COT MCIThe COT MCI script is a market indicator based on the data from the Commitment of Traders Reports.
Integration of COT Report Data:
The script sources COT data from futures contracts, including:
Treasury Bonds (ZB), Dollar Index (DX), 10-Year Treasury Notes (ZN)
Commodities like Soybeans (ZS), Soy Meal (ZM), Soy Oil (ZL), Corn (ZC), Wheat (ZW), Kansas City Wheat (KE), Pork (HE), Cattle (LE)
Precious Metals such as Gold (GC), Silver (SI), Palladium (PA), Platinum (PL)
Industrial Metals like Copper (HG), Aluminum (AUP), Steel (HRC)
Energy Products like Crude Oil (CL), Heating Oil (HO), Gasoline (RB), Natural Gas (NG), Brent Crude (BB)
Currencies such as AUD (6A), GBP (6B), CAD (6C), EUR (6E), JPY (6J), CHF (6S), NZD (6N), BRL (6L), MXN (6M), RUB (6R), ZAR (6Z)
Others: Sugar (SB), Coffee (KC), Cocoa (CC), Cotton (CT), Ethanol (EH), Rice (ZR), Oats (ZO), Whey (DC), Orange Juice (OJ), Lumber (LBS), Livestock (GF), E-mini S&P 500 (ES), E-mini Russell 2000 (RTY), E-mini Dow Jones (YM), E-mini NASDAQ-100 (NQ), VIX Futures (VX), S&P 500 (SP), DJIA (DJIA)
Cryptocurrencies such as Bitcoin (BTC) and Ethereum (ETH)
Functions and Logic of the Script:
COT Calculation: Determines the net positions for commercial actors and large speculators. Also Available are short and long positions of commercials or large speculators.
Position Change Analysis: Analyzes the percentage changes in net positions and open interest data over a period of 6 weeks (Weekly Chart).
Average Value Calculation: Determines short-term and long-term trend averages.
Trend Analysis: Buy and sell signals (represented in colors) are based on linear regressions and average calculations.
Usage and Application Examples:
Ideal for traders looking for a detailed analysis of market dynamics and position changes in the futures market. Suitable for decision-making in transaction timing and assessing market sentiment.
Usage Notes:
Users should be familiar with the interpretation of COT data and basic concepts of futures trading. Particularly suitable for medium to long-term trading strategies.
חפש סקריפטים עבור "THE SCRIPT"
Intersection Value FunctionsWinning entry for the first Pinefest contest. The challenge required providing three functions returning the intersection value between two series source1 and source2 in the event of a cross, crossunder, and crossover.
Feel free to use the code however you like.
🔶 CHALLENGE FUNCTIONS
🔹 crossValue()
//@function Finds intersection value of 2 lines/values if any cross occurs - First function of challenge -> crossValue(source1, source2)
//@param source1 (float) source value 1
//@param source2 (float) source value 2
//@returns Intersection value
example:
value = crossValue(close, close )
🔹 crossoverValue()
//@function Finds intersection value of 2 lines/values if crossover occurs - Second function of challenge -> crossoverValue(source1, source2)
//@param source1 (float) source value 1
//@param source2 (float) source value 2
//@returns Intersection value
example:
value = crossoverValue(close, close )
🔹 crossunderValue()
//@function Finds intersect of 2 lines/values if crossunder occurs - Third function of challenge -> crossunderValue(source1, source2)
//@param source1 (float) source value 1
//@param source2 (float) source value 2
//@returns Intersection value
example:
value = crossunderValue(close, close )
🔶 DETAILS
A series of values can be displayed as a series of points, where the point location highlights its value, however, it is more common to connect each point with a line to have a continuous aspect.
A line is a geometrical object connecting two points, each having y and x coordinates. A line has a slope controlling its steepness and an intercept indicating where the line crosses an axis. With these elements, we can describe a line as follows:
slope × x + intercept
A cross between two series of values occurs when one series is greater or lower than the other while its previous value isn't.
We are interested in finding the "intersection value", that is the value where two crossing lines are equal. This problem can be approached via linear interpolation.
A simple and direct approach to finding our intersection value is to find the common scaling factor of the slopes of the lines, that is the multiplicative factor that multiplies both lines slopes such that the resulting points are equal.
Given:
A = Point A1 + m1 × scaling_factor
B = Point B1 + m2 × scaling_factor
where scaling_factor is the common scaling factor, and m1 and m2 the slopes:
m1 = Point A2 - Point A1
m2 = Point B2 - Point B1
In our cases, since the horizontal distance between two points is simply 1, our lines slopes are equal to their vertical distance (rise).
Under the event of a cross, there exists a scaling_factor satisfying A = B , which allows us to directly compute our intersection value. The solution is given by:
scaling_factor = (B1 - A1)/(m1 - m2)
As such our intersection value can be given by the following equivalent calculations:
(1) A1 + m1 × (B1 - A1)/(m1 - m2)
(2) B1 + m2 × (B1 - A1)/(m1 - m2)
(3) A2 - m2 × (A2 - B2)/(m1 - m2)
(4) B2 - m2 × (A2 - B2)/(m1 - m2)
The proposed functions use the third calculation.
This approach is equivalent to expressions using the classical line equation, with:
slope1 × x + intercept1 = slope2 × x + intercept2
By solving for x , the intersection point is obtained by evaluating any of the line equations for the obtained x solution.
🔶 APPLICATIONS
The intersection point of two crossing lines might lead to interesting applications and creations, in this section various information/tools derived from the proposed calculations are presented.
This supplementary material is available within the script.
🔹 Intersections As Support/Resistances
The script allows extending the lines of the intersection value when a cross is detected, these extended lines could have applications as support/resistance lines.
🔹 Using The Scaling Factor
The core of the proposed calculation method is the common scaling factor, which can be used to return useful information, such as the position of the cross relative to the x coordinates of a line.
The above image highlights two moving averages (in green and red), the cross-interval areas are highlighted in blue, and the intersection point is highlighted as a blue line.
The pane below shows a bar plot displaying:
1 - scaling factor = 1 -
Values closer to 1 indicate that the cross location is closer to x2 (the right coordinate of the lines), while values closer to 0 indicate that the cross location is closer to x1 .
🔹 Intersection Matrix
The main proposed functions of this challenge focus on the crossings between two series of values, however, we might be interested in applying this over a collection of series.
We can see in the image above how the lines connecting two points intersect with each other, we can construct a matrix populated with the intersection value of two corresponding lines. If (X, Y) represents the intersection value between lines X and Y we have the following matrix:
| Line A | Line B | Line C | Line D |
-------|--------|--------|--------|--------|
Line A | | (A, B) | (A, C) | (A, D) |
Line B | (B, A) | | (B, C) | (B, D) |
Line C | (C, A) | (C, B) | | (C, D) |
Line D | (D, A) | (D, B) | (D, C) | |
We can see that the upper triangular part of this matrix is redundant, which is why the script does not compute it. This function is provided in the script as intersectionMatrix :
//@function Return the N * N intersection matrix from an array of values
//@param array_series (array) array of values, requires an array supporting historical referencing
//@returns (matrix) Intersection matrix showing intersection values between all array entries
In the script, we create an intersection matrix from an array containing the outputs of simple moving averages with a period in a specific user set range and can highlight if a simple moving average of a certain period crosses with another moving average with a different period, as well as the intersection value.
