Ethereum ETF Tracker (EET)Get all the information you need about all the different Ethereum ETF.
With the Ethereum ETF Tracker, you can observe all possible Ethereum ETF data:
ETF name.
Ticker.
Price.
Volume.
Share of total ETF volume.
Fees.
Exchange.
Custodian.
At the bottom of the table, you'll find the ETHE Premium (and ETH per Share), and 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 Ethereum 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.
Aggregate volume can be displayed directly on the graph (this volume can be displayed on any asset, such as Ethereum itself). The display can be disabled in the settings.
Cerca negli script per " TABLE"
RSI Analysis with Statistical Summary Scientific Analysis of the Script "RSI Analysis with Statistical Summary"
Introduction
I observed that there are outliers in the price movement liquidity, and I wanted to understand the RSI value at those points and whether there are any notable patterns. I aimed to analyze this statistically, and this script is the result.
Explanation of Key Terms
1. Outliers in Price Movement Liquidity: An outlier is a data point that significantly deviates from other values. In this context, an outlier refers to an unusually high or low liquidity of price movement, which is the ratio of trading volume to the price difference between the open and close prices. These outliers can signal important market changes or unusual trading activities.
2. RSI (Relative Strength Index): The RSI is a technical indicator that measures the speed and change of price movements. It ranges from 0 to 100 and helps identify overbought or oversold conditions of a trading instrument. An RSI value above 70 indicates an overbought condition, while a value below 30 suggests an oversold condition.
3. Mean: The mean is a measure of the average of a dataset. It is calculated by dividing the sum of all values by the number of values. In this script, the mean of the RSI values is calculated to provide a central tendency of the RSI distribution.
4. Standard Deviation (stdev): The standard deviation is a measure of the dispersion or variation of a dataset. It shows how much the values deviate from the mean. A high standard deviation indicates that the values are widely spread, while a low standard deviation indicates that the values are close to the mean.
5. 68% Confidence Interval: A confidence interval indicates the range within which a certain percentage of values of a dataset lies. The 68% confidence interval corresponds to a range of plus/minus one standard deviation around the mean. It indicates that about 68% of the data points lie within this range, providing insight into the distribution of values.
Overview
This Pine Script™, written in Pine version 5, is designed to analyze the Relative Strength Index (RSI) of a stock or other trading instrument and create statistical summaries of the distribution of RSI values. The script identifies outliers in price movement liquidity and uses this information to calculate the frequency of RSI values. At the end, it displays a statistical summary in the form of a table.
Structure and Functionality of the Script
1. Input Parameters
- `rsi_len`: An integer input parameter that defines the length of the RSI (default: 14).
- `outlierThreshold`: An integer input parameter that defines the length of the outlier threshold (default: 10).
2. Calculating Price Movement Liquidity
- `priceMovementLiquidity`: The volume is divided by the absolute difference between the close and open prices to calculate the liquidity of the price movement.
3. Determining the Boundary for Liquidity and Identifying Outliers
- `liquidityBoundary`: The boundary is calculated using the Exponential Moving Average (EMA) of the price movement liquidity and its standard deviation.
- `outlier`: A boolean value that indicates whether the price movement liquidity exceeds the set boundary.
4. Calculating the RSI
- `rsi`: The RSI is calculated with a period length of 14, using various moving averages (e.g., SMA, EMA) depending on the settings.
5. Storing and Limiting RSI Values
- An array `rsiFrequency` stores the frequency of RSI values from 0 to 100.
- The function `f_limit_rsi` limits the RSI values between 0 and 100.
6. Updating RSI Frequency on Outlier Occurrence
- On an outlier occurrence, the limited and rounded RSI value is updated in the `rsiFrequency` array.
7. Statistical Summary
- Various variables (`mostFrequentRsi`, `leastFrequentRsi`, `maxCount`, `minCount`, `sum`, `sumSq`, `count`, `upper_interval`, `lower_interval`) are initialized to perform statistical analysis.
- At the last bar (`bar_index == last_bar_index`), a loop is run to determine the most and least frequent RSI values and their frequencies. Sum and sum of squares of RSI values are also updated for calculating mean and standard deviation.
- The mean (`mean`) and standard deviation (`stddev`) are calculated. Additionally, a 68% confidence interval is determined.
8. Creating a Table for Result Display
- A table `resultsTable` is created and filled with the results of the statistical analysis. The table includes the most and least frequent RSI values, the standard deviation, and the 68% confidence interval.
9. Graphical Representation
- The script draws horizontal lines and fills to indicate overbought and oversold regions of the RSI.
Interpretation of the Results
The script provides a detailed analysis of RSI values based on specific liquidity outliers. By calculating the most and least frequent RSI values, standard deviation, and confidence interval, it offers a comprehensive statistical summary that can help traders identify patterns and anomalies in the RSI. This can be particularly useful for identifying overbought or oversold conditions of a trading instrument and making informed trading decisions.
Critical Evaluation
1. Robustness of Outlier Identification: The method of identifying outliers is solely based on the liquidity of price movement. It would be interesting to examine whether other methods or additional criteria for outlier identification would lead to similar or improved results.
2. Flexibility of RSI Settings: The ability to select various moving averages and period lengths for the RSI enhances the adaptability of the script, allowing users to tailor it to their specific trading strategies.
3. Visualization of Results: While the tabular representation is useful, additional graphical visualizations, such as histograms of RSI distribution, could further facilitate the interpretation of the results.
In conclusion, this script provides a solid foundation for analyzing RSI values by considering liquidity outliers and enables detailed statistical evaluation that can be beneficial for various trading strategies.
Multi Timeframe Moving Average Convergence Divergence {DCAquant}Overview
The MTF MACD indicator provides a unique view of MACD (Moving Average Convergence Divergence) and Signal Line dynamics across various timeframes. It calculates the MACD and Signal Line for each selected timeframe and aggregates them for analysis.
Key Features
MACD Calculation
Utilizes standard MACD calculations based on user-defined parameters like fast length, slow length, and signal smoothing.
Determines the difference between the MACD and Signal Line to identify convergence or divergence.
Multiple Timeframe Analysis
Allows users to select up to six different timeframes for analysis, ranging from minutes to days, providing a holistic view of market trends.
Calculates MACD and Signal Line for each timeframe independently.
Aggregated Analysis
Combines MACD and Signal Line values from multiple timeframes to derive a consolidated view.
Optionally applies moving average smoothing to aggregated MACD and Signal Line values for better clarity.
Position Identification
Determines the trading position (Long, Short, or Neutral) based on the relationship between MACD and Signal Line.
Considers the proximity of MACD and Signal Line to identify potential trading opportunities.
Visual Representation
Plots MACD and Signal Line on the price chart for visual analysis.
Utilizes color-coded backgrounds to indicate trading conditions (Long, Short, or Neutral) for quick interpretation.
Dynamic Table Display
Displays trading position alongside graphical indicators (rocket for Long, snowflake for Short, and star for Neutral) in a customizable table.
Offers flexibility in table placement and size for user preference.
How to Use
Parameter Configuration
Adjust parameters like fast length, slow length, and signal smoothing to fine-tune MACD calculations.
Select desired timeframes for analysis based on trading preferences and market conditions.
Interpretation
Monitor the relationship between MACD and Signal Line on the price chart.
Pay attention to color-coded backgrounds and graphical indicators in the table for actionable insights.
Decision Making
Consider entering Long positions when MACD is above the Signal Line and vice versa for Short positions.
Exercise caution during Neutral conditions, as there may be uncertainty in market direction.
Risk Management
Combine MTF MACD analysis with risk management strategies to optimize trade entries and exits.
Set stop-loss and take-profit levels based on individual risk tolerance and market conditions.
Conclusion
The Multi Timeframe Moving Average Convergence Divergence (MTF MACD) indicator offers a robust framework for traders to analyze market trends across multiple timeframes efficiently. By combining MACD insights from various time horizons and presenting them in a clear and actionable format, it empowers traders to make informed decisions and enhance their trading strategies.
Disclaimer
The Multi Timeframe Moving Average Convergence Divergence (MTF MACD) indicator provided here is intended for educational and informational purposes only. Trading in financial markets involves risk, and past performance is not indicative of future results. The use of this indicator does not guarantee profits or prevent losses.
Please be aware that trading decisions should be made based on your own analysis, risk tolerance, and financial situation. It is essential to conduct thorough research and seek advice from qualified financial professionals before engaging in any trading activity.
The MTF MACD indicator is a tool designed to assist traders in analyzing market trends and identifying potential trading opportunities. However, it is not a substitute for sound judgment and prudent risk management.
By using this indicator, you acknowledge that you are solely responsible for your trading decisions, and you agree to indemnify and hold harmless the developer and distributor of this indicator from any losses, damages, or liabilities arising from its use.
Trading in financial markets carries inherent risks, and you should only trade with capital that you can afford to lose. Exercise caution and discretion when implementing trading strategies, and consider seeking independent financial advice if necessary.
Multi-Timeframe Momentum Indicator [Ox_kali]The Multi-Timeframe Momentum Indicator is a trend analysis tool designed to examine market momentum across various timeframes on a single chart. Utilizing the Relative Strength Index (RSI) to assess the market’s strength and direction, this indicator offers a multidimensional perspective on current trends, enriching technical analysis with a deeper understanding of price movements. Other oscillators, such as the MACD and StochRSI, will be integrated in future updates.
Regarding the operation with the RSI: when its value is below 50 for a given period, the trend is considered bearish. Conversely, a value above 50 indicates a bullish trend. The indicator goes beyond the isolated analysis of each period by calculating an average of the displayed trends, based on user preferences. This average, ranging from “Strong Down” to “Strong Up,” reflects the percentage of periods indicating a bullish or bearish trend, thus providing a precise overview of the overall market condition.
Key Features:
Multi-Timeframe Analysis : Allows RSI analysis across multiple timeframes, offering an overview of market dynamics.
Advanced Customization : Includes options to adjust the RSI period, the RSI trend threshold, and more.
