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
Wyszukaj w skryptach "the script"
Candle Close AlertCandle Close Alert (CCA) :
The "Candle Close Alert" (CCA) is a custom technical analysis tool. It operates as an overlay on price charts and serves to detect and notify users about significant changes in consecutive candle closes. The script calculates the difference between the closing price of the current candle and the previous candle, referred to as the "close difference." It then compares this close difference against a user-specified threshold value.
When the close difference exceeds the threshold, the script triggers an alert, notifying users of a potential noteworthy event. This alert can serve as a prompt for traders and investors to investigate the current price action further or to consider possible trading decisions .
Additionally, the script enhances visualization by plotting the close differences on the price chart. Positive close differences exceeding the threshold are plotted in green, while negative close differences exceeding the threshold in magnitude are plotted in red. This color-coded visualization helps users quickly identify periods of significant price movement and potential market trends.
However, it's important to note that the CCA script is a standalone tool and should be used in conjunction with comprehensive market analysis. Trading decisions should not be solely based on the alerts and visualizations provided by this script. Instead, they should be considered within the broader context of other technical indicators, fundamental analysis, and risk management strategies. Enjoy it!
Liquidity Levels/Voids (VP) [LuxAlgo]The Liquidity Levels/Voids (VP) is a script designed to detect liquidity voids & levels by measuring traded volume at all price levels on the market between two swing points and highlighting the distribution of the liquidity voids & levels at specific price levels.
🔶 USAGE
Liquidity is a fundamental market force that shapes the trajectory of assets.
The creation of a liquidity level comes as a result of an initial imbalance of supply/demand, which forms what we know as a swing high or swing low. As more players take positions in the market, these are levels that market participants will use as a historical reference to place their stops. When the levels are then re-tested, a decision will be made. The binary outcome here can be a breakout of the level or a reversal back to the mean.
Liquidity voids are sudden price changes that occur in the market when the price jumps from one level to another with little trading activity (low volume), creating an imbalance in price. The price tends to fill or retest the liquidity voids area, and traders understand at which price level institutional players have been active.
Liquidity voids are a valuable concept in trading, as they provide insights about where many orders were injected, creating this inefficiency in the market. The price tends to restore the balance.
🔶 SETTINGS
The script takes into account user-defined parameters and detects the liquidity voids based on them, where detailed usage for each user-defined input parameter in indicator settings is provided with the related input's tooltip.
🔹 Liquidity Levels / Voids
Liquidity Levels/Voids: Color customization option for Unfilled Liquidity Levels/Voids.
Detection Length: Lookback period used for the calculation of Swing Levels.
Threshold %: Threshold used for the calculation of the Liquidity Levels & Voids.
Sensitivity: Adjusts the number of levels between two swing points, as a result, the height of a level is determined, and then based on the above-given threshold the level is checked if it matches the liquidity level/void conditions.
Filled Liquidity Levels/Voids: Toggles the visibility of the Filled Liquidity Levels/Voids and color customization option for Filled Liquidity Levels/Voids.
🔹 Other Features
Swing Highs/Lows: Toggles the visibility of the Swing Levels, where tooltips present statistical information, such as price, price change, and cumulative volume between the two swing levels detected based on the detection length specified above, Coloring options to customize swing low and swing high label colors, and Size option to adjust the size of the labels.
🔹 Display Options
Mode: Controls the lookback length of detection and visualization.
# Bars: Lookback length customization, in case Mode is set to Present.
🔶 RELATED SCRIPTS
Liquidity-Voids-FVG
Buyside-Sellside-Liquidity
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AI SuperTrend Clustering Oscillator [LuxAlgo]The AI SuperTrend Clustering Oscillator is an oscillator returning the most bullish/average/bearish centroids given by multiple instances of the difference between SuperTrend indicators.
This script is an extension of our previously posted SuperTrend AI indicator that makes use of k-means clustering. If you want to learn more about it see:
🔶 USAGE
The AI SuperTrend Clustering Oscillator is made of 3 distinct components, a bullish output (always the highest), a bearish output (always the lowest), and a "consensus" output always within the two others.
The general trend is given by the consensus output, with a value above 0 indicating an uptrend and under 0 indicating a downtrend. Using a higher minimum factor will weigh results toward longer-term trends, while lowering the maximum factor will weigh results toward shorter-term trends.