🔹 Magnification Glass
Crosses on a chart can be quite small and might require zooming in significantly to see a detailed picture of them. Using the obtained scaling factor allows reconstructing crossing events with an higher resolution.
A simple supplementary zoomIn function is provided to this effect:
//@function Display an higher resolution representation of intersecting lines
//@param source1 (float) source value 1
//@param source2 (float) source value 2
//@param css1 (color) color of source 1 line
//@param css2 (color) color of source 2 line
//@param intersec_css (color) color of intersection line
//@param area_css (color) color of box area
Users can obtain a higher resolution by modifying the provided "Resolution" setting.
The function returns a higher resolution representation of the most recent crosses between two input series, the intersection value is also provided.
New York Sessions Morning, Lunch and afternoon. AMKDescription
The script is designed to highlight the New York Stock Exchange's trading day, broken down into three specific sub-sessions: morning, lunchtime, and afternoon. Each sub-session is color-coded to provide an immediate visual cue about which portion of the trading day is currently active. Additionally, this script allows the user to adjust the time zone offset, making it adaptable for traders in different time zones around the world.
Originality
While there are scripts that highlight the entire trading day or specific market hours, this script adds granularity by breaking down the New York trading session into its typical behavioral parts: the morning rush, the lunchtime lull, and the afternoon action. The addition of an adjustable time zone offset is a unique feature that makes the tool more versatile and accommodating to a global user base.
Usefulness
The ability to visualize these different trading sessions can be valuable for various types of traders:
Day Traders: The script helps to immediately identify which session they are in, aiding in their trading strategy as market behavior can vary between these periods.
Swing Traders: They may use these sub-sessions to time their entries or exits, especially if they're based in different time zones.
Market Analysts: The color-coded sessions provide a quick way to analyze the historical performance and volatility of an asset during different trading periods.
Global Traders: The time zone adjustment feature makes it easy for traders outside of the Eastern Time Zone to customize the script according to their local time, increasing its utility across different markets.
Educational Purpose: For new traders, this could serve as an educational tool to understand the typical behavior of the stock market at different times of the day.
So, whether you're timing an intraday entry or looking for patterns tied to specific market sessions, this script offers a straightforward, visual way to keep track of where you are in the trading day.
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
Anchored Average Price by Atilla Yurtseven (AAP)Anchored Average Price indicator is designed to pinpoint a specific date and price in a given financial instrument's price chart. Once anchored to the desired date and price level, the script calculates and displays the average price from that anchor point to the current day.
Features
Customizable Source: Allows users to choose the source data for calculations. By default, it uses hlc3, which is the average of high, low, and close prices.
Start Date Input: The script includes a timestamp-based input that allows the user to specify the anchor date easily.
Customizable Color: Users can change the color of the plotted average line, adding an additional layer of customization to the visual representation.
Code Mechanics
Initialization: Declares the variables and arrays required for calculations and display. The array is used to store price data.
Condition Check: Only starts storing and calculating data if the chart's time is equal to or greater than the user-defined start date.
Data Storing: Once the condition is met, the script pushes the src price data into the array for future averaging.
Average Calculation: It calculates the average price of the values stored in the array.
Data Clearing: If the condition is not met, the array is cleared, and no average is plotted.
Plotting: The average price is plotted on the chart with the user-defined color.
By incorporating these features and mechanics, AAP provides traders and investors with a powerful tool for assessing average prices anchored to a specific date or swing.
Disclaimer:
This TradingView script is intended for educational and informational purposes only and should not be considered as investment or trading advice. Past performance is not indicative of future results. Trading and investing carry a high level of risk, and you should consult with a qualified financial advisor before making any financial decisions. The creator of this script, Atilla Yurtseven, is not responsible for any losses or damages incurred as a result of using this script.
Trade smart, stay safe
Atilla Yurtseven
Spot-Vol CorrelationSpot-Vol Correlation Script Guide
Purpose:
This TradingView script measures the correlation between percentage changes in the spot price (e.g., for SPY, an ETF that tracks the S&P 500 index) and the changes in volatility (e.g., as indicated by the VIX, the Volatility Index). Its primary objective is to discern whether the relationship between spot price and volatility behaves as expected ("normal" condition) or diverges from the expected pattern ("abnormal" condition).
Normal vs. Abnormal Correlation:
Normal Correlation: Historically, the VIX (or volatility) and the spot price of major indices like the S&P 500 have an inverse relationship. When the spot price of the index goes up, the VIX tends to go down, indicating lower volatility. Conversely, when the index drops, the VIX generally rises, signaling increased volatility.
Abnormal Correlation: There are instances when this inverse relationship doesn't hold, and both the spot price and the VIX move in the same direction. This is considered an "abnormal" condition and might indicate unusual market dynamics, potential uncertainty, or impending shifts in market sentiment.
Using the Script:
Inputs:
First Symbol: This is set by default to VIX, representing volatility. However, users can input any other volatility metric they prefer.
Second Symbol: This is set to SPY by default, representing the spot price of the S&P 500 index. Like the first symbol, users can substitute SPY with any other asset or index of their choice.
Length of Calculation Period: Users can define the lookback period for the correlation calculation. By default, it's set to 10 periods (e.g., days for a daily chart).
Upper & Lower Bounds of Normal Zone: These parameters define the range of correlation values that are considered "normal" or expected. By default, this is set between -0.60 and -1.00.
Visuals:
Correlation Line: The main line plot shows the correlation coefficient between the two input symbols. When this line is within the "normal zone", it indicates that the spot price and volatility are inversely correlated. If it's outside this zone, the correlation is considered "abnormal".
Green Color: Indicates a period when the spot price and VIX are behaving as traditionally expected (i.e., one rises while the other falls).
Red Color: Denotes a period when the spot price and VIX are both moving in the same direction, which is an abnormal condition.
Shaded Area (Normal Zone): The area between the user-defined upper and lower bounds is shaded in green, highlighting the range of "normal" correlation values.
Interpretation:
Monitor the color and position of the correlation line relative to the shaded area:
If the line is green and within the shaded area, the market dynamics are as traditionally expected.
If the line is red or outside the shaded area, users should exercise caution as this indicates a divergence from typical behavior, which can precede significant market moves or heightened uncertainty.
Intraday Volatility Bands [Honestcowboy]The Intraday Volatility Bands aims to provide a better alternative to ATR in the calculation of targets or reversal points.
How are they different from ATR based bands?
While ATR and other measures of volatility base their calculations on the previous bars on the chart (for example bars 1954 to 1968). The volatility used in these bands measure expected volatility during that time of the day.
