Adaptive Predictive Stops and Targets The indicator is an experiment to Predict Stops and 1st target for any liquid security and for any timeframe,
Intro
The indicator is made using Predictive Differential Filter of 2nd Degree
and an Adaptive Filter to generate Signals and define Targets and Stops
An adaptive filter is a system with a linear filter that has a transfer function controlled by variable parameters and a means to adjust those parameters according to an optimisation algorithm. Because of the complexity of the optimisation algorithms, almost all adaptive filters are digital filters. Thus Helping us classify our intent either long side or short side
The indicator use Adaptive Least mean square algorithm, for convergence of the filtered signals into a category of intents, (either buy or sell)
The Other Category of Filter used in the indicator is Predictive Differential Filter, which helps us estimate the acceleration of the prices and levels of significance for targeting and Stops
The Predictive Differential Filters are capable of predicting the next state of the input based on the interaction with a pre-specified number of filters, The prediction helps in minimising the quantisation error and in removing the granular noise which are caused by PCM systems.
How to Use
The logic to use is simple Buy at the High of the Signal Candle and Sell at the Low of the Signal Candle
Book your 50% position on the first target shown (respectively in green and red lines) and Trail the rest of the positions till you reach stop or breakeven!
vice versa for Sell,
Just Sell on the Low of the Signal Candle
What securities and timeframes will it work upon
The system is designed to work over any liquid security over any timeframe,
The Indicator has provisions for Alert
How to request Access
Just Private message me, do not use comment box for requesting access, use it only for constructive comments
Cerca negli script per "algo"
STD-Stepped Fast Cosine Transform Moving Average [Loxx]STD-Stepped Fast Cosine Transform Moving Average is an experimental moving average that uses Fast Cosine Transform to calculate a moving average. This indicator has standard deviation stepping in order to smooth the trend by weeding out low volatility movements.
What is the Discrete Cosine Transform?
A discrete cosine transform (DCT) expresses a finite sequence of data points in terms of a sum of cosine functions oscillating at different frequencies. The DCT, first proposed by Nasir Ahmed in 1972, is a widely used transformation technique in signal processing and data compression. It is used in most digital media, including digital images (such as JPEG and HEIF, where small high-frequency components can be discarded), digital video (such as MPEG and H.26x), digital audio (such as Dolby Digital, MP3 and AAC), digital television (such as SDTV, HDTV and VOD), digital radio (such as AAC+ and DAB+), and speech coding (such as AAC-LD, Siren and Opus). DCTs are also important to numerous other applications in science and engineering, such as digital signal processing, telecommunication devices, reducing network bandwidth usage, and spectral methods for the numerical solution of partial differential equations.
The use of cosine rather than sine functions is critical for compression, since it turns out (as described below) that fewer cosine functions are needed to approximate a typical signal, whereas for differential equations the cosines express a particular choice of boundary conditions. In particular, a DCT is a Fourier-related transform similar to the discrete Fourier transform (DFT), but using only real numbers. The DCTs are generally related to Fourier Series coefficients of a periodically and symmetrically extended sequence whereas DFTs are related to Fourier Series coefficients of only periodically extended sequences. DCTs are equivalent to DFTs of roughly twice the length, operating on real data with even symmetry (since the Fourier transform of a real and even function is real and even), whereas in some variants the input and/or output data are shifted by half a sample. There are eight standard DCT variants, of which four are common.
The most common variant of discrete cosine transform is the type-II DCT, which is often called simply "the DCT". This was the original DCT as first proposed by Ahmed. Its inverse, the type-III DCT, is correspondingly often called simply "the inverse DCT" or "the IDCT". Two related transforms are the discrete sine transform (DST), which is equivalent to a DFT of real and odd functions, and the modified discrete cosine transform (MDCT), which is based on a DCT of overlapping data. Multidimensional DCTs (MD DCTs) are developed to extend the concept of DCT to MD signals. There are several algorithms to compute MD DCT. A variety of fast algorithms have been developed to reduce the computational complexity of implementing DCT. One of these is the integer DCT (IntDCT), an integer approximation of the standard DCT, : ix, xiii, 1, 141–304 used in several ISO/IEC and ITU-T international standards.
Notable settings
windowper = period for calculation, restricted to powers of 2: "16", "32", "64", "128", "256", "512", "1024", "2048", this reason for this is FFT is an algorithm that computes DFT (Discrete Fourier Transform) in a fast way, generally in 𝑂(𝑁⋅log2(𝑁)) instead of 𝑂(𝑁2). To achieve this the input matrix has to be a power of 2 but many FFT algorithm can handle any size of input since the matrix can be zero-padded. For our purposes here, we stick to powers of 2 to keep this fast and neat. read more about this here: Cooley–Tukey FFT algorithm
smthper = smoothing count, this smoothing happens after the first FCT regular pass. this zeros out frequencies from the previously calculated values above SS count. the lower this number, the smoother the output, it works opposite from other smoothing periods
Included
Alerts
Signals
Loxx's Expanded Source Types
Additional reading
A Fast Computational Algorithm for the Discrete Cosine Transform by Chen et al.
Practical Fast 1-D DCT Algorithms With 11 Multiplications by Loeffler et al.
Cooley–Tukey FFT algorithm
Weighted Burg AR Spectral Estimate Extrapolation of Price [Loxx]Weighted Burg AR Spectral Estimate Extrapolation of Price is an indicator that uses an autoregressive spectral estimation called the Weighted Burg Algorithm. This method is commonly used in speech modeling and speech prediction engines. This method also includes Levinson–Durbin algorithm. As was already discussed previously in the following indicator:
Levinson-Durbin Autocorrelation Extrapolation of Price
What is Levinson recursion or Levinson–Durbin recursion?
In many applications, the duration of an uninterrupted measurement of a time series is limited. However, it is often possible to obtain several separate segments of data. The estimation of an autoregressive model from this type of data is discussed. A straightforward approach is to take the average of models estimated from each segment separately. In this way, the variance of the estimated parameters is reduced. However, averaging does not reduce the bias in the estimate. With the Burg algorithm for segments, both the variance and the bias in the estimated parameters are reduced by fitting a single model to all segments simultaneously. As a result, the model estimated with the Burg algorithm for segments is more accurate than models obtained with averaging. The new weighted Burg algorithm for segments allows combining segments of different amplitudes.
The Burg algorithm estimates the AR parameters by determining reflection coefficients that minimize the sum of for-ward and backward residuals. The extension of the algorithm to segments is that the reflection coefficients are estimated by minimizing the sum of forward and backward residuals of all segments taken together. This means a single model is fitted to all segments in one time. This concept is also used for prediction error methods in system identification, where the input to the system is known, like in ARX modeling
Data inputs
Source Settings: -Loxx's Expanded Source Types. You typically use "open" since open has already closed on the current active bar
LastBar - bar where to start the prediction
PastBars - how many bars back to model
LPOrder - order of linear prediction model; 0 to 1
FutBars - how many bars you want to forward predict
BurgWin - weighing function index, rectangular, hamming, or parabolic
Things to know
Normally, a simple moving average is calculated on source data. I've expanded this to 38 different averaging methods using Loxx's Moving Avreages.
This indicator repaints
Included
Bar color muting
Further reading
Performance of the weighted burg methods of ar spectral estimation for pitch-synchronous analysis of voiced speech
The Burg algorithm for segments
Techniques for the Enhancement of Linear Predictive Speech Coding in Adverse Conditions
Related Indicators
Auto Fibonacci Retracement - Real-Time (Expo)█ Fibonacci retracement is a popular technical analysis method to draw support and resistance levels. The Fibonacci levels are calculated between 2 swing points (high/low) and divided by the key Fibonacci coefficients equal to 23.6%, 38.2%, 50%, 61.8%, and 100%. The percentage represents how much of a prior move the price has retraced.
█ Our Auto Fibonacci Retracement indicator analyzes the market in real-time and draws Fibonacci levels automatically for you on the chart. Real-time fib levels use the current swing points, which gives you a huge advantage when using them in your trading. You can always be sure that the levels are calculated from the correct swing high and low, regardless of the current trend. The algorithm has a trend filter and shifts the swing points if there is a trend change.
The user can set the preferred swing move to scalping, trend trading, or swing trading. This way, you can use our automatic fib indicator to do any trading. The auto fib works on any market and timeframe and displays the most important levels in real-time for you.
█ This Auto Fib Retracement indicator for TradingView is powerful since it does the job for you in real-time. Apply it to the chart, set the swing move to fit your trading style, and leave it on the chart. The indicator does the rest for you. The auto Fibonacci indicator calculates and plots the levels for you in any market and timeframe. In addition, it even changes the swing points based on the current trend direction, allowing traders to get the correct Fibonacci levels in every trend.
█ How does the Auto Fib Draw the levels?
The algorithm analyzes the recent price action and examines the current trend; based on the trend direction, two significant swings (high and low) are identified, and Fibonacci levels will then be plotted automatically on the chart. If the algorithm has identified an uptrend, it will calculate the Fibonacci levels from the swing low and up to the swing high. Similarly, if the algorithm has identified a downtrend, it will calculate the Fibonacci levels from the swing high and down to the swing low.
█ HOW TO USE
The levels allow for a quick and easy understanding of the current Fibonacci levels and help traders anticipate and react when the price levels are tested. In addition, the levels are often used for entries to determine stop-loss levels and to set profit targets. It's also common for traders to use Fibonacci levels to identify resistance and support levels.
Traders can set alerts when the levels are tested.
-----------------
Disclaimer
Copyright by Zeiierman.
The information contained in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell any securities of any type. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!
SIVE 2.0 - [Soldi]SIVE 2.0 IS FINALLY HERE, after the long awaited update we are finally able to bring to you SIVE 2.0!
SIVE 1.0 (Systematic Institutional Volatility Expansion) brought a whole new approach to the algorithm and retail trading game on TradingView. Never before have you had access to a quantitative institutional approach like this, after years in development and testing we finally brought SIVE 1.0 to market. With very very high demand, support and so much positive feedback we knew that what we've created really hit the mark for so many traders!
What is SIVE?
SIVE as stated above stands for, Systematic Institutional Volatility Expansion. What this means is we have a highly effective system that reads what institutional algorithms are proven to be looking at. While only providing alerts during periods where Volatility is Expanding
We don't shy away from volatility here, that is where the bread and butter lays. volatility is a double edged sword that not many people know how to effectively use to their advantage. Simply put, because they are told in their retail trading that volatility is risky, and that you should stay away from volatile products. I say embrace it with the right tools.
What Has Changed?
At the core, SIVE 2.0 brings more efficient calculations to the volatility modelling as well as the triggering of trades!
Trend Scalper - This is a sub-set strategy we have included, what it measures is 'Super Trend' with a deviation of 7 and the MTI ribbon crosses. This is to be used as a way to scalp and trade the momentum of the market. I am aware that another brand/community has put this out as a paid feature to their algorithm. Since they didn't want to credit me for my contribution I decided to release it for free and also add it here. This is listed in my scripts as a free to use access.
Volatility Confluence - We have now also added a feature where you can choose how many volatility models you want to be aligned before SIVE calls an alert. There are a total of 9 models we have included, example. You choose 3 'Volatility Confluence', this means that SIVE will only call alerts when 3 of those 9 models agree. This can be very effective if you want to have more refined volatility trades, giving you more confidence that an expansion will take place.
Low Volatility Flashes - You now have the ability to control the low volatility back ground flash feature that was included with SIVE 1.0
Volatility Candles - You can now plot the volatility strength as candles! before you weren't able to see the actual underlaying volatility . Till now, turn this on and watch it turn you candles into a colourful array of the rainbow based on the volatility . Note - You will either need to *bring to front* or turn off the price data to see it
Take Profit System (beta) - Before on SIVE 1.0 and in the beta versions we had an early version of the money management. Where based on the ATR on the trade it would give you a suggested Stop Loss and Take Profit area. Now we have completely over hauled that and re calculated how we approach this also giving the trader 2 different options to choose from for suggested Stop Loss placement. We also included a 'Dynamic Take Profit' system that's based on the MTI to give you momentum based Take Profits. These are still in beta stages so any feedback is much appreciated and as always will be reviewed and considered.
RSI bands - Reverse plot the RSI onto your chart. Plot the over sold and over Bought static lines to price!
Moving Average Filter ( Multi Time Frame ) - Introducing a way further refine the trade alerts and give more power into the traders hands. We know that many many traders like to only trade if example. price is Greater Than 200 EMA. We wanted to give traders a choice to refine the trade alerts based on this information. You can choose between 'Price vs MA' - which is explained in that example just provided. The other option is 'MA vs MA', this allows you to filter out trades based on if a Moving Average of your choice(MA1) is Greater than MA2. With all this we also provided Multi Time Frame accessibility to just further give the trader more control and range. You also have the ability to just plot the Moving averages and not filter the trades at all!
Kill Zone / Time Sessions - Including another free script that has already been posted to my account. This script is also unique as it plots the specified time zones 24 hours in advanced . If you trade example. 'New York Session', Instead of using an indicator that only shows you after the fact it happens. You can now plot that time zone 24 Hours in advanced and watch how price trades to it and interacts with it. It has 4 completely customizable Time Zone slots. Please adjust to your time zone and desired sessions.