Strong trends are indicated when the bullish/bearish outputs are indicating an opposite sentiment. A strong bullish trend would for example be indicated when the bearish output is above 0, while a strong bearish trend would be indicated when the bullish output is below 0.
When the consensus output is indicating a specific trend direction, an opposite indication from the bullish/bearish output can highlight a potential reversal or retracement.
🔶 DETAILS
The indicator construction is based on finding three clusters from the difference between the closing price and various SuperTrend using different factors. The centroid of each cluster is then returned. This operation is done over all historical bars.
The highest cluster will be composed of the differences between the price and SuperTrends that are the highest, thus creating a more bullish group. The lowest cluster will be composed of the differences between the price and SuperTrends that are the lowest, thus creating a more bearish group.
The consensus cluster is composed of the differences between the price and SuperTrends that are not significant enough to be part of the other clusters.
🔶 SETTINGS
ATR Length: ATR period used for the calculation of the SuperTrends.
Factor Range: Determine the minimum and maximum factor values for the calculation of the SuperTrends.
Step: Increments of the factor range.
Smooth: Degree of smoothness of each output from the indicator.
🔹 Optimization
This group of settings affects the runtime performances of the script.
Maximum Iteration Steps: Maximum number of iterations allowed for finding centroids. Excessively low values can return a better script load time but poor clustering.
Historical Bars Calculation: Calculation window of the script (in bars).
SuperTrend AI (Clustering) [LuxAlgo]The SuperTrend AI indicator is a novel take on bridging the gap between the K-means clustering machine learning method & technical indicators. In this case, we apply K-Means clustering to the famous SuperTrend indicator.
🔶 USAGE
Users can interpret the SuperTrend AI trailing stop similarly to the regular SuperTrend indicator. Using higher minimum/maximum factors will return longer-term signals.
The displayed performance metrics displayed on each signal allow for a deeper interpretation of the indicator. Whereas higher values could indicate a higher potential for the market to be heading in the direction of the trend when compared to signals with lower values such as 1 or 0 potentially indicating retracements.
In the image above, we can notice more clear examples of the performance metrics on signals indicating trends, however, these performance metrics cannot perform or predict every signal reliably.
We can see in the image above that the trailing stop and its adaptive moving average can also act as support & resistance. Using higher values of the performance memory setting allows users to obtain a longer-term adaptive moving average of the returned trailing stop.
🔶 DETAILS
🔹 K-Means Clustering
When observing data points within a specific space, we can sometimes observe that some are closer to each other, forming groups, or "Clusters". At first sight, identifying those clusters and finding their associated data points can seem easy but doing so mathematically can be more challenging. This is where cluster analysis comes into play, where we seek to group data points into various clusters such that data points within one cluster are closer to each other. This is a common branch of AI/machine learning.
Various methods exist to find clusters within data, with the one used in this script being K-Means Clustering , a simple iterative unsupervised clustering method that finds a user-set amount of clusters.
A naive form of the K-Means algorithm would perform the following steps in order to find K clusters:
(1) Determine the amount (K) of clusters to detect.
(2) Initiate our K centroids (cluster centers) with random values.
(3) Loop over the data points, and determine which is the closest centroid from each data point, then associate that data point with the centroid.
(4) Update centroids by taking the average of the data points associated with a specific centroid.
Repeat steps 3 to 4 until convergence, that is until the centroids no longer change.
To explain how K-Means works graphically let's take the example of a one-dimensional dataset (which is the dimension used in our script) with two apparent clusters:
This is of course a simple scenario, as K will generally be higher, as well the amount of data points. Do note that this method can be very sensitive to the initialization of the centroids, this is why it is generally run multiple times, keeping the run returning the best centroids.
🔹 Adaptive SuperTrend Factor Using K-Means
The proposed indicator rationale is based on the following hypothesis:
Given multiple instances of an indicator using different settings, the optimal setting choice at time t is given by the best-performing instance with setting s(t) .
Performing the calculation of the indicator using the best setting at time t would return an indicator whose characteristics adapt based on its performance. However, what if the setting of the best-performing instance and second best-performing instance of the indicator have a high degree of disparity without a high difference in performance?
