Z-Score Forecaster[SS]Hello everyone,
I just released a neat library for Forecasting stock and equities. In it, it has a couple of novel approaches to forecasting (namely, a Moving Average forecaster and a Z-Score Forecaster). These were accomplished applying basic theories on Autoregression, ARIMA modelling and Z-Score to make new approaches to forecasting.
This is one of the novel approaches, the Z-Score forecaster.
How this function works is it identifies the current trend over the duration of the Z-Score assessment period. So, if the Z-Score is being assessed over the previous 75 candles, it will identify the trend over the previous 75 candles. It will then plot out the forecasted levels according to the trend, up to a maximum of the max Z-Score the ticker has reached within its period. At that point, it will show a likely trend reversal.
Here is an example:
This shows that SPY may go to 475.42 before reversing, as 475.42 is the highest z-score that has been achieved in the current trend.
When it is in an uptrend, the forecast line will be green, when in a downtrend, it will be red.
The forecasting line is accomplished through pinescript's new polyline feature.
In addition to the line, you can also have the indicator plot out a forecast table. The Z-Score Forecast table was formatted in a similar way to ARIMA, where it makes no bias about trend, it simply plots out both ends of the spectrum. So, if an uptrend were to continue, it will list the various uptrend targets along the way, vice versa for downtrends.
It will also display what Z-Score these targets would amount to. Here is an example:
Looking at SPY on the daily, we can see that a likely upside target would be around 484 at just over 2 Standard Deviations (Z-Score).
Its not liklely to go higher than that because then we are getting into 3 and 4 standard deviations.
Remember, everything generally should be within 1 and -1 standard deviations of the mean. So if we look at the table, we can see that would be between 466 and 430.
Customization
You can customize the Z-Score length and source. You can also toggle off and on alerts. The alerts will pop up when a ticker is trading at a previous maximum or previous minimum.
I have also added a manual feature to plot the Z-Score SMA, which is simply the SMA over the desired Z-Score lookback time.
And that's the indicator!
If you are interested in the library, you can access it here .
Thanks for checking this out and leave your questions below!
חפש סקריפטים עבור "Table"
KNN ATR Dual Range Predictions [SS]Excited to release this indicator!
I wanted to do a machine learning, ATR based indicator for a while, but I first had to learn about machine learning algos haha.
Now that I have created a KNN based regression methodology (shared in a previous indicator), I can finally do it!
So this is a Nearest Known Neighbor or KNN regression based indicator that uses ATR (average ranges) to predict future ranges.
It operates by calculating the move from High to Open and Open to Low and performing KNN regression to look for other, similar instances of similar movements and what followed those movements.
It provides for 2 methods of KNN regression, the traditional Cluster method (where it identifies a number of clusters within a tolerance range and averages them out), or the method of last instance (where it finds the most recent identical instance and plots the result from that).
You can toggle the parameters as you wish, including the:
a) Type of Regression
b) Number of Clusters
c) Tolerance for Clusters
Others functions:
The indicator provides for the ability to view 2 different timeframe targets. The default calculation is the current timeframe you are on. So if you are on the 1 minute, 5 minute or 1 hour, it will automatically default the primary range to this timeframe. This cannot be changed.
But it permits for a second prediction to be calculated for a timeframe you can specify. The example in the chart above is the 1 hour overlaid on the 5 minute chart.
You can see how the model is performing in the statistics table. The statistics table can be removed as well if you don't want it overlaid on your chart.
You can also toggle off and on the various ranges. IF you only want to visualize 1 hour levels on a 5 minute chart, you can toggle off the bands and just view the higher tf data. Inversely, if you only want the current timeframe data and not the higher tf data, you can toggle the higher tf data off as well.
General Use Tips:
Some general use tips include:
🎯The default settings are appropriate for most common tickers. Because this is performing an autoregression on itself, the parameters tend to be more tight vs. performing dual correlation between two separate tickers which are sizably different in scale (which would require a higher tolerance).
Here is an example of YM1!, which is a sizably larger ticker, however it is performing well with the current settings.
🎯 If you get not great results from your ranges or an error in the correlation table, something like this:
It means the parameters are too tight for what you want to do and it is having trouble identifying other, similar cases (in this case, the lookback length was significantly shortened). The first step is to:
a) Expand your lookback range (up to 500 is usually sufficient). This should resolve most issues in most cases. If not:
b) If you are using the Cluster method, try broadening your cluster tolerance by 0.5 increments.
Between those two implementations, you should get a functional model. And it actually honestly hasn't happened to me in general use, I had to force that example by significantly shortening the lookback period.
Concluding Remarks
And that's pretty much the indicator.
I hope you enjoy it! I was really excited to be finally able to do it, like I said I attempted to do this for a while but needed to research the whole KNN process and how its performed.
Enjoy and leave your comments and questions below!
Harmonic PatternsHarmonic Patterns
Harmonic Pattern utilizes the recognition of specific structures that possess distinct and consecutive Fibonacci ratio alignments that quantify and validate harmonic patterns. These patterns calculate the Fibonacci aspects of these price structures to identify highly probable reversal points in the financial markets. This methodology assumes that harmonic patterns, like many patterns and cycles in life, continually repeat.