Color and Transparency Options : Offers color styles for bullish and bearish trends, as well as adjustable transparency levels for personalized visualization.
Average Trend Display : Calculates and displays the average trend based on activated timeframes, providing a quick summary of the current market state.
Flexible Table Positioning : Allows users to choose the indicator’s display location on the chart for seamless integration.
List of Parameters:
RSI Period : Defines the RSI period for calculation.
RSI Up/Down Threshold: Threshold for determining bullish or bearish trends of the RSI.
Table Position: Location of the indicator’s display on the chart.
Color Style : Selection of the color style for the indicator.
Strong Down/Up Color (User) : Customization of colors for strong market movements.
Table TF Transparency : Adjustment of the transparency level for the timeframe table.
Show X Minute/Hour/Day/Week Trend : Activation of the RSI display for specific timeframes.
Show AVG : Option to display or not the calculated average trend.
the Multi-Timeframe Momentum Indicator , stands as a comprehensive tool for market trend analysis across various timeframes, leveraging the RSI for in-depth market insights. With the promise of future updates including the integration of additional oscillators like the MACD and StochRSI, this indicator is set to offer even more robust analysis capabilities.
Please note that the MTF-Momentum is not a guarantee of future market performance and should be used in conjunction with proper risk management. Always ensure that you have a thorough understanding of the indicator’s methodology and its limitations before making any investment decisions. Additionally, past performance is not indicative of future results.
Backtest any Indicator v5Happy Trade,
here you get the opportunity to backtest any of your indicators like a strategy without converting them into a strategy. You can choose to go long or go short and detailed time filters. Further more you can set the take profit and stop loss, initial capital, quantity per trade and set the exchange fees. You get an overall result table and even a detailed, scroll-able table with all trades. In the Image 1 you see the provided info tables about all Trades and the Result Summary. Further more every trade is marked by a background color, Labels and Levels. An opening Label with the trade direction and trade number. A closing Label again with the trade number, the trades profit in % and the total amount of $ after all past trades. A green line for the take profit level and a red line for the stop loss.
Image 1
Example
For this description we choose the Stochastic RSI indicator from TradingView as it is. In Image 2 is shown the performance of it with decent settings.
Timeframe=45, BTCUSD, 2023-08-01 - 2023-10-20
Stoch RSI: k=30, d=40, RSI-length=140, stoch-length=140
Backtest any Indicator: input signal=Stoch RSI, goLong, take profit=9.1%, stop loss=2.5%, start capital=1000$, qty=5%, fee=0.1%, no Session Filter
Image 2
Usage
1) You need to know the name of the boolean (or integer) variable of your indicator which hold the buy condition. Lets say that this boolean variable is called BUY. If this BUY variable is not plotted on the chart you simply add the following code line at the end of your pine script.
For boolean (true/false) BUY variables use this:
plot(BUY ? 1:0,'Your buy condition hold in that variable BUY',display = display.data_window)
And in case your script's BUY variable is an integer or float then use instate the following code line:
plot(BUY ,'Your buy condition hold in that variable BUY',display = display.data_window)
2) Probably the name of this BUY variable in your indicator is not BUY. Simply replace in the code line above the BUY with the name of your script's trade condition variable.
3) Save your changed Indicator script.
4) Then add this 'Backtest any Indicator' script to the chart ...
5) and go to the settings of it. Choose under "Settings -> Buy Signal" your Indicator. So in the example above choose .
The form is usually: ' : BUY'. Then you see something like Image 2
6) Decide which trade direction the BUY signal should trigger. A go Long or a go Short by set the hook or not.
Now you have a backtest of your Indicator without converting it into a strategy. You may change the setting of your Indicator to the best results and setup the following strategy settings like Time- and Session Filter, Stop Loss, Take Profit etc. More of it below in the section Settings Menu.
Appereance
In the Image 2 you see on the right side the List of Trades . To scroll down you go into the settings again and decrease the scroll value. So you can see all trades that have happened before. In case there is an open trade you will find it at the last position of the list.
Every Long trade is green back grounded while Short trades are red.
Every trade begins with a label that show goLong or goShort and its number. And ends with another label again with its number, Profit in % and the resulting total amount of cash.
If activated you further see the Take Profit as a green line and the Stop Loss as a orange line. In the settings you can set their percentage above or below the entry price.
You also see the Result Summary below. Here you find the usual stats of a strategy of all closed trades. The profit after total amount of fees , amount of trades, Profit Factor and the total amount of fees .
Settings Menu
In the settings menu you will find the following high-lighted sections. Most of the settings have a question mark on their right side. Move over it with the cursor to read specific explanation.
Input Signal of your Indicator: Under Buy you set the trade signal of your Indicator. And under Target you set the value when a trade should happen. In the Example with the Stochastic RSI above we used 20. Below you can set the trade direction, let it be go short when hooked or go long when unhooked.
Trade Settings & List of Trades: Take Profit set the target price of any trade. Stop Loss set the price to step out when a trade goes the wrong direction. Check mark the List of Trades to see any single trade with their stats. In case that there are more trades as fits in the list you can scroll down the list by decrease the value Scroll .
Time Filter: You can set a Start Time or deactivate it by leave it unhooked. The same with End Time .
Session Filter: here you can choose to activate it on weekly base. Which days of the week should be trading and those without. And also on daily base from which time on and until trade are possible. Outside of all times and sessions there will be no new trades if activated.
Invest Settings: here you can choose the amount of cash to start with. The Quantity percentage define for every trade how much of the cash should be invested and the Fee percentage which have to be payed every trade. Open position and closing position.
Other Announcements
This Backtest script don't use the strategy functions of TradingView. It is programmed as an indicator. All trades get executed at candle closing. This script use the functionality "Indicator-on-Indicator" from TradingView.
Conclusion
So now it is your turn, take your promising indicators and connect it to that Backtest script. With it you get a fast impression of how successful your indicator will trade. You don't have to relay on coders who maybe add cheating code lines. Further more you can check with the Time Filter under which market condition you indicator perform the best or not so well. Also with the Session Filter you can sort out repeating good market conditions for your indicator. Even you can check with the GoShort XOR GoLong check mark the trade signals of you indicator in opposite trade direction with one click. And compare your indicators under the same conditions and get the results just after 2 clicks. Thanks to the in-build fee setting you get an impression how much a 0.1% fee cost you in total.
Cheers
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.
Harmonic Trend Fusion [kikfraben]📈 Harmonic Trend Fusion - Your Personal Trading Assistant
This versatile tool combines multiple indicators to provide a holistic view of market trends and potential signals.
🚀 Key Features:
Multi-Indicator Synergy: Benefit from the combined insights of Aroon, DMI, MACD, Parabolic SAR, RSI, Supertrend, and SMI Ergodic Oscillator, all in one powerful indicator.
Customizable Plot Options: Tailor your chart by choosing which signals to visualize. Whether you're interested in trendlines, histograms, or specific indicators, the choice is yours.
Color-Coded Trends: Quickly identify bullish and bearish trends with the color-coded visualizations. Stay ahead of market movements with clear and intuitive signals.
Table Display: Stay informed at a glance with the interactive table. It dynamically updates to reflect the current market sentiment, providing you with key information and trend direction.
Precision Control: Fine-tune your analysis with precision control over indicator parameters. Adjust lengths, colors, and other settings to align with your unique trading strategy.
🛠️ How to Use:
Customize Your View: Select which indicators to display and adjust plot options to suit your preferences.
Table Insights: Monitor the dynamic table for real-time updates on market sentiment and trend direction.
Indicator Parameters: Experiment with different lengths and settings to find the combination that aligns with your trading style.
Whether you're a seasoned trader or just starting, Harmonic Trend Fusion equips you with the tools you need to navigate the markets confidently. Take control of your trading journey and enhance your decision-making process with this comprehensive trading assistant.
Euclidean Distance Predictive Candles [SS]Finally releasing this, its been in the works for the past 2 weeks and has undergone many iterations.
I am not sure if I am 100% happy with it yet, but I guess its best to release and get feedback to make improvements.
So this is the Euclidean distance predictive candle indicator and what it does is exactly what it sounds like, it uses Euclidean distance to identify similar candles and then plot the candles and range that immediately proceeded like candles.
While this is using a general machine learning/data science approach (Euclidean distance), I do not employ the KNN (Nearest Neighbors) algo into this. The reason being is it simply offered no predictive advantage than isolating for the last case. I tried it, I didn't like it, the results were not improve and, at times, acutally hindered so I ditched it. Perhaps it was my approach but using some other KNN indicators, I just don't really find them all that more advantageous to simply relying on the Law of Large Numbers and collecting more data rather than less data (which we will get into later in this explanation).
So using this indicator:
There is a lot of customizability here. And the reason is, not all settings are going to work the same for all tickers. To help you narrow down your parameters, I have included various backtest results that show you how the model is performing. You see in the AMZN chart above, with the current settings, it is performing optimally, with a cumulative range pass of 99% (meaning that, of all the cases, the indicator accurately predicted the next day high OR low range 99% of the time), and the ability to predict the candle slightly over 52%.
The recommended settings, from me, are as follows:
So these are generally my recommended settings.
Euclidian Tolerance: This will determine the parameters to look for similar candles. In general, the lower the tolerance, the greater the precision. I recommend keeping it between 0.5, for tickers with larger prices (like ES1! futures or NQ1!) or 0.05 for tickers with lower TPs, like SPY or QQQ.
If the ED Tolerance is too extreme that the indicator cannot find identical setups, it will alert you:
But in general, the more precise you can get it, the better.
Anchor Type: You will see the option to anchor by "Predicted Open" or by "Previous Close". I suggest sticking with anchoring by predicted open. All this means is, it is going to anchor your range, candle, high and low targets by the predicted open price. Anchoring by previous close will anchor by the close of yesterday. Both work okay, but in general the results from anchoring to predicted open have higher pass rates and more accurately depict the candle.
