easier to interpret overbought and oversold conditions.
◆ Usage Notes:
Setting the Look-Back Period:
Adjust the "Length" input based on the timeframe and the type of trading you are conducting. Shorter periods are more suited for intraday trading, while longer periods can be used for swing trading.
Interpreting Thresholds:
Use the upper and lower threshold inputs to fine-tune the sensitivity of the overbought and oversold signals. Higher absolute values reduce the number of signals but increase their reliability.
Candlestick Coloring:
Enabling the "Plot Bar Color" option can help quickly identify the current state of the oscillator in relation to the zero line. This visual aid can be particularly useful in fast-moving markets.
Mean Reversion and Trend Signals:
Pay attention to the symbols and labels on the chart indicating mean reversion and trend changes. These signals are designed to highlight potential entry and exit points.
Invalidation Levels:
Use the plotted invalidation levels as stop-loss or signal invalidation points. If the price moves beyond these levels, the current trend signal is likely invalid.
This indicator helps traders identify overbought and oversold conditions, potential mean reversions, and trend changes based on the linear regression of the closing prices over a specified look-back period.
Sharpe and Sortino Ratios█ OVERVIEW
This indicator calculates the Sharpe and Sortino ratios using a chart symbol's periodic price returns, offering insights into the symbol's risk-adjusted performance. It features the option to calculate these ratios by comparing the periodic returns to a fixed annual rate of return or the returns from another selected symbol's context.
█ CONCEPTS
Returns, risk, and volatility
The return on an investment is the relative gain or loss over a period, often expressed as a percentage. Investment returns can originate from several sources, including capital gains, dividends, and interest income. Many investors seek the highest returns possible in the quest for profit. However, prudent investing and trading entails evaluating such returns against the associated risks (i.e., the uncertainty of returns and the potential for financial losses) for a clearer perspective on overall performance and sustainability.
The profitability of an investment typically comes at the cost of enduring market swings, noise, and general uncertainty. To navigate these turbulent waters, investors and portfolio managers often utilize volatility , a measure of the statistical dispersion of historical returns, as a foundational element in their risk assessments because it provides a tangible way to gauge the uncertainty in returns. High volatility suggests increased uncertainty and, consequently, higher risk, whereas low volatility suggests more stable returns with minimal fluctuations, implying lower risk. These concepts are integral components in several risk-adjusted performance metrics, including the Sharpe and Sortino ratios calculated by this indicator.
Risk-free rate
The risk-free rate represents the rate of return on a hypothetical investment carrying no risk of financial loss. This theoretical rate provides a benchmark for comparing the returns on a risky investment and evaluating whether its excess returns justify the risks. If an investment's returns are at or below the theoretical risk-free rate or the risk premium is below a desired amount, it may suggest that the returns do not compensate for the extra risk, which might be a call to reassess the investment.
Since the risk-free rate is a theoretical concept, investors often utilize proxies for the rate in practice, such as Treasury bills and other government bonds. Conventionally, analysts consider such instruments "risk-free" for a domestic holder, as they are a form of government obligation with a low perceived likelihood of default.
The average yield on short-term Treasury bills, influenced by economic conditions, monetary policies, and inflation expectations, has historically hovered around 2-3% over the long term. This range also aligns with central banks' inflation targets. As such, one may interpret a value within this range as a minimum proxy for the risk-free rate, as it may correspond to the minimum rate required to maintain purchasing power over time. This indicator uses a default value of 2% as the risk-free rate in its Sharpe and Sortino ratio calculations. Users can adjust this value from the "Risk-free rate of return" input in the "Settings/Inputs" tab.
Sharpe and Sortino ratios
The Sharpe and Sortino ratios are two of the most widely used metrics that offer insight into an investment's risk-adjusted performance . They provide a standardized framework to compare the effectiveness of investments relative to their perceived risks. These metrics can help investors determine whether the returns justify the risks taken to achieve them, promoting more informed investment decisions.
