Ichimoku Strategy - Easiest Backtest [A.R.]▓ INTRODUCTION
This indicator allows a new "sandbox" approach to the Ichimoku system allowing to combine several entry, confirmation and exit conditions, to add basic risk management, to be able to backtest the performance of the strategy using a table directly on chart, and automate entry and exit signals using alerts.
▓ DEFINITION
The Ichimoku strategy is a trading system based on technical analysis, using a set of graphical indicators to evaluate the trend, strength and support/resistance levels of a financial asset. It integrates components such as the conversion line (Tenkan), the baseline (Kijun), the cloud delimited by the Senkou Span A and the Senkou Span B (SSA - SSB - Kumo) and the lagging span (Chikou) to provide different trading signals.
▓ ADDED VALUE
Several indicators and strategies concerning Ichimoku are already available on Tradingview, we are publishing this indicator to make this strategy even more accessible, what makes it original:
▪️ Unique Settings Windows, easy-to-read. The settings categories are clearly separated. Some parameters are aligned to avoid having an endless list of parameters to modify. This makes the settings window easy to understand and pleasant to use.
▪️ Sandbox type settings, you can choose 1 or 2 Entry conditions, choose to add 1 Confirmation, choose to add between 1 and 3 Exit Conditions. Dozens of possible configurations.
▪️ Possibility of adding basic Risk Management (TP/SL)
▪️ Backtest table directly on chart that allow to get quickly the results (script execution <1 sec) which makes it practical, allowing dozens of different configurations to be tested in a short period of time
▪️ Monitoring historical and current trades on chart thanks to Boxes and Labels
▓ HOW TO USE
You can try the indicator with default settings but you can also modify backtesting settings and trade Entry conditions, Entry Confirmation, and Exit conditions, also you can decide to add a Stop Loss and/or a Take Profit. Then you can find the stats of the backtesting in a table directly in the top right corner of the chart. Finally you can automate the strategy using Alert conditions. You can find all the settings below:
Initial backtesting settings:
🔹Set up Side: Choose Long|Short, Long or Short
🔹Set up Investment: Choose an amount in $, it simulates the equity / funds on the trading account.
🔹Set up Position Size: Choose an amount in $, it simulates the amount of the position size of each trade. If you want to simulate leverage trading, you can put a Position Size superior to Investment. For exemple Investment = 10000 and Position Size = 20000 simulates a x2 leverage.
🔹Set up your Fee rate %: Each trade entry and trade exit, a % of position size will be deducted from the PnL stats. For example if you choose 0.04% with 10000 Position Size, 4$ will be deducted each trade entry and each trade exit = 8$ fees each trade.
🔹Set up the Start and End date: It allows to backtest the strategy over a period of time, for Example from 01-01-2021 to 01-12-2022. By default the end date is year 2050, the backtest will start to take into account data from Start Date to the current time.
Backtest the main Ichimoku sub-strategies choosing entry conditions:
🔸Cloud Breakouts trading: Choose this Entry condition to start a trade when Price crosses the Cloud Upside (Long) or Downside (Short)
🔸Tenkan x Kijun cross trading: Choose this Entry condition to start a trade when Tenkan (Red line) crosses Kijun (Blue line) Upside (Long) or Downside (Short)
* There is no repaint, a signal is validated after the condition is confirmed at the end of the previous candle. If a signal appears on the chart, it won't ever disappear.
Entry Confirmations:
✔️ Chikou Above or Below price: if you check this setting, Long entry signals will be confirmed only when the Chikou (White Line) is Above the current price and Short entry signals will be confirmed only when the Chikou (White Line) is below the current price. In the Ichimoku system the Chikou is often used to confirm all types of signals.
Exit Conditions:
❌ Cloud Reintegrations: When a trade is open (Long or Short), if the price goes back into the cloud the trade is closed
❌ Reverse Cloud Breakouts: When a Long trade is open, if the price breaks out of the cloud from below the trade is closed. When a Short trade is open, if the price breaks out of the cloud from above the trade is closed.
❌ Reverse Tenkan-Kijun Cross: When a Long trade is open, if the Tenkan crosses Downside the Kijun the trade is closed. When a Short trade is open, if the Tenkan crosses Upside the Kijun the trade is closed.
Basic Risk Management:
⛔️ SL: Choose to set up a Stop Loss
✅ 1 single TP: Choose to set up a Take Profit
Signals:
🔔 Entry/Exit Alerts available: 4 types of alert conditions are available ENTRY LONG, ENTRY SHORT, EXIT LONG, EXIT SHORT. The entry conditions trigger at the beginning of the candle, choose alert frequence = once per bar.
👉 Tips: Easier to find profitable configurations in High Timeframe above H4.
▓ BACKTESTING SYSTEM
The Backtesting system integrated into the script tracks each trade. It allows you to test the strategy over a fixed period between a start date and an end date. It also allows to quickly and directly display on the chart the most important data to determine if a configuration is profitable such as the % PnL, the Max Drawdown, the amount of fees, the risk-reward ratio. It has been designed to be easy and quick to use even for a beginner.
═════════════════════════════════════════════════════════════════════════
The information published here on TradingView is not prohibited, doesn't constitute investment advice, and isn't created solely for qualified investors.
Important to note: The source code of this indicator is not accessible because it benefits from the code of our backtesting system present in other non-public indicators that we protect. Our indicators with the same backtesting system are published in separate publications because putting them together in a single script would considerably slow down the execution of the script.
Statistics
Sessions [TradingFinder] New York, London, Tokyo & Sydney ForexTiming is one of the influential factors in a trader's position. This indicator categorizes transactions into three sessions (Asia, Europe, and America). Five significant trading cities (New York, London, Frankfurt, Tokyo, and Sydney) are selectable.
I recommend using the tool on a 5-minute time frame, but it is usable on all time frames.
Settings:
• Trading sessions: Display or hide each trading session as needed.
• Color: Change the color of each box.
• Session time intervals: The default is based on the main working hours for each time interval and can be adjusted.
• Information table: Delete or display additional information table.
Information Table:
• Trading sessions
• Opening and closing times of each trading session
How to Use:
Initiating trading sessions involves entering with increased liquidity, and the market usually experiences significant movements. Many trading strategies are based on "time" and "session openings." This tool empowers traders to focus intensely on each time interval.
These trading sessions are crucial for all Forex, stock, and index traders:
The total price ceiling and floor in the Asia session (Tokyo and Sydney) are crucial for traders in the European session.