Here are some examples of SIVE working across various charts with the different features
USDCAD - 1 Hour
Take Profit System
XAUUSD ( Gold ) - 15 min
Trend Scalper System
US30(Dow Jones) - 15 min
Volatility Candles + Low Volatility Flashes
BTCUSD ( Bitcoin ) - 1 hour
Support / Resistance + Dashboard + Multi Time Frame MTI
USOIL (WTI Crude Oil ) - 5m
Kill Zones + Moving Average Filter
APPL( Apple ) - 1 hour
Moving Average Filter
Technimentals RobotThis robot includes multiple trade signal algorithms and technical overlays. With tools for all markets and trading styles, access original and beautiful charting tools that work for you.
Flexible and robust trend detection & confirmation
Maverick mean reversion signals
Immensely customizable settings for all markets
Indicator prediction zones, perfect for options traders
The most beautiful bands in the world
As of this update, Technimentals Robot includes:
Queen Mary - A powerful mean reversion algorithm which compares the performance of the chart against the performance of a user-chosen benchmark. She uses short term mean reversion optionally combined with longer term trend following logic to detect possible deviations and thus unique pivot points which may lead to short term reversals or continuations of trend.
Brian - An agile and fully customizable trend following algorithm which uses various filtering systems to hone signals.
Prediction Zones - Projections of future price levels and indicator levels, currently featuring RSI and MFI.
Volume Weighted Filtered Bands - The most beautiful bands in the world.
...and much more! Check the change log below for new features.
Technimentals Robot is an all-in-one suite of indicators designed to be used as a standalone trading system. The backbone of this indicator is the trade signal generation. However, blindly following trade signals without context is unwise and that's where the supplementary bands and Prediction Zones come in. The signals are designed to be used primarily for entry signals; the bands can be used to determine whether or not a chart is overextended (and worth stopping out or profit taking) or not. The Prediction Zones are built in particular for those wishing to trade these signals via options due to the quantifiable nature of their predictions, but they too can be used to add an extra data point for knowing which areas of support & resistance to use when determining take profit and stop loss locations.
Sub-Component Descriptions:
Queen Mary
Queen Mary is a versatile trading signal generator which uses another symbol as a benchmark to build trading signals for your chart.
Queen Mary works by detecting whether or not there are sustained divergences and alerts the user via trade signals for when reversions to the mean are expected.
A typical use case for Queen Mary would be to set her to run on a technology stock with a technology ETF as the benchmark, but you use any pair of your choice.
Buy signals on the chart simultaneously indicate sell signals in the benchmark.
This can be used for pairs trading and long/short portfolio strategies.
Suppose the following; you’ve applied Queen Mary to a chart of AAPL and are using XLK as the benchmark. A buy signal for AAPL would also indicate a sell signal for the XLK. The user could then long AAPL and short XLK the same dollar amount, expecting a reversion to the mean.
Brian
Brian is a flexible trend following algorithm which uses multiple filtering techniques to hone entries and exits.
Brian has been designed to catch every major trend without fail. The inevitable problem all breakout or trend following algorithms face is their propensity to get chopped up during sideways market action. Brian addresses this problem via the ‘Risk’ setting which allows the user to determine the market conditions via a risk/reward standpoint.
During periods of sideways action, the risk setting should be increased. This will reduce the number of signals Brian gives and increase the odds of the breakout leading to a continuation.
Brian signals profit taking signals via blue flags. These always occur at a user defined risk to reward ratio. Partial profits should always be taken as soon as these flags occur. It is advised to use a user-defined trailing stop loss on the remaining position which suits the user’s own risk preferences.
Prediction Zones
Prediction Zones predict zones of indicator and price levels into the future.
Currently featuring the Relative Strength Index and the Money Flow Index, Prediction Zones will display at what future prices these indicators will reach user defined outputs.
A classic use-case example of this would be for options traders as these zones can be used as support and resistance areas. For example, if you believe the daily RSI won’t reach below 30 before the end of the week, you can use this zone as another data point for deciding where to put your short strike.
The zones can be shown into the past too so you can see how they behaved on historical data.
Volume Weighted Filtered Bands
These bands are built by firstly using a volatility and short term range detection algorithm and plugging this into three different lengths of smoothing filters. The output is then combined and filtered one last time before being coloured and plotted as multiple bands.
They can be customized to suit any trading style, but were built with scalp traders particularly in mind. It’s rare for prices to deviate from these bands for long.
A typical use case for these bands would be to trade with the trend while price is trading cleanly inside and in the same direction as the bands. Profit taking should typically be considered when price exceeds the bands, although this will depend on the settings chosen by the user.
The bands can also be used to gauge volatility (with an unusual increase in width) and volume (increased brightness).
The brightness of the bands are determined by volume, the brighter the bands are, the greater the volume.
Queen Mary
Brian
Most of the above images were carefully chosen, others were not. No indicator or strategy is perfect. Trend following algorithms will inevitably experience chop. Mean reversion algorithms will inevitably miss out on the big moves. Our tools aim to give you the data to help you determine which signals to act upon.
You are responsible for your own trading decisions. Trading signals are worthless if you do not have a clear plan, including exit targets and risk management. If you do not have these, you should study them seriously before considering fancy indicators. This indicator is probably unsuitable for beginners.
SIVE 2.0SIVE 2.0 IS FINALLY HERE, after the long awaited update we are finally able to bring to you SIVE 2.0!
SIVE 1.0 (Systematic Institutional Volatility Expansion) brought a whole new approach to the algorithm and retail trading game on TradingView. Never before have you had access to a quantitative institutional approach like this, after years in development and testing we finally brought SIVE 1.0 to market. With very very high demand, support and so much positive feedback we knew that what we've created really hit the mark for so many traders!
What is SIVE?
SIVE as stated above stands for, Systematic Institutional Volatility Expansion. What this means is we have a highly effective system that reads what institutional algorithms are proven to be looking at. While only providing alerts during periods where Volatility is Expanding
We don't shy away from volatility here, that is where the bread and butter lays. volatility is a double edged sword that not many people know how to effectively use to their advantage. Simply put, because they are told in their retail trading that volatility is risky, and that you should stay away from volatile products. I say embrace it with the right tools.
What Has Changed?
At the core, SIVE 2.0 brings more efficient calculations to the volatility modelling as well as the triggering of trades!
Trend Scalper - This is a sub-set strategy we have included, what it measures is 'Super Trend' with a deviation of 7 and the MTI ribbon crosses. This is to be used as a way to scalp and trade the momentum of the market. I am aware that another brand/community has put this out as a paid feature to their algorithm. Since they didn't want to credit me for my contribution I decided to release it for free and also add it here. This is listed in my scripts as a free to use access.
Volatility Confluence - We have now also added a feature where you can choose how many volatility models you want to be aligned before SIVE calls an alert. There are a total of 9 models we have included, example. You choose 3 'Volatility Confluence', this means that SIVE will only call alerts when 3 of those 9 models agree. This can be very effective if you want to have more refined volatility trades, giving you more confidence that an expansion will take place.
Low Volatility Flashes - You now have the ability to control the low volatility back ground flash feature that was included with SIVE 1.0
Volatility Candles - You can now plot the volatility strength as candles! before you weren't able to see the actual underlaying volatility. Till now, turn this on and watch it turn you candles into a colourful array of the rainbow based on the volatility. Note - You will either need to *bring to front* or turn off the price data to see it
Take Profit System (beta) - Before on SIVE 1.0 and in the beta versions we had an early version of the money management. Where based on the ATR on the trade it would give you a suggested Stop Loss and Take Profit area. Now we have completely over hauled that and re calculated how we approach this also giving the trader 2 different options to choose from for suggested Stop Loss placement. We also included a 'Dynamic Take Profit' system that's based on the MTI to give you momentum based Take Profits. These are still in beta stages so any feedback is much appreciated and as always will be reviewed and considered.
RSI bands - Reverse plot the RSI onto your chart. Plot the over sold and over Bought static lines to price!
Moving Average Filter (Multi Time Frame) - Introducing a way further refine the trade alerts and give more power into the traders hands. We know that many many traders like to only trade if example. price is Greater Than 200 EMA . We wanted to give traders a choice to refine the trade alerts based on this information. You can choose between 'Price vs MA' - which is explained in that example just provided. The other option is 'MA vs MA', this allows you to filter out trades based on if a Moving Average of your choice(MA1) is Greater than MA2. With all this we also provided Multi Time Frame accessibility to just further give the trader more control and range. You also have the ability to just plot the Moving averages and not filter the trades at all!
Kill Zone / Time Sessions - Including another free script that has already been posted to my account. This script is also unique as it plots the specified time zones 24 hours in advanced. If you trade example. 'New York Session', Instead of using an indicator that only shows you after the fact it happens. You can now plot that time zone 24 Hours in advanced and watch how price trades to it and interacts with it. It has 4 completely customizable Time Zone slots. Please adjust to your time zone and desired sessions.
Here are some examples of SIVE working across various charts with the different features
USDCAD - 1 Hour
Take Profit System
XAUUSD(Gold) - 15 min
Trend Scalper System
US30(Dow Jones) - 15 min
Volatility Candles + Low Volatility Flashes
BTCUSD(Bitcoin) - 1 hour
Support / Resistance + Dashboard + Multi Time Frame MTI
USOIL(WTI Crude Oil) - 5m
Kill Zones + Moving Average Filter
APPL(Apple) - 1 hour
Moving Average Filter
Please report any bugs, feedback or suggestions you have about SIVE to myself or in the Discord so we can review it and take action!
If it isn't Soldi, it isn't money
Synthetic Price Action GeneratorNOTICE:
First thing you need to know, it "DOES NOT" reflect the price of the ticker you will load it on. THIS IS NOT AN INDICATOR FOR TRADING! It's a developer tool solely generating random values that look exactly like the fractals we observe every single day. This script's generated candles are as fake as the never ending garbage news cycles we are often force fed and expected to believe by using carefully scripted narratives peddled as hypnotic truth to psychologically and emotionally influence you to the point of control by coercion and subjugation. I wanted to make the script's synthetic nature very clear using that analogy, it's dynamically artificial. Do not accidentally become disillusioned by this scripts values, make trading decisions from it, and lastly don't become victim to predatory media magic ministry parrots with pretty, handsome smiles, compelling you to board their ferris wheel of fear. Now, on to the good stuff...
BACKSTORY:
Occasionally I find myself in situations where I have to build analyzers in Pine to actually build novel quantitative analytic indicators and tools worthy of future use. These analyzers certainly don't exist on this platform, but usually are required to engineer and tweak algorithms of the highest quality with the finest computational caliber. I have numerous other synthesizers to publish besides this one.
For many reasons, I needed a synthetic environment to utilize the analyzers I built in Pine, to even pursue building some exotic indicators and algorithms. Pine doesn't allow sourcing of tuples. Not to mention, I required numerous Pine advancements to make long held dreams into tangible realities. Many Pine upgrades have arrived and MANY, MANY more are in need of implementation for all. Now that I have this, intending to use it in the future often when in need, you can now use it too. I do anticipate some skilled Pine poets will employ this intended handy utility to design and/or improved indicators for trading.
ORIGIN:
This was inspired by the brilliance from the world renowned ALGOmist John F. Ehlers, but it's taken on a completely alien form from its original DNA. Browsing on the internet for something else, I came across an article with a small code snippet, and I remembered an old wish of mine. I have long known that by flipping back and forth on specific tickers and timeframes in my Watchlist is not the most efficient way to evaluate indicators in multiple theatres of price action. I realized, I always wanted to possess and use this sort of tool, so... I put it into Pine form, but now have decided to inject it with Pine Script steroids. The outcome is highly mutable candle formations in a reusable mutagenic package, observable above and masquerading as genuine looking price candles.
OVERVIEW:
I guess you could call it a price action synthesizer, but I entitled it "Synthetic Price Action Generator" for those who may be searching for such a thing. You may find this more useful on the All or 5Y charts initially to witness indication from beginning (barstate.isfirst === barindex==0) to end (last_bar_index), but you may also use keyboard shortcuts + + to view the earliest plottable bars on any timeframe. I often use that keyboard shortcut to qualify an indicator through the entirety of it's runtime.
A lot can go wrong unexpectedly with indicator initialization, and you will never know it if you don't inspect it. Many recursively endowed Infinite Impulse Response (IIR) Filters can initialize with unintended results that minutely ring in slightly erroneous fashion for the entire runtime, beginning to end, causing deviations from "what should of been..." values with false signals. Looking closely at spg(), you will recognize that 3 EMAs are employed to manage and maintain randomness of CLOSE, HIGH, and LOW. In fact, any indicator's barindex==0 initialization can be inspected with the keyboard shortcuts above. If you see anything obviously strange in an authors indicator, please contact the developer if possible and respectfully notify them.