Both metrics measure risk-adjusted performance similarly. However, they have some differences in their formulas and their interpretation:
1. Sharpe ratio
The Sharpe ratio , developed by Nobel laureate William F. Sharpe, measures the performance of an investment compared to a theoretically risk-free asset, adjusted for the investment risk. The ratio uses the following formula:
Sharpe Ratio = (𝑅𝑎 − 𝑅𝑓) / 𝜎𝑎
Where:
• 𝑅𝑎 = Average return of the investment
• 𝑅𝑓 = Theoretical risk-free rate of return
• 𝜎𝑎 = Standard deviation of the investment's returns (volatility)
A higher Sharpe ratio indicates a more favorable risk-adjusted return, as it signifies that the investment produced higher excess returns per unit of increase in total perceived risk.
2. Sortino ratio
The Sortino ratio is a modified form of the Sharpe ratio that only considers downside volatility , i.e., the volatility of returns below the theoretical risk-free benchmark. Although it shares close similarities with the Sharpe ratio, it can produce very different values, especially when the returns do not have a symmetrical distribution, since it does not penalize upside and downside volatility equally. The ratio uses the following formula:
Sortino Ratio = (𝑅𝑎 − 𝑅𝑓) / 𝜎𝑑
Where:
• 𝑅𝑎 = Average return of the investment
• 𝑅𝑓 = Theoretical risk-free rate of return
• 𝜎𝑑 = Downside deviation (standard deviation of negative excess returns, or downside volatility)
The Sortino ratio offers an alternative perspective on an investment's return-generating efficiency since it does not consider upside volatility in its calculation. A higher Sortino ratio signifies that the investment produced higher excess returns per unit of increase in perceived downside risk.
The risk-free rate (𝑅𝑓) in the numerator of both ratio formulas acts as a baseline for comparing an investment's performance to a theoretical risk-free alternative. By subtracting the risk-free rate from the expected return (𝑅𝑎−𝑅𝑓), the numerator essentially represents the risk premium of the investment.
Comparison with another symbol
In addition to the conventional Sharpe and Sortino ratios, which compare an instrument's returns to a risk-free rate, this indicator can also compare returns to a user-specified benchmark symbol , allowing the calculation of Information ratios .
An Information ratio is a generalized form of the Sharpe ratio that compares an investment's returns to a risky benchmark , such as SPY, rather than a risk-free rate. It measures the investment's active return (the difference between its returns and the benchmark returns) relative to its tracking error (i.e., the volatility of the active return) using the following formula:
𝐼𝑅 = (𝑅𝑝 − 𝑅𝑏) / 𝑇𝐸
Where:
• 𝑅𝑝 = Average return on the portfolio or investment
• 𝑅𝑏 = Average return from the benchmark instrument
• 𝑇𝐸 = Tracking error (volatility of 𝑅𝑝 − 𝑅𝑏)
Comparing returns to a benchmark instrument rather than a theoretical risk-free rate offers unique insights into risk-adjusted performance. Higher Information ratios signify that the investment produced higher active returns per unit of increase in risk relative to the benchmark. Conventional choices for non-risk-free benchmarks include major composite indices like the S&P 500 and DJIA, as the resulting ratios can provide insight into the effectiveness of an investment relative to the broader market.
Users can enable this generalized calculation for both the Sharpe and Sortino ratios by selecting the "Benchmark symbol returns" option from the "Benchmark type" dropdown in the "Settings/Inputs" tab.
It's crucial to note that this indicator compares the charts symbol's rate of change (return) to the rate of change in the benchmark symbol. Consequently, not all symbols available on TradingView are suitable for use with these ratios due to the nature of what their values represent. For instance, using a bond as a benchmark will produce distorted results since each bar's values represent yields rather than prices, meaning it compares the rate of change in the yield. To maintain consistency and relevance in the calculated ratios, ensure the values from the compared symbols strictly represent price information.