Why would you take this approach?
Markets behave different during certain times of the day, also called sessions.
Here are a couple examples.
Asian Session (generally low volatility)
London Session (bigger volatility starts)
New York Session (overlap of New York with London creates huge volatility)
Generally when using bands or channel type indicators intraday they do not account for the upcoming sessions. On London open price will quickly spike through a bollinger band and it will take some time for the bands to adjust to new volatility.
This script will show expected volatility targets at the start of each new bar and will not adjust during the bar. It already knows what price is expected to do at this time of day.
Script also plots arrows when price breaches either the top or bottom of the bands. You can also set alerts for when this occurs. These are non repainting as the script knows the level at start of the bar and does not change.
🔷 CALCULATION
Think of this script like an ATR but instead it uses past days data instead of previous bars data. Charts below should visualise this more clearly:
The scripts measure of volatility is based on a simple high-low.
The script also counts the number of bars that exist in a day on your current timeframe chart. After knowing that number it creates the matrix used in it's calculations and data storage.
See how it works perfectly on a lower timeframe chart below:
Getting this right was the hardest part, check the coding if you are interested in this type of stuff. I commented every step in the coding process.
🔷 SETTINGS
Every setting of the script has a tooltip but I provided a breakdown here:
Some more examples of different charts:
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
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
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).
Filtered Volume Profile [ChartPrime]The "Filtered Volume Profile" is a powerful tool that offers insights into market activity. It's a technical analysis tool used to understand the behavior of financial markets. It uses a fixed range volume profile to provide a histogram representing how much volume occurred at distinct price levels.
Profile in action with various significant levels displayed
How to Use
The script is designed to analyze cumulative trading volumes in different price bins over a certain period, also known as `'lookback'`. This lookback period can be defined by the user and it represents the number of bars to look back for calculating levels of support and resistance.
The `'Smoothing'` input determines the degree to which the output is smoothed. Higher values lead to smoother results but may impede the responsiveness of the indicator to rapid changes in volatility.
The `'Peak Sensitivity'` input is used to adjust the sensitivity of the script's peak detection algorithm. Setting this to a lower value makes the algorithm more sensitive to local changes in trading volume and may result in "noisier" outputs.
The `'Peak Threshold'` input specifies the number of bins that the peak detection mechanism should account for. Larger numbers imply that more volume bins are taken into account, and the resultant peaks are based on wider intervals.
The `'Mean Score Length'` input is used for scaling the mean score range. This is particularly important in defining the length of lookback bars that will be used to calculate the average close price.
Sinc Filter
The application of the sinc-filter to the Filtered Volume Profile reduces the risk of viewing artefacts that may misrepresent the underlying market behavior. Sinc filtering is a high-quality and sharp filter that doesn't manifest any ringing effects, making it an optimal choice for such volume profiling.
Histogram
On the histogram, the volume profile is colored based on the balance of bullish to bearish volume. If a particular bar is more intense in color, it represents a larger than usual volume during a single price bar. This is a clear signal of a strong buying or selling pressure at a particular price level.
Threshold for Peaks
The `peak_thresh` input determines the number of bins the algorithm takes in account for the peak detection feature. The 'peak' represents the level where a significant amount of volume trading has occurred, and usually is of interest as an indicative of support or resistance level.
By increasing the `peak_thresh`, you're raising the bar for what the algorithm perceives as a peak. This could result in fewer, but more significant peaks being identified.
History of Volume Profiles and Evolution into Sinc Filtering
Volume profiling has a rich history in market analysis, dating back to the 1950s when Richard D. Wyckoff, a legendary trader, introduced the concept of volume studies. He understood the critical significance of volume and its relationship with market price movement. The core of Wyckoff's technical analysis suite was the relationship between prices and volume, often termed as "Effort vs Results".
Moving forward, in the early 1800s, the esteemed mathematician J. R. Carson made key improvements to the sinc function, which formed the basis for sinc filtering application in time series data. Following these contributions, trading studies continued to create and integrate more advanced statistical measures into market analysis.
This culminated in the 1980s with J. Peter Steidlmayer’s introduction of Market Profile. He suggested that markets were a function of continuous two-way auction processes thus introducing the concept of viewing markets in price/time continuum and price distribution forms. Steidlmayer's Market Profile was the first wide-scale operation of organized volume and price data.
However, despite the introduction of such features, challenges in the analysis persisted, especially due to noise that could misinform trading decisions. This gap has given rise to the need for smoothing functions to help eliminate the noise and better interpret the data. Among such techniques, the sinc filter has become widely recognized within the trading community.
The sinc filter, because of its properties of constructing a smooth passing through all data points precisely and its ability to eliminate high-frequency noise, has been considered a natural transition in the evolution of volume profile strategies. The superior ability of the sinc filter to reduce noise and shield against over-fitting makes it an ideal choice for smoothing purposes in trading scripts, particularly where volume profiling forms the crux of the market analysis strategy, such as in Filtered Volume Profile.
Moving ahead, the use of volume-based studies seems likely to remain a core part of technical analysis. As long as markets operate based on supply and demand principles, understanding volume will remain key to discerning the intent behind price movements. And with the incorporation of advanced methods like sinc filtering, the accuracy and insight provided by these methodologies will only improve.
Mean Score
The mean score in the Filtered Volume Profile script plays an important role in probabilistic inferences regarding future price direction. This score essentially characterizes the statistical likelihood of price trends based on historical data.
The mean score is calculated over a configurable `'Mean Score Length'`. This variable sets the window or the timeframe for calculation of the mean score of the closing prices.
Statistically, this score takes advantage of the concept of z-scores and probabilities associated with the t-distribution (a type of probability distribution that is symmetric and bell-shaped, just like the standard normal distribution, but has heavier tails).
The z-score represents how many standard deviations an element is from the mean. In this case, the "element" is the price level (Point of Control).
The mean score section of the script calculates standard errors for the root mean squared error (RMSE) and addresses the uncertainty in the prediction of the future value of a random variable.
The RMSE of a model prediction concerning observed values is used to measure the differences between values predicted by a model and the values observed.
The lower the RMSE, the better the model is able to predict. A zero RMSE means a perfect fit to the data. In essence, it's a measure of how concentrated the data is around the line of best fit.
Through the mean score, the script effectively predicts the likelihood of the future close price being above or below our identified price level.
Summary
Filtered Volume Profile is a comprehensive trading view indicator which utilizes volume profiling, peak detection, mean score computations, and sinc-filter smoothing, altogether providing the finer details of market behavior.
It offers a customizable look back period, smoothing options, and peak sensitivity setting along with a uniquely set peak threshold. The application of the Sinc Filter ensures a high level of accuracy and noise reduction in volume profiling, making this script a reliable tool for gaining market insights.