The European session starts with Frankfurt, and an hour later, London begins, collectively forming the European session.
The dashboard provides additional information, displaying hours based on UTC.
Customization options are considered in all sections so that everyone can apply their own settings.
Important: Default times are the most accurate for each region, and in most indicators, this time is not correctly selected. Therefore, the level of influence and time intervals are specified at the beginning of each session. If you are using another indicator, match its default time to the announced time and share the results with me in the comments.
Kendall's Tau Correlation Regimes [NariCapitalTrading]The "Kendall's Tau Correlation Regimes" indicator is designed to analyze price data and determine market regimes based on Kendall's Tau correlation coefficient. It provides insight into the strength and direction of the correlation between two data series: close price and a selected moving average.
User Inputs:
Period: Defines the lookback period for calculating Kendall's Tau correlation. It can be adjusted using the input slider, with a minimum value of 1.
Threshold: Sets the threshold for identifying bullish and bearish market regimes. The user can adjust this value within the range of 0.1 to 1.0 with step increments of 0.1.
MA Type: Allows users to select the type of moving average to be used in the correlation calculation. Options include Simple Moving Average (SMA), Exponential Moving Average (EMA), and Hull Moving Average (HMA).
Kendall's Tau Correlation Calculation:
Calculates Kendall's Tau correlation coefficient between the closing price and the selected moving average.
Kendall's Tau measures the strength and direction of the ordinal association between two data series. It assesses whether the data pairs are in the same order or not.
The calculation involves counting concordant and discordant pairs of data points and then computing the coefficient.
Market Regime Identification:
Based on the threshold defined by the user, the indicator identifies two market regimes: bullish and bearish.
A regime is considered bullish when the Kendall's Tau correlation coefficient is greater than the threshold.
A regime is considered bearish when the Kendall's Tau correlation coefficient is less than the negative of the threshold.
Plotting:
The indicator plots the calculated Kendall's Tau correlation coefficient as a blue line on a separate indicator pane.
It also highlights bullish regimes with a green background and bearish regimes with a red background.
Conclusion:
The "Kendall's Tau Correlation Regimes" indicator provides traders with a visual aid for assessing market regimes based on the strength of correlation between price and a selected moving average.
Disclaimer: This indicator is for educational and informational purposes only.
Least Median of Squares Regression | ymxbThe Least Median of Squares (LMedS) is a robust statistical method predominantly used in the context of regression analysis. This technique is designed to fit a model to a dataset in a way that is resistant to outliers. Developed as an alternative to more traditional methods like Ordinary Least Squares (OLS) regression, LMedS is distinguished by its focus on minimizing the median of the squares of the residuals rather than their mean. Residuals are the differences between observed and predicted values.
The key advantage of LMedS is its robustness against outliers. In contrast to methods that minimize the mean squared residuals, the median is less influenced by extreme values, making LMedS more reliable in datasets where outliers are present. This is particularly useful in linear regression, where it identifies the line that minimizes the median of the squared residuals, ensuring that the line is not overly influenced by anomalies.
STATISTICAL PROPERTIES
A critical feature of the LMedS method is its robustness, particularly its resilience to outliers. The method boasts a high breakdown point, which is a measure of an estimator's capacity to handle outliers. In the context of LMedS, this breakdown point is approximately 50%, indicating that it can tolerate corruption of up to half of the input data points without a significant degradation in accuracy. This robustness makes LMedS particularly valuable in real-world data analysis scenarios, where outliers are common and can severely skew the results of less robust methods.
Rousseeuw, Peter J.. “Least Median of Squares Regression.” Journal of the American Statistical Association 79 (1984): 871-880.
The LMedS estimator is also characterized by its equivariance under linear transformations of the response variable. This means that whether you transform the data first and then apply LMedS, or apply LMedS first and then transform the data, the end result remains consistent. However, it's important to note that LMedS is not equivariant under affine transformations of both the predictor and response variables.
ALGORITHM
The algorithm randomly selects pairs of points, calculates the slope (m) and intercept (b) of the line, and then evaluates the median squared deviation (mr2) from this line. The line minimizing this median squared deviation is considered the best fit.
DISCLAIMER
In the LMedS approach, a subset of the data is randomly selected to compute potential models (e.g., lines in linear regression). The method then evaluates these models based on the median of the squared residuals. Since the selection of data points is random, different runs may select different subsets, leading to variability in the computed models.
Autocorrelation Candles [SS]Hey everyone, this is the Autocorrelation Candles indicator!
I have formulated it in a way that is similar to the TD 9 candle counting indicators, only instead of TD, its using a lagged autocorrelation of previous candle over a 14 period look back.
It operates similar to trend correlations (for example, my Trend Correlation Oscillator Indicator), however instead of correlating to time, it correlates to itself (autoregression). The theory being, as the autoregression correlation increases and the market becomes too "trendy", we are due for a reversal.
The indicator will display the current lagged correlation of each candle below it. When we approach a period of previous reversal, it will change the colour to orange. When we reach a very high autocorrelation (0.94 or greater), it will turn red and signal a potential reversal to the upside or downside:
Uses:
I will reference this on the larger timeframes (Daily, weekly and 4 hour) about a couple times a week or after a major trend day to see where we are.
You can use this on the smaller timeframes as well, it will work just fine.
Customizations:
I have been listening and learning my lesson, I have made the ability to customize the base text colour to black or white depending on your theme use! SO if you have white theme, you can change to black and vice versa.
As well, if you don't want labels on every candle, in the settings menu there is an option to limit the labels to a desired amount. You select the max amount and it will adjust.
You can also adjust the size of the labels between tiny, medium, and large.
Conclusion
And that's the indicator! Despite being fairly simple in concept, I have been working away on it for a bit with some logistic issues that I finally got sorted.
Hopefully, you enjoy,
Leave your questions below!
Safe trades everyone!
Advanced Volume Analytics and Distribution IndicatorThe Advanced Volume Analytics and Distribution Indicator is a sophisticated tool designed for financial analysts and traders who seek in-depth insights into market volume dynamics. This Pine Script-based indicator is a comprehensive solution, offering a rich set of features that analyze volume data using various statistical methods and theories. It's tailored for those who require a deeper understanding of market movements and volume distribution.
Key Features:
Volume Distribution Analysis: Utilizes standard deviation and mean calculations to analyze the distribution of trading volume. Employs z-scores to measure the standard deviations of volume from its mean, offering insights into volume anomalies.