Input Parameters:
Zigzag Setup:
These group of parameters are used to identify the swing points. The script also draws the Zigzag line and swing labels based on these parameters.
Harmonic Pattern Setup:
Ignore XD leg calculations – Optionally one can choose to ignore the XD leg calculation.
Fixed value leg offset % - Fixed value leg parameters are such parameters where single value Fibonacci value is used. This makes pattern identification very rare. To overcome this one can input % value which would be used to derive the range of Fibonacci numbers for pattern identification. E.g. XD leg in Bat pattern has fixed leg of 88.6%, If we input 5% as fixed value leg offset % then instead of fixed value of 88.6%, script calculates range as 88.6% + 5% (Value 1) and 88.6% - 5% (Value 2) and uses the same for pattern identification.
The script plots a diamond shape label on the last candle of the chart. The label has been enabled with a tooltip which shows number of patterns of each type along with the time where latest pattern is located.
This script covers harmonic patterns listed in the table below. Each harmonic pattern has bullish and bearish variants. All these patterns have 4 legs known as XABCD.
The Patterns have been configured as specified in the table below. Refer to Figure 1 and Figure 2 to understand how to read and interpret the table.
Figure 1
Figure 2
5EMA BollingerBand Nifty Stock Scanner
What ?
We all heard about (well: over-heard) 5-EMA strategy. Which falls into the broader category of mean reversal type of trading setup.
What is mean reversal?
Price (or any time series, in fact) tries to follow a mean . Whenever price diverges from the mean it tries to meet it back.
It is empirically observed by some traders (I honestly don't know who first time observed it) that in Indian context specially, 5 Exponential Moving Average (5-EMA) works pretty good as that mean.
So whenever price moves away from that 5-EMA, it ultimately comes back and attain total nirvana :) Means: if price moved way higher than the 5EMA without touching it, then price will correct to meet it's 5-EMA and if price moved way lower, it will be uplifted to meet it's 5-EMA. Funny - but it works !
Now there are already enough social media coverage on this 5-EMA strategy/setup. Even TradingView has some excellent work done on these setups. Kudos to all those great souls.
So when we came to know about this, we were thinking what we should do for the community. Because it is well cover topic (specially in Indian context). Also, there are public indicators.
Then we thought why not come up with a scanner which will scan all the Nifty-50 constituent stocks and find out on the fly, real-time which all stocks are matching this 5-EMA setup and causing a Buy/Sell trade recommendation.
Hence here we are with the first version of our first scanner on the 5EMA setup (well it has some more masala than merely a 5-EMA setup).
Why?
Parts of why is already covered up.
Now instead of blindly following 5-EMA setup, we added the Bollinger band as well. Again: it's also not new. There are enough coverage in social media about the 5-EMA+BB strategy/setup. We mercilessly borrowed from all of these.
Suppose you have an indicator.
Now you apply the indicator in your chart. And then you need to (rock) and roll through your watchlist of Nifty-50 stocks (note: TradingView has no default watchlist of Nifty-50 stock by default - you have to create one custom watchlist to list all manually) to find out which all are matching the setup, need to take a note about the trade recomendations (entry, SL, target) and other stuffs like VWAP, Volume, volatility (Bollinger Band Width).
Not any more.
This scanner will track all the Nifty-50 stocks (technically: 40 stocks other than Banking stocks) and provide which one to Buy or Sell (if any), what's the entry, SL, target, where is the VWAP of the day, what's the picture in volume (high, low, rising, falling) and the implied volatility (using Bolling band width). Also it has a naive alerting mechanism as well.
In fact the code is there to monitor the (Future) OI also and all the OI drama (OI vs price and all the 4 stuffs like long build up, long unwinding, short covering, short buildup). But unfortunately, due to some limitations of the TradingView (that one can not monitor more than 40 `ta.security` call) we have to comment out the code. If you wish you can monitor only 20 stocks and enable the OI monitoring also (20 for stocks + 20 for their OI monitoring .. total 40 `ta.security` call).
How?
To know the divergence from 5-EMA we just check if the high of the candle (on closing) is below the 5-EMA. Then we check if the closing is inside the Bollinger Band (BB). That's a Buy signal. SL: low of the candle, T: middle and higher BB.
Just opposite for selling. 5-EMA low should be above 5-EMA and closing should be inside BB (lesser than BB higher level). That's a Sell signal. SL: high of the candle, T: middle and lower BB.
Along with we compare the current bar's volume with the last-20 bar VWMA (volume weighted moving average) to determine if the volume is high or low.
Present bar's volume is compared with the previous bar's volume to know if it's rising or falling.
VWAP is also determined using `ta.vwap` built-in support of TradingView.
The Bolling Band width is also notified, along with whether it is rising or falling (comparing with previous candle).
Simple, but effective.