Furthermore, the use of mean score calculations provides probabilistic insights into price movements, thus providing traders with a statistically sound foundation for their trading decisions. As trading markets advance, the use of such methodologies plays a pivotal role in formulating effective trading strategies and the Filtered Volume Profile is a successful embodiment of such advancements in the field of market analysis.
Volume Delta Methods (Chart) [LuxAlgo]The Volume Delta Methods (Chart) aims at highlighting the relationship between Buying or Selling Pressure and Price by presenting Volume Delta , and multiple derivatives of volume delta such as Cumulative Volume Delta (CVD) , Buy/Sell Volume , Total Volume , etc on top of the Main Price Chart .
The script uses two different intrabar (chart bars at a lower timeframe than the chart's) analyses to achieve the most approximate calculation of the volume delta and offers fully customizable visualization features using various types of charts such as line, area, baseline, candles, and histograms.
The script allows traders to see "within" the price bar, provides more transparency over a traditional volume histogram, and also allows users to monitor price and volume activity together.
🔶 USAGE
Volume delta is the difference between the buying volume and the selling volume, in other words, it is the net demand at a given bar allowing traders a more detailed insight when analyzing the market sentiment. A volume delta greater than 0 indicates more buying than selling pressure, whereas a volume delta less than 0 indicates more selling than buying pressure.
Volume delta plus total volume (regular volume) adds additional insight, where the total volume represents all the recorded trades for security that occurs in a given time interval. It is a measurement of the participation, enthusiasm, and interest in a given security.
Divergences occur when the polarity of the volume delta does not match the polarity of the price bar.
The users can enable the display of the numerical values of the volume delta.
Cumulative Volume Delta (CVD) is a way of using Volume Delta to measure an asset’s mid-to-long-term buy and sell pressure. It compares buying and selling volume over time and offers insights into market behavior at specific price points. Cumulative Volume Delta is effectively a continuation of the principles of Volume Delta but involves longer time periods and offers different trading signals.
Like the Volume Delta, the Cumulative Volume Delta (CVD) indicator measures the relationship between buy and sell pressure but does not focus on one specific candle in particular. Rather, the Cumulative Volume Delta takes the relative differences and combines them all over an extended time period.
Users have the ability Cumulative Volume Delta in various types of charts along with an optional smoothing line.
Placed above price bars options.
Interacting with price bar options helps to better identify CVD Divergences.
CVD Divergences
CVD reveals buying and selling trends that may or may not complement the price trend of the asset itself. Sometimes, price trends can run in contrast to trading behavior — sell volume can be dominant while the spot price is rising, and vice versa.
🔶 DETAILS
Theoretically, volume delta is calculated by taking the difference between the volume that traded at the ask price and the volume that traded at the bid price. The most precise calculation method uses tick data but requires huge amounts of data on historical bars, which usually limits the historical depth of charts. This indicator uses two different intrabar analysis methods for the volume delta calculation, where intrabars are chart bars at a lower timeframe than the chart's timeframe:
The logic used to assign intrabar volume to the "up" or "down".
- Buying/Selling pressure of the intrabar option (default)
(close - low) > (high - close) => UP
(close - low) < (high - close) => DOWN
(close - low) = (high - close) => close - previous close is used
- Polarity of the intrabar option
close > open => UP
close < open => DOWN
close = open => close - previous close is used
🔶 SETTINGS
The script takes into account user-defined parameters and performs calculations and presentations based on them, where detailed usage for each user-defined input parameter in indicator settings is provided with the related input's tooltip.
🔹 Calculation Settings
Calculation Method: Calculation method selection, available options 'Intrabar Buying/Selling Pressure' or 'Intrabar Polarity'.
Lower Timeframe Precision: Sets indicator precision, default option is 'Auto'.
🔹 Presentation Settings
Volume Delta: Toggles the visibility of the Volume Delta
Cumulative Volume Delta: Toggles the visibility of the Cumulative Volume Delta
Volume Delta/Price Bar Divergences: Toggles the visibility of the Volume Delta Divergences
Volume Delta Numerical Values: Toggles the visibility of the Volume Delta Numerical Values
🔹 Other Features
Volume MA: Toggles the visibility of the Volume Moving Average
CVD Smoothing: Toggles the visibility of the Cumulative Volume Delta's Smoothing Line
🔹 Volume Delta, Others
Volume Delta: Positive, Negative: Volume Delta color customization options
Volume Histogram: Growing, Falling: Volume Histogram color customization options
Display Length: Length of the visual objects presented with this indicator
Volume Delta Height: Volume delta height customization options
Volume Histogram Height: Volume histogram height customization options
Vertical Offset: Volume delta and histogram vertical positioning customization options
🔹 Cumulative Volume Delta, Others
CVD Line, Width, and Color: Cumulative Volume Delta - Line Width and Color customization options
CVD Area/Baseline, Gradient Coloring: Cumulative Volume Delta - Area and Baseline background gradient coloring customization options
CVD Candles Color, Positive, and Negative: Cumulative Volume Delta - Candles coloring customization options
CVD/Smoothing Background: Highlights and adjusts the transparency of the area between the Cumulative Volume Delta Line and it's Smoothing Line
🔶 RELATED SCRIPTS
Liquidity-Sentiment-Profile
EquiVolume
Volume-Footprint
Liquidity Sentiment Profile [LuxAlgo]The Liquidity Sentiment Profile is an advanced charting tool that measures by combining PRICE and VOLUME data over specified anchored periods and highlights within a sequence of profiles the distribution of the liquidity and the market sentiment at specific price levels.
The Liquidity Sentiment Profile allows traders to reveal significant price levels, dominant market sentiment, support and resistance levels, supply and demand zones, liquidity availability levels, liquidity gaps, consolidation zones, and more based on price and volume data.
Liquidity refers to the availability of orders at specific price levels in the market, allowing transactions to occur smoothly.
🔶 USAGE
A Liquidity Sentiment Profile is a combination of a liquidity and a sentiment profile, where the right part of the profile displays the distribution of the traded activity at different price levels and the left part displays the market sentiment at those price levels.
The Liquidity Sentiment Profiles are visualized with different colors, where each color has a different meaning.
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)
🔶 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 Profiles
Anchor Period: The indicator resolution is set by the input of the Anchor Period, the default option is AUTO.
🔹 Liquidity Profile Settings
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 Settings
Sentiment Profile: Toggles the visibility of the Sentiment Profiles
Bullish Nodes: Color option for Bullish Nodes
Bearish Nodes: Color option for Bearish Nodes
🔹 Other Settings
Level of Significance: Toggles the visibility of the Level of Significance Line
Profile Price Levels: 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
🔶 LIMITATIONS
The amount of drawing objects that can be used is limited, as such using a high number of rows can display fewer historical profiles and occasionally incomplete profiles.
🔶 RELATED SCRIPTS
🔹 Buyside-Sellside-Liquidity
🔹 ICT-Concepts
🔹 Swing-Volume-Profiles
New York, London and custom trading sessionsHi Traders
The script :
The Time sessions script plots the trading sessions of both New York and London markets (background fills), In addition to the above the script also plots a user defined trading session period (vertical lines). All plots may be toggled true or false inorder to ensure you can focus on the respective market / markets / custom session.