Bell Curve Modeling: Constructs a bell curve (normal distribution) based on volume data, enabling users to visualize and assess the distribution of volume in a standard statistical format.
Provides a z-score based bell curve, offering a normalized view of volume deviations.
Exponential Smoothing: Applies exponential smoothing to volume data, giving more weight to recent observations. This feature is crucial for analyzing trending behaviors in volume data.
Stress Metric Calculation: Introduces a unique 'stress' metric, calculated using a custom formula. This metric is designed to evaluate the volatility or variability in the volume data over a specified period.
Central Limit Theorem (CLT) Mean Estimation: Implements CLT for estimating the mean of volume data. The CLT states that the distribution of sample means approximates a normal distribution as the sample size becomes larger.
Variance Point Estimation: Calculates the variance of volume data, providing insights into its variability and consistency over time.
Chi-Squared Test (Commented): Although not active in the initial release, the script includes a framework for a Chi-Squared Test to compare observed and expected volume frequencies, offering potential for future statistical comparisons.
Percentile Calculations and Convolution: Performs percentile calculations on volume data and employs convolution to these percentiles, enabling a more nuanced analysis of volume distribution.
Customizability: Users can input various parameters like anchor period, degrees of freedom, and smoothing preferences, making the tool adaptable to different analysis needs.
Visualization and Plotting: Features multiple plots for easy visualization of volume metrics, including stress, bell curves, point estimators, and smoothed data.
Theoretical Foundations:
This indicator is grounded in established statistical theories and methods, including the Central Limit Theorem, Chi-Squared Test (for future implementations), and convolution techniques. These foundations ensure that the indicator not only provides practical insights but also maintains a high standard of statistical rigor.
Intended Users:
This indicator is ideal for technical analysts, traders, and financial professionals who require a deep and statistically sound understanding of market volume behavior.
Release Notes:
This tool is designed a theoretical test of established statistical models and requires familiarity with Pine Script for customization. Future updates may include activation and expansion of the Chi-Squared Test functionality and additional statistical modules based on user feedback. It should be noted that it is advisable to use a logarithmic-inverted scale; when combined, these scales can provide a unique perspective that neither could offer alone. This combination might be particularly useful in highlighting exponential growth or decay trends, or in cases where the most significant data points are in the lower range of the dataset.
Notes of Stress Calculations:
The "stress metric" in the script is a custom-designed feature intended to measure the level of variability or volatility in the volume data over a given time period. This metric is calculated using a novel approach with concepts similar to those used in the field of engineering , particularly in stress analysis and finite element analysis (FEA).
Segmentation of Time Frame:
The script divides the given time frame (timeFrame) into smaller segments based on a specified number of units (units). This segmentation essentially breaks down the entire period into smaller, more manageable intervals for analysis. For each segment, the script calculates a 'stress' value. This involves iterating through each segment and performing calculations based on the source data (src), the default src is the volume data.
Calculation per Segment:
For each segment, the script identifies two points: the starting point (x1) and the ending point (x2). It then retrieves the corresponding values of the source data at these points (y1 and y2).
It calculates the difference in the x-axis (delta_x, the length of the segment) and the difference in the y-axis (delta_y, the change in volume over that segment).
Stress Calculation:
The script then calculates the 'stress' for each segment as the ratio of delta_y to delta_x. This ratio gives a measure of how much the volume has changed per unit of time within each segment. The stress values for each segment are then summed up to provide a cumulative measure of stress over the entire time frame.
The stress metric is essentially a measure of the volatility or variability in volume data. High stress values indicate larger changes in volume over shorter periods, suggesting more volatile market conditions. For traders and analysts, understanding the level of volatility is crucial. It can inform decision-making processes, risk management strategies, and provide insights into market sentiment. By comparing stress levels across different time frames or different securities, analysts can gain insights into relative market dynamics.
KD Momentum MatrixI believe many traders think that fluctuation is very troublesome. The money earned in the trends is easily lost in the fluctuation. Because it is hard to find the high and low points of range.
Indicator: KD Momentum Matrix is the best choice for analyzing fluctuation, with potential volatility reminder.
KD Momentum Matrix is not only a momentum indicator, but also a short-term indicator. It divides the movement of the candle into long and short term trends, as well as bullish and bearish momentum. It identifies the points where the bullish and bearish momentum increases and weakens, and effectively capture profits.
💠Usage：
Potential volatility reminder:
"strong" represents an increase in potential volatility, indicating that the fluctuation of the candles may increase in the future.
"weak" represents a decrease in potential volatility, indicating that the fluctuation of the candles may decrease in the future.
Momentum column:
·The short-term momentum column, the "green and red columns", represents the short-term bullish and bearish momentum, and is the main reference feature of this indicator.
·Long term momentum columns, known as "dark green and purple columns", represent long-term bullish and bearish momentum and serve as auxiliary reference feature.
Note: Long and short term momentum columns usually have the same direction, and in rare cases, they may deviate. Sometimes there may be overlapping long and short term columns. The reference bullish and bearish directions are consistent regardless of the long and short term.
🎈Tip I：
When there is a potential volatility reminder: "weak" or "strong", it is important to note that there may be something different on amplitude of fluctuation in the future. If you have a position, you need to think new about the direction of your position.
🎈Tip II：
Taking the main reference feature - the short-term momentum column as an example, when the momentum column changes from red to green, it indicates short-term bullishness, and there may be a small upward trend. If the price happens to be near the bottom of the visible range at this time, consider executing a round of opening long positions or closing short positions.
When holding a long position, the bearish signal indicated by the momentum bar is used for departure, i.e. the momentum bar changes from green to red.
🎈Advanced tip I：
Deviation. The long and short term momentum columns are mostly consistent, but occasionally there may be deviations, indicating intense competition between bulls and bears. In the short term, it is recommended not to engage in trading because of its high uncertainty.
🎈Advanced tip II：
Volatility indicators can also be used in trends, but it is important to remember the idea of following the trend. For example, when there is a callback during an upward trend, we choose to buy or add a long position when the momentum bar becomes a long signal.
*The signals in the indicators are for reference only and not intended as investment advice. Past performance of a strategy is not indicative of future earnings results.
Update -
Optimize the alarm function. If you need to monitor the "strong " or "weak" signal, when creating an alarm, set the condition bar to:
KD Momentum Matrix --> "strong " or "weak" --> Crossing Up --> value -> 1
Universal RPPI Indices & Futures [SS Premium]Hello everyone,
For the much-anticipated indicator release, the universal RPPI for Futures and Indices!