Customization
As usual the EMA setup (5 default), the BB setup (20 SMA with 1.5 standard deviation), we provided option wherther to include or exclude BB role in the 5-EMA setup (as we found out there are two schools of thought .. some people use BB some don't. Lets make all happy :))
We also provide options to choose other symbols using Settings if they wish so. We have the default 40 non banking Nifty stocks (why non-banking? - Bank Nifty is in ATH :) .. enough :)). But if user wishes can monitor others too (provided the symbol is there in TradingView).
Although we strongly recommend the timeframe as 30 minutes , you can choose what's fit you most.
The output of the scanner is a table. By default the table is placed in the right-bottom (as we are most comfortable with that). However you can change per your wish. We have the option to choose that.
What is unique in it ?
This is more of an indicator. This is a scanner (of Nifty-50 stocks). So you can apply (our recommendation is in 30m timeframe) it to any chart (does not matter which chart it is) and it will show every 30 mins (which is also configurable) which all stocks (along with trade levels) to Buy and Sell according to the setup.
It will ease your trading activity.
You can concentrate only on the execution, the filtering you can leave it to this one.
Limitations
There is a build in limitation of the TradingView platform is that one can call only upto 40 securities API. Not beyond that. So naturally we are constraint by that. Otherwise we could monitor 190 Nifty F&O stocks itself.
30m is the recommended timeframe. In very lower (say 5m) this script tends to go out of heap (out of memory). Please note that also.
How to trade using this?
Put any chart in 30m (recommended) timeframe.
Apply this screener from Indicators (shortcut to launch indicators is just type / in your keyboard).
This will provide the Buy (shown in green color) or Sell (shown in red color) recommendations in a table, at every 30m candle closing.
Note the volume and BB width as well.
Wait for at least 2 5-minutes candles to close above/below the recommended level .
Take the trade with the SL and target mentioned.
Mentions
@QuantNomad. The whole implementation concept we mercilessly borrowed from him, even some of his code snippet we took it (after asking him through one of his videos comment section and seeking explicit permission which he readily granted within an hour). Thank You sir @QuantNomad. Indebted to you.
Monika (Rawat) ji: for reviewing, correcting, providing real time examples during live market hours, often compromising her own trading activities, about the effectiveness and usefulness of this setup. Thank You madam ji. Indebted to you.
There are innumerable contents in social media about this. Don't even know whom all we checked. Thanks to all of them.
Happy Trading (in stocks - isn't enough of Indices already?)
Disclaimer
This piece of software does not come up with any warrantee or any rights of not changing it over the future course of time.
We are not responsible for any trading/investment decision you are taking out of the outcome of this indicator.
Display Trade Volume with MA Angle and Price VelocityThis Pine Script indicator is designed to provide traders with a visual representation of trade volume, moving average (MA) angle, and price velocity on a chart. The primary components of this indicator are:
Trade Volume: The indicator compares the current bar's trade volume with the average volume over a user-defined lookback period. The volume is displayed as either "Low" or "Trade" in a table, with red or green background color, respectively, to indicate whether it's below or above the average volume.
MA Angle: The indicator calculates the angle of the moving average (either Simple, Exponential, or Hull) over a user-defined length. A positive angle is shown in green, while a negative angle is shown in red. The angle is displayed in degrees in the table.
Price Velocity: This component calculates the velocity of price movement by comparing the difference between high and low prices over a user-defined lookback period. It then displays the velocity as either "Slow" or "Fast" in the table, with red or green background color, respectively, depending on whether it's below or above the average difference.
The indicator also includes alert conditions for high and low volume situations, notifying the trader when the current bar's volume is significantly higher or lower than the average volume.
Wavemeter [theEccentricTrader]█ OVERVIEW
This indicator is a representation of my take on price action based wave cycle theory. The indicator counts the number of confirmed wave cycles, keeps a rolling tally of the average wave length, wave height and frequency, and displays the statistics in a table. The indicator also displays the current wave measurements as an optional feature.
█ 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.
Peak and Trough Prices (Basic)
• The peak price of a complete swing high is the high price of either the red candle that completes the swing high or the high price of the preceding green candle, depending on which is higher.
• The trough price of a complete swing low is the low price of either the green candle that completes the swing low or the low price of the preceding red candle, depending on which is lower.
Historic Peaks and Troughs
The current, or most recent, peak and trough occurrences are referred to as occurrence zero. Previous peak and trough occurrences are referred to as historic and ordered numerically from right to left, with the most recent historic peak and trough occurrences being occurrence one.
Wave Cycles
A wave cycle is here defined as a complete two-part move between a swing high and a swing low, or a swing low and a swing high. As can be seen in the example above, the first swing high or swing low will set the course for the sequence of wave cycles that follow; a chart that begins with a swing low will form its first complete wave cycle upon the formation of the first complete swing high and vice versa.
Wave Length
Wave length is here measured in terms of bar distance between the start and end of a wave cycle. For example, if the current wave cycle ends on a swing low the wave length will be the difference in bars between the current swing low and current swing high. In such a case, if the current swing low completes on candle 100 and the current swing high completed on candle 95, we would simply subtract 95 from 100 to give us a wave length of 5 bars.