█ FEATURES
This indicator provides traders with two widely used metrics for assessing risk-adjusted performance, generalized to allow users to compare the chart symbol's price returns to a fixed risk-free rate or the returns from another risky symbol. Below are the key features of this indicator:
Timeframe selection
The "Returns timeframe" input determines the timeframe of the calculated price returns. Users can select any value greater than or equal to the chart's timeframe. The default timeframe is "1M".
Periodic returns tracking
This indicator compounds and collects requested price returns from the selected timeframe over monthly or daily periods, similar to how the Broker Emulator works when calculating strategy performance metrics on trade data. It employs the following logic:
• Track returns over monthly periods if the chart's data spans at least two months.
• Track returns over daily periods if the chart's data spans at least two days but not two months.
• Do not track or collect returns if the data spans less than two days, as the amount of data is insufficient for meaningful ratio calculations.
The indicator uses the returns collected from up to a specified number of periods to calculate the Sharpe and Sortino ratios, depending on the available historical data. It also uses these periodic returns to calculate the average returns it displays in the Data Window.
Users can control the maximum number of periods the indicator analyzes with the "Max no. of periods used" input in the "Settings/Inputs" tab. The default value is 60 periods.
Benchmark specification
The "Benchmark return type" input specifies the benchmark type the indicator compares to the chart symbol's returns in the ratio calculations. It features the following two options:
• "Risk-free rate of return (%)": Compares the price returns to a user-specified annual rate of return representing a theoretical risk-free rate (e.g., 2%).
• "Benchmark symbol return": Compares the price returns to a selected benchmark symbol (e.g., "AMEX:SPY) to calculate Information ratios.
When comparing a chart symbol's returns to a specified benchmark symbol, this indicator aligns the times of data points from the benchmark with the times of data points from the chart's symbol to facilitate a fair comparison between symbols with different active sessions.
Visualization and display
• The indicator displays the periodic returns requested from the specified "Returns timeframe" in a separate pane. The plot includes dynamic colors to signify positive and negative returns.
• When the "Returns timeframe" value represents a higher timeframe, the indicator displays background highlights on the main chart pane to signify when a new value is available and whether the return is positive or negative.
• When the specified benchmark return type is a benchmark symbol, the indicator displays the requested symbol's returns in the separate pane as a gray line for visual comparison.
• Within the separate pane, the indicator displays a single-cell table that shows the base period it uses for periodic returns, the number of periods it uses in the calculation, the timeframe of the requested data, and the calculated Sharpe and Sortino ratios.
• The Data Window displays the chart symbol and benchmark returns, their periodic averages, and the Sharpe and Sortino ratios.
█ FOR Pine Script™ CODERS
• This script utilizes the functions from our RiskMetrics library to determine the size of the periods, calculate and collect periodic returns, and compute the Sharpe and Sortino ratios.
• The `getAlignedPrices()` function in this script requests price data for the chart's symbol and a benchmark symbol with consistent time alignment by utilizing spread symbols , which helps facilitate a fair comparison between different symbol types. Retrieving prices from spreads avoids potential information loss and data misalignment that can otherwise occur when using separate requests from each symbol's context when those symbols have different sessions or data times.
• For consistency, the `getAlignedPrices()` function includes extended hours and dividend adjustment modifiers in its data requests. Additionally, it includes other settings inherited from the chart's context, such as "settlement-as-close" preferences for fair comparison between futures instruments.
• This script uses the `changePercent()` function from our ta library to calculate the percentage changes of the requested data.
• The newly released `force_overlay` parameter in display-related functions allows indicators to display visuals on the main chart and a separate pane simultaneously. We use the parameter in this script's bgcolor() call to display background highlights on the main chart.
Look first. Then leap.
TASC 2024.07 Gaps and Extreme Closes█ OVERVIEW
This script, inspired by Perry Kaufman's article "Trading Opening Gaps and Extreme Closes in Stocks" from the TASC's July 2024 edition of Traders' Tips , provides analytical insights into stock price behaviors following significant price moves. The information about the frequency, pullbacks, and closing patterns of these extreme price movements can aid in developing more effective trading strategies by understanding what to expect during volatile market conditions.