If you follow me, chances are you know this indicator by now, since its the basis of all of my analyses and target prices, but if not, let me introduce you!
What is it?
The RPPI for Indices & Futures is essentially a compendium indicator. It contains hundreds of, just over 100 different math models of various futures and indices.
These models are designed to forecast the current targets on multiple timeframes including:
1. The daily
2. The weekly
3. The monthly
4. The Three Month (for SPY and QQQ ONLY)
5. The 6 Month (for DJI, SPX and USOIL/CLI1! ONLY)
6. The annual (for DJI, SPX and USOIL/CLI1! ONLY)
7. The 3 hour
So I will go over the details of the models within the indicators compendium and how they are produced. If you are not interested, just skip to the next section!
What is a model and how is it produced?
Models are math equations and frameworks that attempt to predict future behavior. They are developed in many ways and through many methods. In this particular indicator, each index and future is unique and has been created in various ways, such as using principles of data smoothing, data interpolation, data substitution and data omission.
All this means is, I have manually adjusted model parameters to correct for rare, outlier events. The outcome is having a more accurate model that is better prepared to predict what you want it to predict.
Now let's get into the indicator use.
The first thing we need to talk about is selecting a model type. Different model types are available on a handful of stocks in the indicator, such as SPY, QQQ, DJI and DIA, and so it is important to explain the difference.
Corrected vs Uncorrected Models (i.e. Low Precision vs High Precision Models)
In the settings menu, you will see the second option that reads "Precision". This is where you have the ability to select the model type.
"High Precision" is a corrected model. It is a model that I have used data manipulation for (like the examples above) to enhance its accuracy.
"Low Precision" is a UNCORRECTED model. These models have undergone no data manipulation and are just raw projections.
Which do you use?
There are only a handful of tickers that have both models, like SPY, GLD1! and DJI (among others). Some tickers perform better with low precision models, others perform better with high precision models.
To know what model works best with which stock, the indicator will tell you. At the bottom of the settings table, simply select "Show Model Data":
Selecting this, you will get a table that looks like this:
It will tell you the available model types and which one works best. For IWM, the high-precision corrected model is best. This is true for QQQ and NQ1! as well. However, for SPY and ES1!, the uncorrected model is actually better:
Sometimes, different models perform better at various levels of precision, for example, high on the monthly but low on the daily.
This is why I have omitted this option for the majority of stocks. I don't want this to be confusing to use. For 90% of the included tickers, I have selected the model of best fit. However, for a few of the very popular and volatile tickers (ES, NQ specifically), I have included the ability to use both.
Rule of Thumb:
The rule of thumb with selecting high vs low, is essentially this:
a) If the market is hugely volatility with major swings intraday that exceed its normal behaviour, switch to the low precesion model. This will not be skewed by the massive swings.
b) If the market is stable, trendy or range bound, but not trending beyond its normal, general behaviour, keep it at high precision.
With that, you will be good to go!
Using the indicator:
The indicator is intended as a standalone indicator. Of course, you can combine other indicators that you like to help you out, but there is a strategy version of this that will be released within the coming days/weeks, as this is intended to be a full strategy in and of itself.
As with the universal forecaster, you are given threshold levels that are labelled "Bullish Condition" and "Bearish Condition", a break and hold of the "Bullish Condition" and it is a long to the high targets. Inverse for the bearish condition.
In addition to these conditionals, the indicator also provides you with a high probability retracement level. These are available on the weekly, monthly and higher timeframes. A special moving retracement level is available for SPY only, however it moves based on the PA to give you a sort of POC.
Testing Model Performance:
It is possible to see model performance. At the bottom of the settings menu, select the option to "Show Demographic Data". You need to be sure you are on the chart of the selected timeframe.
This is ES1! on the daily timeframe. It shows you the demographics, i.e. the extent targets are hit, the extent that the high prob retracement targets are missed, the extent that ES closes in and out of its daily range.
This is very valuable information. This table is essentially saying there is only a 10% chance that ES will close above its range and a 9% chance ES closes below its range. This means, that the most ideal setups are a move outside of its range!!
You can view it on all timeframes. If your chart isn't aligned with the lookback, you will get a warning sign:
Misc Functions:
Show price accumulation:
There is an option to toggle on price accumulation. It will show you the amount of accumulation in each of the ranges:
This will show where the accumulation of price rests in relation to the targets.
Autoregression Assessment:
You can have the indicator plot an autoregressive trendline of the expected stock trajectory. You can select the forecast length and it will plot the direction it suspects the stock will go:
Show Standard Deviation:
In the menu, you can toggle on the show standard deviation function. This will plot the standard deviation that each price rests at. The default timeframe for standard deviation is the daily. If you are looking at the weekly, please select the weekly timeframe.
This is helpful because you can see which targets are likely based on where the standard deviation rests. In the above example, a move to the low range would be a move to -2 standard deviations and beyond. This is not something that a ticker would normally do in general circumstances.
FAQ Table:
There is also an option to display an FAQ table. This will show you model revisions and pending revision dates. This will allow you to see when each model was last updated and when new updates will be pushed:
Which models does this contain?
The indicator contains models for the following stocks:
SPY
QQQ
DIA
DJI
ES1!
SPX
NQ1!
NDX
SOXX
IWM
RTY
GCL1! (Gold)
CL1! / USOIL (Oil)
XLE
XLF
YM1!
And some more are in the works (like JETS).
NOTE: Feel free to leave a comment of future ones you would like to see!
The indicator will automatically select the model for whichever ticker you are on.
Some models are cross-compatible, such as CL1! and USOIL, but the indicator is programmed to recognize those that are cross-compatible and auto-select those models.
From there, you just need to select the timeframe you wish to view!
And that is the indicator! I know very wordy explanation but wanted to cover all basis on the indicator so you can be well prepared!
As always, leave your questions, and comments below, and safe trades!
Autoreg Trend Clouds [SS Premium]This is the autoregressive (or Autoreg) trend cloud indicator included in the Pro and Elite trading level.
About:
The autoregressive trend clouds operate on 2 major statistical concepts, as the name implies, the use of autoregression being the primary facet, as well as the use of an ANOVA statistical analysis of mean variance. I will elaborate on each of these below, but first will discuss the gist of what the indicator does.
The indicator plots the expected range based on an autogenerated autoregressed model of the stock. The indicator will train itself for lookback time and for modelling and will fit a model to whichever ticker, index, FOREX or crypto, etc. you are on.