Average wave length is here measured in terms of total bars as a proportion as total waves. The average wavelength is calculated by dividing the total candles by the total wave cycles.
Wave Height
Wave height is here measured in terms of current range. For example, if the current peak price is 100 and the current trough price is 80, the wave height will be 20.
Amplitude
Amplitude is here measured in terms of current range divided by two. For example if the current peak price is 100 and the current trough price is 80, the amplitude would be calculated by subtracting 80 from 100 and dividing the answer by 2 to give us an amplitude of 10.
Frequency
Frequency is here measured in terms of wave cycles per second (Hertz). For example, if the total wave cycle count is 10 and the amount of time it has taken to complete these 10 cycles is 1-year (31,536,000 seconds), the frequency would be calculated by dividing 10 by 31,536,000 to give us a frequency of 0.00000032 Hz.
Range
The range is simply the difference between the current peak and current trough prices, generally expressed in terms of points or pips.
█ FEATURES
Inputs
Show Sample Period
Start Date
End Date
Position
Text Size
Show Current
Show Lines
Table
The table is colour coded, consists of two columns and, as many as, nine rows. Blue cells display the total wave cycle count and average wave measurements. Green cells display the current wave measurements. And the final row in column one, coloured black, displays the sample period. Both current wave measurements and sample period cells can be hidden at the user’s discretion.
Lines
For a visual aid to the wave cycles, I have added a blue line that traces out the waves on the chart. These lines can be hidden at the user’s discretion.
█ HOW TO USE
The 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.
For example, the indicator can be used to compare the current range and frequency with the average range and frequency, which can be useful for gauging current market conditions versus historic and getting a feel for how different markets and timeframes behave.
█ 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.
Multi-Timeframe Trend IndicatorThe Multi-Timeframe Trend Indicator (MTFTI) is a trend analysis tool designed to help traders quickly and easily assess the market direction across multiple timeframes. With the help of a table to visualize the trends on different timeframes.
Key features:
Multi-timeframe trend indicator for the following timeframes: 5 minutes, 15 minutes, 30 minutes, 1 hour, 2 hours, 4 hours, 6 hours, 12 hours, 1 day, and 1 week and average.
Displays trends for selected timeframes in a table.
Considers short and long-term exponential moving averages (EMAs) to determine trends.
Calculation of the average trend for all timeframes.
Display of trends with appropriate coloring for better readability (green for "Up", red for "Down", and intermediate shades for neutral or strong trends).
List of Parameters
Customization of the table's position on the screen (top-left, top-right, middle-left, middle-right, bottom-left, bottom-right).
Setting the lengths of the short and long-term exponential moving averages.
Option to activate or deactivate the display of EMAs for better customization (true by default).
Please note that the MTFTI 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.
Relative Performance Dashboard v. 2This is a smaller and cleaner version of my previous Relative Performance table. It looks at the rate of change over 1M, 3M, 6M, 1YR & YTD and displays those for the current chart's ticker vs. an index/ticker of your choosing (SPX is default). I also have some fields for the ADR of the displayed chart, how far away the displayed chart is from 52-week highs, and a single number that compares the average relative strength of the displayed chart vs. the index. The way this average calculates is customizable by the user.
I like using this table next to an Earnings/Sales/Volume table that already exists by another user in the same pane and I designed this one so it can look just like that one to give a great view of the both fundamental and technical strength of your ticker in the same pane.
Keeping fundamental data independent from performance data allows you to still be able to see performance on things without fundamental data (i.e. ETFs, Indices, Crypto, etc.) as any script that uses fundamental data will not display when a chart that does not have fundamental data is displayed.
ILM COT Financials PlotUse this indicator on Daily Timeframe
Please refer to the below link for CFTC Financials
www.cftc.gov
This script is very similar to COT Financial Table indicator except that it plots the data (Longs - Shorts) instead of showing in a table.
LazyScalp BoardThis indicator allows you to quickly view all important parameters in the table.
The table consists of a daily volume indicator, an average volume for a certain period, a volatility indicator (normalized ATR) and a correlation coefficient.
All parameters can be flexibly customized. You can also customize the table display, styles, and more.
This indicator is primarily useful for intraday traders and scalpers to quickly select an instrument to trade.
Position Size Calc. (Minimalist)This is a simplified position size calculator in the form of a table.
The reason I published this script is because all other position size calculator scripts try to provide way too much when it should be much simpler, position in strange areas of the chart and leave unwanted chart pollution.
This is a bare-bones functional table that takes your risk level, entry, stop and take profit as inputs, and calculates your loss, profit and required position size for your chosen risk level as a result.
Inspired by a table type position size calculator made by DojiEmoji design/color-wise. Functionally different however.
I hope you find this script useful and include it on your trading journey.
Everything Bitcoin [Kioseff Trading]Hello!
This script retrieves most of the available Bitcoin data published by Quandl; the script utilizes the new request.security_lower_tf() function.