█ CONCEPTS
Perry Kaufman's article investigates the behavior of stock prices following substantial opening gaps and extreme closing moves to identify patterns and expectations that traders can utilize to make informed decisions. The motivation behind the article is to offer traders a more scientific approach to understanding price movements during volatile market conditions, particularly during earnings season or significant economic events. Kaufman's analysis reveals that stock prices have a history of exhibiting certain behaviors after substantial price gaps and extreme closes. This script follows Perry Kaufman's study and helps provide insight into how prices often behave after significant price changes. This analysis can help traders establish price movement expectations and potential strategies for trading such occurrences.
█ CALCULATIONS
Input Parameters:
This script offers users the choice to analyze "Opening Gaps" or "Extreme Closes" for price movements of different predefined magnitudes in a specified direction ("Upward" or "Downward").
Outputs:
Based on the specified inputs, the script performs the following calculations for the active ticker displayed on the chart:
Frequency of Extreme Price Movements : Quantifies the occurrences of directional price movements within predefined percentage ranges.
Average Pullbacks : Computes the average retracement (pullback) from analyzed price movements within each percentage range.
Average Closes : Analyzes the typical closing behavior relative to the directional price movements within each range.
The script organizes the results from these calculations within the table on a separate chart pane, providing users with helpful insights into how a stock historically behaved following significant price movements.
Sticky Notes, Checklist, To-do, Journal [algoat]I forgot to bring my notes again...
Ever feel like your trading notes are all over the place, much like your portfolio after a market dip? Worry not! With this script, you'll have all your trading notes, tasks, and brilliant (or not so brilliant) ideas neatly organized right on your chart. It's like having a sticky note board, but way cooler and without the risk of paper cuts.
⭐ Features :
To-Do Lists
Keep track of tasks with satisfying checkmarks for those dopamine hits.
Journal Entries
Document your market insights, trade plans, or just random thoughts. "I forgot something" – we've all been there.
Due Dates
Never miss an important deadline again. Red alert for overdue tasks because procrastination is a trader's worst enemy.
Customization
Choose the size and position of your notes because one size doesn't fit all.
Perfect for the organized trader who loves a bit of fun or the chaotic one who needs a bit of structure. Embrace the power of notes and stay on top of your trading game!
══════════════════
🧠 General advice
Trading effectively requires a range of techniques, experience, and expertise. From technical analysis to market fundamentals, traders must navigate multiple factors, including market sentiment and economic conditions. However, traders often find themselves overwhelmed by market noise, making it challenging to filter out distractions and make informed decisions. By integrating multiple analytical approaches, traders can tailor their strategies to fit their unique trading styles and objectives.
Confirming Signals with other indicators
As with all technical indicators, it is important to confirm potential signals with other analytical tools, such as support and resistance levels, as well as indicators like RSI, MACD, and volume. This helps increase the probability of a successful trade.
Use proper risk management
When using this or any other indicator, it is crucial to have proper risk management in place. Consider implementing stop-loss levels and thoughtful position sizing.
Combining with other technical indicators
The indicator can be effectively used alongside other technical indicators to create a comprehensive trading strategy and provide additional confirmation.
Keep in mind
Thorough research and backtesting are essential before making any trading decisions. Furthermore, it's crucial to have a solid understanding of the indicator and its behavior. Additionally, incorporating fundamental analysis and considering market sentiment can be vital factors to take into account in your trading approach.
══════════════════
⭐ Conclusion
We hold the view that the true path to success is the synergy between the trader and the tool, contrary to the common belief that the tool itself is the sole determinant of profitability. The actual scenario is more nuanced than such an oversimplification. A word to the wise is enough: developed by traders, for traders — pioneering innovations for the modern era.