Even though this specific case is rare its however not uncommon to see that performance can be similar for a group of specific settings (this could be observed in a parameter optimization heatmap), then filtering out desirable settings to only use the best-performing one can seem too strict. We can as such reformulate our first hypothesis:
Given multiple instances of an indicator using different settings, an optimal setting choice at time t is given by the average of the best-performing instances with settings s(t) .
Finding this group of best-performing instances could be done using the previously described K-Means clustering method, assuming three groups of interest (K = 3) defined as worst performing, average performing, and best performing.
We first obtain an analog of performance P(t, factor) described as:
P(t, factor) = P(t-1, factor) + α * (∆C(t) × S(t-1, factor) - P(t-1, factor))
where 1 > α > 0, which is the performance memory determining the degree to which older inputs affect the current output. C(t) is the closing price, and S(t, factor) is the SuperTrend signal generating function with multiplicative factor factor .
We run this performance function for multiple factor settings and perform K-Means clustering on the multiple obtained performances to obtain the best-performing cluster. We initiate our centroids using quartiles of the obtained performances for faster centroids convergence.
The average of the factors associated with the best-performing cluster is then used to obtain the final factor setting, which is used to compute the final SuperTrend output.
Do note that we give the liberty for the user to get the final factor from the best, average, or worst cluster for experimental purposes.
🔶 SETTINGS
ATR Length: ATR period used for the calculation of the SuperTrends.
Factor Range: Determine the minimum and maximum factor values for the calculation of the SuperTrends.
Step: Increments of the factor range.
Performance Memory: Determine the degree to which older inputs affect the current output, with higher values returning longer-term performance measurements.
From Cluster: Determine which cluster is used to obtain the final factor.
🔹 Optimization
This group of settings affects the runtime performances of the script.
Maximum Iteration Steps: Maximum number of iterations allowed for finding centroids. Excessively low values can return a better script load time but poor clustering.
Historical Bars Calculation: Calculation window of the script (in bars).
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.
Heikin Ashi ROC Percentile Strategy**User Guide for the "Heikin Ashi ROC Percentile Strategy"**
This strategy, "Heikin Ashi ROC Percentile Strategy", is designed to provide an easy-to-use framework for trading based on the Heikin Ashi Rate of Change (ROC) and its percentiles.
Here's how you can use it:
1. **Setting the Start Date**: You can set the start date for the strategy in the user inputs at the top of the script. The variable `startDate` defines the point from which the script begins executing trades. Simply input the desired date in the format "YYYY MM DD". For example, to start the strategy from March 3, 2023, you would enter `startDate = timestamp("2023 03 03")`.
2. **Adjusting the Midline, Lookback Period, and Stop Loss Level**: The `zerohLine`, `rocLength`, and `stopLossLevel` inputs allow you to adjust the baseline for ROC, the lookback period for the SMA and ROC, and the level at which the strategy stops the loss, respectively. By tweaking these parameters, you can fine-tune the strategy to better suit your trading style or the particular characteristics of the asset you are trading.
3. **Understanding the Trade Conditions**: The script defines conditions for entering and exiting long and short positions based on crossovers and crossunders of the ROC and the upper and lower "kill lines". These lines are defined as certain percentiles of the ROC's highest and lowest values over a specified lookback period. When the ROC crosses above the lower kill line, the script enters a long position; when it crosses below the upper kill line, it exits the position. Similarly, when the ROC crosses below the upper kill line, the script enters a short position; when it crosses above the lower kill line, it exits the position.
In my testing, this strategy performed best on a day and hour basis. However, I encourage you to experiment with different timeframes and settings to see how the strategy performs under various conditions. Remember, there's no one-size-fits-all approach to trading; what works best will depend on your specific circumstances, goals, and risk tolerance.
If you find other useful applications for this strategy, please let me know in the comments. Your feedback is invaluable in helping to refine and improve this tool. Happy trading!
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.
------------------------------------------------------------------------------------
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.
//----------------
FEW EXAMPLES:
//----------------
ASIANPAINT
TATAMOTORS
TITAN
ITC
DIVISLAB
MARUTI
---------------------------------------------
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.
//////////////////////////////////////////////////////Breakdown of the script////////////////////////////////////////////////////////
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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