Included statistics,
True price
Volume
Difficulty
My Wallet # Of Users
Average Block Size
api.blockchain size
Median Transaction Confirmation Time
Miners' Revenue
Hash Rate
Cost Per Transaction
Cost % of Transaction Volume
Estimated Transaction Volume USD
Total Output Volume
Number Of Transactions Per Block
# of Unique BTC Addresses
# of BTC Transactions Excluding Popular Addresses
Total Number of Transactions
Daily # of Transactions
Total Transaction Fees USD
Market Cap
Total BTC
Retrieved data can be plotted as line graphs; however, the data is initially split between two tables.
The image above shows how the requested Bitcoin data is displayed.
However, in the user inputs tab, you can modify how the data is displayed.
For instance, you can append the data displayed in the floating statistics box to the stagnant statistics box.
The image above exemplifies the instance.
You can hide any and all data via the user inputs tab.
In addition to data publishing, the script retrieves lower timeframe price/volume/indicator data, to which the values of the requested data are appended to center-right table.
The image above shows the script retrieving one-minute bar data.
Up arrows reflect an increase in the more recent value, relative to the immediately preceding value.
Down arrows reflect a decrease in the more recent value relative to the immediately preceding value.
The ascending minute column reflects the number of minutes/hours (ago) the displayed value occurred.
For instance, 15 minutes means the displayed value occurred 15 minutes prior to the current time (value).
Volume, price, and indicator data can be retrieved on lower timeframe charts ranging from 1 minute to 1440 minutes.
The image above shows retrieved 5-minute volume data.
Several built-in indicators are included, to which lower timeframe values can be retrieved.
The image above shows LTF VWAP data. Also distinguished are increases/decreases for sequential values.
The image above shows a dynamic regression channel. The channel terminates and resets each fiscal quarter. Previous channels remain on the chart.
Lastly, you can plot any of the requested data.
The new request.security_lower_tf() function is immensely advantageous - be sure to try it in your scripts!
Volatility Percentile🎲 Volatility is an important measure to be included in trading plan and strategy. Strategies have varied outcome based on volatility of the instruments in hand.
For example,
🚩 Trend following strategies work better on low volatility instruments and reversal patterns work better in high volatility instruments. It is also important for us to understand the median volatility of an instrument before applying particular strategy strategy on them.
🚩 Different instrument will have different volatility range. For instance crypto currencies have higher volatility whereas major currency pairs have lower volatility with respect to their price. It is also important for us to understand if the current volatility of the instrument is relatively higher or lower based on the historical values.
This indicator is created to study and understand more about volatility of the instruments.
⬜ Process
▶ Volatility metric used here is ATR as percentage of price. Other things such as bollinger bandwidth etc can also be used with few changes.
▶ We use array based counters to count ATR values in different range. For example, if we are measuring ATR range based on precision 2, we will use array containing 10000 values all initially set to 0 which act as 10000 buckets to hold counters of different range. But, based on the ATR percentage range, they will be incremented. Let's say, if atr percent is 2, then 200th element of the array is increased by 1.
▶ When we do this for every bar, we have array of counters which has the division on how many bars had what range of atr percent.
▶ Using this array, we can calculate how many bars had atr percent more than current value, how many had less than current value, and how many bars in history has same atr percent as current value.
▶ With these information, we can calculate the percentile of atr percentage value. We can also plot a detailed table mentioning what percentile each range map to.
⬜ Settings
▶ ATR Parameters - this include Moving average type and Length for atr calculation.
▶ Rounding type refers to rounding ATR percentage value before we put into certain bucket. For example, if ATR percentage 2.7, round or ceil will make it 3, whereas floor will make it 2 which may fall into different buckets based on the precision selected.
▶ Precision refers to how much detailed the range should be. If precision set to 0, then we get array of 100 to collect the range where each value will represent a range of 1%. Similarly precision of 1 will lead to array of 1000 with each item representing range of 0.1. Default value used is 2 which is also the max precision possible in this script. This means, we use array of 10000 to track the range and percentile of the ATR.
▶ Display Settings - Inverse when applied track percentile with respect to lowest value of ATR instead of high. By default this is set to false. Other two options allow users to enable stats table. When detailed stats are enabled, ATR Percentile as plot is hidden.
▶ Table Settings - Allows users to select set size and coloring options.
▶ Indicator Time Window - Allow users to select particular timeframe instead of all available bars to run the study. By default windows are disabled. Users can chose start and end time individually.
Indicator display components can be described as below:
Zigzag Trend/Divergence DetectorPullbacks are always hardest part of the trade and when it happen, we struggle to make decision on whether to continue the trade and wait for recovery or cut losses. Similarly, when an instrument is trending well, it is often difficult decision to make if we want to take some profit off the table. This indicator is aimed to make these decisions easier by providing a combined opinion of sentiment based on trend and possible divergence.
⬜ Process
▶ Use any indicator to find trend bias. Here we are using simple supertrend
▶ Use any oscillator. I have added few inbuilt oscillators as option. Default used is RSI.