Risk Notice
Everything provided by algoat — from scripts, tools, and articles to educational materials — is intended solely for educational and informational purposes. Past performance does not assure future returns.
Ichimoku Theories [LuxAlgo]The Ichimoku Theories indicator is the most complete Ichimoku tool you will ever need. Four tools combined into one to harness all the power of Ichimoku Kinkō Hyō.
This tool features the following concepts based on the work of Goichi Hosoda:
Ichimoku Kinkō Hyō: Original Ichimoku indicator with its five main lines and kumo.
Time Theory: automatic time cycle identification and forecasting to understand market timing.
Wave Theory: automatic wave identification to understand market structure.
Price Theory: automatic identification of developing N waves and possible price targets to understand future price behavior.
🔶 ICHIMOKU KINKŌ HYŌ
Ichimoku with lines only, Kumo only and both together
Let us start with the basics: the Ichimoku original indicator is a tool to understand the market, not to predict it, it is a trend-following tool, so it is best used in trending markets.
Ichimoku tells us what is happening in the market and what may happen next, the aim of the tool is to provide market understanding, not trading signals.
The tool is based on calculating the mid-point between the high and low of three pre-defined ranges as the equilibrium price for short (9 periods), medium (26 periods), and long (52 periods) time horizons:
Tenkan sen: middle point of the range of the last 9 candles
Kinjun sen: middle point of the range of the last 26 candles
Senkou span A: middle point between Tankan Sen and Kijun Sen, plotted 26 candles into the future
Senkou span B: midpoint of the range of the last 52 candles, plotted 26 candles into the future
Chikou span: closing price plotted 26 candles into the past
Kumo: area between Senkou pans A and B (kumo means cloud in Japanese)
The most basic use of the tool is to use the Kumo as an area of possible support or resistance.
🔶 TIME THEORY
Current cycles and forecast
Time theory is a critical concept used to identify historical and current market cycles, and use these to forecast the next ones. This concept is based on the Kihon Suchi (translating to "Basic Numbers" in Japanese), these are 9 and 26, and from their combinations we obtain the following sequence:
9, 17, 26, 33, 42, 51, 65, 76, 129, 172, 200, 257
The main idea is that the market moves in cycles with periods set by the Kihon Suchi sequence.
When the cycle has the same exact periods, we obtain the Taito Suchi (translating to "Same Number" in Japanese).
This tool allows traders to identify historical and current market cycles and forecast the next one.
🔹 Time Cycle Identification
Presentation of 4 different modes: SWINGS, HIGHS, KINJUN, and WAVES .
The tool draws a horizontal line at the bottom of the chart showing the cycles detected and their size.
The following settings are used:
Time Cycle Mode: up to 7 different modes
Wave Cycle: Which wave to use when WAVE mode is selected, only active waves in the Wave Theory settings will be used.
Show Time Cycles: keep a cleaner chart by disabling cycles visualisation
Show last X time cycles: how many cycles to display
🔹 Time Cycle Forecast
Showcasing the two forecasting patterns: Kihon Suchi and Taito Suchi
The tool plots horizontal lines, a solid anchor line, and several dotted forecast lines.
The following settings are used:
Show time cycle forecast: to keep things clean
Forecast Pattern: comes in two flavors
Kihon Suchi plots a line from the anchor at each number in the Kihon Suchi sequence.
Taito Suchi plot lines from the anchor with the same size detected in the anchored cycle
Anchor forecast on last X time cycle: traders can place the anchor in any detected cycle
🔶 WAVE THEORY
All waves activated with overlapping
The main idea behind this theory is that markets move like waves in the sea, back and forth (making swing lows and highs). Understanding the current market structure is key to having realistic expectations of what the market may do next. The waves are divided into Simple and Complex.