PURPOSE:
The primary intended application of this script, is to offer developers from advanced to even novice skill levels assistance with building next generation indicators. Mostly, it's purpose is for testing and troubleshooting indicators AND evaluating how they perform in a "manageable" randomized environment. Some times indicators flake out on rare but problematic price fluctuations, and this may help you with finding your issues/errata sooner than later. While the candles upon initial loading look pristine, by tweaking it to the minval/maxval parameters limits OR beyond with a few code modifications, you can generate unusual volatility, for instance... huge wicks. Limits of minval= and maxval= of are by default set to a comfort zone of operation. Massive wicks or candle bodies will undoubtedly affect your indication and often render them useless on tickers that exhibit that behavior, like WGMCF intraday currently.
Copy/paste boundaries are provided for relevant insertion into another script. Paste placement should happen at the very top of a script. Note that by overwriting the close, open, high, etc... values, your compiler will give you generous warnings of "variable shadowing" in abundance, but this is an expected part of applying it to your novel script, no worries. plotcandle() can be copied over too and enabled/disabled in Settings->Style. Always remember to fully remove this scripts' code and those assignments properly before actual trading use of your script occurs, AND specifically when publishing. The entirety of this provided code should never, never exist in a published indicator.
OTHER INTENTIONS:
Even though these are 100% synthetic generated price points, you will notice ALL of the fractal pseudo-patterns that commonly exist in the markets, are naturally occurring with this generator too. You can also swiftly immerse yourself in pattern recognition exercises with increased efficiency in real time by clicking any SPAG Setting in focus and then using the up/down arrow keys. I hope I explained potential uses adequately...
On a personal note, the existence of fractal symmetry often makes me wonder, do we truly live in a totality chaotic universe or is it ordered mathematically for some outcomes to a certain extent. I think both. My observations, it's a pre-deterministic reality completely influenced by infinitesimal amounts of sentient free will with unimaginable existing and emerging quantities. Some how an unknown mysterious mechanism governing the totality of universal physics and mathematics counts this 100.0% flawlessly and perpetually. Anyways, you can't change the past that long existed before your birth or even yesterday, but you can choose to dream, create, and forge the future into your desires and hopes. As always, shite always happens when your not looking for it. What you choose to do after stepping in it unintentionally... is totally up to you. :) Maybe this tool and tips provided will aid you in not stepping in an algo cachucha up to your ankles somehow.
SCRIPTING LESSONS PORTRAYED IN THIS SCRIPT:
Pine etiquette and code cleanliness
Overwrite capabilities of built-in Pine variables for testing indicators
Various techniques to organize Settings panel while providing ease of adjustment utility
Use of tooltip= to provide users adequate valuable information. Most people want to trade with indicators, not blindly make adjustments to them without any knowledge of their intended operation/effects
When available time provides itself, I will consider your inquiries, thoughts, and concepts presented below in the comments section, should you have any questions or comments regarding this indicator. When my indicators achieve more prevalent use by TV members , I may implement more ideas when they present themselves as worthy additions. Have a profitable future everyone!
SB Master Chart v5 (Public)SB Master Chart v5 is the latest progression of the SB Master Chart series of charts.
The original SB Master Chart and its successors was designed to be a visual aid for the savvy investor. The original concept was designed to provide valuable information so decisions could be made at a glance with utmost confidence.
As the chart progressed through versions, it has slowly shifted the responsibility of decision making from the trader to the indicator. In this version of the script, we have updated the backend decision code. The script has 3 distinct personalities coded to compliment each other, as well as keep the others in check..
The first personality is the buy algorithm. The buy personality is based on two conditions. The first algorithm first determines a trend, then it waits for a confirmation. The personality is comprised of the following indicators.
EMA 7
EMA 14
MACD
Stochastic
RSI
By default, the first personality has its visual settings disabled. Its still working, its just not displayed on the chart. It can be enabled in the settings. The background colors designate trend and confirmation.
The second personality is stubborn and its committed to making a profit. Its a hard line in the sand that configurable by you the user. Its the take profit/trailing take profit setting. It will not let other personalities sell for less than these configured values. The visual component of personality two is represented by black dots. This serves to showcase its minimum profit target when opening a trade and a trailing stop loss when the price exceeds the minimum profit target.
The third personality is the guy that does the dirty work that nobody wants to admit they do. This personality is based on the original SB Master Chart algorithm. This personality takes over when the first personality is unable to turn a profit. This personality goes to work finding appropriate places to dollar cost average. There are two settings that affect this personality.
DCA %
Risk Multiplier (use extreme caution, this could cause a margin call if used inappropriately).
DCA percent setting restricts this algorithm from buying when the price has not fallen below this threshold.
Risk Multiplier instructs this algorithm how much positions/qty to buy when it buys. At 2x, the algorithm will buy enough shares to double its current position, at 3x the algorithm will buy enough shares to triple its current position.
The visual representations of the third personality are that of red, orange, yellow and green. Red means overbought. When an orange appears just prior to a red, that orange means overbought with volume. Green means oversold and an orange preceding a green is an oversold with volume. Both the red and green represent an possible trend reversal and that's the signal to buy when its green.
This personality is comprised of the following indicators:
RSI
Stochastic
MACD
Bollinger
Volume
The code also features 3 modes. Altering the mode setting changes the way the personalities work together (or do not work together).
Normal
Aggressive
Buy the Dip
Mode Normal works exactly like described above. Each personality has its own duty and they do not interfere with each others work.
Aggressive mode adjusts the dynamic and both the first personality and the third personality share an equal part in opening starter positions.
Buy the Dip mode prevents personality one from buying. Since personality one only buys uptrends, you will never see it buying a dip. This mode puts personality 3 in the spotlight. All position are typically opened during a fast/quick market decline. Personality three is still bound by the rules of personality 2, but its responsible for buying and dollar cost averaging.
I have also included labels for every buy/sell. A green label is the script making its first purchase, yellow is points where it decided to dollar cost average and the red is where it chose to deleverage by closing out all its positions. Nothing prevents the algorithm from buying immediately after a sell, this is by design because we do not want to miss out on an uptrend, but we also do not want to be caught with too much leverage.
Also included vital statistics on the top right of the chart.
Open Positions
Cost Basis
Current Gain/Loss
Minimum Profit Target
Trailing Stop Loss
Total Trades to Date
Maximum Positions/Qty to Date
In the bottom right of the chart, I have the user configurable settings. This is important so a user can at a glance see the settings of the chart without having to open the options menu.
Together, all three personalities form a COMPLETE trading system. The system tracks purchase quantity, cost basis from the first buy, adjust with each new buy and calculates the running profit from the begining of the date set in the settings if it were to have bought and sold at every signal. The public version of the script requires the trader to use the script in real time watching for buy and sell opportunities. The private subscription version of the script has custom alerts that can be configured to alert the user on when to buy and sell and also gives the user appropriate trailing stop loss settings to automate the trading process.
I want to name the personalities at some point in time for the novelty factor, but I wanted to release the script as soon as possible for others to enjoy, so they are nameless at this point. If you have suggestions, please contact me with your suggestion. I will credit the person with the best personality with a free subscription to the private version of this indicator.
As always, understand the risks of trading and trade responsibly. Nothing in this script can predict the future. Past results do not guarantee future performance
CroSel Indicator ToolboxA value-packed or all-in-one indicator. The main one is probably the algorithmic signal. I have noticed a few trading groups that rely solely on their algo trading signals. I have derived my own using MACD . I find that it works better or just as good as what I have seen. The others indicators are also very powerful and could even be used on a stand alone basis. There are different variations included. I wanted to provide 10x the value at whatever price I would put on this. However I think I've provided at least 20x the expected value. What I like about this is that with more signals, we can visually see confluence. In turn, that should give us traders confidence. The follow is a list of all the indicators I've included so far:
How to use (for all indicators): I suggest using these trade signals as confluence for the main algorithmic trade signals. Aside from MACD and RSI , there are a limited number of signals, but they will all show up within the most recent bars that have passed. Buy when green/lime and sell when red/fuchsia. I suggest experimenting with the the different modes to see what you believe works best for your trading style.
I prefer to use the last signal provided, but I also like to rely on looking at signals as a group, if they are all rising, I'm bullish ; if they are all falling, I'm bearish .
Note on Color Scheme: Red/Fuchsia color means to short/sell and green/lime color means to long/buy.
- Algorithmic signal - provides trade signals. How to use: When there is a green arrow up, it means you should go long. When there is a red arrow down, it means you should exit your long or short sell. If the arrow is lime colored, it means the stock is trending upwards and if the arrow is fuchsia, it means the stock is trending downwards.
- Band and hit count - provides bands to track volatility , as well as tracks the number of times the price hits the upper or lower bands. It also provides candle-to-candle slope as a %. How to use: You can use this to play the odds in your favor. For example: if a stock hits the upper bands 13 times during the morning, and then hits the lower bands 4 times afterwards and then moves upwards away from the lower bands towards the middle of the bands, from here we may be able to say that since 13 is greater than 4, that the stock price may rise again and start hitting the upper bands. Another way I like to use this indicator, is if a stock hits the upper bands more than 16 to 20 times, I like to exit the trade before it has a chance to drop. Lastly, there are zones where a stock price will go above or below 100% or 0% respectively. For example, a stock starts to hit the 110% area of the bands. This could be an excellent time to sell/short the stock.
- Volume surge - provides signals of when volume is increasing/decreasing depending on the color and direction. How to use: Gives you confidence that the price will rise higher/lower.
- EMA 5 & 10 - It is the exponential moving average of the past 5 or 10 bars. It will be either be red or green depending on the slope. How to use: I like to use it as if it were a trend line (which I like to call slanted support/resistance ). For example, if I buy a stock and it falls below EMA 10 I will generally sell the stock, and if it rises past EMA 5 I will generally buy the stock.
- Background color - Background color shows whether the stock is bullish or bearish . If it is green/red, it is slightly bullish / bearish respectively. If it is lime/fuchsia, it is very bullish / bearish respectively. How to use: Take long positions if the background color is greenish(i.e. green/lime) and take short position if the background color is reddish (i.e.red/fuchsia). Please bear in mind, background color will look slightly different if you are already coloring the extended hour session backgrounds.
- Channel Breakout Lines - These lines show the rigid channel that the stock will travel through. How to use: Watch a stock that is in a channel, if it is going up, watch the red dotted line which extends into the future,
if it the stock falls below that previous red dotted line you should sell/short the stock. If a stock is going down, watch the green dotted line, and if the stock goes past the previous green dotted line, you should buy.
- MACD - Moving Average Convergence and Divergence provides trade signals. How to use: 1 turns it off. 2 provides the classic, buy and sell signals based on when the MACD line crosses over or under the signal line. 3 provides faster trade
signals. 4 provides the algorithmic signals. All variations can change according to Algo sensitivity and Algo Signal speed since the algo uses MACD as it's base.
- RSI - Relative Strength Index provides trade signals. How to use: 1 turn it off, 2 turns on and provides the buy and sell signals for above 70 and below 30 RSI respectively. 3 and 4 provide slow and fast RSI trade signals respectively.
4 is my favorite and can be used to provide confluence.
- VWAP - Volume Weighted Average Price . a 2 value is the regular vwap line. A value of 3 or 4 will show that the VWAP line or fill from line until the close is colored
according to slope of EMA 5. How to use: Buy below the VWAP if it shows some support and sell/Short above if it shows some resistance. When the color is red it will show the
- ROC - Rate of Change trade signals. Take note of the circle shaped symbols. Normal mode shows you when the rate of change has crossed the zero line; this can be a very bullish or bearish signal. 3rd mode will gives signals based on whether ROC has stopped making new highs or new lows. 4th mode gives the fastest signals, making it the least risky.
- MFI - Money Flow Index trade Signals. Take note of the Long arrow symbols. Modes work as described.
- BOP - Balance of power trade signals. Take note of the square symbols. The simple mode provides only the biggest trade signals, and the complex mode provides both the biggest and smallest trade signals.
- OBV - A running total of positive and negative volume . Take note of the diamond shaped symbols. Slow signals are really slow. Fast signals are really fast. Use according to your trading speed preference.
- Stochastics - A momentum oscillator that provides trade signals. Take note of the plus shaped symbols and factor them into your judgement on when to trade.
- CCI - Commodity Channel Index trade signals based on momentum. Take note of the X symbols.
- CMF - Chaikin Money Flow trade signals. Take note of the flag symbols.
- ADX - ADX is a component of the Directional Movement System developed by Welles Wilder. When it says to buy, I suggest that you go long, and then before it says to sell you try to sell. And then you can also try to go long before it says to buy. As soon as I see buy, I want to be in the stock and conversely, when I see sell I want to be out of it.
- Price-Volume Divergence - This indicator is a candle by candle indicator which shows that if volume is rising and price is falling, then there is bullish divergence , Conversely if price is rising and volume is falling there is bearish divergence. This a leading indicator.
- Ichimoku Clouds - This indicator just shows the clouds in the Ichimoku cloud system. It can be used to buy under the clouds and sell over the clouds. It can also be used as a possible support/resistance level during an uptrend/downtrend respectively.