▶ Find divergence by using zigzag to detect pivot high/low of price and observing indicator movement difference between subsequent pivots in the same direction.
▶ Combine divregence type, divergence bias and trend bias to derive overall sentiment.
Complete details of all the possible combinations are present here along with table legend
⬜Chart Legend
C - Continuation
D - Divergence
H - Hidden Divergence
I - Indeterminate
⬜ Settings
▶ Zigzag parameters : These let you chose zigzag properties. If you check "Use confirmed pivots", then unconfirmed pivot will be ignored in the table and in the chart
▶ Oscillator parameters : Lets you select different oscillators and settings. Available oscillators involve
CCI - Commodity Channel Index
CMO - Chande Momentum Oscillator
COG - Center Of Gravity
DMI - Directional Movement Index (Only ADX is used here)
MACD - Moving average convergence divergence (Can chose either histogram or MACD line)
MFI - Money Flow Index
MOM - Momentum oscillator
ROC - Rate Of Change
RSI - Relative Strength Index
TSI - Total Strength Index
WPR - William Percent R
BB - Bollinger Percent B
KC - Keltner Channel Percent K
DC - Donchian Channel Percent D
ADC - Adoptive Donchian Channel Percent D ( Adoptive-Donchian-Channel )
▶ Trend bias : Supertrend is used for trend bias. Coloring option color candles in the direction of supertrend. More option for trend bias can be added in future.
▶ Stats : Enables you to display history in tabular format.
Overview of settings present here:
⬜ Notes
Trend detection is done only with respect to previous pivot in the same direction. Hence, if chart has too many zigzags in short period, try increasing the zigzag length or chart timeframe. Similarly, if there is a steep trend, use lower timeframe charts to dig further.
Oscillators does not always make pivots at same bar as price. Due to this some the divergence calculation may not be correct. Hence visual inspection is always recommended.
⬜ Possible future enhancements
More options for trend bias
Enhance divergence calculation. Possible options include using oscillator based zigzag as primary or using close prices based zigzag instead of high/low.
Multi level zigzag option - Can be messy to include more than one zigzag. Option can be added to chose either Level1 or Level2 zigzags.
Alerts - Alerts can only be added for confirmed pivots - otherwise it will generate too many unwanted alerts. Will think about it :)
If I get time, I will try to make a video.
Obsidian Flux Matrix# Obsidian Flux Matrix | JackOfAllTrades
Made with my Senior Level AI Pine Script v6 coding bot for the community!
Narrative Overview
Obsidian Flux Matrix (OFM) is an open-source Pine Script v6 study that fuses social sentiment, higher timeframe trend bias, fair-value-gap detection, liquidity raids, VWAP gravitation, session profiling, and a diagnostic HUD. The layout keeps the obsidian palette so critical overlays stay readable without overwhelming a price chart.
Purpose & Scope
OFM focuses on actionable structure rather than marketing claims. It documents every driver that powers its confluence engine so reviewers understand what triggers each visual.
Core Analytical Pillars
1. Social Pulse Engine
Sentiment Webhook Feed: Accepts normalized scores (-1 to +1). Signals only arm when the EMA-smoothed value exceeds the `sentimentMin` input (0.35 by default).
Volume Confirmation: Requires local volume > 30-bar average × `volSpikeMult` (default 2.0) before sentiment flags.
EMA Cross Validation: Fast EMA 8 crossing above/below slow EMA 21 keeps momentum aligned with flow.
Momentum Alignment: Multi-timeframe momentum composite must agree (positive for longs, negative for shorts).
2. Peer Momentum Heatmap
Multi-Timeframe Blend: RSI + Stoch RSI fetched via request.security() on 1H/4H/1D by default.
Composite Scoring: Each timeframe votes +1/-1/0; totals are clamped between -3 and +3.
Intraday Readability: Configurable band thickness (1-5) so scalpers see context without losing space.
Dynamic Opacity: Stronger agreement boosts column opacity for quick bias checks.
3. Trend & Displacement Framework
Dual EMA Ribbon: Cyan/magenta ribbon highlights immediate posture.
HTF Bias: A higher-timeframe EMA (default 55 on 4H) sets macro direction.
Displacement Score: Body-to-ATR ratio (>1.4 default) detects impulses that seed FVGs or VWAP raids.
ATR Normalization: All thresholds float with volatility so the study adapts to assets and regimes.
4. Intelligent Fair Value Gap (FVG) System
Gap Detection: Three-candle logic (bullish: low > high ; bearish: high < low ) with ATR-sized minimums (0.15 × ATR default).
Overlap Prevention: Price-range checks stop redundant boxes.
Spacing Control: `fvgMinSpacing` (default 5) avoids stacking from the same impulse.
Storage Caps: Max three FVGs per side unless the user widens the limit.
Session Awareness: Kill zone filters keep taps focused on London/NY if desired.
Auto Cleanup: Boxes delete when price closes beyond their invalidation level.