These clouds represent the anticipated range for an instrument to fall in based on its current trend and its autoregressed relationship.
Below is an example with BTC on the 1 hour:
And QQQ on the 1 hour:
Autoregression:
The autoregression model uses an automatic trend identifier to identified the appropriate lookback length. It then generates two types of models, a lag 1 model (1 lag autoregression back) and a 3 lag model (using the last 3 lags, or candles, to create a model). It then compares which model is stronger and selects the best fit. It identifies this by looking at the R (correlation) of the models performance.
ANOVA:
ANOVA stands for Analysis of Variance. It is a statistical test commonly used in comparative analyses based research. What it does is it compares the statistical significance of the variance between a group of means. In this indicator, the ANOVA is uses 3 variables, the lagged high, lagged low and lagged close value over a 14 candle lookback period. In my observations, these settings have been very useful in identifying pivots and breakouts when a significant ANOVA is triggered.
There are two ways to visualize this with this indicator. The first is by just looking at the chart. When a significant ANOVA results, the chart will display "Reversal" (see below):
Reversal is a bit of a misnomer, because it doesn't always mean that a "reversal" will happen, but that a big move is coming. In this case, the stock broke out to the upside.
How do you know which direction it will go? You can get an idea based on the position within the cloud, for example, when it is at the bottom of the range, reversal signals tend to mean it will go up:
But what it does more importantly is puts you on alert that something is about to happen, whether it is a pivot or a breakout/down.
ANOVA has also been applied to buy and sell signals that the indicator produces:
The indicator will look at the SMA of the ANOVA, as well as the position of the stock in relation to the autoregerssion model, and decide when to signal a sell or buy signal. Generally, the parameters are a significant ANOVA that is above its SMA and a move outside of the expected range.
There is another way to visualize the ANOVA using this indicator, and that is with the candle counting chart:
This will show you areas of significance over the last 31 candles, so you can identify precise areas of reversals in the most recent trading history. The table and candle numbers can be toggled off as well.
Significance Value:
And important note needs to be made about the significance value. ANOVA requires a "critical value", a value that must be met in order for something to be deemed "statistically significant". There are different levels of critical values for ANOVA based on the desired confidence. All this means is, how strict to you want your signals to be. The general recommendation for this indicator is this:
On any timeframe 4 hours or below, leave the critical value at 0.01.
On any timeframe above 4 hours, including the daily timeframe, use 0.05 or 0.10.
You can toggle these settings in the menu:
It also works really well on the larger timeframes:
QQQ 1D:
Uses & Tips:
This can be used as a standalone indicator or in combination with other indicators/strategies. I personally use this indicator frequently on the 1 hour and 5 minute timeframes to see where we are in relation to the anticipated range, and whether there is any significance on the ANOVA analysis.
Some tips for use:
Works best on the 5 minute chart for intra-day trades.
Works best on a ranging market on the shorter timeframes.
Works great on the larger timeframes in all markets!
Can be used on any instrument, be it Crypto, commodities, futures, indices etc..
And that is the indicator!
As always leave your questions and comments below.
For access, please follow the instructions below.
Safe trades everyone!
Blockunity Drawdown Visualizer (BDV)Monitor the drawdown (value of the drop between the highest and lowest points) of assets and act accordingly to reduce your risk.
Introducing BDV, the incredibly intuitive metric that visualizes asset drawdowns in the most visually appealing manner. With its color gradient display, BDV allows you to instantly grasp the state of retracement from the asset’s highest price level. But that’s not all – you have the option to display the oscillator’s colorization directly on your chart, enhancing your analysis even further.
The Idea
The goal is to provide the community with the best and most complete tool for visualizing the Drawdown of any asset.
How to Use
Very simple to use, the indicator takes the form of an oscillator, with colors ranging from red to green depending on the Drawdown level. A table summarizes several key data points.
Elements
On the oscillator, you'll find a line with a color gradient showing the asset's Drawdown. The flatter line represents the Max Drawdown (the lowest value reached).
In addition, the table summarizes several data:
The asset's All Time High (ATH).
Current Drawdown.
The Max Drawdown that has been reached.
Settings
First of all, you can activate a "Bar Color" in the settings (You must also uncheck "Borders" and "Wick" in your Chart Settings):
You can display Fibonacci levels on the oscillator. You'll see that levels can be relevant to drawdown. The color of the levels is also configurable.
In the calculation parameters, you can first choose between taking the High of the candles or the Close. By default this is Close, but if you change the parameter to High, the indication next to ATH in the table will change, and you'll see that the values in the table will be affected.
The second calculation parameter (Start Date) lets you modify the effective start date of the ATH, which will affect the drawdown level. Here's an example:
How it Works
First, we calculate the ATH:
var bdv_top = bdv_source
bdv_top := na(bdv_top ) ? bdv_source : math.max(bdv_source, bdv_top )
Then the drawdown is calculated as follows:
bdv = ((bdv_source / bdv_top) * 100) - 100
Then the max drawdown :
bdv_max = bdv
bdv_max := na(bdv_max ) ? bdv : math.min(bdv, bdv_max )
Hodl Calculation v1.0I have developed an indicator that calculates the value of our currency if we had periodically bought any stock or cryptocurrency on any exchange. I believe many individuals would be interested in computing such values.
You can customize the start and end times, choose the amount of currency to be used for each deal, and select from two frequency options.
The first option involves specific intervals, such as hourly, every three days, or bi-weekly.
The second option allows purchases at specific dates or times, like every 15th of the month at 12:00 PM, every Monday at 11:00 AM, or every day at 6:00 AM.
After selecting the frequency, the indicator performs calculations and presents statistical information in a table.
The summarized data includes frequency value, total selected period duration, number of deals, total quantity, total cost, current value, and profit/loss status.
IBIT Premium to CoinbaseThe BTC ETF premium indicator for TradingView is a specialized tool designed to measure and visualize the premium or discount of the iShares Bitcoin Trust (IBIT), an investment vehicle that holds Bitcoin, relative to the actual price of Bitcoin on the Coinbase exchange. This indicator can be particularly insightful for traders interested in the BTC securities market and those analyzing the demand for Bitcoin as reflected by institutional investment products.