Euclidean Distance Measurement Type: You can choose to measure by candle body or from high to low wicks. I haven't played around with measuring from high to low wicks all that much, because candle body tends to do the job. But remember, ED is a neutral measurement. Which means, its not going to distinguish between a red or green candle, just the formation of the candle. Thus, I tend to recommend, pragmatically, not to necessarily rely on the candle being red or green, but one the formation of the candle (where are the wicks going, are there more bearish wicks or bullish wicks) etc. Examples will follow.
Range Prediction Type: You can filter the range prediction type by last instance (in which, it will pull the previous identical candle and plot the next candle that followed it, adjusted for the current ranges) or "Average of All Cases". So this is where we need to talk a little bit about the law of large numbers.
In general, in statistics, when you have a huge amount of random data, the law of large numbers stipulates that, within this randomness should be repeated events. This is why sometimes chart patterns work, sometimes they don't. When we filter by the average of all cases, we are relying on the law of large numbers. In general, if you are getting good Backtest readings from Last Instance, then you don't need to use this function. But it provides an alternative insight into potential candle formations next day. Its not a bad idea to compare between the two and look for similarities and differences.
So now that we have covered the boring details, let's get into how to use the indicator and some examples.
So the indicator is plotting the range and candle for the next day. As such, we are not looking at the current candle being plotted, but we are looking at the previous candle (see image below for example):
The green arrow shows the prediction for Friday, along with the corresponding result. The purple arrow shows the prediction for Monday which we have yet to realize.
So remember when you are using this, you need to look at the previous candle, and not the candle that it is currently plotting with realtime data, because it is plotting for the next candle.
If you are plotting by last instance, the indicator will tell you which day it is pulling its data from if you have opted to toggle on the demographic data:
You can see the green arrow pointing to the date where it is pulling from. This data serves as the example candle with the candle proceeding this date being the anchored candle (or the predicted candle).
Price Targets and Probability:
In the chart, you can see the green arrow pointing to the green portion of the table. In this table, it will give you the current TPs. These represent the current time target price, which means, the TPs shown here are for Friday. On Monday, the table will update with the TPs for Monday, etc. If you want to view the TPs in advance, you can view them from the actual candle itself.
Below the TPs, you see a bullish 7:6. It means, in a total of 13 cases, the next candle was bullish 7 times and bearish 6 times. Where do we see the number of cases? In the demographic table as well:
Auxiliary functions
Because you are using the previous candle, if you want to avoid confusion, you can have the indicator plot the price targets over the predicted candle, to anchor your attention so to speak. Simply select "Label" in the "Show Price Targets" section, which will look like this:
You can also ask the indicator to plot the demographic data of Higher High, Low, etc. information. What this does is simply looks at all the cases and plots how many times higher highs, lows, lower lows, highs etc. were made:
This will just count all of the cases identified and plot the number of times higher highs, lows, etc. were made.
Concluding Remarks
This is a kind of complex indicator and I can appreciate it may take some getting used to.
I will try to post a tutorial video at some point next week for it, so stay tuned for that.
But this isn't designed to make your life more complicated, just to help give you insights into potential outcomes for the next day or hour or 5 minute (it can be used on all timeframes).
If you find it helpful, great! If not, that's okay, too :-).
Please be aware, this is not my forte of indicators. I am not a data scientist or programmer. My background is in Epi and we don't use these types of data science approaches, so if you have any suggestions or critiques, feel free to share them below.
Otherwise, I hope you enjoy!
Take care everyone and safe trades!
buyer_seller_scalping_indicatorThis code is a custom script designed for analyzing trading volume within a specific time window on the TradingView platform. It offers a comprehensive analysis of buying and selling activity during a defined period and provides visual aids and data summaries for traders to make informed decisions. Here's a detailed breakdown of its functionality and how to use it:
1. Custom Time Period: The script starts by allowing you to specify a custom time period for analysis. In this example, it's set from 04:00 to 09:29. You can modify these time values to suit your specific trading needs.
2. Volume Calculation: The script calculates buying and selling volume based on price levels. It takes into account the open, high, low, and close prices to determine whether buying or selling pressure is dominant during the specified time frame.
3. Total Volume Calculation: It calculates the total volume within the custom time period. This can help you gauge the overall activity and liquidity during the chosen time window.
4. Visualizations: The script then plots visual elements on the chart:
- A volume histogram, which provides a graphical representation of the total volume during the time period.
- Buying and selling volume indicators, which are shown as circles on the chart, highlighting the relative strength of buyers and sellers.
- An average volume line, represented in gray, which helps you identify the average trading volume over a 50-period moving average.
5. Volume Type Determination: The script determines whether buyers or sellers dominate the market during the specified time period. It labels this as "Buyers Volume > Sellers Volume," "Sellers Volume > Buyers Volume," or "Buyers Volume = Sellers Volume." This information can be crucial for assessing market sentiment.
6. Percentage Breakdown: The script calculates the percentage of buying and selling volume in relation to the total volume, helping you understand the distribution of market participants. These percentages are displayed in a table.
7. Table Display: Finally, the script creates a table that displays the following information:
- The current volume type (buyers, sellers, or balanced), with corresponding text colors.
- The percentage of buyers and sellers in the market.
How to Use:
1. Copy the script and add it as a custom script on TradingView.
2. Apply the script to your desired financial chart.
3. Adjust the custom time period if needed.
4. Interpret the visual elements and table to gain insights into market sentiment and volume distribution during the specified time frame.
5. Use this information to inform your trading decisions and strategies, especially when trading within the chosen time window.
This script is a valuable tool for traders seeking to understand market dynamics and volume behavior during specific trading hours, ultimately aiding in more informed trading decisions.
Disclaimer:
The indicator provided herein is experimental and has not undergone comprehensive testing. Its usage is solely at your own risk.
The publisher assumes no responsibility for any trading decisions made based on the utilization of this indicator.
AlpHay : ToolKitToolKit:
First Impressions for Securities; (like crime scene investigators) 🧐
Our first job is to understand "What did happen here?" (historically, like Price Ranges or Price Performances) 🤔
Secondly, we try to figure out "where are we now?" (like common indicators or Moving Averages) 🤔
Then "What was the chain of events?" (macro, local, fundamentals, shorts, etc.)
Note: There are a lot of useful scripts out there, but If you want to see my approach for "Fundamentals" or "Finra Short Report" scripts, have a look.
Now we have a Clue. 😎
Includes;
1. Daily Metrics (Price performance, Price Difference, Volume, Trade)
2. Historic Price Performances
3. Historic Price ranges
4. RSI and MACD (you can change) Indicators for four "Time Frame" (you can change also)
5. Moving Averages (also shows daily values on the chart)
* Easy to customize.
* You can be positioned where ever you need. (be careful about overlays)
* You can turn on/off tables for your daily usage.
* You can flip Horizontally for some of the tables.
* Always look at tooltips (mouse over for Averages etc.)
I hope you enjoy it.
Disclaimer and Warning!
* Do not forget this is my Interpolation of the data sets. You can't invest in relying on this indicator. This is just a visual representation of the data sets.
* Just be careful what you wish for. And search for anomalies.
// ToDO List.
* Pre/Post Market Price and Volume
Candle Trend Counter [theEccentricTrader]█ OVERVIEW
This indicator counts the number of confirmed candle trend scenarios on any given candlestick chart and displays the statistics in a table, which can be repositioned and resized at the user's discretion.
█ CONCEPTS
Green and Red Candles
• A green candle is one that closes with a high price equal to or above the price it opened.
• A red candle is one that closes with a low price that is lower than the price it opened.
Swing Highs and Swing Lows
• A swing high is a green candle or series of consecutive green candles followed by a single red candle to complete the swing and form the peak.
• A swing low is a red candle or series of consecutive red candles followed by a single green candle to complete the swing and form the trough.
Muti-Part Green and Red Candle Trends
• A multi-part green candle trend begins upon the completion of a swing low and continues until a red candle completes the swing high, with each green candle counted as a part of the trend.
• A multi-part red candle trend begins upon the completion of a swing high and continues until a green candle completes the swing low, with each red candle counted as a part of the trend.
█ FEATURES
Inputs
Start Date
End Date
Position
Text Size
Show Sample Period
Show Plots
Table
The table is colour coded, consists of seven columns and, as many as, thirty-one rows. Blue cells denote the multi-part candle trend scenarios, green cells denote the corresponding green candle trend scenarios and red cells denote the corresponding red candle trend scenarios.
The candle trend scenarios are listed in the first column with their corresponding total counts to the right, in the second column. The last row in column one, displays the sample period which can be adjusted or hidden via indicator settings.
The third column displays the total candle trend scenarios as percentages of total 1-candle trends, or complete swing highs and swing lows. And column four displays the total candle trend scenarios as percentages of the, last, or preceding candle trend part. For example 4-candle trends as a percentage of 3-candle trends. This offers more insight into what might happen next at any given point in time.
Plots
I have added plots as a visual aid to the various candle trend scenarios listed in the table. Green up-arrows, with the number of the trend part, denote green candle trends. Red down-arrows, with the number of the trend part, denote red candle trends.
█ HOW TO USE
This indicator is intended for research purposes, strategy development and strategy optimisation. I hope it will be useful in helping to gain a better understanding of the underlying dynamics at play on any given market and timeframe.
It can, for example, give you an idea of whether the next candle will close higher or lower than it opened, based on the current scenario and what has happened in the past under similar circumstances. Such information can be very useful when conducting top down analysis across multiple timeframes and making strategic decisions.
What you do with these statistics and how far you decide to take your research is entirely up to you, the possibilities are endless.
█ LIMITATIONS
Some higher timeframe candles on tickers with larger lookbacks such as the DXY , do not actually contain all the open, high, low and close (OHLC) data at the beginning of the chart. Instead, they use the close price for open, high and low prices. So, while we can determine whether the close price is higher or lower than the preceding close price, there is no way of knowing what actually happened intra-bar for these candles. And by default candles that close at the same price as the open price, will be counted as green. You can avoid this problem by utilising the sample period filter.