5. VWAP Magnet + Liquidity Raid Engine
Session or Rolling VWAP: Toggle resets to match intraday or rolling preferences.
Equal High/Low Scanner: Looks back 20 bars by default for liquidity pools.
Displacement Filter: ATR multiplier ensures raids represent genuine liquidity sweeps.
Mean Reversion Focus: Signals fire when price displaces back toward VWAP following a raid.
6. Session Range Breakout System
Initial Balance Tracking: First N bars (15 default) define the session box.
Breakout Logic: Requires simultaneous liquidity spikes, nearby FVG activity, and supportive momentum.
Z-Score Volume Filter: >1.5σ by default to filter noisy moves.
7. Lifestyle Liquidity Scanner
Volume Z-Scores: 50-bar baseline highlights statistically significant spikes.
Smart Money Footprints: Bottom-of-chart squares color-code buy vs sell participation.
Panel Memory: HUD logs the last five raid timestamps, direction, and normalized size.
8. Risk Matrix & Diagnostic HUD
HUD Structure: Table in the top-right summarizes HTF bias, sentiment, momentum, range state, liquidity memory, and current risk references.
Signal Tags: Aggregates SPS, FVG, VWAP, Range, and Liquidity states into a compact string.
Risk Metrics: Swing-based stops (5-bar lookback) + ATR targets (1.5× default) keep risk transparent.
Signal Families & Alerts
Social Pulse (SPS): Volume-confirmed sentiment alignment; triangle markers with “SPS”.
Kill-Zone FVG: Session + HTF alignment + FVG tap; arrow markers plus SL/TP labels.
Local FVG: Captures local reversals when HTF bias has not flipped yet.
VWAP Raid: Equal-high/low raids that snap toward VWAP; “VWAP” label markers.
Range Breakout: Initial balance violations with liquidity and imbalance confirmation; circle markers.
Liquidity Spike: Z-score spikes ≥ threshold; square markers along the baseline.
Visual Design & Customization
Theme Palette: Primary background RGB (12,6,24). Accent shading RGB (26,10,48). Long accents RGB (88,174,255). Short accents RGB (219,109,255).
Stylized Candles: Optional overlay using theme colors.
Signal Toggles: Independently enable markers, heatmap, and diagnostics.
Label Spacing: Auto-spacing enforces ≥4-bar gaps to prevent text overlap.
Customization & Workflow Notes
Adjust ATR/FVG thresholds when volatility shifts.
Re-anchor sentiment to your webhook cadence; EMA smoothing (default 5) dampens noise.
Reposition the HUD by editing the `table.new` coordinates.
Use multiples of the chart timeframe for HTF requests to minimize load.
Session inputs accept exchange-local time; align them to your market.
Performance & Compliance
Pure Pine v6: Single-line statements, no `lookahead_on`.
Resource Safe: Arrays trimmed, boxes limited, `request.security` cached.
Repaint Awareness: Signals confirm on close; alerts mirror on-chart logic.
Runtime Safety: Arrays/loops guard against `na`.
Use Cases
Measure when social sentiment aligns with structure.
Plan ICT-style intraday rebalances around session-specific FVG taps.
Fade VWAP raids when displacement shows exhaustion.
Watch initial balance breaks backed by statistical volume.
Keep risk/target references anchored in ATR logic.
Signal Logic Snapshot
Social Pulse Long/Short: `sentimentEMA` gated by `sentimentMin`, `volSpike`, EMA 8/21 cross, and `momoComposite` sign agreement. Keeps hype tied to structural follow-through.
Kill-Zone FVG Long/Short: Requires session filter, HTF EMA bias alignment, and an active FVG tap (`bullFvgTap` / `bearFvgTap`). Labels include swing stops + ATR targets pulled from `swingLookback` and `liqTargetMultiple`.
Local FVG Long/Short: Uses `localBullish` / `localBearish` heuristics (EMA slope, displacement, sequential closes) to surface intraday reversals even when HTF bias has not flipped.
VWAP Raids: Detect equal-high/equal-low sweeps (`raidHigh`, `raidLow`) that revert toward `sessionVwap` or rolling VWAP when displacement exceeds `vwapAlertDisplace`.
Range Breakouts: Combine `rangeComplete`, breakout confirmation, liquidity spikes, and nearby FVG activity for statistically backed initial balance breaks.
Liquidity Spikes: Volume Z-score > `zScoreThreshold` logs direction, size, and timestamp for the HUD and optional review workflows.
Session Logic & VWAP Handling
Kill zone + NY session inputs use TradingView’s session strings; `f_inSession()` drives both visual shading and whether FVG taps are tradeable when `killZoneOnly` is true.
Session VWAP resets using cumulative price × volume sums that restart when the daily timestamp changes; rolling VWAP falls back to `ta.vwap(hlc3)` for instruments where daily resets are less relevant.
Initial balance box (`rangeBars` input) locks once complete, extends forward, and stays on chart to contextualize later liquidity raids or breakouts.
Parameter Reference
Trend: `emaFastLen`, `emaSlowLen`, `htfResolution`, `htfEmaLen`, `showEmaRibbon`, `showHtfBiasLine`.