#### Description:
The BTC ETF premium indicator in TradingView leverages an advanced Pine Script algorithm to calculate the premium (or discount) percentage of IBIT compared to the spot price of Bitcoin (BTC/USD) on Coinbase. The premium is a critical insight that reflects market sentiment and potentially arbitrage opportunities between the trust's share price and the underlying cryptocurrency asset.
Here's how the indicator works:
1. **Calculation Methodology:**
- **Implied Bitcoin Price of IBIT:** We determine the implied price of Bitcoin within IBIT by dividing the IBIT closing price by the known ratio of Bitcoin per share.
- **IBIT Premium to Coinbase:** The percentage premium is then calculated as:
$$\text{IBIT Premium} = \frac{(\text{Implied Bitcoin Price of IBIT } - \text{Actual Bitcoin Price on Coinbase})}{\text{Actual Bitcoin Price on Coinbase}} \times 100$$
- This calculation is performed using the closing prices on a per-minute basis to ensure timely and accurate analysis.
2. **Visualization:** The indicator plots the premium as a step line chart, making it easy to visualize changes over time. A dynamic label accompanies the plot, displaying the implied Bitcoin price, the actual percentage premium or discount, and whether the premium is trending up or down compared to the previous day's value.
3. **Usage Scenario:** Traders can use this indicator to monitor the live premium 24/7 and analyze how it behaves during different market conditions, including when the equity market, where IBIT is traded, is closed.
#### Additional Features:
- **Color-Coding:** The premium is color-coded in green when positive (premium) and in red when negative (discount), aiding quick visual assessment.
- **Zero-Line Reference:** A horizontal line is drawn at zero to easily identify when IBIT is trading at par with the spot price of Bitcoin.
- **Real-Time Label Updates:** The label updates in real time with the latest premium/discount information and includes an arrow to signify the trend direction.
#### Access and Usage:
The indicator can be favorited or added to your TradingView charts. You are also welcome to use the source code as a foundation for further customization to suit your trading strategies.
#### Notes:
Please consider that the IBIT has specific trading hours, and the indicator can show live changes even when its market is closed, which might lead to discrepancies from official static data. For best performance, use this indicator alongside the IBIT candlestick chart on TradingView.
GBTC Premium to CoinbaseThe BTC ETF premium indicator for TradingView is a specialized tool designed to measure and visualize the premium or discount of the Grayscale Bitcoin Trust (GBTC), an investment vehicle that holds Bitcoin, relative to the actual price of Bitcoin on the Coinbase exchange. This indicator can be particularly insightful for traders interested in the BTC securities market and those analyzing the demand for Bitcoin as reflected by institutional investment products.
#### Description:
The BTC ETF premium indicator in TradingView leverages an advanced Pine Script algorithm to calculate the premium (or discount) percentage of GBTC compared to the spot price of Bitcoin (BTC/USD) on Coinbase. The premium is a critical insight that reflects market sentiment and potentially arbitrage opportunities between the trust's share price and the underlying cryptocurrency asset.
Here's how the indicator works:
1. **Calculation Methodology:**
- **Implied Bitcoin Price of GBTC:** We determine the implied price of Bitcoin within GBTC by dividing the GBTC closing price by the known ratio of Bitcoin per share.
- **GBTC Premium to Coinbase:** The percentage premium is then calculated as:
$$\text{GBTC Premium} = \frac{(\text{Implied Bitcoin Price of GBTC} - \text{Actual Bitcoin Price on Coinbase})}{\text{Actual Bitcoin Price on Coinbase}} \times 100$$
- This calculation is performed using the closing prices on a per-minute basis to ensure timely and accurate analysis.
2. **Visualization:** The indicator plots the premium as a step line chart, making it easy to visualize changes over time. A dynamic label accompanies the plot, displaying the implied Bitcoin price, the actual percentage premium or discount, and whether the premium is trending up or down compared to the previous day's value.
3. **Usage Scenario:** Traders can use this indicator to monitor the live premium 24/7 and analyze how it behaves during different market conditions, including when the equity market, where GBTC is traded, is closed.
#### Additional Features:
- **Color-Coding:** The premium is color-coded in green when positive (premium) and in red when negative (discount), aiding quick visual assessment.
- **Zero-Line Reference:** A horizontal line is drawn at zero to easily identify when GBTC is trading at par with the spot price of Bitcoin.
- **Real-Time Label Updates:** The label updates in real time with the latest premium/discount information and includes an arrow to signify the trend direction.
#### Access and Usage:
The indicator can be favorited or added to your TradingView charts. You are also welcome to use the source code as a foundation for further customization to suit your trading strategies.
#### Notes:
Please consider that the GBTC has specific trading hours, and the indicator can show live changes even when its market is closed, which might lead to discrepancies from official static data. For best performance, use this indicator alongside the GBTC candlestick chart on TradingView.
TabulateTabulate statistics from up to 10 symbols and display in a table format
you can choose to display up to 20 periods data points back in time
Symbol and description
Select a symbol and provide a description for it, this would be used as the label on the left column
Highlighting options
Color based on value increase/decrease
Colors the value green if it has increased from previous value, or red if it has decreased
Color based on positive/negative value
Stat will be colored accordingly green if positive, red if negative
Table value formatting
Allows you to change how the values are formatted for easy viewing
if 0.000% is selected, the source will be replaced by the following formula (close - open)/open
table text color should be changed to "Color based on positive/negative value"
NOTE: symbols that hold only monthly values would need to be placed in a chart with real time data to show the latest period.
Trended CVD [Mxwll]Hey!
This indicator "Trended CVD" categorizes price movement by trend (using zig zag) and calculates cumulative volume delta for the entirety of the price move.
Features
CVD calculated for the trend
CVD divergences are distinguished (uptrend and falling CVD / downtrend and rising CVD)
CVD output normalized to scale with chart, and is plotted alongside the trend
Can be used for trend confirmation (CVD trend correlating with price trend)
All regular zig-zag features available
What constitutes a trend is customizable. Can locate small, medium, large price trends with detailed user-input settings.
How-To Use Trended CVD
The image above shows one of two primary uses for the indicator.
In the left-half of the image, price is downtrending simultaneously with CVD; thereby, CVD is confirming the downtrend.
The right-half of the image shows price uptrending simultaneously with CVD; CVD is confirming the uptrend.
This information can be used to classify the "strength" of the price move, and decide to trade with it or against it.
The image above shows the second primary use for the indicator.
A slight price decrease transpires while CVD increases - CVD diverging upwards from the price trend.
This information can be used to classify the strength of the downtrend, and decide to trade against it, or abstain from trading with it.