The green and red candle calculations are based solely on differences between open and close prices, as such I have made no attempt to account for green candles that gap lower and close below the close price of the preceding candle, or red candles that gap higher and close above the close price of the preceding candle. I can only recommend using 24-hour markets, if and where possible, as there are far fewer gaps and, generally, more data to work with. Alternatively, you can replace the scenarios with your own logic to account for the gap anomalies, if you are feeling up to the challenge.
It is also worth noting that the sample size will be limited to your Trading View subscription plan. Premium users get 20,000 candles worth of data, pro+ and pro users get 10,000, and basic users get 5,000. If upgrading is currently not an option, you can always keep a rolling tally of the statistics in an excel spreadsheet or something of the like.
Bearish Market Indicator V2Definition
Have you ever wonder whether if the stock/index/market is "bearish" ? A Bearish Market Indicator (B.M.I) is not a new concept, the definition is simply 20% lower from the recent (term: short-term, recent: usually within a year, a.k.a 1 year) highs (closing price with in the recent period or within in a year or simply a 52-Week High). It is called “bearish” by definition when the closing price is below 20% from the highest price within the year (52-Week high: Green Line). To visualize the “20%” below the recent highs, there is a plot (line: light yellow color in the middle) called a Bearish Market By Definition Value. For example, the SPX 500 has been in a bearish market which is why there is a purple color highlight over the 52-Week High (green line) since September 21, 2022 because the closing price is below the Bearish Market By Definition Value (light yellow color) or “20% below the recent highs”. Finally, there is a red line under in the graph and it is the lowest price within a year. So when you hear, “this ticker is at a 52-Week Low”, you know what it means.
Line Summary:
Green Color Line = 52-Week High
Yellow Color Line = 20% away from the 52-Week High or Bearish Market By Definition Value
Red Color Line = 52-Week Low
Color Summary:
Red Color = Bad
Saturated Red Color = Very Bad
Purple Color = Bearish (It may look pink: red + purple)
White Color = Less Bad (That’s because there is no certainty only probability)
Green Color = Not too Bad (That’s because there is no certainty only probability)
Now to more complicated Metrics
>> If you do not like the technical indicators, go to the indicator settings, uncheck the tables. Otherwise, please continue reading. <<
Pre-requisites
+ Understand that the indicators are lagging indicators.
+ Using it under “D” or “Day” interval
+ Already Understand: Moving Averages, Stochastic-RSI, RSI, Super Trend and MACD.
+ Please be aware that this might not be compatible with traders!
Indicators
This B.M.I is fused (comprised, combined) with multiple indicators:
- Moving Averages
I would not rely just on the Moving Averages (MA) since it is a lagging indicator. The values are derived by finding the differences with respect to the MAs (between the closing price and with the respect MA).
- Stochastic-RSI
Stochastic and RSI combo with RSI-Color coating. The first value is the rsi-stochastic-k followed by the rsi-stochastic-d both are compartmentalized with “|”.
Parameter:
Numbers > 80 Not Good
Numbers < 20 Is it time? (You can manually verify the lines (k, d) or the values from them)
- Relative Strength Index (RSI)
The first value is the rsi followed by the rsi-ma both are compartmentalized with “|”. It is also coated with RSI-color.
Parameter:
Numbers > 70 Overbought | Color Red
If the RSI > RSI’s MA = Green
If the RSI < RSI’s MA = Red
Numbers < 30 Oversold | Color Red
- Moving Averages Convergence Divergence (MACD)
The first value is the MACD-line followed by the signal-line both are compartmentalized with “|”.
Macd-line > signal line = green
Macd-line < signal line = red
- Supertrend (please look up from the documentation; i can not embed the link)
Think of this way, you’re riding a wave. If the wave is climbing, expect the price to follow.
Direction < 0 = Green
Direction > 0 = Red
- Other Trend similar to supertrend
This is similar to the Super Trend according the some. Imagine you’re drawing a trend line manually within 6 months.
Within the period, the line gets smoothed over and over til the n=9.
> If the closing is less than the 9th value, it implies the trend is slowing down.
Usage
Adjustments
+ Since there are different holidays from different countries, you can change the BMI-Period from the indicator settings “BMI-4khansolo”.
+ You can hide Technical Indicator Tables, it is also under the settings (see above).
> This will show red over the 52-Week high if it tests for positive .
Purpose
Do you like eating the same food over and over? No! I love different food! I also love a variety of indicators. Especially, I love having MULTIPLE indicators presented in one canvas at the same time (personalized).
After spending a lot of time, I want to share my “FOOD” which is made of different ingredients (indicators) with someone who appreciates food! This Makes me a chef isn't it? Yes! Chef!
Questions?
If you have questions or spotted errors, please comment them below so that I can improve.
Sources
All the materials (i.e., functions like ta.rsi, etc...) used in here are available in the platform.
All the references or sources materials are commented with the code since the I am not allowed to put them here.
R:R Trading System FrameworkFirst off, huge thanks to @fikira! He was able to adapt what I built to work much more efficiently, allowing for more strategies to be used simultaneously. Simply put, I could not have gotten to this point without you. Thanks for what you do for the TV community. Second, I am fairly new to pinescript writing, so I welcome criticism, thoughtful input and improvement suggestions. I would love to grow this concept into something even better, if possible. So please let me know if you have any ideas for improvement. However I do juggle a lot of different things outside of TV, so implementations may be delayed.
I have decided, at this time, not to add alerts. First, because I feel most people looking to adapt this framework can add their own pretty easily. Also, given how customized the framework is currently, while also attempting to account for all the possible ways in which people may want alerts to function after they customize it, it seems best to leave them out as it doesn't exactly fit the idea of a framework.
For best viewing, I recommend hovering over the script's name > ... > Visual order > Bring to front. Also I found hollow candles with mono-toned colors (like pictured) are more visually appealing for me personally. I HIGHLY RECOMMEND USING WITH BAR REPLAY TO BETTER UNDERSTAND THE FRAMEWORK'S FUNCTIONALITY.
▶️ WHAT THIS FRAMEWORK IS
- A huge collection of concepts and capabilities for those trying to better understand, learn, or teach pinescript.
- A system designed to showcase Risk:Reward concepts more holistically by providing all of the most popular components of retail trading to include backtesting, trade visual plotting, position tracking, market condition shifts, and useful info while positioned to help highlight changes in your risk:reward based decision-making processes.
- A system that can showcase individual strategies regardless of trade direction, allowing you to develop hedging strategies without having multiple indicators that do not correlate with each other.
- Designed around the idea that you trade less numbers of assets but manage your positions and risk based on multiple concurrently running strategies to manage your risk exposure and reward potential.
- An attempt to combine all the things you need to execute with an active trading management style.
- A framework that uses backtested results (in this case the number of averaged bars it takes to hit key levels) in real-time to inform your risk:reward decision-making while in-trade (in this case in your Trade Tracking Table using dynamic color to show how you might be early, on-time, or late compared to the average amount of backtested time it normally takes to hit that specific key level).
▶️ WHAT THIS FRAMEWORK IS NOT
- A complete trading product. DO NOT USE as-is. It is a FRAMEWORK for you to generate ideas of your own and fairly easily implement your own triggering conditions in the appropriate sections of the script.
▶️ USE CASES
- If you decide you like the Stop, Target, Trailing Stop, and Risk:Reward components as-is, then just understanding how to plug in your Entry and Bullish / Bearish conditions (Triangles) and adjust the input texts to match your custom naming will be all you need to make it your own!
- If you want to adapt certain components, then this system gives you a great starting point to adapt your different concepts and ideas from.
▶️ SYSTEM COMPONENTS
- Each of the system's components are described via tooltips both in the input menu and in the tables' cells.
- Each label on the chart displays the corresponding price at those triggered conditions on hover with tooltips.
- The Trailing Stop only becomes active once it is above the Entry Price for that trade, and brightens to show it is active. The STOP line (right of price) moves once it takes over for the Entry Stop representing the level of the Trailing Stop at that time for that trade.
- The Lines / Labels to the right of price will brighten once price is above for Longs or below for Shorts. The Trade Tracking Table cells will add ☑️ once price is above for Longs or below for Shorts.
- The brighter boxes on the chart show the trades that occurred based on your criteria and are color coded for all components of each trade type to ensure your references are consistent. (Defaults are TV built-in strategies)
- The lighter boxes on the chart show the highest and lowest price levels reached during those trades, to highlight areas where improvements can be made or additional considerations can be accounted for by either adjusting Entry triggers or Bullish / Bearish triggers.
- Default Green and Red Triangles (Bullish / Bearish) default to having the same triggering condition as the Entry it corresponds to. This is to highlight either a pyramiding concept, early exit, or you can change to account for other things occurring during your trades which could help you with Stop and Target management/considerations.
TradingView and many of its community members have done a lot for me, so this is my attempt to give back.
Crypto Terminal [Kioseff Trading]Hello!
Introducing Crypto Terminal (:
The indicator makes use of cryptocurrency data provided by vendor INTOTHEBLOCK.
NOTE: The cryptocurrency on your chart must be paired with USD or USDT. Data won't load otherwise - possibly transient. For instance, BTCUSD or BTCUSDT, ETHUSD or ETHUSDT.
Provided datasets:
Twitter Sentiment Data
Telegram Sentiment Data
Whale Data (i.e. % of Asset Belonging to Whales)
$100,000+ Transactions
Bulls/Bears (Bulls Buying | Bears Selling)
Current Position PnL (Currently Open Positions for the Coin are Retrieved and Plotted. Data is Split into Currently Profitable Positions, Losing Positions, and B/E Positions)
Average Balance
Holders/Traders Percentage (Addresses are Retrieved and Classified as Holding Accounts or Trader Accounts)
Correlation
Futures OI
Perpetual OI
Zero Balance Addresses
Flow (Money Inflow & Outflow)
Active Addresses
Average Transaction Time
Realized PnL (Addresses with Realized Profits, Realized Losses, and B/E)
Cruisers
A few more data points are provided.
Additionally, you can plot the values of any dataset in a pane below price.