- PSAR - Parabolic Stop and Reverse . Denotes uptrends/downtrends, by multiple dotted lines. You can use it by buying/selling when it breaks out of a downtrend/uptrend respectively. Or you can use it to sell/buy during an uptrend/downtrend respectively. Warning: it is generally slow. I find that it's very reliable from a 5 minute perspective.
- Fibonacci levels - People generally use Fibonacci levels for retracement for when a stock pulls back. I personally like to use it as a predictive tool along with looking at the slope. If the slope is negative/positive and moving away/near from 50% line then, I would be bearish / bullish respectively.
- Moving Average ( EMA and SMA ) lines - Exponential moving average and Smooth moving average lines. EMA lines move faster and SMA lines move slower. I like to use these lines as trend lines which can tell me if there is an uptrend or downtrend. The strength of the trend is shown by the distance away from the slowest EMA / SMA lines. I like to sell when it's far above the trendline, and buy when it's closer to the trendline. Be weary of the price crossing trendlines .
- Information Panel - (Price location, Trend Strength, Volatilty Ratio, Current State, Reversal/Continuation Odds): Mode 2 will give you basic price location info. Mode 3 is my favorite and will give you the most info. and Mode 4 will give you the Schwager volatility ratio which can help with stock selection; the higher the ratio, the more movement can be expected.
- Support & Resistance levels - Horizontal dotted lines which show the stock price and where it experiences support/resistance . Can be used in many ways. I like to use it by counting the number of support/resistance lines provided and if support lines exceed resistance lines, I will be more likely to go long.
- Candle Colors - Overlay a color onto the Candles. Note: I encourage the use of Heiken Ashi which helps a lot with low volume candles. Candles can be colored according to their location within the bands, and also according to a trailing stop loss based on Average True Range . Buy low, sell high for the location mode and for the stop loss mode, selling/buying is encouraged when the bars go completely red/green respectively.
- Linear Regression - Draws a (black) line of best fit, and shows 2 standard deviations away from the line of best fit above(red) and below(green). I suggest buying/selling below/above the line of best fit respectively. Strong buys or sells generally occur below or above the standard deviation lines respectively.
JD's Apollo ConfirmationsJD Apollo Confirmations Indicator is used as the confirmation indicators for a number of other algorithms.
This has been specifically designed for Indicies, namely the US30.
How to use;
When the bars align, it means the price is heading in the direction of alignment.
This indicator is intended to be used as a confirmation indicator for other algorithms for best effect.
This algorithm combines a number of indicators with specifically tested and chosen settings that have shown to work on a number of timeframes.
How to Access
Gain access to JD Apollo Confirmations for your TradingView account through our website, links below.
7 day paid trials, subscriptions and lifetime access are all available.
JD Progress ConfirmationsJD Progress Confirmations Indicator is used as the confirmation indicators for a number of other algorithms.
This can be applied to Forex, Stocks and Crypto.
How to use;
When the bars align, it means the price is heading in the direction of alignment.
This indicator is intended to be used as a confirmation indicator for other algorithms for best effect.
This algorithm combines a number of indicators with specifically tested and chosen settings that have shown to work on a number of timeframes.
How to Access
Gain access to JD Progress Confirmations for your TradingView account through our website, links below.
7 day paid trials, subscriptions and lifetime access are all available.
All tiers give you full instructions on how to trade this strategy.
JD ConfirmationsJD Confirmations Indicator is used as the confirmation indicators for a number of other algorithms.
This can be applied to Forex, Stocks and Crypto.
How to use;
When the bars align, it means the price is heading in the direction of alignment.
This indicator is intended to be used as a confirmation indicator for other algorithms for best effect.
This algorithm combines a number of indicators with specifically tested and chosen settings that have shown to work on a number of timeframes.
How to Access
Gain access to JD Core for your TradingView account through our website, links below.
Both 7 day paid trials and lifetime access are available.
Both tiers give you full instructions on how to trade this strategy.
the "fasle" hull moving averageThere is a little different between my "fasle hull moving average" the "correct one".
the correct algorithm:
hma = wma((2*wma(close,n/2) - wma(close,n),sqrt(n))
the "fasle" algorithm:
=wma((2*wma(close,n/4) - wma(close,n),sqrt(n))
Amazing! Why the "fasle" describe the trend so accurate!?
FIAfirecrest Trading System(INVITE ONLY indicator. TRIAL ONLY indicator Delay by 15 candles available here .)
To access real time indicators click here for subscription.
Please don't post comment to ask for invitation. This indicator based on our own smart signal algorithm:
FIAfirecrest IS BASED ON OUR OWN ALGORITHM:
FIAfirecrest is actually a trading system based on ‘trend following’ strategy. The system consists of several indicators which can give users trading signals as well as shows the validity of the trading signals.
Since FIAfirecrest are very concerned about ‘trend following’, therefore we urge our trader to also focus on ‘trend following’ only. Besides thats, FIAfirecrest also features several important qualities:
• The usage of colours improve trading clarity
• Easily to determine the market structure
• Enable to translate trading signal in many angle
• Includes take profit and stop loss level
• Early alert on any trend changes possibilities
FIAfirecrest trading system originally based on 3 smart signal indicators: FIAbreakout, FIAmist and FIApierce. FIAbreakout initial calculation based on higher lower high/low price, FIAmist originally based on momentum thus forming the trend, while FIApierce use as filter based on non-lag adaptive moving averages.
How to use:
FIAbreakout | area Grey, Yellow & Blue
FIAmist | area Green & Red
FIApierce | cross Green & Red
FIAosc | triangle Green & Red
FIAbreakout and FIAmist condition:
• LONG when price cross above Grey area and forming Yellow above Grey. Entry within FIAmist Green. Set your stop loss at lowest Grey.
• SHORT when price cross below Grey area and forming Blue below Grey. Entry within FIAmist Red. Set your stop loss at highest Grey.
FIApierce and FIAosc condition:
• FIApierce cross Green or sharp turn formation from Grey area. Is early signal price reverse from long to short. Entry short within FIAmist Red.
• FIApierce cross Red or sharp turn formation from Grey area. Is early signal price reverse from short to long. Entry short within FIAmist Green.
• Use FIAosc to filter whether both setup are valid or not.
That’s all for our FIAfirecrest Trading System.
FIAfirecrest Trading System Trial(TRIAL ONLY indicator Delay by 15 candles.)
To access real time indicators click here for subscription.
Please don't post comment to ask for remove delay. This indicator based on our own smart signal algorithm:
FIAfirecrest IS BASED ON OUR OWN ALGORITHM:
FIAfirecrest is actually a trading system based on ‘trend following’ strategy. The system consists of several indicators which can give users trading signals as well as shows the validity of the trading signals.
Since FIAfirecrest are very concerned about ‘trend following’, therefore we urge our trader to also focus on ‘trend following’ only. Besides thats, FIAfirecrest also features several important qualities:
• The usage of colours improve trading clarity
• Easily to determine the market structure
• Enable to translate trading signal in many angle
• Includes take profit and stop loss level
• Early alert on any trend changes possibilities
FIAfirecrest trading system originally based on 3 smart signal indicators: FIAbreakout, FIAmist and FIApierce. FIAbreakout initial calculation based on higher lower high/low price, FIAmist originally based on momentum thus forming the trend, while FIApierce use as filter based on non-lag adaptive moving averages.
How to use:
FIAbreakout | area Grey, Yellow & Blue
FIAmist | area Green & Red
FIApierce | cross Green & Red
FIAosc | triangle Green & Red
FIAbreakout and FIAmist condition:
• LONG when price cross above Grey area and forming Yellow above Grey. Entry within FIAmist Green. Set your stop loss at lowest Grey.
• SHORT when price cross below Grey area and forming Blue below Grey. Entry within FIAmist Red. Set your stop loss at highest Grey.
FIApierce and FIAosc condition:
• FIApierce cross Green or sharp turn formation from Grey area. Is early signal price reverse from long to short. Entry short within FIAmist Red.
• FIApierce cross Red or sharp turn formation from Grey area. Is early signal price reverse from short to long. Entry short within FIAmist Green.
• Use FIAosc to filter whether both setup are valid or not.
That’s all for our FIAfirecrest Trading System.
PRICE SATURATION INDEX / FİYAT YOĞUNLUK ENDEKSİEN: PRICE SATURATION INDEX is a momentum algorithm that measures price intensity. It helps us to determine the times when the price reaches intensity and calculates the latency in those moving averages. Moving averages have lag. The lag is necessary because the smoothing is done using past data. It shows you how to filtered a selected amount of lag from an exponential moving average (ema) and price movements. Removing all the lag is not necessarily a good thing, because with no lag, the indicator would just track out the price we were filtering, just as it is the moving average of 1 period; the amount of lag removed is a tradeoff with the amount of smoothing we are willing to forgo with golden ratio and multiline function. We show you the effects of lag removal in an indicator and then use the filter in an effective trading strategy with multiline function. The multiline function is inspired by Jhon Ehlers' zero lag formule, smooth moving average strategy and Schrödinger equation. The Schrödinger equation is a wave function based on quantum mechanics
TR: FİYAT YOĞUNLUK ENDEKSİ, fiyat yoğunluğunu ölçen bir momentum algoritmasıdır. Fiyatın yoğunluğa ulaştığı zamanları belirlememize ve hareketli ortalamalardaki gecikmeyi hesaplamamıza yardımcı olur. Hareketli ortalamalar daima gecikir. Gecikme gereklidir çünkü yumuşatma geçmiş veriler kullanılarak yapılır. Bu algoritma hem fiyat hareketlerindeki hemde üstel hareketli ortalamadaki gecikme miktarının nasıl filtreleneceğini gösterir. Tüm gecikmenin kaldırılması iyi bir şey değildir, çünkü gecikme olmadığında gösterge sadece 1 periyodun hareketli ortalaması gibi davranacağı için filtrelediğimiz fiyatı izleyecektir; filtrelenen gecikme miktarı, terk etmek istediğimiz yumuşatma miktarına alternatif bir multiline fonksiyon ve altın orana uyarlanan frekans değirinden oluşur. Bu göstergede gecikmenin ortadan kaldırılmasının etkilerini gösteriyoruz ve daha sonra filtreyi multiline fonksiyona sahip etkili bir trading stratejisi olarak kullanıyoruz. Multiline fonksiyon, Jhon Ehler'in zero lag formülü, smooth hareketli ortalama stratejisi ve Schrödinger denkleminden esinlenmiştir. Schrödinger denklemi ise kuantum mekaniğini temel alan bir dalga fonksiyonudur.
UltraTrend Pro - Phoenix Engine EditionUltraTrend Pro – Phoenix Engine Edition
Overview
This is a technical analysis tool designed to help identify the current market trend and provide context on the market's "personality." It is built around a proprietary Phoenix Engine that analyzes price action to classify the market into distinct regimes—such as strong trends, weak trends, or choppy conditions—and then adapts its core algorithm accordingly.
Technical Features
The indicator is built on these main ideas:
1. The Phoenix Engine (Market Regime Classification):
Instead of using a one-size-fits-all approach, the Phoenix Engine constantly analyzes price volatility, strength, and stability to classify the current market into one of several regimes:
* Strong Trend (Up/Down): Clear, high-momentum directional movement.
* Medium/Weak Trend (Up/Down): Developing or fading directional movement.
* Ranging: Sideways price action with low volatility.
* Volatile: Large price swings but with no clear direction.
* Choppy: Unpredictable, messy price action to be cautious of.
This classification is displayed in real-time in the on-screen "Market Regime Display."
2. AI-Style Adaptive Trend Algorithm:
When "AI-Style Adaptation" is enabled, the core trend-following algorithm automatically adjusts its own internal parameters (Sensitivity and Period) based on the regime detected by the Phoenix Engine.
* In strong trends, it becomes less sensitive to ride the trend longer.
* In choppy or volatile markets, it becomes more conservative to help filter out noise.
This allows the indicator to dynamically adapt its behavior to the ever-changing personality of the market.
3. Adaptive Fibonacci TP/SL System:
The indicator's Take Profit (TP) and Stop Loss (SL) levels can operate in two modes:
* Standard Mode: Uses fixed Risk-Reward ratios set by the user.
* Adaptive Mode: This is the AI-style feature. It analyzes the historical success rate of signals within the current market regime to calculate and display:
* Adjusted TP/SL Levels: Levels are automatically widened or tightened based on what has historically worked best in that specific regime (e.g., wider TPs in strong trends, tighter TPs in ranging markets).
* Success Probabilities: An estimated probability (%) of reaching each TP level is shown on the chart.
* Expected Duration: An estimated time-to-target (in bars) is displayed for each TP, helping with trade management expectations.
4. Built-in Backtest & Data Analysis Engine:
To power the adaptive system, the indicator includes a powerful backtest engine that scans historical signals. It can operate in two modes:
* Deep Historical Scan: Analyzes thousands of past candles to build a robust statistical baseline.
* Recent Signals Only: Focuses only on the most recent signals within each regime, allowing the system to adapt more quickly to changing market character.