The following settings are used:
Basic Waves: allows traders to activate waves I, V and N
Complex Waves: allows traders to activate waves P, Y and W
Overlapping waves: to avoid missing out on any of the waves activated
Show last X waves: how many waves will be displayed
🔹 Basic Waves
The three basic waves
The basic waves from which all waves are made are I, V, and N
I wave: one leg moves
V wave: two legs move, one against the other
N wave: Three legs move, push, pull back, and another push
🔹 Complex Waves
Three complex waves
There are other waves like
P wave: contracting market
Y wave: expanding market
W wave: double top or double bottom
🔶 PRICE THEORY
All targets for the current N wave with their calculations
This theory is based on identifying developing N waves and predicting potential price targets based on that developing wave.
The tool displays 4 basic targets (V, E, N, and NT) and 3 extended targets (2E and 3E) according to the calculations shown in the chart above. Traders can enable or disable each target in the settings panel.
🔶 USING EVERYTHING TOGETHER
Please DON'T do this. This is not how you use it
Now the real example:
Daily chart of Nasdaq 100 futures (NQ1!) with our Ichimoku analysis
Time, waves, and price theories go together as one:
First, we identify the current time cycles and wave structure.
Then we forecast the next cycle and possible key price levels.
We identify a Taito Suchi with both legs of exactly 41 candles on each I wave, both together forming a V wave, the last two I waves are part of a developing N wave, and the time cycle of the first one is 191 candles. We forecast this cycle into the future and get 22nd April as a key date, so in 6 trading days (as of this writing) the market would have completed another Taito Suchi pattern if a new wave and time cycle starts. As we have a developing N wave we can see the potential price targets, the price is actually between the NT and V targets. We have a bullish Kumo and the price is touching it, if this Kumo provides enough support for the price to go further, the market could reach N or E targets.
So we have identified the cycle and wave, our expectations are that the current cycle is another Taito Suchi and the current wave is an N wave, the first I wave went for 191 candles, and we expect the second and third I waves together to amount to 191 candles, so in theory the N wave would complete in the next 6 trading days making a swing high. If this is indeed the case, the price could reach the V target (it is almost there) or even the N target if the bulls have the necessary strength.
We do not predict the future, we can only aim to understand the current market conditions and have future expectations of when (time), how (wave), and where (price) the market will make the next turning point where one side of the market overcomes the other (bulls vs bears).
To generate this chart, we change the following settings from the default ones:
Swing length: 64
Show lines: disabled
Forecast pattern: TAITO SUCHI
Anchor forecast: 2
Show last time cycles: 5
I WAVE: enabled
N WAVE: disabled
Show last waves: 5
🔶 SETTINGS
Show Swing Highs & Lows: Enable/Disable points on swing highs and swing lows.
Swing Length: Number of candles to confirm a swing high or swing low. A higher number detects larger swings.
🔹 Ichimoku Kinkō Hyō
Show Lines: Enable/Disable the 5 Ichimoku lines: Kijun sen, Tenkan sen, Senkou span A & B and Chikou Span.
Show Kumo: Enable/Disable the Kumo (cloud). The Kumo is formed by 2 lines: Senkou Span A and Senkou Span B.
Tenkan Sen Length: Number of candles for Tenkan Sen calculation.
Kinjun Sen Length: Number of candles for the Kijun Sen calculation.
Senkou Span B Length: Number of candles for Senkou Span B calculation.
Chikou & Senkou Offset: Number of candles for Chikou and Senkou Span calculation. Chikou Span is plotted in the past, and Senkou Span A & B in the future.
🔹 Time Theory
Show Time Cycle Forecast: Enable/Disable time cycle forecast vertical lines. Disable for better performance.
Forecast Pattern: Choose between two patterns: Kihon Suchi (basic numbers) or Taito Suchi (equal numbers).
Anchor forecast on last X time cycle: Number of time cycles in the past to anchor the time cycle forecast. The larger the number, the deeper in the past the anchor will be.
Time Cycle Mode: Choose from 7 time cycle detection modes: Tenkan Sen cross, Kijun Sen cross, Kumo change between bullish & bearish, swing highs only, swing lows only, both swing highs & lows and wave detection.