Below are images of plottable data; different cryptocurrencies will be shown for each example (:
Twitter sentiment data.
Assess this data lightly; difficult to confirm accuracy.
Telegram sentiment data.
Assess this data lightly; difficult to confirm accuracy.
Percentage of asset belonging to whales.
$100,000+ transactions (volume oriented)
Bulls buying; bears selling.
Current positions at profit; current positions at loss; current positions at breakeven.
Average balance.
Percentage of asset belonging to traders; percentage of asset belonging to holders.
Asset's 30-interval correlation to BTC.
Perpetual open interest.
Zero-balance addresses.
Flows.
Active addresses.
Average transaction time.
Addresses at realized profit; addresses at realized loss; addresses at breakeven.
Cruiser data.
Futures open interest.
Naturally, this data isn't provided for every cryptocurrency; NaN values are returned in some instances.
Table 1
I provided three data tables, which load independently, so you don't have to change plotted data to access values.
Table 2
Lastly, you can create a 10-asset crypto index and run calculations against it.
The image shows an example.
I'll update this script with additional calculations/data in the near future. If you've any suggestions - please let me know!
Enjoy (:
_matrixLibrary "_matrix"
Library helps visualize matrix as array of arrays and enables users to use array methods such as push, pop, shift, unshift etc along with cleanup activities on drawing objects wherever required
unshift(mtx, row) unshift array of lines to first row of the matrix
Parameters:
mtx : matrix of lines
row : array of lines to be inserted in row
Returns: resulting matrix of lines
unshift(mtx, row) unshift array of labels to first row of the matrix
Parameters:
mtx : matrix of labels
row : array of labels to be inserted in row
Returns: resulting matrix labels
unshift(mtx, row) unshift array of boxes to first row of the matrix
Parameters:
mtx : matrix of boxes
row : array of boxes to be inserted in row
Returns: resulting matrix of boxes
unshift(mtx, row) unshift array of linefill to first row of the matrix
Parameters:
mtx : matrix of linefill
row : array of linefill to be inserted in row
Returns: resulting matrix of linefill
unshift(mtx, row) unshift array of tables to first row of the matrix
Parameters:
mtx : matrix of tables
row : array of tables to be inserted in row
Returns: resulting matrix of tables
unshift(mtx, row) unshift array of int to first row of the matrix
Parameters:
mtx : matrix of int
row : array of int to be inserted in row
Returns: resulting matrix of int
unshift(mtx, row) unshift array of float to first row of the matrix
Parameters:
mtx : matrix of float
row : array of float to be inserted in row
Returns: resulting matrix of float
unshift(mtx, row) unshift array of bool to first row of the matrix
Parameters:
mtx : matrix of bool
row : array of bool to be inserted in row
Returns: resulting matrix of bool
unshift(mtx, row) unshift array of string to first row of the matrix
Parameters:
mtx : matrix of string
row : array of string to be inserted in row
Returns: resulting matrix of string
unshift(mtx, row) unshift array of color to first row of the matrix
Parameters:
mtx : matrix of colors
row : array of colors to be inserted in row
Returns: resulting matrix of colors
push(mtx, row) push array of lines to end of the matrix row
Parameters:
mtx : matrix of lines
row : array of lines to be inserted in row
Returns: resulting matrix of lines
push(mtx, row) push array of labels to end of the matrix row
Parameters:
mtx : matrix of labels
row : array of labels to be inserted in row
Returns: resulting matrix of labels
push(mtx, row) push array of boxes to end of the matrix row
Parameters:
mtx : matrix of boxes
row : array of boxes to be inserted in row
Returns: resulting matrix of boxes
push(mtx, row) push array of linefill to end of the matrix row
Parameters:
mtx : matrix of linefill
row : array of linefill to be inserted in row
Returns: resulting matrix of linefill
push(mtx, row) push array of tables to end of the matrix row
Parameters:
mtx : matrix of tables
row : array of tables to be inserted in row
Returns: resulting matrix of tables
push(mtx, row) push array of int to end of the matrix row
Parameters:
mtx : matrix of int
row : array of int to be inserted in row
Returns: resulting matrix of int
push(mtx, row) push array of float to end of the matrix row
Parameters:
mtx : matrix of float
row : array of float to be inserted in row
Returns: resulting matrix of float
push(mtx, row) push array of bool to end of the matrix row
Parameters:
mtx : matrix of bool
row : array of bool to be inserted in row
Returns: resulting matrix of bool
push(mtx, row) push array of string to end of the matrix row
Parameters:
mtx : matrix of string
row : array of string to be inserted in row
Returns: resulting matrix of string
push(mtx, row) push array of colors to end of the matrix row
Parameters:
mtx : matrix of colors
row : array of colors to be inserted in row
Returns: resulting matrix of colors
shift(mtx) shift removes first row from matrix of lines
Parameters:
mtx : matrix of lines from which the shift operation need to be performed
Returns: void
shift(mtx) shift removes first row from matrix of labels
Parameters:
mtx : matrix of labels from which the shift operation need to be performed
Returns: void
shift(mtx) shift removes first row from matrix of boxes
Parameters:
mtx : matrix of boxes from which the shift operation need to be performed
Returns: void
shift(mtx) shift removes first row from matrix of linefill
Parameters:
mtx : matrix of linefill from which the shift operation need to be performed
Returns: void
shift(mtx) shift removes first row from matrix of tables
Parameters:
mtx : matrix of tables from which the shift operation need to be performed
Returns: void
shift(mtx) shift removes first row from matrix of int
Parameters:
mtx : matrix of int from which the shift operation need to be performed
Returns: void
shift(mtx) shift removes first row from matrix of float
Parameters:
mtx : matrix of float from which the shift operation need to be performed
Returns: void
shift(mtx) shift removes first row from matrix of bool
Parameters:
mtx : matrix of bool from which the shift operation need to be performed
Returns: void
shift(mtx) shift removes first row from matrix of string
Parameters:
mtx : matrix of string from which the shift operation need to be performed
Returns: void
shift(mtx) shift removes first row from matrix of colors
Parameters:
mtx : matrix of colors from which the shift operation need to be performed
Returns: void
pop(mtx) pop removes last row from matrix of lines
Parameters:
mtx : matrix of lines from which the pop operation need to be performed
Returns: void
pop(mtx) pop removes last row from matrix of labels
Parameters:
mtx : matrix of labels from which the pop operation need to be performed
Returns: void
pop(mtx) pop removes last row from matrix of boxes
Parameters:
mtx : matrix of boxes from which the pop operation need to be performed
Returns: void
pop(mtx) pop removes last row from matrix of linefill
Parameters:
mtx : matrix of linefill from which the pop operation need to be performed
Returns: void
pop(mtx) pop removes last row from matrix of tables
Parameters:
mtx : matrix of tables from which the pop operation need to be performed
Returns: void
pop(mtx) pop removes last row from matrix of int
Parameters:
mtx : matrix of int from which the pop operation need to be performed
Returns: void
pop(mtx) pop removes last row from matrix of float
Parameters:
mtx : matrix of float from which the pop operation need to be performed
Returns: void
pop(mtx) pop removes last row from matrix of bool
Parameters:
mtx : matrix of bool from which the pop operation need to be performed
Returns: void
pop(mtx) pop removes last row from matrix of string
Parameters:
mtx : matrix of string from which the pop operation need to be performed
Returns: void
pop(mtx) pop removes last row from matrix of colors
Parameters:
mtx : matrix of colors from which the pop operation need to be performed
Returns: void
clear(mtx) clear clears the matrix of lines
Parameters:
mtx : matrix of lines which needs to be cleared
Returns: void
clear(mtx) clear clears the matrix of labels
Parameters:
mtx : matrix of labels which needs to be cleared
Returns: void
clear(mtx) clear clears the matrix of boxes
Parameters:
mtx : matrix of boxes which needs to be cleared
Returns: void
clear(mtx) clear clears the matrix of linefill
Parameters:
mtx : matrix of linefill which needs to be cleared
Returns: void
clear(mtx) clear clears the matrix of tables
Parameters:
mtx : matrix of tables which needs to be cleared
Returns: void
clear(mtx) clear clears the matrix of int
Parameters:
mtx : matrix of int which needs to be cleared
Returns: void
clear(mtx) clear clears the matrix of float
Parameters:
mtx : matrix of float which needs to be cleared
Returns: void
clear(mtx) clear clears the matrix of bool
Parameters:
mtx : matrix of bool which needs to be cleared
Returns: void
clear(mtx) clear clears the matrix of string
Parameters:
mtx : matrix of string which needs to be cleared
Returns: void
clear(mtx) clear clears the matrix of colors
Parameters:
mtx : matrix of colors which needs to be cleared
Returns: void
Currency Strength Meter [HeWhoMustNotBeNamed]⬜ Note: This is not the strength of currency pairs. But, in this script we are trying to derive strength of individual currencies by matching against single base currency.
⬜ Process
This is based on similar concept as that of Magic Numbers for stocks. Idea is simple.
▶ Calculate strength of each currency against USD. Derive the strength for both price movement and volume movement.
▶ Similarly calculate momentum of price and volume change.
▶ If USD is base currency, inverse momentum and strength index for the given symbol.
▶ Once these calculations are done, rank each currencies based on individual score on given things.
▶ Add up all the ranks to derive combined rank
▶ sort the currencies in the ascending order of overall rank.
⬜ USAGE
▶ Identify a base currency. In our case, we have used USD as base currency as it is easy to get pairs of all currencies with USD.
▶ Identify most used combos for all other currencies which are paired with USD. Fx pair can either have USD as base currency or quote currency. It is desirable to use the pair which is most traded. For example, USDJPY is more traded pair than JPYUSD - hence it is advisable to use USDJPY instead of JPYUSD. Similarly AUDUSD is more traded than USDAUD - hence choosing AUDUSD for the purpose of this exercise is better approach. Notice that USDJPY has USD as base currency whereas AUDUSD has USD as quote currency. These calculations are handled internally to derive the right outcome irrespective of position of USD in the pair.