The results are displayed in a comprehensive on-screen "Backtest Statistics Table."
5. Multi-Layered Filtering System:
To qualify signals, the indicator allows for additional filters, including:
* Dual Moving Averages: Ensure signals align with a broader market trend (e.g., above the 200 SMA).
* Trading Session Filter: Restricts signals to specific user-defined trading hours.
How to Use This Indicator
1. Use the Feature Control Panel: The settings menu has been simplified. The top sections allow you to quickly toggle major visual components on or off to customize your chart.
2. Enable AI-Style Adaptation (Recommended): For the indicator to use the Phoenix Engine to its full potential, ensure "Enable AI-Style Adaptation" is checked.
3. Observe the Market Regime Display: This on-screen table is your guide to the current market's personality. It tells you the detected regime, its strength, and how the indicator is adapting.
4. Watch for Signals: A "BUY" or "SELL" signal indicates that the trend algorithm has detected a potential shift in direction.
5. Assess Adaptive TP/SL Levels: When a signal appears, observe the on-chart TP levels. The displayed probabilities and expected durations provide valuable context for managing the trade. For example, a high-probability TP1 with a short duration might be a good scalping target.
6. Use Tables for Deeper Insight: The "Backtest Statistics Table" provides a detailed breakdown of how signals have historically performed in each market regime, helping you decide which setups to trust more.
Intended Use & Limitations
* Recommended Assets: Designed for use on all assets. The Phoenix Engine's adaptive nature allows it to adjust to different market types automatically.
* Timeframes: Can be used on all timeframes.
Limitations:
* This is a tool to support analysis. It does not generate automatic buy or sell advice.
* The indicator is not a standalone strategy and does not guarantee results. Users are responsible for their own trading decisions.
* Probabilities and statistics are based on historical data and do not predict future results.
* Always use this tool in combination with your own analysis and a robust risk management plan.
We believe that no indicator is a magic solution. Technical analysis tools provide value through their convenience, adaptability, and unique logic. Combining these elements can help a trader make more educated and planned decisions, hopefully contributing to their overall success.
RISK ROTATION MATRIX ║ BullVision [3.0]🔍 Overview
The Risk Rotation Matrix is a comprehensive market regime detection system that analyzes global market conditions across four critical domains: Liquidity, Macroeconomic, Crypto/Commodities, and Risk/Volatility. Through proprietary algorithms and advanced statistical analysis, it transforms 20+ diverse market metrics into a unified framework for identifying regime transitions and risk rotations.
This institutional-grade system aims to solve a fundamental challenge: how to synthesize complex, multi-domain market data into clear, actionable trading intelligence. By combining proprietary liquidity calculations with sophisticated cross-asset analysis.
The Four-Domain Architecture
1. 💧 LIQUIDITY DOMAIN
Our liquidity analysis combines standard metrics with proprietary calculations:
Proprietary Components:
Custom Global Liquidity Index (GLI): Unique formula aggregating central bank assets, credit spreads, and FX dynamics through our weighted algorithm
Federal Reserve Balance Proxy: Advanced calculation incorporating reverse repos, TGA fluctuations, and QE/QT impacts
China Liquidity Proxy: First-of-its-kind metric combining PBOC operations with FX-adjusted aggregates
Global M2 Composite: Custom multi-currency M2 aggregation with proprietary FX normalization
2. 📈 MACRO DOMAIN
Sophisticated integration of global economic indicators:
S&P 500: Momentum and trend analysis with custom z-score normalization
China Blue Chips: Asian market sentiment with correlation filtering
MBA Purchase Index: Real estate market health indicator
Emerging Markets (EEMS): Risk appetite measurement
Global ETF (URTH): Worldwide equity exposure tracking
Each metric undergoes proprietary transformation to ensure comparability and regime-specific sensitivity.
3. 🪙 CRYPTO/COMMODITIES DOMAIN
Unique cross-asset analysis combining:
Total Crypto Market Cap: Liquidity flow indicator with custom smoothing
Bitcoin SOPR: On-chain profitability analysis with adaptive periods
MVRV Z-Score: Advanced implementation with multiple MA options
BTC/Silver Ratio: Novel commodity-crypto relationship metric
Our algorithms detect when crypto markets lead or lag traditional assets, providing crucial timing signals.
4. ⚡ RISK/VOLATILITY DOMAIN
Advanced volatility regime detection through:
MOVE Index: Bond volatility with inverse correlation analysis
VVIX/VIX Ratio: Volatility-of-volatility for regime extremes
SKEW Index: Tail risk measurement with custom normalization
Credit Stress Composite: Proprietary combination of credit spreads
USDT Dominance: Crypto flight-to-safety indicator
All risk metrics are inverted and normalized to align with the unified scoring system.
🧠 Advanced Integration Methodology
Multi-Stage Processing Pipeline
Data Collection: Real-time aggregation from 20+ sources
Normalization: Custom z-score variants accounting for regime-specific volatility
Domain Scoring: Proprietary weighting within each domain
Cross-Domain Synthesis: Advanced correlation matrix between domains
Regime Detection: State-transition model identifying four market phases
Signal Generation: Composite score with adaptive smoothing
🔁 Composite Smoothing & Signal Generation
The user can apply smoothing (ALMA, EMA, etc.) to highlight trends and reduce noise. Smoothing length, type, and parameters are fully customizable for different trading styles.
🎯 Color Feedback & Market Regimes
Visual dynamics (color gradients, labels, trails, and quadrant placement) offer an at-a-glance interpretation of the market’s evolving risk environment—without forecasting or forward-looking assumptions.
🎯 The Quadrant Visualization System
Our innovative visual framework transforms complex calculations into intuitive intelligence:
Dynamic Ehlers Loop: Shows current position and momentum
Trailing History: Visual path of regime transitions
Real-Time Animation: Immediate feedback on condition changes
Multi-Layer Information: Depth through color, size, and positioning
🚀 Practical Applications
Primary Use Cases
Multi-Asset Portfolio Management: Optimize allocation across asset classes based on regime
Risk Budgeting: Adjust exposure dynamically with regime changes
Tactical Trading: Time entries/exits using regime transitions
Hedging Strategies: Implement protection before risk-off phases
Specific Trading Scenarios
Domain Divergence: When liquidity improves but risk metrics deteriorate
Early Rotation Detection: Crypto/commodity signals often lead broader markets
Volatility Regime Trades: Position for mean reversion or trend following
Cross-Asset Arbitrage: Exploit temporary dislocations between domains
⚙️ How It Works
The Composite Score Engine
The system's intelligence emerges from how it combines domains:
Each domain produces a normalized score (-2 to +2 range)
Proprietary algorithms weight domains based on market conditions
Composite score indicates overall market regime
Smoothing options (ALMA, EMA, etc.) optimize for different timeframes
Regime Classification
🟢 Risk-On (Green): Positive composite + positive momentum
🟠 Weakening (Orange): Positive composite + negative momentum
🔵 Recovery (Blue): Negative composite + positive momentum
🔴 Risk-Off (Red): Negative composite + negative momentum
Signal Interpretation Framework
The indicator provides three levels of analysis:
Composite Score: Overall market regime (-2 to +2)
Domain Scores: Identify which factors drive regime
Individual Metrics: Granular analysis of specific components
🎨 Features & Functionality
Core Components
Risk Rotation Quadrant: Primary visual interface with Ehlers loop
Data Matrix Dashboard: Real-time display of all 20+ metrics
Domain Aggregation: Separate scores for each domain
Composite Calculation: Unified score with multiple smoothing options
Customization Options
Selective Metrics: Enable/disable individual components
Period Adjustment: Optimize lookback for each metric
Smoothing Selection: 10 different MA types including ALMA
Visual Configuration: Quadrant scale, colors, trails, effects
Advanced Settings
Pre-smoothing: Reduce noise before final calculation
Adaptive Periods: Automatic adjustment during volatility
Correlation Filters: Remove redundant signals
Regime Memory: Hysteresis to prevent whipsaws
📋 Implementation Guide
Setup Process
Add to chart (optimized for daily, works on all timeframes)
Review default settings for your market focus
Adjust domain weights based on trading style
Configure visual preferences
Optimization by Trading Style
Position Trading: Longer periods (60-150), heavy smoothing
Swing Trading: Medium periods (20-60), balanced smoothing
Active Trading: Shorter periods (10-40), minimal smoothing
Best Practices
Monitor domain divergences for early signals
Use extreme readings (-1.5/+1.5) for high-conviction trades
Combine with price action for confirmation
Adjust parameters during major events (FOMC, earnings)
💎 What Makes This Unique
Beyond Traditional Indicators
Multi-Domain Integration: Only system combining liquidity, macro, crypto, and volatility
Proprietary Calculations: Custom formulas for GLI, Fed, China, and M2 proxies
Adaptive Architecture: Dynamically adjusts to market regimes
Institutional Depth: 20+ integrated metrics vs typical 3-5
Technical Innovation
Statistical Normalization: Custom z-score variants for cross-asset comparison
Correlation Management: Prevents double-counting related signals
Regime Persistence: Algorithms to identify sustainable vs temporary shifts
Visual Intelligence: Information-dense display without overwhelming
🔢 Performance Characteristics
Strengths
Early regime detection (typically 1-3 weeks ahead)
Robust across different market environments
Clear visual feedback reduces interpretation errors
Comprehensive coverage prevents blind spots
Optimal Conditions
Most effective with 100+ bars of history
Best on daily timeframe (4H minimum recommended)
Requires liquid markets for accurate signals
Performance improves with more enabled components
⚠️ Risk Considerations & Limitations
Important Disclaimers
Probabilistic system, not predictive
Requires understanding of macro relationships
Signals should complement other analysis
Past regime behavior doesn't guarantee future patterns
Known Limitations
Black swan events may cause temporary distortions
Central bank interventions can override signals
Requires active management during regime transitions
Not suitable for pure technical traders
💎 Conclusion
The Risk Rotation Matrix represents a new paradigm in market regime analysis. By combining proprietary liquidity calculations with comprehensive multi-domain monitoring, it provides institutional-grade intelligence previously available only to large funds. The system's strength lies not just in its individual components, but in how it synthesizes diverse market information into clear, actionable trading signals.
⚠️ Access & Intellectual Property Notice
This invite-only indicator contains proprietary algorithms, custom calculations, and years of quantitative research. The mathematical formulations for our liquidity proxies, cross-domain correlation matrices, and regime detection algorithms represent significant intellectual property. Access is restricted to protect these innovations and maintain their effectiveness for serious traders who understand the value of comprehensive market regime analysis.
IME's Community First Presented FVGsIME's Community First Presented FVGs v1.5 - Advanced Implementation
ORIGINALITY & INNOVATION
This indicator advances beyond basic Fair Value Gap detection by implementing a sophisticated 24-hour FVG lifecycle management system aligned with institutional trading patterns. While many FVG indicators simply detect gaps and extend them indefinitely, this implementation introduces temporal intelligence that mirrors how institutional algorithms actually manage these inefficiencies.
Key Innovations that set this apart:
- 24-Hour Lifecycle Management: FVGs extend dynamically until 16:59, then freeze until removal at 17:00 next day
- Institutional Day Alignment: Recognizes 18:00-16:59 trading cycles vs standard calendar days
- Multi-Session Detection: Simultaneous monitoring of Midnight, London, NY AM, and NY PM sessions
- Advanced Classification System: A.FVG detection with volume imbalance analysis vs classic FVG patterns
- Volatility Settlement Logic: Blocks contamination from opening mechanics (3:01+, 0:01+, 13:31+ rules)
- Visual Enhancement System: C.E. lines, contamination warnings, dark mode support with proper transparency handling
BASED ON ICT CONCEPTS
This indicator implements First Presented Fair Value Gap methodology taught by ICT (Inner Circle Trader). The original F.P. FVG concepts, timing rules, and session-based detection are credited to ICT's educational material. This implementation extends those foundational concepts with advanced lifecycle management and institutional alignment features.
ICT's Core F.P. FVG Rules Implemented:
- First clean FVG after session opening (avoids opening contamination)
- 3-candle pattern requirement for valid detection
- Session-specific timing windows and volatility settlement
- Consequent Encroachment level identification
IME's Advanced Enhancements:
- Automated lifecycle management with institutional day recognition
- Multi-session simultaneous monitoring with proper isolation
- Advanced visual system with transparency states for aged FVGs
- A.FVG classification with volume imbalance detection algorithms
HOW IT WORKS
Core Detection Engine
The indicator monitors four key institutional sessions using precise timing windows:
- Midnight Session: 00:01-00:30 (blocks 00:00 contamination)
- London Session: 03:01-03:30 (blocks 03:00 contamination)
- NY AM Session: 09:30-10:00 (configurable 9:30 detection)
- NY PM Session: 13:31-14:00 (blocks 13:30 contamination)
During each session window, the algorithm scans for the first valid FVG pattern using ICT's 3-candle rule while applying volatility settlement principles to avoid false signals from opening mechanics.
Advanced Classification System
Classic FVG Detection:
Standard 3-candle wick-to-wick gap where candle 1 and 3 don't overlap, creating an inefficiency that institutions must eventually fill.