The image above shows, subsequent to divergence, price failed to sustain "meaningful" downwards movement.
Labels oriented at the final pivot of a trend show the cumulative volume delta for the entirety of the price move (distinguishable by the superimposed zig zag line).
That's really it! A more complex concept integrated with a simple output.
Thank you!
BTC ETF VolumesVolume
This script plots the trading volume of all BTC spot ETFs as well as the aggregate volume. Works on any chart and any timeframe.
Indicators
The volume of every ETF is plotted in a different color, with the total column adding up to the aggregate volume.
If you have price and indicator labels enabled you will also see individual ETF volume on your price scale on the right hand side.
If more BTC ETFs get launched I will add them.
Bitcoin ETF Tracker (BET)Get all the information you need about all the different Bitcoin ETFs.
With the Bitcoin ETF Tracker, you can observe all possible Bitcoin ETF data:
The ETF name.
The ticker.
The price.
The volume.
The share of total ETF volume.
The ETF fees.
The exchange and custodian.
At the bottom of the table, you'll find the day's total volume.
In addition, you can see the volume for the different Exchanges, as well as for the different Custodians.
If you don't want to display these lines to save space, you can uncheck "Show Additional Data" in the indicator settings.
The Idea
The goal is to provide the community with a tool for tracking all Bitcoin ETF data in a synthesized way, directly in your TradingView chart.
How to Use
Simply read the information in the table. You can hover above the Fees and Exchanges cells for more details.
The table takes space on the chart, you can remove the extra lines by unchecking "Show Additional Data" in the indicator settings or reduce text size by changing the "Table Text Size" parameter.
Upcoming Features
As soon as we have a little more history, we'll add variation rates as well as plots to observe the breakdown between the various Exchanges and Custodians.
Candle Strength AnalysisView candles differently with this new indicator designed to simply visualise and analyse price movements on your chart!
The more vibrant the colour, the stronger the conviction of its respective candle.
This simple script calculates the closing price as a percentage within the candles high/low range. A colour/strength rating is then assigned to the candle based on where this close price sits within the range.
Strong coloured candles occur when the close is very close to a high or low.
User defined percentage and colour inputs allow for quick personalisation and flexibility.
An additional wick imbalance feature identifies when a candle has a larger wick than its body, which may be used to identify a ranging market or shift in trader sentiment.
For any questions, concerns, or requests, please reach out to me in the comments below.
- The Pine Guru
ARIMA Moving Average and Forecaster [SS]Finally releasing this. This took months, over 3 months to be precise, to figure out, code and troubleshoot! I honestly was going to give up on this project, but I finally got it to actually work fairly reliably. So hopefully you like it!
This is a very basic ARIMA modeler. It can do the following:
1. Provide you with an ARIMA based Moving Average;
2. Provide you with a standard error band;
3. Auto-select a lag length for assessment based on stationarity;
3. Provide you with the option of extending the error range by a user selected amount of standard deviations; and
4. Forecasting and plotting the forecast on the chart.
I will go over each function individually, but before I do, I think its important to talk a bit about what an ARIMA Model is and does:
ARIMA stands for AutoRegressive Integrated Moving Average and is an approach to modeling and time series forecasting. In simple terms, it combines autoregressive (AR) and moving average (MA) components to capture the underlying patterns in a time series data. The "AutoRegressive" part accounts for the relationship between an observation and its previous values, while the "Moving Average" part considers the relationship between an observation and a residual error from past observations. The "Integrated" component involves differencing the time series to make it stationary, which aids in stabilizing the model. ARIMA models help predict future values based on patterns observed in historical data, making them useful for forecasting in various fields such as economics, finance, and weather prediction.
The benefits to ARIMA is it will forecast based on the current trend, but it also provides for both the up and down scenario of the trend (i.e., if we are in a downtrend, what it would look like and what values we could expect if the trend reverses and vice versa). All of this is within the scope of this indicator, believe it or not!
If you would like more information on ARIMA, you can check out my educational post about it here:
Alrighty, now for the indicator functions.
ARIMA Moving Average and Standard Error Band
The ARIMA moving average is very simple, it takes the SMA of the current trend, lags it and plots out the lagged SMA. You can toggle the auto-select lag on, or you can pick your own lag manually. The above image is an auto-selected lag, but if we manually lag it by 5, this is what it looks like:
Its simply a lagged average of the 5 SMA (that is essentially how ARIMA works, by creating a moving average and lagging the moving average).
There are some implications to selecting a lag factor when it comes to forecasting, but I will cover this in the forecasting section. But I do want to make mention, you can use the ARIMA moving average in lieu of other moving averages. The advantage to doing this is it will be able to plot out the error bands. For example, if we wanted to get an ARIMA MA of the 200 SMA, we can toggle on the error bands and this is what we get:
Or the 50 MA:
NOTE: You ABSOLUTELY SHOULD NEVER use more than a lag of 4 or 5 for Forecasting (will be discussed later).
Auto-Select Lag
The indicator pulls the ARIMA modeler framework from my Forecasting library and pulls the stationarity assessment from my SPTS library. When you are doing an ARIMA model for forecasting, we need to ensure the data is stationary. Thus, if you want to forecast out the current trend, its highly recommended you select the "Auto Determine Lag Length" to find the most appropriate lag and forecast accordingly.
You can, however, chose your own lag order (model order), but this should never be above 4 or 5.
You should never select a lag of more than 5 because you are introducing too much "trendiness" into the equation, and you will get astronomical readings. ARIMA models never generally exceed a lag of 3 or 4 at most, as they are supposed be stationary and de-trended.
Extending by Standard Deviation
There is an option to select a standard deviation extension band. This is helpful for active day trading. Here is NIO extended by 2 standard deviations:
General suggestion is to only extend by 2 standard deviations and this is sufficient for most stocks.
Forecasting
The hallmark of an ARIMA model is the ability to use it for forecasting. Thus, the forecasting feature is a large portion of this indicator. You can see it displayed in the main chart above, but let's show some other examples:
NIO on the 1 hour:
TSLA on the 4 hour:
You can also display a forecasting table:
The result row shows the most likely, conservative, price at each time increment.
The Upper Confidence and Lower Confidence show what the trend would look like if it continued up or down at the current rate and the 95% confidence intervals show the values that the true source is likely to fall between at various increments in time with a 95% confidence (i.e. 95% probability that it should fall between these levels at period xyz assuming normal distribution).