▶ Identify the forex broker which has all the selected forex tickers. All comparison is done against a single broker. Hence, choosing broker which does not wide range of forex pairs will show NAN for many rows.
▶ Once we set these, we get tabular output containing strength and oscillator based trend indexes for both price and volume indicator. Currencies are ordered in descending order of strength. Hence, top of the list can be considered as currency having highest strength and bottom of the table can be considered as currency having lowest strength. Please note that the calculation is valid only for selected timeframe and users can set other parameters such as moving average type, oscillator type, length etc which can alter the outcome.
▶ Use multiple timeframes to find out stronger and weaker currencies. Use directional indicators to understand where they are heading. Combine all these info to come up with currency pair you would like to trade :)
⬜ Settings
▶ Main settings and Currencies
Base Currency : This is set to USD by default as rest of the tickers used are paired with USD. Whatever the base currency is selected, rest of the tickers should follow the same combination.
Timeframe : Timeframe for which rankings need to be calculated.
Currencies : These should be the currency pair which involve base currency defined in the setting on either side.
▶ Display
Table : Allows users to set table location and size of the table. By default this is set to middle center and default size is normal. If user want to use multiple timeframes side by side, they can do so by changing these display settings.
Stat Type : To show either comparative ranking or actual indicator values
vx_termsUSAGE
--------
This script helps train your intuition for changes in the VX term structure. I recommend using it on the VIX chart, so you can compare changes in the terms to changes in VIX. It's also nice for calendar spread traders who want to get a feel for the same changes.
1. Select a day, month, and year using the inputs
2. Observe the data table.
3. Open the input again and increment or decrement the day (and month, year as necessary).
4. Click "Ok".
5. Click to deselect the indicator, which allows the chart to load new data.
6. The data table will be reloaded with the next/previous day's data.
The data table has the following columns:
- contract: the VX contracts, in sequence. refer to the CBOE for month codes (F for January, etc.)
- close: the closing price of the contract.
- ma:mb: the spread (difference) between this row and the next row.
- ma:mb chg: the spread's change from prior close.
For example, given the following values for the first two columns:
VXQ2021, 16.5, -3.1, -0.2
VXU2021, 19.6, ..., ...
The front month (Q = august) closed at 16.5, $3.1 below the s\September contract. The negative spread enlarged by $0.20 from $2.90 on the previous trading day.
BUGS, ODDITIES, AND LIMITATIONS:
-------------------------------------------
- The first column will be greyed out after expiration day, which is the 3rd Tuesday of that month. Unfortunately, I can't load the next month's contract due to some limitations with TV.
- The active date is highlighted with a yellow background. When a non-trading date is selected, the highlight will disappear. However, the data table will sometimes fill with the nearest trading date, prematurely. No worries, just know that the data is probably for the previous Friday.
- The script is clunky and slow, but this is the best I can do with TV. Hopefully they add more continuous contracts or allow true dynamic symbol loading.
SPECIAL THANKS:
---------------------
Thanks to HeWhoMustNotBeNamed for helping me get through some messiness. Very helpful guy.
www.tradingview.com
BankNifty Multi-TimeFrames Price Panel [MaestroTrader]█ OVERVIEW
Price Panel provides Nifty /BankNifty Index comprehensive Price Insights on different time intervals. It helps to determine the trend of Index using top Index Heavy Weights along with Dow, India VIX & Index Spot Prices. It helps to determine the price behavior of the underlying Index/stock to make informed decisions while trading.
█ FEATURES
a) Displays Price in Multi Time Frames for Multi time frame analysis
b) Displays Weighted Securities price for Weighted INDEX price analysis.
c) Displays INDIA VIX and DOW for Combined INDIX VOLATALITY Analysis
█ MUTLI TIME FRAME ANALYSIS
How to use Multiple time frame analysis?
Multiple time frame analysis follows a top-down approach when trading and allows traders to gauge the longer-term trend while spotting ideal entries on a smaller time frame. Traders can then conduct technical analysis using multiple time frames to confirm or reject their trading bias.
Multiple time frame analysis, is the process of viewing the same symbols under different time frames. Usually, the larger time frame is used to establish a longer-term trend, while a shorter time frame is used to spot ideal entries into the market.
Let’s Say 75 & 15 TF’s Trend is up, then shorter time 5M is used to spot ideal entries on long side.
█ WEIGHTED INDEXS PRICE ANALYSIS
How to use Weighted Index Price Movement in Multi timeframes?
The index future trading price is based on the trading prices of the individual securities (stocks) that comprise the index basket. In other words, the stocks with higher weights will have more impact on the movement of the index. Price Panel provides the insights of these heavy weight stock price movement in different time frames, that can help you confirm or reject your trading bias.
HDFC Bank (28% Weight) will have more impact on the BankNifty Movement. By looking the top 4 bank's price movement in different timeframes, you can derive the BankNifty price trend.
█ VOLATALITY ANALYSIS
India VIX is a short form for India Volatility Index. It is the volatility index that measures the market’s expectation of volatility over the near term.
A lower VIX level usually implies that the market is confident about the movement and is expecting lower volatility and a stable range.
A higher VIX level usually signals high volatility and lower trader confidence about the current range of the market. A major directional move can be expected in the market and a quick broadening of range can be expected.
█ SETTINGS
• Time Frame Settings: Configure Time Frames 5 Min, 15 Min, 75 Min
• Table Settings: Configure Table Styles- Position- Font Color
• Symbol Settings: Configure Securities. Toggle (on/Off) Securities display.
• Index Settings: Display Bank Nifty or Nifty Heavy Weights.
█ PANEL DISPLAY VARIATIONS
BANK NIFTY VIEW
NIFTY VIEW
WITHOUT STOCKS - ONLY INDEX, VIX, DOW
█ THANKS
Thanks to Pine Team for this new great feature tables & Thanks to PineCoders for the `f_strRightOf` function.
█ DISCLIAMER
Indicator is built for educational purposes. Test it before use.
Hope - These features help you get quick insights of the price movement to take informed trades.
You are free to use the code, please share the credit for reuse.
Happy Trading !!
Big Mo’s Glaskugel — Macro Drawdown Risk (v1.1.2)What it does / what you see
An at-a-glance drawdown-risk oscillator that blends several macro US signals.
• A smooth, color-blended line (green→orange→red) shows the scaled risk score (0–100).
• Subtle shading marks “re-steepen warning windows” (starts when the yield curve re-steepens after an inversion; ends on normalization/cool-down).
• A compact status table summarizes: overall risk level, Yield Curve (10y–3m), Credit Stress (Baa–10y), Economy (LEI), and Valuation (CAPE).
Data used & why
Yield Curve (10y–3m) — FRED:T10Y3M. Inversions and subsequent re-steepens often precede recessions/equity drawdowns.
Credit Stress — FRED:BAA10Y vs its 1-year average (deviation in bps). Widening credit spreads flag tightening financial conditions.
Economy (LEI) — ECONOMICS:USLEI. 6-month annualized growth below a cutoff highlights macro deterioration.
Valuation (CAPE) — SHILLER_PE_RATIO_MONTH. Elevated valuations can amplify downside risk.
VIX spikes — optional boost that recognizes sudden risk repricings.
Important disclaimer
This is not a reliable or predictive indicator in all regimes. No guarantees or warranties of any kind are provided. It is not financial advice. Signals can be early, late, or wrong.
That said, it leans on well-studied warning factors (yield-curve dynamics, credit spreads, LEI weakness, valuation extremes) that have flagged major market downturns in the past.
Key customization / tweaks
Weights for each component (Yield, Credit, LEI, VIX, CAPE).
Thresholds: yield inversion months, re-steepen lookback, credit-stress bps, LEI cutoff, CAPE level, VIX spike levels.
Re-steepen boost: enable/disable, base points, half-life decay.
Shading behavior: cool-down bars to “unwarn,” max warning duration, only shade when risk ≠ green.
Scaling & smoothing: dynamic rolling max, EMA length, yellow/red thresholds.
Status table: position, and a snapshot mode to view values at a chosen historical time.
Sunmool's Silver Bullet Model FinderICT Silver Bullet Model Indicator - Complete Guide
📈 Overview
The ICT Silver Bullet Model indicator is a supplementary tool for utilizing ICT's (Inner Circle Trader) market structure analysis techniques. This indicator detects institutional liquidity hunting patterns and automatically identifies structural levels, helping traders analyze market structure more effectively.
🎯 Core Features
1. Structural Level Identification
STL (Short Term Low): Recent support levels formed in the short term
STH (Short Term High): Recent resistance levels formed in the short term
ITL (Intermediate Term Low): Stronger support levels with more significance
ITH (Intermediate Term High): Stronger resistance levels with more significance
2. Kill Zone Time Display
London Kill Zone: 02:00-05:00 (default)
New York Kill Zone: 08:30-11:00 (default)
These are the most active trading hours for institutional players where significant price movements occur
3. Smart Sweep Detection
Bear Sweep (🔻): Pattern where price sweeps below lows then recovers - Simply indicates sweep occurrence
Bull Sweep (🔺): Pattern where price sweeps above highs then declines - Simply indicates sweep occurrence
Important: Sweep labels only mark liquidity hunting locations, not directional bias.
🔧 Configuration Parameters
Basic Settings
Sweep Detection Lookback: Number of candles for sweep detection (default: 20)
Structure Point Lookback: Number of candles for structural point detection (default: 10)
Sweep Threshold: Percentage threshold for sweep validation (default: 0.1%)
Time Settings
London Kill Zone: Active hours for London session
New York Kill Zone: Active hours for New York session
Visualization Settings
Customizable colors for each level type
Enable/disable alert notifications
📊 How to Use
1. Chart Setup
Most effective on 1-minute to 1-hour timeframes
Recommended for major currency pairs (EUR/USD, GBP/USD, etc.)