Market sessions are useful for technical or quantitative analysis, as the majority of trading activity and net daily volume occurs in these zones, in fact the U.S./London market overlap tends to have the greatest volume accumulation across that range of time / bars than that range at any other time within the daily session. For FX traders it may also be important to take into account for many currency pairs the average exchange rate pip movement is greatest within these zones.
The custom session, is intended to be used for traders who trade only within specific intervals within the market session or day for 24/7 traded asset classes
Additional notes :
Not as of now, I have only added three optional trading sessions. If you would like to change the sessions, copy the scripts code and change the "ctm_session" default time range value, insuring the second time value is 1 min > than the first.
As always i Hope this is a useful script, and I will be updating this script in the near future.
[DisDev] D-I-Y Gridbot🟩 This script is a “do-it-yourself” Grid Bot Simulator, used for visualizing support and resistance levels. Prices are divided into grids, or trade zones, that will trigger signals each time a new zone is entered. During ranging markets, each transaction is followed by a “take profit.” As the market starts to trend, transactions are stacked (compare to DCA ), until the market consolidates. No signals are triggered above the upper gridline or below the lower gridline. Unlike the previous version, all grids may be adjusted in real-time by dragging the gridlines up and down to the desired support and resistance levels.
When adding the indicator to a new chart, you must choose six grid levels by clicking on the desired support or resistance price. You can change all of these levels at any time directly on the chart.
⚡ OVERVIEW ⚡
The D-I-Y Gridbot is an interactive tool designed for visualizing support and resistance levels. As a continuation of the original Gridbot Simulator , which has received significant recognition on TradingView, earning over 4000 boosts and an Editor's Pick status. This tool serves not only as an evolved version of its predecessor, but also as an open-source template for developing future gridbots. It aims to foster discussions and facilitate innovations around grid-trading strategies.
One of the new features of this gridbot is the real-time adjustability of all gridlines. Users can move these lines up and down to set their desired support and resistance levels in response to changing market conditions. Additionally, the D-I-Y Gridbot is compatible with multiple timeframes and can be used on most TradingView charts.
Drag gridlines up or down to desired price level.
Key Features 🔑
All gridlines are adjustable in real-time, directly on the chart
Signals can be filtered by a customizable moving average or by VWAP
Customizable support and resistance levels
Potentially increases profitability in ranging markets
Benefits 💸
Customizable Support and Resistance Levels : The D-I-Y Gridbot allows users to set their preferred support and resistance levels, which can be changed at any time directly on the chart. This provides users with the ability to customize their trading parameters based on their strategy and risk tolerance.
Various Trading Strategies : The D-I-Y Gridbot supports various trading strategies, including Mean Reversion, Ranging Markets, and Dollar-cost averaging (DCA). This allows users to capitalize on price reversals, execute buy and sell orders at predetermined levels, and buy more of an asset as the price falls, respectively.
Multi-Timeframe and Versatility : The D-I-Y Gridbot is compatible with multiple timeframes and can be used on any TradingView chart.
Experimental and Educational : The D-I-Y Gridbot is considered a proof-of-concept tool that is both experimental and educational. This can provide traders with a deeper understanding of grid trading strategies and the ability to experiment with different trading parameters and strategies.
⚙️ CONFIGURATION & SETTINGS ⚙️
Inputs 🔧
Trigger : Candle location to trigger the signal. "Wick" will use either high or low, depending on the signal direction. "Close" will use the close price. “MA” will use the selected moving average or VWAP.
Confirmation : Market direction to confirm the candle trigger. "Reverse" will confirm the signal when the price crosses back over the trigger. "Breakout" will confirm when the price breaks out of the trigger.
Number of Support/Resistance zones : 1 = Only Top Grid is Support/Only Bottom Grid is Resistance. 2 = Top two grids are Resistance/Bottom two grids are Support. 3 = Top three grids are Resistance/Bottom three grids are Support
MA Type : Exponential Moving Average (EMA), Hull Moving Average (HMA), Simple Moving Average (SMA), Triple Exponential Moving Average (TEMA), Volume Weighted Moving Average (VWMA), Volume Weighted Average Price (VWAP)
MA Filter : Use Moving Average as a reversion filter for signals. When enabled, no buys when above MA, no sells when below. Use in conjunction with S/R zones to reduce false signals.
Allow Repeat Signals . When enabled, signals will reset when nearest gridline is triggered. When disabled, only one signal will be triggered per gridline.
Line/Fill colors
Gridlines . Adjusts gridline prices manually.
Left : Trigger = Wick. Confirm = Breakout. Buys are signaled when LOW breaks below gridline. Sells are triggered when HIGH breaks above gridline.
Right : Trigger = Close. Confirm = Breakout. Buys are signaled when the candle CLOSES below the gridline. Sells are triggered when the candle CLOSES above the gridline.
Left : Confirm=Breakout. Signals on breaking through the next gridline.
Right : Confirm=Reverse. Signals only when crossing back from the gridline.
S/R Zones=1. Upper gridline is Resistance / Lower is Support. Middle 4 are neutral.
S/R Zones = 3. Upper three gridlines are Resistance / Lower three are Support
Notes:
If gridlines are dragged out of order on a live chart, they will auto-sort into the correct order.
Price levels may be entered in settings, or adjusted in real-time directly on the chart.
When changing symbols, remember to adjust the gridlines to accommodate the new symbol.
Alerts 🔔
Users can set alerts based on their chosen parameters for triggers, confirmations, number of support/resistance zones, and smoothing type, enabling precise control over alert conditions.
💡 USAGE & STRATEGY 💡
Trading Strategies 📈
Mean Reversion: The script can be used to capitalize on price reversals back to the mean.
Ranging Markets: The script excels in ranging markets, executing buy and sell orders at predetermined levels.
Dollar-cost averaging (DCA): The script can be used to execute DCA orders, buying more of an asset as the price falls, and lowering the average cost per unit.
Timeframes and Symbols ⌚
Multi-Timeframe: The indicator is compatible with multiple timeframes.
Versatile: Can be used on any crypto trading pair on TradingView.
🤖 DETAILS & METHODOLOGY 🤖
Algorithm and Calculation 🛡️
Grids are set and adjusted when loading the indicator on the chart and may be customized anytime afterward by clicking and dragging the gridlines on the chart.
Gridlines are updated, sorted, and stored in a float array.
Signals are calculated based on candle trigger, market direction, and previous price level.
📚 ADDITIONAL RESOURCES 📚
Chart Examples 📊
S/R Zones = 3: Three Support and Three Resistance. Filter = 50-period Triple Exponential Moving Average (TEMA)
S/R Zones = 1: One Support, One Resistance, and Four Neutral Zones. Support Zones: Buys only. Resistance Zones: Sells only. Neutral Zones: Grid-dependent
When MA filter is enabled, Buys are only triggered below Moving Average, and Sells are only triggered above.