Momentum: `tf1`, `tf2`, `tf3`, `rsiLen`, `stochLen`, `stochSmooth`, `heatmapHeight`.
Volume/Liquidity: `volLookback`, `volSpikeMult`, `zScoreLen`, `zScoreThreshold`, `equalLookback`.
VWAP & Sessions: `vwapMode`, `showVwapLine`, `vwapAlertDisplace`, `killSession`, `nySession`, `showSessionShade`, `rangeBars`.
FVG/Risk: `fvgMinTicks`, `fvgLookback`, `fvgMinSpacing`, `killZoneOnly`, `liqTargetMultiple`, `swingLookback`.
Visualization Toggles: `showSignalMarkers`, `showHeatmapBand`, `showInfoPanel`, `showStylizedCandles`.
Workflow Recipes
Kill-Zone Continuation: During the defined kill session, look for `killFvgLong` or `killFvgShort` arrows that line up with `sentimentValid` and positive `momoComposite`. Use the HUD’s risk readout to confirm SL/TP distances before entering.
VWAP Raid Fade: Outside kill zone, track `raidToVwapLong/Short`. Confirm the candle body exceeds the displacement multiplier, and price crosses back toward VWAP before considering reversions.
Range Break Monitor: After the initial balance locks, mark `rangeBreakLong/Short` circles only when the momentum band is >0 or <0 respectively and a fresh FVG box sits near price.
Liquidity Spike Review: When the HUD shows “Liquidity” timestamps, hover the plotted squares at chart bottom to see whether spikes were buy/sell oriented and if local FVGs formed immediately after.
Metadata
Author: officialjackofalltrades
Platform: TradingView (Pine Script v6)
Category: Sentiment + Liquidity Intelligence
Hope you Enjoy!
ST -Dashboard Volume MTF , [Sese04]User Guide: ST - Dashboard Volume MTF
Introduction
This script displays a multi-timeframe (MTF) volume dashboard, tracking buy and sell volumes and the moving averages of volume. It is designed for traders using ICT (Inner Circle Trader) and SMC (Smart Money Concepts) to quickly visualize market dynamics across multiple timeframes.
Settings and Features
📌 User Inputs
Customizable settings allow traders to adjust the dashboard display and volume moving averages.
Volume Display per Timeframe
show_vol_1m: Show volume for 1-minute chart.
show_vol_5m: Show volume for 5-minute chart.
show_vol_15m: Show volume for 15-minute chart.
show_vol_1h: Show volume for 1-hour chart.
show_vol_4h: Show volume for 4-hour chart.
show_vol_1d: Show volume for 1-day chart.
Volume Moving Average Settings
ma_length_short: Length of the short-term moving average (default 5 periods).
ma_length_long: Length of the long-term moving average (default 14 periods).
Dashboard Customization
dashboard_position: Dashboard position (Bottom Right, Bottom Left, Top Right, Top Left).
text_color: Text color for the dashboard.
text_size: Text size (small, normal, large).
How the Script Works
🔹 1. Calculating Buy and Sell Volume
The calculate_buy_sell function separates buy and sell volume based on the candle's open and close price:
If the closing price is higher than the opening price → Buy volume 📈.
If the closing price is lower or equal to the opening price → Sell volume 📉.
🔹 2. Retrieving Volume Data Across Multiple Timeframes
The function get_volumes collects buy and sell volume data for different timeframes using request.security().
The available timeframes are: 1m, 5m, 15m, 1h, 4h, and 1d.
🔹 3. Calculating Volume Moving Averages
The script uses ta.sma() to compute moving averages for volume trends:
ma_vol_short: Short-term moving average (e.g., 5 periods).
ma_vol_long: Long-term moving average (e.g., 14 periods).
🔹 4. Creating and Displaying the Dashboard
A table (table.new()) is generated at the last bar (barstate.islast) to display the volume data:
A title “📊 Volume Dashboard (Buy vs Sell)” in purple.
Column headers:
TIMEFRAME (e.g., 1M, 5M, 15M, 1H, 4H, 1D).
BUY VOLUME (dark blue).
SELL VOLUME (dark red).
Buy and Sell Volume values are displayed in their respective cells for easy reading.
How to Use This Script on TradingView?
Adding the Script
Open TradingView.
Go to Pine Editor and paste the script.
Click "Add to Chart".
Configuring the Settings
Open the indicator settings.
Enable/disable the desired timeframes.
Adjust the moving average lengths if necessary.
Interpreting the Data
Increasing buy volume across timeframes may indicate bullish momentum.
Rising sell volume suggests a bearish reversal.
Crossovers of volume moving averages can help detect market shifts.
Conclusion
This script is a powerful tool for analyzing volume dynamics across multiple timeframes. It provides a quick overview of the balance between buyers and sellers, essential for ICT scalping and liquidity-based trading.
🚀 Pro Tip: Combine this dashboard with other SMC indicators (engulfing candles, pivot points) to refine your trading decisions.