Also applicable to cryptocurrencies and indices
2. Signal Interpretation
🔻 Bear Sweep / 🔺 Bull Sweep Labels
Simply indicate liquidity hunting occurrence points
Not directional bias indicators
Reference for understanding overall context on HTF
🟢 Silver Bullet Long (Huge Green Triangle)
After Bear Sweep occurrence
Within Kill Zone timeframe
Current price positioned above swept level
→ Actual BUY entry signal
🔴 Silver Bullet Short (Huge Red Triangle)
After Bull Sweep occurrence
Within Kill Zone timeframe
Current price positioned below swept level
→ Actual SELL entry signal
3. Risk Management
Use swept levels as stop-loss reference points
Approach signals outside Kill Zone hours with caution
Recommended to use alongside other technical analysis tools
💡 Trading Strategies
Silver Bullet Strategy
Preparation Phase: Monitor charts 30 minutes before Kill Zone
Sweep Observation: Identify liquidity hunting points with 🔻🔺 labels (reference only)
Entry: Enter ONLY when huge triangle Silver Bullet signal appears within Kill Zone
Take Profit: Target opposite structural level or 1:2 reward ratio
Stop Loss: Beyond the swept level
Important: Small sweep labels are NOT trading signals!
Multi-Timeframe Approach
Step 1: HTF (Higher Time Frame) Sweep Reference
Observe 🔻🔺 sweep labels on 4-hour and daily charts
Reference only sweeps occurring at major structural levels
HTF sweeps are used to identify liquidity hunting points
Reference only, not for directional bias
Step 2: Transition to LTF (Lower Time Frame)
Move to 15-minute, 5-minute, and 1-minute charts
Analyze LTF with reference to HTF sweep information
Use STL, STH, ITL, ITH for precise entry point identification
Structural levels on LTF are the core of actual trading decisions
Only huge triangle (Silver Bullet) signals are actual entry signals
Recommended Usage
Identify overall sweep occurrence points on HTF (🔻🔺 labels)
Use this indicator on LTF to identify structural levels
Reference only huge triangle signals for actual trading during Kill Zone
Small sweep labels (🔻🔺) are for reference only, not entry signals
📋 Information Table Interpretation
Real-time information in the top-right table:
Kill Zone Status: Current active session status
Level Counts: Number of each structural level type
⚠️ Important Disclaimers
Backtesting results do not guarantee future performance
Exercise caution during high market volatility periods
Always apply proper risk management
Recommend comprehensive analysis with other analytical tools
🎓 Learning Resources
Study original ICT concepts through free YouTube educational content
Research Market Structure analysis techniques
Optimize through backtesting for personal use
🔬 Technical Implementation
Algorithm Logic
Pivot Point Detection: Uses TradingView's built-in pivot functions to identify swing highs and lows
Classification System: Automatically categorizes levels based on recent price action frequency
Sweep Validation: Confirms legitimate sweeps through price action analysis
Time-Based Filtering: Prioritizes signals during institutional active hours
Performance Optimization
Efficient array management prevents memory overflow
Dynamic level cleanup maintains chart clarity
Real-time calculation ensures minimal lag
🛠️ Customization Tips
Adjust lookback periods based on market volatility
Modify kill zone times for different market sessions
Experiment with sweep threshold for different instruments
Color-code levels according to personal preference
📈 Expected Outcomes
When properly implemented, this indicator can help traders:
Identify high-probability reversal points
Time entries with institutional flow
Reduce false signals through kill zone filtering
Improve risk-to-reward ratios
This indicator automates ICT's concepts into a user-friendly tool that can be enhanced through continuous learning and practical application. Success depends on understanding the underlying market structure principles and combining them with proper risk management techniques.
Advanced Trend Momentum [Alpha Extract]The Advanced Trend Momentum indicator provides traders with deep insights into market dynamics by combining exponential moving average analysis with RSI momentum assessment and dynamic support/resistance detection. This sophisticated multi-dimensional tool helps identify trend changes, momentum divergences, and key structural levels, offering actionable buy and sell signals based on trend strength and momentum convergence.
🔶 CALCULATION
The indicator processes market data through multiple analytical methods:
Dual EMA Analysis: Calculates fast and slow exponential moving averages with dynamic trend direction assessment and ATR-normalized strength measurement.
RSI Momentum Engine: Implements RSI-based momentum analysis with enhanced overbought/oversold detection and momentum velocity calculations.
Pivot-Based Structure: Identifies and tracks dynamic support and resistance levels using pivot point analysis with configurable level management.
Signal Integration: Combines trend direction, momentum characteristics, and structural proximity to generate high-probability trading signals.
Formula:
Fast EMA = EMA(Close, Fast Length)
Slow EMA = EMA(Close, Slow Length)
Trend Direction = Fast EMA > Slow EMA ? 1 : -1
Trend Strength = |Fast EMA - Slow EMA| / ATR(Period) × 100
RSI Momentum = RSI(Close, RSI Length)
Momentum Value = Change(Close, 5) / ATR(10) × 100
Pivot Support/Resistance = Dynamic pivot arrays with configurable lookback periods
Bullish Signal = Trend Change + Momentum Confirmation + Strength > 1%
Bearish Signal = Trend Change + Momentum Confirmation + Strength > 1%
🔶 DETAILS
Visual Features:
Trend EMAs: Fast and slow exponential moving averages with dynamic color coding (bullish/bearish)
Enhanced RSI: RSI oscillator with color-coded zones, gradient fills, and reference bands at overbought/oversold levels
Trend Fill: Dynamic gradient between EMAs indicating trend strength and direction
Support/Resistance Lines: Horizontal levels extending from pivot-based calculations with configurable maximum levels
Momentum Candles: Color-coded candlestick overlay reflecting combined trend and momentum conditions
Divergence Markers: Diamond-shaped signals highlighting bullish and bearish momentum divergences
Analysis Table: Real-time summary of trend direction, strength percentage, RSI value, and momentum reading
Interpretation:
Trend Direction: Bullish when Fast EMA crosses above Slow EMA with strength confirmation
Trend Strength > 1%: Strong trending conditions with institutional participation
RSI > 70: Overbought conditions, potential selling opportunity
RSI < 30: Oversold conditions, potential buying opportunity
Momentum Divergence: Price and momentum moving opposite directions signal potential reversals
Support/Resistance Proximity: Dynamic levels provide optimal entry/exit zones
Combined Signals: Trend changes with momentum confirmation generate high-probability opportunities
🔶 EXAMPLES
Trend Confirmation: Fast EMA crossing above Slow EMA with trend strength exceeding 1% and positive momentum confirms strong bullish conditions.
Example: During institutional accumulation phases, EMA crossovers with momentum confirmation have historically preceded significant upward moves, providing optimal long entry points.
15min
4H
Momentum Divergence Detection: RSI reaching overbought levels while momentum decreases despite rising prices signals potential trend exhaustion.
Example: Bearish divergence signals appearing at resistance levels have marked major market tops, allowing traders to secure profits before corrections.
Support/Resistance Integration: Dynamic pivot-based levels combined with trend and momentum signals create high-probability trading zones.
Example: Bullish trend changes occurring near established support levels offer optimal risk-reward entries with clearly defined stop-loss levels.
Multi-Dimensional Confirmation: The indicator's combination of trend, momentum, and structural analysis provides comprehensive market validation.
Example: When trend direction aligns with momentum characteristics near key structural levels, the confluence creates institutional-grade trading opportunities with enhanced probability of success.
🔶 SETTINGS
Customization Options:
Trend Analysis: Fast EMA Length (default: 12), Slow EMA Length (default: 26), Trend Strength Period (default: 14)
Support & Resistance: Pivot Length for level detection (default: 10), Maximum S/R Levels displayed (default: 3), Toggle S/R visibility
Momentum Settings: RSI Length (default: 14), Oversold Level (default: 30), Overbought Level (default: 70)
Visual Configuration: Color schemes for bullish/bearish/neutral conditions, transparency settings for fills, momentum candle overlay toggle
Display Options: Analysis table visibility, divergence marker size, alert system configuration
The Advanced Trend Momentum indicator provides traders with comprehensive insights into market dynamics through its sophisticated integration of trend analysis, momentum assessment, and structural level detection. By combining multiple analytical dimensions into a unified framework, this tool helps identify high-probability opportunities while filtering out market noise through its multi-confirmation approach, enabling traders to make informed decisions across various market cycles and timeframes.
Advanced Volume Profile Pro Delta + POC + VAH/VAL# Advanced Volume Profile Pro - Delta + POC + VAH/VAL Analysis System
## WHAT THIS SCRIPT DOES
This script creates a comprehensive volume profile analysis system that combines traditional volume-at-price distribution with delta volume calculations, Point of Control (POC) identification, and Value Area (VAH/VAL) analysis. Unlike standard volume indicators that show only total volume over time, this script analyzes volume distribution across price levels and estimates buying vs selling pressure using multiple calculation methods to provide deeper market structure insights.
## WHY THIS COMBINATION IS ORIGINAL AND USEFUL
**The Problem Solved:** Traditional volume indicators show when volume occurs but not where price finds acceptance or rejection. Standalone volume profiles lack directional bias information, while basic delta calculations don't provide structural context. Traders need to understand both volume distribution AND directional sentiment at key price levels.