Trigger = Wick. Confirmation = Breakout. Buys are signaled when Low breaks above the next grid level. Sells are signaled when High breaks below the next grid level.
🚀 CONCLUSION 🚀
The D-I-Y Gridbot is a proof-of-concept, emphasizing its experimental and educational nature. In future versions, we will aim to incorporate concepts such as auto-adjusting grids and angled grids for trending markets. The script is designed to evolve through user feedback and suggestions, shaping its future iterations.
Credit: This is a continuation of the Gridbot series by xxattaxx-DisDev . Explicit permission was granted by user xxattaxx-disdev to re-use all Gridbot code and all materials without restrictions.
⚠️ DISCLAIMER ⚠️
This indicator is a proof-of-concept and is considered experimental and educational. When gridlines are drawn in hindsight, signals appear to be predictive and valid. Future results may always vary when the trend direction changes. Comments and suggestions are encouraged.
This indicator is provided as a tool for traders and should not be used as the sole basis for making trading decisions. Always conduct your own research and consider your risk tolerance before entering any trades.
Pi - Intraday High-Low Predictor
Pi - Intraday High-Low Predictor
This is not my Strategy/Research , I've just coded it into a indicator.
I found it interesting & useful so I'm sharing it here.
This Strategy/Research is by Kshirod Chandra Mohanty ( y-o-u-t-u-b-e : Trade with IITIAN )
You can watch his video on y-o-u-t-u-b-e for more info on this one.
the video has following title :
"1Cr Paid Strategy For Free || 10000 Subscribers Special Giveaway || How to find Day High or Low"
This will not tell you which is day high or day low, but it will help you to predict the day high from a day low and day low from a day high.
It will give you a possible range to which the prices could move to.
He has explained/used this on Banknifty.
How to Find out Day High from Day Low & Day Low from Day High :-
He uses the value of Pi (3.14) and the Range of 1st 5minute candle to find out the possible highs from day low and the possible lows from day high.
Range = value of Pi * 1st 5minutes Range
Small range = Range / 2
Large range = Range + Small range
so to find out the possible lows from day high we do following calculations
Small range low = day high - Small range
Range low = day high - Range
Large range low = day high - Large range
and to find out the possible highs from day low we do following calculations
Small range high = day low + Small range
Range high = day low + Range
Large range high = day low + Large range
Note :- This Indicator does Repaint in following ways,
As the script uses the Day High to predict the possible lows ,
so if it's an up-trending day and price keeps on making new High's then the ranges for lows will keep on changing.
similarly the script uses the Day Low to predict the possible high's ,
so if it's an down-trending day and price keeps on making new Low's then the ranges for highs will keep on changing.
My observations / thoughts about this :-
This script does not provide buy/sell recommendations. it just provides possible ranges to where prices can go from Day-High & Day-Low.
It's better to avoid trading when the price is trading between the Small range high & Small range low levels.
As it has high probability that it will be a range bound day and price will stay in between those two levels.
There is a high probability that it will be a trending day if price breaks either the Small range high/low ,
then the price could move to Range low/high.
If price breaks from Range High/Low then there is a high probability that it will be a trending day and the price could move to Large Range low/high.
Note :- If you want to use this on instruments/scripts/indexes which are active for large session such as forex/cryptos , then i suggest that you use the Opening Range period of 4Hours i.e 240minutes, to get better results.
using the default setting of 5minutes will not give good results on them.
play around with this value to find out which one suits that instrument/script/index the best.
Don't trust these levels blindly, do backtest or live testing of this then use for real trade if you want.
Use Price action near these levels to make any trading decision's.
The script provides following options :
1. Option to display Ranges in a Table (which you can enable/hide as you wish)
You can set the Table's location, size , background color & text color according to your preference.
2. Option to enable/hide Predicted-Highs from Day-Low on chart.
3. Option to enable/hide Predicted-Lows from Day-High on chart.
4. Option to set the Opening range period - here you can select your preferred opening range for calculation purpose.
5. Option to enable/hide historical levels on chart.
6. Options to customize the colors & line styles for lines.
7. Options to customize the colors , position & size for labels.
ICT Macros [LuxAlgo]The ICT Macros indicator aims to highlight & classify ICT Macros, which are time intervals where algorithmic trading takes place to interact with existing liquidity or to create new liquidity.
🔶 SETTINGS
🔹 Macros
Macro Time options (such as '09:50 AM 10:10'): Enable specific macro display.
Top Line , Mid Line , Bottom Line and Extending Lines options: Controls the lines for the specific macro.
🔹 Macro Classification
Length : A length to detect Market Structure Brakes and classify macro type based on detection.
Swing Area : Swing or Liquidity Area selection, highest/lowest of the wick or the candle bodies.
Accumulation , Manipulation and Expansion color options for the classified macros.
🔹 Others
Macro Texts : Controls both the size and the visibility of the macro text.
Alert Macro Times in Advance (Minutes) : This option will plot a vertical line presenting the start of the next macro time. The line will not appear all the time, but it will be there based on remaining minutes specified in the option.
Daylight Saving Time (DST) : Adjust time appropriate to Daylight Saving Time of the specific region.
🔶 USAGE
A macro is a way to automate a task or procedure which you perform on a regular basis.
In the context of ICT's teachings, a macro is a small program or set of instructions that unfolds within an algorithm, which influences price movements in the market. These macros operate at specific times and can be related to price runs from one level to another or certain market behaviors during specific time intervals. They help traders anticipate market movements and potential setups during specific time intervals.
To trade these effectively, it is important to understand the time of day when certain macros come into play, and it is strongly advised to introduce the concept of liquidity in your analysis.
Macros can be classified into three categories where the Macro classification is calculated based on the Market Structure prior to macro and the Market Structure during the macro duration:
Manipulation Macro
Manipulation macros are characterized by liquidity being swept both on the buyside and sellside.
Expansion Macro
Expansion macros are characterized by liquidity being swept only on the buyside or sellside. Prices within these macros are highly correlated with the overall trend.
Accumulation Macro
Accumulation macros are characterized by an accumulation of liquidity. Prices within these macros tend to range.
The script returns the maximum/minimum price values reached during the macro interval alongside the average between the maximum/minimum and extends them until a new macro starts. These levels can act as supports and resistances.
🔶 DETAILS
All required data for the macro detection and classification is retrieved using 1 minute data sets, this includes candles as well as pivot/swing highs and lows. This approach guarantees the visually presented objects are same (same highs/lows) on higher timeframes as well as the macro classification remain same as it is in 1 min charts.