The important levels, in my opinion, are the upper and lower confidence levels. These show you the current rate of decline or increase that the stock is expecting and what the trend would look like with a continuation or a reversal. This is ARIMA's biggest strength, as it has the ability to plot both outcomes assuming the current trend rate and time remains constant.
And that is the indicator! ARIMA is a bit of a complex process, but its a very powerful tool when used properly!
Troubleshooting:
One thing of note. Sometimes when autoselecting a length for forecasting, if there has been a heavy trend in one direction, you will not get the upper or lower confidence levels because of the lack of any up or down movement. In this case, manually select a lag of 3 to 5 to correct for this.
Let me know if you have any questions below and safe trades everyone!
GARCH Volatility Estimation - The Quant ScienceThe GARCH (Generalized Autoregressive Conditional Heteroskedasticity) model is a statistical model used to forecast the volatility of a financial asset. This model takes into account the fluctuations in volatility over time, recognizing that volatility can vary in a heteroskedastic (i.e., non-constant variance) manner and can be influenced by past events.
The general formula of the GARCH model is:
σ²(t) = ω + α * ε²(t-1) + β * σ²(t-1)
where:
σ²(t) is the conditional variance at time t (i.e., squared volatility)
ω is the constant term (intercept) representing the baseline level of volatility
α is the coefficient representing the impact of the squared lagged error term on the conditional variance
ε²(t-1) is the squared lagged error term at the previous time period
β is the coefficient representing the impact of the lagged conditional variance on the current conditional variance
In the context of financial forecasting, the GARCH model is used to estimate the future volatility of the asset.
HOW TO USE
This quantitative indicator is capable of estimating the probable future movements of volatility. When the GARCH increases in value, it means that the volatility of the asset will likely increase as well, and vice versa. The indicator displays the relationship of the GARCH (bright red) with the trend of historical volatility (dark red).
USER INTERFACE
Alpha: select the starting value of Alpha (default value is 0.10).
Beta: select the starting value of Beta (default value is 0.80).
Lenght: select the period for calculating values within the model such as EMA (Exponential Moving Average) and Historical Volatility (default set to 20).
Forecasting: select the forecasting period, the number of bars you want to visualize data ahead (default set to 30).
Design: customize the indicator with your preferred color and choose from different types of charts, managing the design settings.
G7&ECB Balance SheetThis script shows aggregated balance sheet of G7 countries and European central banks: Italy, France, Canada, Japan, United Kingdom, United States, Germany, ECB.
Balance sheets of central banks are converted from their local currencies into US Dollars to get the aggregated value.
Script works in two modes (needs to be selected from settings):
1) Shows aggregated value in USD trillions
2) Shows Rate of Change
Length parameter must be selected for Rate of Change, e.g. on a daily timeframe 365, for year over year values.
Forecast: PastFluxDelta PredictionThe theory is that time periods and the conditions during these periods repeat themselves. Especially if it is the same day of the week in the past, there is a high probability that price fluctuations will roughly repeat themselves.
Eternal return (or eternal recurrence) is a philosophical concept which states that time repeats itself in an infinite loop, and that exactly the same events will continue to occur in exactly the same way, over and over again, for eternity.
History does repeat itself.
The stock market is a manifest example.
Chief market strategist at Miller Tabak + Co. Matt Maley pointed out the strong resemblance between the stock market recently and that in the past.
Various scientific studies and articles show that there could be something to this theory
Most of the investors are ignoring the parallels between stocks today and "heady" years 1929, 1999 and 2007…
Post Labor Day sees investors returning to the S&P 500 near all-time highs and some dark economic shadows lurking …
So how should we regard these inescapable results?
Nietzsche said we should embrace them, accept them, and love them. Once they stop, expect them to start again.
But remember that the future is fundamentally uncertain and that past results are by no means a guarantee of future performance.
Based on this, this indicator uses historical trading data from a year, a week or a day ago and compares price fluctuations in the past with current conditions.
"Bars to predict" can be used to indicate how far into the future the indicator is looking.
"Amount of bars to show" determines how many bars are generally displayed. A high value allows you to see how accurate the method was in the past.
Liquidation Level ScreenerThe Liquidation Level Screener is an analytical tool designed for traders who seek a comprehensive view of potential liquidation zones in the market. This script, adaptable to almost any timeframe from 1 minute to 3 days, offers a unique perspective by mapping out key liquidation levels where significant market actions could occur.
Key Features:
Multi-Exchange Data Aggregation: Unlike many other indicators, the Liquidation Levels Indicator compiles data from multiple leading exchanges including Binance, Bitmex, Kraken, and Bitfinex. This approach ensures a more holistic and accurate representation of market sentiment, providing insights into potential liquidation points across various platforms.
Customizable Timeframes and Modes: The script is versatile, working effectively across various timeframes. It operates in two distinct modes:
Actual Levels Display: Visually represents potential liquidation levels.
Settings Mode: Showcases an open interest (OI) oscillator. When OI is exceptionally high, indicating a surge in opened positions at a specific candle, it signals traders to be vigilant about upcoming liquidation levels.
Three-Tier Liquidation System: The indicator categorizes liquidation levels into three distinct tiers based on open interest levels—1, 2, and 3—with Level 3 representing the highest concentration of open positions. This tiered approach allows traders to gauge the significance of each level and adjust their strategies accordingly.
Histogram Visualization: A novel feature of this script is the histogram on the chart's right side, representing the concentration of liquidation levels in specific market zones. This visual aid helps traders identify crucial areas that warrant close attention, enhancing decision-making.
Customizable Options:
Moving Averages: Choose from a wide range of moving average types, including VWMA, SMA, EMA, and more, to tailor the indicator to your analysis style.
Histogram Settings: Adjust the number of histograms, lookback bars, and their proximity to the latest candle, allowing for a personalized density and range of visualization.
Liquidation Level Sensitivity: Set thresholds for different liquidation levels, fine-tuning the indicator to detect varying degrees of market leverage.
Color Coding: Customize the color scheme for different leverage levels, enhancing visual clarity and ease of interpretation.
The Liquidation Level Screener offers a unique edge by highlighting potential zones where significant market movements can occur due to liquidations. By consolidating data from multiple exchanges, it provides a more rounded view of market behavior, which is essential in today’s interconnected trading environment. The tiered liquidation system and histogram feature equip traders with the ability to identify and focus on key market segments where high activity is expected. This tool is particularly valuable for traders who base their strategies on market liquidity and leverage dynamics.