**The Solution:** This script implements an integrated approach that:
- Maps volume distribution across price levels using configurable row density
- Estimates delta (buying vs selling pressure) using three different methodologies
- Identifies Point of Control (highest volume price level) for key support/resistance
- Calculates Value Area boundaries where 70% of volume traded
- Provides real-time alerts for key level interactions and volume imbalances
**Unique Features:**
1. **Developing POC Visualization**: Real-time tracking of Point of Control migration throughout the session via blue dotted trail, revealing institutional accumulation/distribution patterns before they complete
2. **Multi-Method Delta Calculation**: Price Action-based, Bid/Ask estimation, and Cumulative methods for different market conditions
3. **Adaptive Timeframe System**: Auto-adjusts calculation parameters based on chart timeframe for optimal performance
4. **Flexible Profile Types**: N Bars Back (precise control), Days Back (calendar-based), and Session-based analysis modes
5. **Advanced Imbalance Detection**: Identifies and highlights significant buying/selling imbalances with configurable thresholds
6. **Comprehensive Alert System**: Monitors POC touches, Value Area entry/exit, and major volume imbalances
## HOW THE SCRIPT WORKS TECHNICALLY
### Core Volume Profile Methodology:
**1. Price Level Distribution:**
- Divides price range into user-defined rows (10-50 configurable)
- Calculates row height: `(Highest Price - Lowest Price) / Number of Rows`
- Distributes each bar's volume across price levels it touched proportionally
**2. Delta Volume Calculation Methods:**
**Price Action Method:**
```
Price Range = High - Low
Buy Pressure = (Close - Low) / Price Range
Sell Pressure = (High - Close) / Price Range
Buy Volume = Total Volume × Buy Pressure
Sell Volume = Total Volume × Sell Pressure
Delta = Buy Volume - Sell Volume
```
**Bid/Ask Estimation Method:**
```
Average Price = (High + Low + Close) / 3
Buy Volume = Close > Average ? Volume × 0.6 : Volume × 0.4
Sell Volume = Total Volume - Buy Volume
```
**Cumulative Method:**
```
Buy Volume = Close > Open ? Volume : Volume × 0.3
Sell Volume = Close ≤ Open ? Volume : Volume × 0.3
```
**3. Point of Control (POC) Identification:**
- Scans all price levels to find maximum volume concentration
- POC represents the price level with highest trading activity
- Acts as significant support/resistance level
- **Developing POC Feature**: Tracks POC evolution in real-time via blue dotted trail, showing how institutional interest migrates throughout the session. Upward POC migration indicates accumulation patterns, downward migration suggests distribution, providing early trend signals before price confirmation.
**4. Value Area Calculation:**
- Starts from POC and expands up/down to encompass 70% of total volume
- VAH (Value Area High): Upper boundary of value area
- VAL (Value Area Low): Lower boundary of value area
- Expansion algorithm prioritizes direction with higher volume
**5. Adaptive Range Selection:**
Based on profile type and timeframe optimization:
- **N Bars Back**: Fixed lookback period with performance optimization (20-500 bars)
- **Days Back**: Calendar-based analysis with automatic timeframe adjustment (1-365 days)
- **Session**: Current trading session or custom session times
### Performance Optimization Features:
- **Sampling Algorithm**: Reduces calculation load on large datasets while maintaining accuracy
- **Memory Management**: Clears previous drawings to prevent performance degradation
- **Safety Constraints**: Prevents excessive memory usage with configurable limits
## HOW TO USE THIS SCRIPT
### Initial Setup:
1. **Profile Configuration**: Select profile type based on trading style:
- N Bars Back: Precise control over data range
- Days Back: Intuitive calendar-based analysis
- Session: Real-time session development
2. **Row Density**: Set number of rows (30 default) - more rows = higher resolution, slower performance
3. **Delta Method**: Choose calculation method based on market type:
- Price Action: Best for trending markets
- Bid/Ask Estimate: Good for ranging markets
- Cumulative: Smoothed approach for volatile markets
4. **Visual Settings**: Configure colors, position (left/right), and display options
### Reading the Profile:
**Volume Bars:**
- **Length**: Represents relative volume at that price level
- **Color**: Green = net buying pressure, Red = net selling pressure
- **Intensity**: Darker colors indicate volume imbalances above threshold
**Key Levels:**
- **POC (Blue Line)**: Highest volume price - major support/resistance
- **VAH (Purple Dashed)**: Value Area High - upper boundary of fair value
- **VAL (Orange Dashed)**: Value Area Low - lower boundary of fair value
- **Value Area Fill**: Shaded region showing main trading range
**Developing POC Trail:**
- **Blue Dotted Lines**: Show real-time POC evolution throughout the session
- **Migration Patterns**: Upward trail indicates bullish accumulation, downward trail suggests bearish distribution
- **Early Signals**: POC movement often precedes price movement, providing advance warning of institutional activity
- **Institutional Footprints**: Reveals where smart money concentrated volume before final POC establishment
### Trading Applications:
**Support/Resistance Analysis:**
- POC acts as magnetic price level - expect reactions
- VAH/VAL provide intermediate support/resistance levels
- Profile edges show areas of low volume acceptance
**Developing POC Analysis:**
- **Upward Migration**: POC moving higher = institutional accumulation, bullish bias
- **Downward Migration**: POC moving lower = institutional distribution, bearish bias
- **Stable POC**: Tight clustering = balanced market, range-bound conditions
- **Early Trend Detection**: POC direction change often precedes price breakouts
**Entry Strategies:**
- Buy at VAL with POC as target (in uptrends)
- Sell at VAH with POC as target (in downtrends)
- Breakout plays above/below profile extremes
**Volume Imbalance Trading:**
- Strong buying imbalance (>60% threshold) suggests continued upward pressure
- Strong selling imbalance suggests continued downward pressure
- Imbalances near key levels provide high-probability setups
**Multi-Timeframe Context:**
- Use higher timeframe profiles for major levels
- Lower timeframe profiles for precise entries
- Session profiles for intraday trading structure
## SCRIPT SETTINGS EXPLANATION
### Volume Profile Settings:
- **Profile Type**: Determines data range for calculation
- N Bars Back: Exact number of bars (20-500 range)
- Days Back: Calendar days with timeframe adaptation (1-365 days)
- Session: Trading session-based (intraday focus)
- **Number of Rows**: Profile resolution (10-50 range)
- **Profile Width**: Visual width as chart percentage (10-50%)
- **Value Area %**: Volume percentage for VA calculation (50-90%, 70% standard)
- **Auto-Adjust**: Automatically optimizes for different timeframes
### Delta Volume Settings:
- **Show Delta Volume**: Enable/disable delta calculations
- **Delta Calculation Method**: Choose methodology based on market conditions
- **Highlight Imbalances**: Visual emphasis for significant volume imbalances
- **Imbalance Threshold**: Percentage for imbalance detection (50-90%)
### Session Settings:
- **Session Type**: Daily, Weekly, Monthly, or Custom periods
- **Custom Session Time**: Define specific trading hours
- **Previous Sessions**: Number of historical sessions to display
### Days Back Settings:
- **Lookback Days**: Number of calendar days to analyze (1-365)
- **Automatic Calculation**: Script automatically converts days to bars based on timeframe:
- Intraday: Accounts for 6.5 trading hours per day
- Daily: 1 bar per day
- Weekly/Monthly: Proportional adjustment
### N Bars Back Settings:
- **Lookback Bars**: Exact number of bars to analyze (20-500)
- **Precise Control**: Best for systematic analysis and backtesting
### Visual Customization:
- **Colors**: Bullish (green), Bearish (red), and level colors
- **Profile Position**: Left or Right side of chart
- **Profile Offset**: Distance from current price action
- **Labels**: Show/hide level labels and values
- **Smooth Profile Bars**: Enhanced visual appearance
### Alert Configuration:
- **POC Touch**: Alerts when price interacts with Point of Control
- **VA Entry/Exit**: Alerts for Value Area boundary interactions
- **Major Imbalance**: Alerts for significant volume imbalances
## VISUAL FEATURES
### Profile Display:
- **Horizontal Bars**: Volume distribution across price levels
- **Color Coding**: Delta-based coloring for directional bias
- **Smooth Rendering**: Optional smoothing for cleaner appearance
- **Transparency**: Configurable opacity for chart readability
### Level Lines:
- **POC**: Solid blue line with optional label
- **VAH/VAL**: Dashed colored lines with value displays
- **Extension**: Lines extend across relevant time periods
- **Value Area Fill**: Optional shaded region between VAH/VAL
### Information Table:
- **Current Values**: Real-time POC, VAH, VAL prices
- **VA Range**: Value Area width calculation
- **Positioning**: Multiple table positions available
- **Text Sizing**: Adjustable for different screen sizes
## IMPORTANT USAGE NOTES
**Realistic Expectations:**
- Volume profile analysis provides structural context, not trading signals
- Delta calculations are estimations based on price action, not actual order flow
- Past volume distribution does not guarantee future price behavior
- Combine with other analysis methods for comprehensive market view
**Best Practices:**
- Use appropriate profile types for your trading style:
- Day Trading: Session or Days Back (1-5 days)
- Swing Trading: Days Back (10-30 days) or N Bars Back
- Position Trading: Days Back (60-180 days)
- Consider market context (trending vs ranging conditions)
- Verify key levels with additional technical analysis
- Monitor profile development for changing market structure
**Performance Considerations:**
- Higher row counts increase calculation complexity
- Large lookback periods may affect chart performance
- Auto-adjust feature optimizes for most use cases
- Consider using session profiles for intraday efficiency
**Limitations:**
- Delta calculations are estimations, not actual transaction data
- Profile accuracy depends on available price/volume history
- Effectiveness varies across different instruments and market conditions
- Requires understanding of volume profile concepts for optimal use
**Data Requirements:**
- Requires volume data for accurate calculations
- Works best on liquid instruments with consistent volume
- May be less effective on very low volume or exotic instruments
This script serves as a comprehensive volume analysis tool for traders who need detailed market structure information with integrated directional bias analysis and real-time POC development tracking for informed trading decisions.
Candle AnalyzerThis tool classifies candles based on their body size and wick proportions, helping you quickly identify:
"Strong" Candles: When the body dominates, showing clear bullish or bearish momentum.
"Rejection" Candles: Long wicks indicate price was pushed back, suggesting potential reversals.
"Indecisive" Candles: When neither buyers nor sellers are clearly in control, or if wicks are balanced.
"Doji/Indecision": Very small or non-existent bodies, highlighting significant uncertainty.
Features
Manual Entry Time (Defaults to NY Open): The indicator analyzes the candle at this specific time.
Current Bar Analysis: This feature classifies the current, developing candle in real-time.
Analysis Table: A table displays details for the last four completed bars, including body size and wick percentages.
Customizable Thresholds: Adjust the "Min Body vs Wick %" and "Dominant Wick vs Body Ratio" to fine-tune how "strong" or "rejection" candles are identified.