8 Macros can be displayed by the script (4 are enabled by default):
02:33 AM 03:00 London Macro
04:03 AM 04:30 London Macro
08:50 AM 09:10 New York Macro
09:50 AM 10:10 New York Macro
10:50 AM 11:10 New York Macro
11:50 AM 12:10 New York Launch Macro
13:10 PM 13:40 New York Macro
15:15 PM 15:45 New York Macro
🔶 ALERTS
When an alert is configured, the user will have the ability to be notified in advance of the next Macro time, where the value specified in 'Alert Macro Times in Advance (Minutes)' option indicates how early to be notified.
🔶 LIMITATIONS
The script is supported on 1 min, 3 mins and 5 mins charts.
🔶 RELATED SCRIPTS
Volume Weighted Pivot Point Moving Averages VPPMAAs traders and investors, we are constantly on the lookout for tools that can assist us in making informed decisions. While there are countless technical analysis tools available, sometimes even small, simple scripts can provide valuable insights. In this post, we will explore the Volume-Weighted Pivot Point Moving Average (PPMA) Indicator – a modest yet helpful script that could potentially enhance your trading experience.
Background
// © peacefulLizard50262
//@version=5
indicator("PPMA", overlay = true)
vppma(left, right)=>
signal = ta.change(ta.pivothigh(high, left, right)) or ta.change(ta.pivotlow(low, left, right))
var int count = na
var float sum = na
var float volume_sum = na
if not signal
count := nz(count ) + 1
sum := nz(sum ) + close * volume
volume_sum := nz(volume_sum ) + volume
else
count := na
sum := na
volume_sum := na
sum/volume_sum
left = input.int(50, "Pivot Left", 0)
plot(vppma(left, 0))
The Concept Behind PPMA Indicator
The Volume-Weighted Pivot Point Moving Average (PPMA) Indicator is a straightforward technical analysis tool that aims to help traders identify potential market turning points and trends. It does this by calculating a moving average based on price and volume data while considering pivot highs and pivot lows. The PPMA Indicator is designed to be more responsive than traditional moving averages by incorporating volume into its calculations.
Understanding the Script
The script is compatible with version 5 of the TradingView Pine Script language, and it features an overlay setting, allowing the indicator to be plotted directly onto the price chart. The customizable pivot left input enables traders to adjust the sensitivity of the pivot points.
The script first identifies pivot points, which are areas where the price changes direction. It then calculates the volume-weighted average price (VWAP) of each trading period between the pivot points. Finally, it plots the PPMA line on the chart, providing a visual representation of the volume-weighted average prices.
Using the PPMA Indicator
To use the PPMA Indicator, simply add the script to your TradingView chart. The indicator will plot the PPMA line directly onto the price chart. You can adjust the pivot left input to modify the sensitivity of the pivot points, depending on your preferred trading style.
When the PPMA line is trending upward, it may indicate a potential bullish trend. Conversely, a downward-trending PPMA line could suggest a bearish trend. The PPMA Indicator can be used in conjunction with other technical analysis tools to confirm potential trend changes and to establish entry or exit points for trades.
Conclusion
While the Volume-Weighted Pivot Point Moving Average (PPMA) Indicator may not be a game-changer, it is a modest yet helpful tool for traders looking to enhance their technical analysis. By incorporating volume into its calculations, the PPMA Indicator aims to provide more responsive signals compared to traditional moving averages. As with any trading tool, it is crucial to conduct your own analysis and combine multiple indicators before making any trading decisions.
Trading Zones based on RS / Volume / PullbackThis is an Indicator which identifies different Trading Zones on the chart.
This should be Primarily used for Long Trades.
Trading Zones: and the Reasoning behind them
Long Zone -> One can do a Potential Entry (Buy) when this Zone is identified, but one could also wait for 'Entry Zone' (explained next) for a better Risk/Reward Trade.
Long Zones are identified with the help of Relative Strength and by an Intermediate Top in price.
Entry Zone -> This can be a better Risk/Reward zone to enter positions within the Long Zone.
Entry Zone is identified by a Pullback in Price & Volume contraction after the Long Zone is activated
Warning Zone -> One needs to be careful in this zone, no need to panic, Script will now try to find an Exit when Price Retraces towards Highs.
Warning Zone identifies weakness in the Price using Relative Strength of the current Stock (w.r.t. the Reference Symbol configured) and the severity of Pullback in Price.
Exit Zone -> are found only after transitioning to Warning Zone, this is a Zone which helps in minimising losses after a trade has gone into losses. Exit Zone is identified by making sure a local peak forms in Warning Zone. However, there are instances when Exit Zone detection can get prolonged when a local price peak is not formed soon enough. So one needs to be careful and use other strategies for exit.
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What is different in this Script:
The Script uses Relative Strength in combination with Pullback in Price from Highs in a Novel way.
Over-trading is avoided by ignoring Sideways price movements, using Relative Strength.
Only Trending Upward movement is detected and traded.
How to use this Indicator:
Use these 'Trading Zones' only as a reference so it can minimise your time in screening stocks.
Preferred Settings for using the Indicator:
Stick to 1-Day candles
Keep Relative Symbol as "Nifty" for Indian Stocks.
For US stocks, we can use "SPX" as the Relative Symbol.
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FEW EXAMPLES:
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ASIANPAINT
TATAMOTORS
TITAN
ITC
DIVISLAB
MARUTI
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Feedback is welcome.
Vertical Lines 2A vertical line plotting function is missing in Pinescript. This is another method to plot vertical line on a chart, and an improvement on my previous script "vertical lines" .
The script hacks the plotcandle function to display just the wicks without the body. This hack simulates a vertical line. The body of the candle is non-existing since the open and close are the same and its color is set to null. The wicks are abutting resulting in a continuous vertical line.
Drawbacks include inability to set width and transparency of the lines. The plotcandle function does not allow setting the width and transparency of the wicks. This feature would be desirable.
The crossing of the RSI of overbought and undersold zones is used as an example in this published script. Any indicator can be used and this script can be executed on any other indicator by using "add indicator" on the desired indicator, and selecting the indicator as the source. I added crossover lines on the plotted RSI as an example.
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The src input determines which price data is used for the highest value calculation. By default, it is set to the close price.
The length input determines the length of the RSI calculation. By default, it is set to 14.
The mult input determines the multiplier of the highest value that is used to determine the height of the vertical lines. By default, it is set to 100%, meaning the lines will reach the highest value in the dataset.
The top and bot inputs determine the overbought and oversold levels for the RSI. By default, they are set to 70 and 30, respectively.
The current_rsi and previous_rsi variables calculate the RSI values for the current bar and the previous bar, respectively.
The hi_value variable finds the highest value in the dataset, and the hi variable calculates the height of the vertical lines based on the highest value and the user-defined multiplier. The lo variable calculates the distance between the highest value and the current price data.
The uph, dnh, upl, and dnl variables determine the height and low of the vertical lines for when the RSI crosses overbought or oversold levels.
The if statements check if the RSI has crossed overbought or oversold levels and set the uph, dnh, upl, and dnl variables accordingly.