Wave Cycle: Choose which type of wave to detect from 6 different wave types when the time cycle mode is set to WAVES.
Show Time Cycles: Enable/Disable time cycle horizontal lines. Disable for better performance.
how last X time cycles: Maximum number of time cycles to display.
🔹 Wave Theory
Basic Waves: Enable/Disable the display of basic waves, all at once or one at a time. Disable for better performance.
Complex Waves: Enable/Disable complex wave display, all at once or one by one. Disable for better performance.
Overlapping Waves: Enable/Disable the display of waves ending on the same swing point.
Show last X waves: 'Maximum number of waves to display.
🔹 Price Theory
Basic Targets: Enable/Disable horizontal price target lines. Disable for better performance.
Extended Targets: Enable/Disable extended price target horizontal lines. Disable for better performance.
Volume Bull/Bear Activity [ZC]Volume Bull/Bear Activity Summary
This indicator generates a summary of bull/bear activity for 20 symbols.
For each symbol, two bars are displayed, colored green and red.
The green bar indicates bull volume, reflecting activity within the last candle of the symbol.
The red bar signifies bear volume within the real-time bar, continuously updated.
You can seamlessly adjust the timeframe for this indicator.
Features :
Bear/Bull Volume bars ( Realtime )
ability to add 20 symbols
price is colored in Green or red to determine if its Green/Red candle .
More into its data
Mxwll Price Action Suite [Mxwll]Introducing the Mxwll Price Action Suite!
The Mxwll Price Action Suite is an all-in-one analysis indicator incorporating elements of SMC and also ideas extending beyond the trading methodology!
Features
Internal structures
External structures
Customizable Sensitivities
BoS/CHoCH
Order Blocks
HH/LH/LL/LH Areas
Rolling TF highs/lows
Rolling Volume Comparisons
Auto Fibs
And more!
The image above shows the indicator's market structure identification capabilities. Internal BoS and CHoCH structures in addition to overarching market structures are available with customizable sensitivities.
The image above shows the indicator identifying order blocks! Additionally, HH/LH/LL/LH areas are also identified.
The image above shows a rolling area of interest. These areas can be compared to supply/demand zones, where traders might consider a bargain long/short/sell area.
The indicator displays a rolling 4hr high/low and 1D high/low, alongside auto fibonacci levels with a customizable sensitivity.
Finally, the Mxwll Price Action Suite shows relevant session information.
Table information
Current Session
Countdown to session close
Next Session
Countdown to next session open
Rolling 4-Hr volume intensity
Rolling 24-Hr volume intensity
Introducing the Mxwll SMC Suite!
The Mxwll SMC Suite is an all-in-one analysis indicator incorporating elements of SMC and also ideas extending beyond the trading methodology!
Features
Internal structures
External structures
Customizable Sensitivities
BoS/CHoCH
Order Blocks
HH/LH/LL/LH Areas
Rolling TF highs/lows
Rolling Volume Comparisons
Auto Fibs
And more!
The image above shows the indicator's market structure identification capabilities. Internal BoS and CHoCH structures in addition to overarching market structures are available with customizable sensitivities.
The image above shows the indicator identifying order blocks! Additionally, HH/LH/LL/LH areas are also identified.
The image above shows a rolling area of interest. These areas can be compared to supply/demand zones, where traders might consider a bargain long/short/sell area.
The indicator displays a rolling 4hr high/low and 1D high/low, alongside auto fibonacci levels with a customizable sensitivity.
Finally, the Mxwll Price Action Suite shows relevant session information.
Table information
Current Session
Countdown to session close
Next Session
Countdown to next session open
Rolling 4-Hr volume intensity
Rolling 24-Hr volume intensity
Expanded Features of Mxwll Price Action Suite
Internal and External Structures
Internal Structures: These elements refer to the price formations and patterns that occur within a smaller scope or a specific trading session. The suite can detect intricate details like minor support/resistance levels or short-term trend reversals.