A.FVG (Advanced FVG) Detection:
Enhanced pattern recognition that includes volume imbalance analysis (deadpool detection) to identify more significant institutional inefficiencies. A.FVGs incorporate both the basic gap plus additional price imbalances between candle bodies, creating larger, more significant levels.
24-Hour Lifecycle Management
Phase 1 - Dynamic Extension (Creation Day):
From detection until 16:59 of creation day, FVGs extend in real-time as new bars form, maintaining their relevance as potential support/resistance levels.
Phase 2 - Freeze Period (Next Day):
At 16:59, FVGs stop extending and "freeze" at their final size, remaining visible as reference levels but no longer growing. This prevents outdated levels from contaminating fresh analysis.
Phase 3 - Cleanup (17:00 Next Day):
Exactly 24+ hours after creation, FVGs are automatically removed to maintain chart clarity. This timing aligns with institutional trading cycle completion.
Institutional Day Logic
The algorithm recognizes that institutional trading days run from 18:00-16:59 (not midnight-midnight). This alignment ensures FVGs are managed according to institutional timeframes rather than arbitrary calendar boundaries.
Contamination Avoidance System
Volatility Settlement Principle:
Opening mechanics create artificial volatility that can produce false FVG signals. The indicator automatically blocks detection during exact session opening times (X:00) and requires settlement time (X:01+) before identifying clean institutional inefficiencies.
Special NY AM Handling:
Provides configurable 9:30 detection for advanced users who want to capture potential opening range FVGs, with clear visual warnings about contamination risk.
VISUAL SYSTEM
Color Intelligence
- Current Day FVGs: Full opacity with session-specific colors
- Previous Day FVGs: 70% transparency for historical reference
- Special Timing (9:30): Dedicated warning color with alert labels
- Dark Mode Support: Automatic text/line color adaptation
Enhanced Visual Elements
C.E. (Consequent Encroachment) Lines:
Automatically calculated 50% levels within each FVG, representing the most likely fill point based on institutional behavior patterns. These levels extend and freeze with their parent FVG.
Contamination Warnings:
Visual alerts when FVGs are detected during potentially contaminated timing, helping traders understand signal quality.
Session Identification:
Clear labeling system showing FVG type (FVG/A.FVG), session origin (NY AM, London, etc.), and creation date for easy reference.
HOW TO USE
Basic Setup
1. Session Selection: Enable/disable specific sessions based on your trading strategy
2. FVG Type: Choose between Classic FVGs or A.FVGs depending on your analysis preference
3. Visual Preferences: Adjust colors, text size, and enable dark mode if needed
Trading Applications
Intraday Reference Levels:
Use current day FVGs as potential support/resistance for price action analysis. The dynamic extension ensures levels remain relevant throughout the trading session.
Multi-Session Analysis:
Monitor how price interacts with FVGs from different sessions to understand institutional flow and market structure.
C.E. Level Trading:
Focus on the 50% consequent encroachment levels for high-probability entry points when price approaches FVG zones.
Historical Context:
Previous day FVGs (shown with transparency) provide context for understanding market structure evolution across multiple trading days.
Advanced Features
9:30 Special Detection:
For experienced traders, enable 9:30 FVG detection to capture opening range inefficiencies, but understand the contamination risks indicated by warning labels.
A.FVG vs Classic Toggle:
Switch between detection modes based on market conditions - A.FVGs for trending environments, Classic FVGs for ranging conditions.
Best Practices
- Use on 1-minute to 15-minute timeframes for optimal session detection
- Combine with other institutional concepts (order blocks, liquidity levels) for comprehensive analysis
- Pay attention to transparency states - current day FVGs are more actionable than previous day references
- Consider C.E. levels as primary targets rather than full FVG fills
TECHNICAL SPECIFICATIONS
Platform: Pine Script v6 for optimal performance and reliability
Timeframe Compatibility: All timeframes (optimized for 1M-15M)
Market Compatibility: 24-hour markets (Forex, Crypto, Futures)
Session Management: Automatic trading day detection with weekend handling
Memory Management: Intelligent capacity limits with automatic cleanup
Performance: Optimized algorithms for smooth real-time operation
CLOSED SOURCE JUSTIFICATION
This indicator is published as closed source to protect the proprietary algorithms that enable:
- Precise 24-hour lifecycle timing calculations with institutional day alignment
- Advanced A.FVG classification with sophisticated volume imbalance detection
- Complex multi-session coordination with contamination filtering
- Optimized memory management preventing performance degradation
- Specialized visual state management for transparency and extension logic
The combination of these advanced systems creates a unique implementation that goes far beyond basic FVG detection, warranting protection of the underlying computational methods while providing full transparency about functionality and usage.
PERFORMANCE CHARACTERISTICS
Real-Time Operation: Smooth performance with minimal resource usage
Accuracy: Precise session detection with timezone consistency
Reliability: Robust error handling and edge case management
Scalability: Supports multiple simultaneous FVGs without performance impact
This advanced implementation represents significant evolution beyond basic FVG indicators, providing institutional-grade analysis tools for serious traders while maintaining the clean visual presentation essential for effective technical analysis.
IMPORTANT DISCLAIMERS
Past performance does not guarantee future results. This indicator is an educational tool based on ICT's Fair Value Gap concepts and should be used as part of a comprehensive trading strategy. Users should understand the risks involved in trading and consider their risk tolerance before making trading decisions. The indicator identifies potential support/resistance levels but does not predict market direction with certainty.
2 days ago
Release Notes
IME's Community First Presented FVGs v1.5.2 - Critical Bug Fixes
Bug Fixes:
v1.5.1 - Fixed 9:30 Contamination Blocking:
Issue: When 9:30 detection toggle was OFF, script still detected 9:30 candles as F.P. FVGs
Fix: Added proper contamination blocking logic that prevents 9:30 middle candle detection when toggle is OFF
Result: Toggle OFF now correctly shows clean F.P. FVGs at 9:31+ (proper ICT volatility settlement)
v1.5.2 - Fixed A.FVG Box Calculation Accuracy:
Issue: A.FVG boxes incorrectly included ALL body levels even when no actual deadpool existed between specific candles
Fix: Implemented selective body level inclusion - only adds body prices where actual volume imbalances exist
Result: A.FVG boxes now accurately represent only areas with real institutional volume imbalances
Impact:
More Accurate Detection: 9:30 contamination properly blocked when disabled
Precise A.FVG Zones: Boxes only include levels with actual deadpools/volume imbalances
Institutional Accuracy: Both fixes align detection with true institutional trading principles
Technical Details:
Enhanced contamination blocking checks middle candle timing in normal mode
A.FVG calculation now selectively includes body levels based on individual deadpool existence
Maintains backward compatibility with all existing features and settings
These fixes ensure the indicator provides institutionally accurate FVG detection and sizing for professional trading analysis.
Tensor Market Analysis Engine (TMAE)# Tensor Market Analysis Engine (TMAE)
## Advanced Multi-Dimensional Mathematical Analysis System
*Where Quantum Mathematics Meets Market Structure*
---
## 🎓 THEORETICAL FOUNDATION
The Tensor Market Analysis Engine represents a revolutionary synthesis of three cutting-edge mathematical frameworks that have never before been combined for comprehensive market analysis. This indicator transcends traditional technical analysis by implementing advanced mathematical concepts from quantum mechanics, information theory, and fractal geometry.
### 🌊 Multi-Dimensional Volatility with Jump Detection
**Hawkes Process Implementation:**
The TMAE employs a sophisticated Hawkes process approximation for detecting self-exciting market jumps. Unlike traditional volatility measures that treat price movements as independent events, the Hawkes process recognizes that market shocks cluster and exhibit memory effects.
**Mathematical Foundation:**
```
Intensity λ(t) = μ + Σ α(t - Tᵢ)
```
Where market jumps at times Tᵢ increase the probability of future jumps through the decay function α, controlled by the Hawkes Decay parameter (0.5-0.99).
**Mahalanobis Distance Calculation:**
The engine calculates volatility jumps using multi-dimensional Mahalanobis distance across up to 5 volatility dimensions:
- **Dimension 1:** Price volatility (standard deviation of returns)
- **Dimension 2:** Volume volatility (normalized volume fluctuations)
- **Dimension 3:** Range volatility (high-low spread variations)
- **Dimension 4:** Correlation volatility (price-volume relationship changes)
- **Dimension 5:** Microstructure volatility (intrabar positioning analysis)
This creates a volatility state vector that captures market behavior impossible to detect with traditional single-dimensional approaches.
### 📐 Hurst Exponent Regime Detection
**Fractal Market Hypothesis Integration:**
The TMAE implements advanced Rescaled Range (R/S) analysis to calculate the Hurst exponent in real-time, providing dynamic regime classification:
- **H > 0.6:** Trending (persistent) markets - momentum strategies optimal
- **H < 0.4:** Mean-reverting (anti-persistent) markets - contrarian strategies optimal
- **H ≈ 0.5:** Random walk markets - breakout strategies preferred
**Adaptive R/S Analysis:**
Unlike static implementations, the TMAE uses adaptive windowing that adjusts to market conditions:
```
H = log(R/S) / log(n)
```
Where R is the range of cumulative deviations and S is the standard deviation over period n.
**Dynamic Regime Classification:**
The system employs hysteresis to prevent regime flipping, requiring sustained Hurst values before regime changes are confirmed. This prevents false signals during transitional periods.
### 🔄 Transfer Entropy Analysis
**Information Flow Quantification:**
Transfer entropy measures the directional flow of information between price and volume, revealing lead-lag relationships that indicate future price movements:
```
TE(X→Y) = Σ p(yₜ₊₁, yₜ, xₜ) log
```
**Causality Detection:**
- **Volume → Price:** Indicates accumulation/distribution phases
- **Price → Volume:** Suggests retail participation or momentum chasing
- **Balanced Flow:** Market equilibrium or transition periods
The system analyzes multiple lag periods (2-20 bars) to capture both immediate and structural information flows.
---
## 🔧 COMPREHENSIVE INPUT SYSTEM
### Core Parameters Group
**Primary Analysis Window (10-100, Default: 50)**
The fundamental lookback period affecting all calculations. Optimization by timeframe:
- **1-5 minute charts:** 20-30 (rapid adaptation to micro-movements)
- **15 minute-1 hour:** 30-50 (balanced responsiveness and stability)
- **4 hour-daily:** 50-100 (smooth signals, reduced noise)
- **Asset-specific:** Cryptocurrency 20-35, Stocks 35-50, Forex 40-60
**Signal Sensitivity (0.1-2.0, Default: 0.7)**
Master control affecting all threshold calculations:
- **Conservative (0.3-0.6):** High-quality signals only, fewer false positives
- **Balanced (0.7-1.0):** Optimal risk-reward ratio for most trading styles
- **Aggressive (1.1-2.0):** Maximum signal frequency, requires careful filtering
**Signal Generation Mode:**
- **Aggressive:** Any component signals (highest frequency)
- **Confluence:** 2+ components agree (balanced approach)
- **Conservative:** All 3 components align (highest quality)
### Volatility Jump Detection Group
**Volatility Dimensions (2-5, Default: 3)**
Determines the mathematical space complexity:
- **2D:** Price + Volume volatility (suitable for clean markets)
- **3D:** + Range volatility (optimal for most conditions)
- **4D:** + Correlation volatility (advanced multi-asset analysis)
- **5D:** + Microstructure volatility (maximum sensitivity)
**Jump Detection Threshold (1.5-4.0σ, Default: 3.0σ)**
Standard deviations required for volatility jump classification:
- **Cryptocurrency:** 2.0-2.5σ (naturally volatile)
- **Stock Indices:** 2.5-3.0σ (moderate volatility)
- **Forex Major Pairs:** 3.0-3.5σ (typically stable)
- **Commodities:** 2.0-3.0σ (varies by commodity)
**Jump Clustering Decay (0.5-0.99, Default: 0.85)**
Hawkes process memory parameter:
- **0.5-0.7:** Fast decay (jumps treated as independent)
- **0.8-0.9:** Moderate clustering (realistic market behavior)
- **0.95-0.99:** Strong clustering (crisis/event-driven markets)
### Hurst Exponent Analysis Group
**Calculation Method Options:**
- **Classic R/S:** Original Rescaled Range (fast, simple)
- **Adaptive R/S:** Dynamic windowing (recommended for trading)
- **DFA:** Detrended Fluctuation Analysis (best for noisy data)
**Trending Threshold (0.55-0.8, Default: 0.60)**
Hurst value defining persistent market behavior:
- **0.55-0.60:** Weak trend persistence
- **0.65-0.70:** Clear trending behavior
- **0.75-0.80:** Strong momentum regimes
**Mean Reversion Threshold (0.2-0.45, Default: 0.40)**
Hurst value defining anti-persistent behavior:
- **0.35-0.45:** Weak mean reversion
- **0.25-0.35:** Clear ranging behavior
- **0.15-0.25:** Strong reversion tendency
### Transfer Entropy Parameters Group
**Information Flow Analysis:**
- **Price-Volume:** Classic flow analysis for accumulation/distribution
- **Price-Volatility:** Risk flow analysis for sentiment shifts
- **Multi-Timeframe:** Cross-timeframe causality detection
**Maximum Lag (2-20, Default: 5)**
Causality detection window:
- **2-5 bars:** Immediate causality (scalping)
- **5-10 bars:** Short-term flow (day trading)
- **10-20 bars:** Structural flow (swing trading)
**Significance Threshold (0.05-0.3, Default: 0.15)**
Minimum entropy for signal generation:
- **0.05-0.10:** Detect subtle information flows
- **0.10-0.20:** Clear causality only
- **0.20-0.30:** Very strong flows only
---
## 🎨 ADVANCED VISUAL SYSTEM
### Tensor Volatility Field Visualization
**Five-Layer Resonance Bands:**
The tensor field creates dynamic support/resistance zones that expand and contract based on mathematical field strength:
- **Core Layer (Purple):** Primary tensor field with highest intensity
- **Layer 2 (Neutral):** Secondary mathematical resonance
- **Layer 3 (Info Blue):** Tertiary harmonic frequencies
- **Layer 4 (Warning Gold):** Outer field boundaries
- **Layer 5 (Success Green):** Maximum field extension
**Field Strength Calculation:**
```
Field Strength = min(3.0, Mahalanobis Distance × Tensor Intensity)
```
The field amplitude adjusts to ATR and mathematical distance, creating dynamic zones that respond to market volatility.