Finally, the plotcandle() function is used to plot the vertical lines on the chart. The open and close values are set to the src input, and the high and low values are set to the uph, dnh, upl, and dnl variables. The bordercolor argument is set to na to hide the borders of the lines, and the wickcolor argument is set to green or red, depending on whether the line is an overbought or oversold crossover.
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The Strat [LuxAlgo]The Strat indicator is a full toolkit regarding most of the concepts within "The Strat" methodology with features such as candle numbering, pivot machine gun (PMG) highlighting, custom combo highlighting, and various statistics included.
Alerts are also included for the detection of specific candle numbers, custom combos, and PMGs.
🔶 SETTINGS
Show Numbers on Chart: Shows candle numbering on the chart.
Style Candles: Style candles based on the detected number. Only effective on non-line charts and if the script is brought to the front.
🔹 Custom Combo Search
Combo: User defined combo to be searched by the script. Combos can be composed of any series of numbers including (1, 2, -2, 3), e.g : 2-21. No spaces or other characters should be used.
🔹 Pivot Machine Gun
Show Labels: Highlight detected PMGs with a label.
Min Sequence Length: Minimum sequence length of consecutive higher lows/lower highs required to detect a PMG.
Min Breaks: Minimum amount of broken previous highs/lows required to detect a PMG.
Show Levels: Show levels of the broken highs/lows.
🔹 Pivot Combos
Pivot Lookback: Lookback period used for detecting pivot points.
Right Bars Scan: Number of bars scanned to the right side of a detected pivot.
Left Bars Scan: Number of bars scanned to the left side of a detected pivot.
🔹 Dashboard
Show Dashboard: Displays statistics dashboard on chart.
Numbers Counter: Displays the numbers counter section on the dashboard.
Pivot Combos: Displays pivots combo section on the dashboard.
%: Display the percentage of detected pivot combos on the dashboard instead of absolute numbers.
Pivot Combos Rows: Number of rows displayed by the "Pivots Combo" dashboard section.
Show MTF: Showa MTF candle numbering on the dashboard.
Location: Location of the dashboard on the chart.
Size: Size of the displayed dashboard.
🔶 USAGE
This script allows users with an understanding of The Strat to quickly highlight elements such as candle numbers, pivot machine guns, and custom combos. The usage for these concepts is given in the sub-sections below.
🔹 Candle Numbers
The Strat assigns a number to individual candles, this number is determined by the current candle position relative to the precedent candle, these include:
Number 1 - Inside bar, occurs when the previous candle range engulfs the current one.
Number 2 Up - Upside Directional Bar, occurs when the current price high breaks the previous high while the current low is lower than the previous high.
Number 2 Down - Downside Directional Bar, occurs when the current price low breaks the previous low while the current high is higher than the previous low.
Number 3 - Outside bar, occurs when the current candle range engulfs the previous one.
The script can highlight the number of a candle by using labels but can also style candles by depending on the candle number. Inside bars (1) only have their candle wick highlighted, directional bars (2) (-2) only have their candle body highlighted. Outside bars have their candle range highlighted.
Note that downside directional bars are highlighted with the number -2.
Users can see the total amount of times a specific candle number is detected on the historical data on the dashboard available within the settings, as well as the number of times a candle number is detected relative to the total amount of detected candle numbers expressed as a percentage.
It is also possible to see the current candle numbers returned by multiple timeframes on the dashboard.
🔹 Searching For Custom Combos
Combos are made of a sequence of two or more candle numbers. These combos can highlight multiple reversals/continuation scenarios. Various common combos are documented by The Strat community.
This script allows users to search for custom combos by entering them on the Combo user setting field.
When a user combo is found, it is highlighted on the chart as a box highlighting the combo range.
🔹 Pivot Combos
It can be of interest to a user to display the combo associated with a pivot high/low. This script will highlight the location of pivot points on the chart and display its associated combo by default. These are based on the Pivot Combo lookback and not displayed in real-time.
Users can see on the dashboard the combos associated with a pivot high/low, these are ranked by frequency.
🔹 Pivot Machine Gun (PMG)
Pivot Machine Guns (PMG)s describe the scenario where a single price variation breaks the value of multiple past successive higher lows/lower highs. This can highlight a self-exciting behavior, where even more past successive higher lows/lower highs get broken.
Users can select the minimum sequence length of successive higher lows/lower highs required for a PMG to be detected, as well the amount of these successive higher lows/lower highs that must be broken.
ICT MacrosThis script allows traders to visualize the range of time when a macro (an automated series of instructions/trades from large fund traders, executed by an algorithm) will likely occur in the market. It does this by drawing vertical lines and labels on the chart at these specific times:
(Macro Open) - 9:50 AM EST
(Macro Close) - 10:10 AM EST
(Macro Open) - 10:50 AM EST
(Macro Close) - 11:10 AM EST
(Macro Open) - 1:10 PM EST
(Macro Close) - 1:40 PM EST
(Macro Open) - 3:15 PM EST
(Macro Close) - 3:45 PM EST
The theory behind the use of these macros - is that the market will either seek buy side or sell side liquidity, or seek to rebalance price at a point of interest in between the open and close of the macro. Traders who follow this theory can use that information to anticipate how price might behave.
When a macro occurs, the script draws a vertical line on the chart using a dotted line style with a user-defined color. Additionally, a label is placed above the line to indicate whether it is a Macro Open or Macro Close event.
To preserve space, the labels are abbreviated on chart - "Macro Open" (M.O.) and "Macro Close" (M.C.) for both the morning and afternoon trading sessions. The labels may be turned on/off by the user.
The script also includes alerts that can notify traders when a macro occurs. These alerts can be set to go off once per bar close, and the alert message indicates the specific macro type and time.
This script is entirely open-source, meaning that traders can read the code and modify it as needed. Credit to the foundation of this script goes to TradingView user @rickyzcarroll for his open source Strat Assistant Hour Flip script. Important changes include the specific time changes and alert function.
Wave Generator (WG)Pine Script Wave Generator Utility
Introduction:
The Pine Script Wave Generator Utility is a versatile tool that creates different wave patterns. The script provides the user with four different wave styles to choose from (Sine, Triangle, Saw, Square) with customizable parameters for the wave height, duration, number of harmonics, and phase shift.
Technical Details:
The script utilizes the mathematical functions sin, pi, and array.avg to generate wave patterns. The wave height and duration are the main inputs, and the number of harmonics and phase shift are additional inputs that add fine-tuning to the wave pattern.
The wave styles are created using different combinations of sine waves and are normalized so that the resulting wave always lies within a range of -1 to 1.
Usage:
The user can adjust the wave parameters using the input options in the script. The user can choose the wave style from the “Wave Select” option and set the wave height, wave duration, number of harmonics and phase shift by adjusting the corresponding input options.
Conclusion:
The Pine Script Wave Generator Utility is an efficient and effective tool for generating wave patterns. It can be used for a variety of purposes such as creating wave patterns for technical analysis, simulation, and testing purposes. The user can easily adjust the wave parameters to create custom wave patterns, making it a flexible and valuable tool.