External Structures: These involve larger, more significant market patterns and trends spanning multiple sessions or time frames. This capability helps traders understand overarching market directions.
Customizable Sensitivities
Adjusting sensitivity settings allows users to tailor the indicator's responsiveness to market changes. Higher sensitivity can catch smaller fluctuations, while lower sensitivity might focus on more significant, reliable market moves.
Break of Structure (BoS) and Change of Character (CHoCH)
BoS: This feature identifies points where the price breaks a significant structure, potentially indicating a new trend or a trend reversal.
CHoCH: Detects subtle shifts in the market's behavior, which could suggest the early stages of a trend change before they become apparent to the broader market.
Order Blocks and Market Phases
Order Blocks: These are essentially price levels or zones where significant trading activities previously occurred, likely pointing to the positions of smart money.
HH/LH/LL/LH Areas: Identifying Higher Highs (HH), Lower Highs (LH), Lower Lows (LL), and Lower Highs (LH) helps in understanding the trend and market structure, aiding in predictive analysis.
Rolling Timeframe Highs/Lows and Volume Comparisons
Tracks highs and lows over specified rolling periods, providing dynamic support and resistance levels.
Compares volume data across different timeframes to assess the strength or weakness of the current price movements.
Auto Fibonacci Levels
Automatically calculates and plots Fibonacci retracement levels, a popular tool among traders to identify potential reversal points based on past movements.
Session Data and Volume Intensity
Session Information: Displays current and upcoming trading sessions along with countdown timers, which is crucial for day traders and those trading on session overlaps.
Volume Intensity: Measures and compares the volume within the last 4 hours and 24 hours to gauge market activity and potential breakout/breakdown movements.
Visualizations and Practical Use
Dynamic Visuals: The suite provides dynamic visual aids, such as real-time updating of high/low markers and Fibonacci levels, which adjust as new data comes in. This feature is critical in fast-paced markets.
Strategic Entry/Exit Points: By identifying order blocks and using Fibonacci levels, traders can pinpoint strategic entry and exit points, maximizing potential returns.
Risk Management: Enhanced features like session countdowns and volume intensity help in better risk management by providing traders with more data on market sentiment and potential volatility.
Percent Rank HistogramThis Pine script indicator is designed to create a visual representation of the percent rank for multiple financial instruments. Here's a breakdown of its key features:
Percent Rank Calculation:
The core functionality of this Pine script indicator revolves around the calculation of the percent rank for each selected financial instrument.
The percent rank is a statistical measure that indicates the percentage of historical data points that are less than or equal to the current value in a given series.
Symbol Selection:
The script allows the user to select up to 10 financial instruments (tickers) for analysis. The default symbols include various cryptocurrencies such as BTCUSD, ETHUSD etc., and TOTAL market cap at ticker 1, to show overal trend of crypto market.
(Top 9 Coins by market cap).
Columns and Colors:
The script visually represents the percent rank using columns based on lines.
The color of each column is determined by a gradient from red to green based on the calculated percent rank, providing a quick visual indication of the instrument's relative performance.
BTC Trending Up while other coins are underperformance:
Labels:
Labels are displayed on the chart, indicating the symbol name and the corresponding percent rank percentage.
The labels include directional arrows (▲ or ▼) to denote whether the percent rank is increasing or decreasing.
Customization:
Users can customize parameters such as the percent rank length and column width to adapt the indicator to their specific preferences, or select needed assets to compare them to each other.
Chart Desk and Scales:
The script includes the visualization of a chart desk with scale lines to provide additional context to the chart. When Percent Rank above middle scale line (50) usually it signaling about asset trending up and below 50 asset trending down.
Mozilla Public License:
The script is subject to the terms of the Mozilla Public License 2.0.
This indicator is useful for traders and analysts interested in visually assessing the percent rank of multiple financial instruments simultaneously, helping them identify potential opportunities or trends in the market.