**Radiation Line Network:**
During active tensor states, the system projects directional radiation lines showing field energy distribution:
- **8 Directional Rays:** Complete angular coverage
- **Tapering Segments:** Progressive transparency for natural visual flow
- **Pulse Effects:** Enhanced visualization during volatility jumps
### Dimensional Portal System
**Portal Mathematics:**
Dimensional portals visualize regime transitions using category theory principles:
- **Green Portals (◉):** Trending regime detection (appear below price for support)
- **Red Portals (◎):** Mean-reverting regime (appear above price for resistance)
- **Yellow Portals (○):** Random walk regime (neutral positioning)
**Tensor Trail Effects:**
Each portal generates 8 trailing particles showing mathematical momentum:
- **Large Particles (●):** Strong mathematical signal
- **Medium Particles (◦):** Moderate signal strength
- **Small Particles (·):** Weak signal continuation
- **Micro Particles (˙):** Signal dissipation
### Information Flow Streams
**Particle Stream Visualization:**
Transfer entropy creates flowing particle streams indicating information direction:
- **Upward Streams:** Volume leading price (accumulation phases)
- **Downward Streams:** Price leading volume (distribution phases)
- **Stream Density:** Proportional to information flow strength
**15-Particle Evolution:**
Each stream contains 15 particles with progressive sizing and transparency, creating natural flow visualization that makes information transfer immediately apparent.
### Fractal Matrix Grid System
**Multi-Timeframe Fractal Levels:**
The system calculates and displays fractal highs/lows across five Fibonacci periods:
- **8-Period:** Short-term fractal structure
- **13-Period:** Intermediate-term patterns
- **21-Period:** Primary swing levels
- **34-Period:** Major structural levels
- **55-Period:** Long-term fractal boundaries
**Triple-Layer Visualization:**
Each fractal level uses three-layer rendering:
- **Shadow Layer:** Widest, darkest foundation (width 5)
- **Glow Layer:** Medium white core line (width 3)
- **Tensor Layer:** Dotted mathematical overlay (width 1)
**Intelligent Labeling System:**
Smart spacing prevents label overlap using ATR-based minimum distances. Labels include:
- **Fractal Period:** Time-based identification
- **Topological Class:** Mathematical complexity rating (0, I, II, III)
- **Price Level:** Exact fractal price
- **Mahalanobis Distance:** Current mathematical field strength
- **Hurst Exponent:** Current regime classification
- **Anomaly Indicators:** Visual strength representations (○ ◐ ● ⚡)
### Wick Pressure Analysis
**Rejection Level Mathematics:**
The system analyzes candle wick patterns to project future pressure zones:
- **Upper Wick Analysis:** Identifies selling pressure and resistance zones
- **Lower Wick Analysis:** Identifies buying pressure and support zones
- **Pressure Projection:** Extends lines forward based on mathematical probability
**Multi-Layer Glow Effects:**
Wick pressure lines use progressive transparency (1-8 layers) creating natural glow effects that make pressure zones immediately visible without cluttering the chart.
### Enhanced Regime Background
**Dynamic Intensity Mapping:**
Background colors reflect mathematical regime strength:
- **Deep Transparency (98% alpha):** Subtle regime indication
- **Pulse Intensity:** Based on regime strength calculation
- **Color Coding:** Green (trending), Red (mean-reverting), Neutral (random)
**Smoothing Integration:**
Regime changes incorporate 10-bar smoothing to prevent background flicker while maintaining responsiveness to genuine regime shifts.
### Color Scheme System
**Six Professional Themes:**
- **Dark (Default):** Professional trading environment optimization
- **Light:** High ambient light conditions
- **Classic:** Traditional technical analysis appearance
- **Neon:** High-contrast visibility for active trading
- **Neutral:** Minimal distraction focus
- **Bright:** Maximum visibility for complex setups
Each theme maintains mathematical accuracy while optimizing visual clarity for different trading environments and personal preferences.
---
## 📊 INSTITUTIONAL-GRADE DASHBOARD
### Tensor Field Status Section
**Field Strength Display:**
Real-time Mahalanobis distance calculation with dynamic emoji indicators:
- **⚡ (Lightning):** Extreme field strength (>1.5× threshold)
- **● (Solid Circle):** Strong field activity (>1.0× threshold)
- **○ (Open Circle):** Normal field state
**Signal Quality Rating:**
Democratic algorithm assessment:
- **ELITE:** All 3 components aligned (highest probability)
- **STRONG:** 2 components aligned (good probability)
- **GOOD:** 1 component active (moderate probability)
- **WEAK:** No clear component signals
**Threshold and Anomaly Monitoring:**
- **Threshold Display:** Current mathematical threshold setting
- **Anomaly Level (0-100%):** Combined volatility and volume spike measurement
- **>70%:** High anomaly (red warning)
- **30-70%:** Moderate anomaly (orange caution)
- **<30%:** Normal conditions (green confirmation)
### Tensor State Analysis Section
**Mathematical State Classification:**
- **↑ BULL (Tensor State +1):** Trending regime with bullish bias
- **↓ BEAR (Tensor State -1):** Mean-reverting regime with bearish bias
- **◈ SUPER (Tensor State 0):** Random walk regime (neutral)
**Visual State Gauge:**
Five-circle progression showing tensor field polarity:
- **🟢🟢🟢⚪⚪:** Strong bullish mathematical alignment
- **⚪⚪🟡⚪⚪:** Neutral/transitional state
- **⚪⚪🔴🔴🔴:** Strong bearish mathematical alignment
**Trend Direction and Phase Analysis:**
- **📈 BULL / 📉 BEAR / ➡️ NEUTRAL:** Primary trend classification
- **🌪️ CHAOS:** Extreme information flow (>2.0 flow strength)
- **⚡ ACTIVE:** Strong information flow (1.0-2.0 flow strength)
- **😴 CALM:** Low information flow (<1.0 flow strength)
### Trading Signals Section
**Real-Time Signal Status:**
- **🟢 ACTIVE / ⚪ INACTIVE:** Long signal availability
- **🔴 ACTIVE / ⚪ INACTIVE:** Short signal availability
- **Components (X/3):** Active algorithmic components
- **Mode Display:** Current signal generation mode
**Signal Strength Visualization:**
Color-coded component count:
- **Green:** 3/3 components (maximum confidence)
- **Aqua:** 2/3 components (good confidence)
- **Orange:** 1/3 components (moderate confidence)
- **Gray:** 0/3 components (no signals)
### Performance Metrics Section
**Win Rate Monitoring:**
Estimated win rates based on signal quality with emoji indicators:
- **🔥 (Fire):** ≥60% estimated win rate
- **👍 (Thumbs Up):** 45-59% estimated win rate
- **⚠️ (Warning):** <45% estimated win rate
**Mathematical Metrics:**
- **Hurst Exponent:** Real-time fractal dimension (0.000-1.000)
- **Information Flow:** Volume/price leading indicators
- **📊 VOL:** Volume leading price (accumulation/distribution)
- **💰 PRICE:** Price leading volume (momentum/speculation)
- **➖ NONE:** Balanced information flow
- **Volatility Classification:**
- **🔥 HIGH:** Above 1.5× jump threshold
- **📊 NORM:** Normal volatility range
- **😴 LOW:** Below 0.5× jump threshold
### Market Structure Section (Large Dashboard)
**Regime Classification:**
- **📈 TREND:** Hurst >0.6, momentum strategies optimal
- **🔄 REVERT:** Hurst <0.4, contrarian strategies optimal
- **🎲 RANDOM:** Hurst ≈0.5, breakout strategies preferred
**Mathematical Field Analysis:**
- **Dimensions:** Current volatility space complexity (2D-5D)
- **Hawkes λ (Lambda):** Self-exciting jump intensity (0.00-1.00)
- **Jump Status:** 🚨 JUMP (active) / ✅ NORM (normal)
### Settings Summary Section (Large Dashboard)
**Active Configuration Display:**
- **Sensitivity:** Current master sensitivity setting
- **Lookback:** Primary analysis window
- **Theme:** Active color scheme
- **Method:** Hurst calculation method (Classic R/S, Adaptive R/S, DFA)
**Dashboard Sizing Options:**
- **Small:** Essential metrics only (mobile/small screens)
- **Normal:** Balanced information density (standard desktop)
- **Large:** Maximum detail (multi-monitor setups)
**Position Options:**
- **Top Right:** Standard placement (avoids price action)
- **Top Left:** Wide chart optimization
- **Bottom Right:** Recent price focus (scalping)
- **Bottom Left:** Maximum price visibility (swing trading)
---
## 🎯 SIGNAL GENERATION LOGIC
### Multi-Component Convergence System
**Component Signal Architecture:**
The TMAE generates signals through sophisticated component analysis rather than simple threshold crossing:
**Volatility Component:**
- **Jump Detection:** Mahalanobis distance threshold breach
- **Hawkes Intensity:** Self-exciting process activation (>0.2)
- **Multi-dimensional:** Considers all volatility dimensions simultaneously
**Hurst Regime Component:**
- **Trending Markets:** Price above SMA-20 with positive momentum
- **Mean-Reverting Markets:** Price at Bollinger Band extremes
- **Random Markets:** Bollinger squeeze breakouts with directional confirmation
**Transfer Entropy Component:**
- **Volume Leadership:** Information flow from volume to price
- **Volume Spike:** Volume 110%+ above 20-period average
- **Flow Significance:** Above entropy threshold with directional bias
### Democratic Signal Weighting
**Signal Mode Implementation:**
- **Aggressive Mode:** Any single component triggers signal
- **Confluence Mode:** Minimum 2 components must agree
- **Conservative Mode:** All 3 components must align
**Momentum Confirmation:**
All signals require momentum confirmation:
- **Long Signals:** RSI >50 AND price >EMA-9
- **Short Signals:** RSI <50 AND price 0.6):**
- **Increase Sensitivity:** Catch momentum continuation
- **Lower Mean Reversion Threshold:** Avoid counter-trend signals
- **Emphasize Volume Leadership:** Institutional accumulation/distribution
- **Tensor Field Focus:** Use expansion for trend continuation
- **Signal Mode:** Aggressive or Confluence for trend following
**Range-Bound Markets (Hurst <0.4):**
- **Decrease Sensitivity:** Avoid false breakouts
- **Lower Trending Threshold:** Quick regime recognition
- **Focus on Price Leadership:** Retail sentiment extremes
- **Fractal Grid Emphasis:** Support/resistance trading
- **Signal Mode:** Conservative for high-probability reversals
**Volatile Markets (High Jump Frequency):**
- **Increase Hawkes Decay:** Recognize event clustering
- **Higher Jump Threshold:** Avoid noise signals
- **Maximum Dimensions:** Capture full volatility complexity
- **Reduce Position Sizing:** Risk management adaptation
- **Enhanced Visuals:** Maximum information for rapid decisions
**Low Volatility Markets (Low Jump Frequency):**
- **Decrease Jump Threshold:** Capture subtle movements
- **Lower Hawkes Decay:** Treat moves as independent
- **Reduce Dimensions:** Simplify analysis
- **Increase Position Sizing:** Capitalize on compressed volatility
- **Minimal Visuals:** Reduce distraction in quiet markets
---
## 🚀 ADVANCED TRADING STRATEGIES
### The Mathematical Convergence Method
**Entry Protocol:**
1. **Fractal Grid Approach:** Monitor price approaching significant fractal levels
2. **Tensor Field Confirmation:** Verify field expansion supporting direction
3. **Portal Signal:** Wait for dimensional portal appearance
4. **ELITE/STRONG Quality:** Only trade highest quality mathematical signals
5. **Component Consensus:** Confirm 2+ components agree in Confluence mode
**Example Implementation:**
- Price approaching 21-period fractal high
- Tensor field expanding upward (bullish mathematical alignment)
- Green portal appears below price (trending regime confirmation)
- ELITE quality signal with 3/3 components active
- Enter long position with stop below fractal level
**Risk Management:**
- **Stop Placement:** Below/above fractal level that generated signal
- **Position Sizing:** Based on Mahalanobis distance (higher distance = smaller size)
- **Profit Targets:** Next fractal level or tensor field resistance
### The Regime Transition Strategy
**Regime Change Detection:**
1. **Monitor Hurst Exponent:** Watch for persistent moves above/below thresholds
2. **Portal Color Change:** Regime transitions show different portal colors
3. **Background Intensity:** Increasing regime background intensity
4. **Mathematical Confirmation:** Wait for regime confirmation (hysteresis)
**Trading Implementation:**
- **Trending Transitions:** Trade momentum breakouts, follow trend
- **Mean Reversion Transitions:** Trade range boundaries, fade extremes
- **Random Transitions:** Trade breakouts with tight stops
**Advanced Techniques:**
- **Multi-Timeframe:** Confirm regime on higher timeframe
- **Early Entry:** Enter on regime transition rather than confirmation
- **Regime Strength:** Larger positions during strong regime signals
### The Information Flow Momentum Strategy
**Flow Detection Protocol:**
1. **Monitor Transfer Entropy:** Watch for significant information flow shifts
2. **Volume Leadership:** Strong edge when volume leads price
3. **Flow Acceleration:** Increasing flow strength indicates momentum
4. **Directional Confirmation:** Ensure flow aligns with intended trade direction
**Entry Signals:**
- **Volume → Price Flow:** Enter during accumulation/distribution phases
- **Price → Volume Flow:** Enter on momentum confirmation breaks
- **Flow Reversal:** Counter-trend entries when flow reverses
**Optimization:**
- **Scalping:** Use immediate flow detection (2-5 bar lag)
- **Swing Trading:** Use structural flow (10-20 bar lag)
- **Multi-Asset:** Compare flow between correlated assets
### The Tensor Field Expansion Strategy
**Field Mathematics:**
The tensor field expansion indicates mathematical pressure building in market structure:
**Expansion Phases:**
1. **Compression:** Field contracts, volatility decreases
2. **Tension Building:** Mathematical pressure accumulates
3. **Expansion:** Field expands rapidly with directional movement
4. **Resolution:** Field stabilizes at new equilibrium
**Trading Applications:**
- **Compression Trading:** Prepare for breakout during field contraction
- **Expansion Following:** Trade direction of field expansion
- **Reversion Trading:** Fade extreme field expansion
- **Multi-Dimensional:** Consider all field layers for confirmation
### The Hawkes Process Event Strategy
**Self-Exciting Jump Trading:**
Understanding that market shocks cluster and create follow-on opportunities:
**Jump Sequence Analysis:**
1. **Initial Jump:** First volatility jump detected
2. **Clustering Phase:** Hawkes intensity remains elevated
3. **Follow-On Opportunities:** Additional jumps more likely
4. **Decay Period:** Intensity gradually decreases
**Implementation:**
- **Jump Confirmation:** Wait for mathematical jump confirmation
- **Direction Assessment:** Use other components for direction
- **Clustering Trades:** Trade subsequent moves during high intensity
- **Decay Exit:** Exit positions as Hawkes intensity decays
### The Fractal Confluence System
**Multi-Timeframe Fractal Analysis:**
Combining fractal levels across different periods for high-probability zones:
**Confluence Zones:**
- **Double Confluence:** 2 fractal levels align
- **Triple Confluence:** 3+ fractal levels cluster
- **Mathematical Confirmation:** Tensor field supports the level
- **Information Flow:** Transfer entropy confirms direction
**Trading Protocol:**
1. **Identify Confluence:** Find 2+ fractal levels within 1 ATR
2. **Mathematical Support:** Verify tensor field alignment
3. **Signal Quality:** Wait for STRONG or ELITE signal
4. **Risk Definition:** Use fractal level for stop placement
5. **Profit Targeting:** Next major fractal confluence zone
---
## ⚠️ COMPREHENSIVE RISK MANAGEMENT
### Mathematical Position Sizing
**Mahalanobis Distance Integration:**
Position size should inversely correlate with mathematical field strength:
```
Position Size = Base Size × (Threshold / Mahalanobis Distance)
```
**Risk Scaling Matrix:**
- **Low Field Strength (<2.0):** Standard position sizing
- **Moderate Field Strength (2.0-3.0):** 75% position sizing
- **High Field Strength (3.0-4.0):** 50% position sizing
- **Extreme Field Strength (>4.0):** 25% position sizing or no trade
### Signal Quality Risk Adjustment
**Quality-Based Position Sizing:**
- **ELITE Signals:** 100% of planned position size
- **STRONG Signals:** 75% of planned position size
- **GOOD Signals:** 50% of planned position size
- **WEAK Signals:** No position or paper trading only
**Component Agreement Scaling:**
- **3/3 Components:** Full position size
- **2/3 Components:** 75% position size
- **1/3 Components:** 50% position size or skip trade
### Regime-Adaptive Risk Management
**Trending Market Risk:**
- **Wider Stops:** Allow for trend continuation
- **Trend Following:** Trade with regime direction
- **Higher Position Size:** Trend probability advantage
- **Momentum Stops:** Trail stops based on momentum indicators
**Mean-Reverting Market Risk:**
- **Tighter Stops:** Quick exits on trend continuation
- **Contrarian Positioning:** Trade against extremes
- **Smaller Position Size:** Higher reversal failure rate
- **Level-Based Stops:** Use fractal levels for stops
**Random Market Risk:**
- **Breakout Focus:** Trade only clear breakouts
- **Tight Initial Stops:** Quick exit if breakout fails
- **Reduced Frequency:** Skip marginal setups
- **Range-Based Targets:** Profit targets at range boundaries
### Volatility-Adaptive Risk Controls
**High Volatility Periods:**
- **Reduced Position Size:** Account for wider price swings
- **Wider Stops:** Avoid noise-based exits
- **Lower Frequency:** Skip marginal setups
- **Faster Exits:** Take profits more quickly
**Low Volatility Periods:**
- **Standard Position Size:** Normal risk parameters
- **Tighter Stops:** Take advantage of compressed ranges
- **Higher Frequency:** Trade more setups
- **Extended Targets:** Allow for compressed volatility expansion
### Multi-Timeframe Risk Alignment
**Higher Timeframe Trend:**
- **With Trend:** Standard or increased position size
- **Against Trend:** Reduced position size or skip
- **Neutral Trend:** Standard position size with tight management
**Risk Hierarchy:**
1. **Primary:** Current timeframe signal quality
2. **Secondary:** Higher timeframe trend alignment
3. **Tertiary:** Mathematical field strength
4. **Quaternary:** Market regime classification
---
## 📚 EDUCATIONAL VALUE AND MATHEMATICAL CONCEPTS
### Advanced Mathematical Concepts
**Tensor Analysis in Markets:**
The TMAE introduces traders to tensor analysis, a branch of mathematics typically reserved for physics and advanced engineering. Tensors provide a framework for understanding multi-dimensional market relationships that scalar and vector analysis cannot capture.
**Information Theory Applications:**
Transfer entropy implementation teaches traders about information flow in markets, a concept from information theory that quantifies directional causality between variables. This provides intuition about market microstructure and participant behavior.
**Fractal Geometry in Trading:**
The Hurst exponent calculation exposes traders to fractal geometry concepts, helping understand that markets exhibit self-similar patterns across multiple timeframes. This mathematical insight transforms how traders view market structure.
**Stochastic Process Theory:**
The Hawkes process implementation introduces concepts from stochastic process theory, specifically self-exciting point processes. This provides mathematical framework for understanding why market events cluster and exhibit memory effects.
### Learning Progressive Complexity
**Beginner Mathematical Concepts:**
- **Volatility Dimensions:** Understanding multi-dimensional analysis
- **Regime Classification:** Learning market personality types
- **Signal Democracy:** Algorithmic consensus building
- **Visual Mathematics:** Interpreting mathematical concepts visually
**Intermediate Mathematical Applications:**
- **Mahalanobis Distance:** Statistical distance in multi-dimensional space
- **Rescaled Range Analysis:** Fractal dimension measurement
- **Information Entropy:** Quantifying uncertainty and causality
- **Field Theory:** Understanding mathematical fields in market context
**Advanced Mathematical Integration:**
- **Tensor Field Dynamics:** Multi-dimensional market force analysis
- **Stochastic Self-Excitation:** Event clustering and memory effects
- **Categorical Composition:** Mathematical signal combination theory
- **Topological Market Analysis:** Understanding market shape and connectivity
### Practical Mathematical Intuition
**Developing Market Mathematics Intuition:**
The TMAE serves as a bridge between abstract mathematical concepts and practical trading applications. Traders develop intuitive understanding of:
- **How markets exhibit mathematical structure beneath apparent randomness**
- **Why multi-dimensional analysis reveals patterns invisible to single-variable approaches**
- **How information flows through markets in measurable, predictable ways**
- **Why mathematical models provide probabilistic edges rather than certainties**
---
## 🔬 IMPLEMENTATION AND OPTIMIZATION
### Getting Started Protocol
**Phase 1: Observation (Week 1)**
1. **Apply with defaults:** Use standard settings on your primary trading timeframe
2. **Study visual elements:** Learn to interpret tensor fields, portals, and streams
3. **Monitor dashboard:** Observe how metrics change with market conditions
4. **No trading:** Focus entirely on pattern recognition and understanding
**Phase 2: Pattern Recognition (Week 2-3)**
1. **Identify signal patterns:** Note what market conditions produce different signal qualities
2. **Regime correlation:** Observe how Hurst regimes affect signal performance
3. **Visual confirmation:** Learn to read tensor field expansion and portal signals
4. **Component analysis:** Understand which components drive signals in different markets
**Phase 3: Parameter Optimization (Week 4-5)**
1. **Asset-specific tuning:** Adjust parameters for your specific trading instrument
2. **Timeframe optimization:** Fine-tune for your preferred trading timeframe
3. **Sensitivity adjustment:** Balance signal frequency with quality
4. **Visual customization:** Optimize colors and intensity for your trading environment
**Phase 4: Live Implementation (Week 6+)**
1. **Paper trading:** Test signals with hypothetical trades
2. **Small position sizing:** Begin with minimal risk during learning phase
3. **Performance tracking:** Monitor actual vs. expected signal performance
4. **Continuous optimization:** Refine settings based on real performance data
### Performance Monitoring System
**Signal Quality Tracking:**
- **ELITE Signal Win Rate:** Track highest quality signals separately
- **Component Performance:** Monitor which components provide best signals
- **Regime Performance:** Analyze performance across different market regimes
- **Timeframe Analysis:** Compare performance across different session times
**Mathematical Metric Correlation:**
- **Field Strength vs. Performance:** Higher field strength should correlate with better performance
- **Component Agreement vs. Win Rate:** More component agreement should improve win rates
- **Regime Alignment vs. Success:** Trading with mathematical regime should outperform
### Continuous Optimization Process
**Monthly Review Protocol:**
1. **Performance Analysis:** Review win rates, profit factors, and maximum drawdown
2. **Parameter Assessment:** Evaluate if current settings remain optimal
3. **Market Adaptation:** Adjust for changes in market character or volatility
4. **Component Weighting:** Consider if certain components should receive more/less emphasis
**Quarterly Deep Analysis:**
1. **Mathematical Model Validation:** Verify that mathematical relationships remain valid
2. **Regime Distribution:** Analyze time spent in different market regimes
3. **Signal Evolution:** Track how signal characteristics change over time
4. **Correlation Analysis:** Monitor correlations between different mathematical components
---
## 🌟 UNIQUE INNOVATIONS AND CONTRIBUTIONS
### Revolutionary Mathematical Integration
**First-Ever Implementations:**
1. **Multi-Dimensional Volatility Tensor:** First indicator to implement true tensor analysis for market volatility
2. **Real-Time Hawkes Process:** First trading implementation of self-exciting point processes
3. **Transfer Entropy Trading Signals:** First practical application of information theory for trade generation
4. **Democratic Component Voting:** First algorithmic consensus system for signal generation
5. **Fractal-Projected Signal Quality:** First system to predict signal quality at future price levels
### Advanced Visualization Innovations
**Mathematical Visualization Breakthroughs:**
- **Tensor Field Radiation:** Visual representation of mathematical field energy
- **Dimensional Portal System:** Category theory visualization for regime transitions
- **Information Flow Streams:** Real-time visual display of market information transfer
- **Multi-Layer Fractal Grid:** Intelligent spacing and projection system
- **Regime Intensity Mapping:** Dynamic background showing mathematical regime strength
### Practical Trading Innovations
**Trading System Advances:**
- **Quality-Weighted Signal Generation:** Signals rated by mathematical confidence
- **Regime-Adaptive Strategy Selection:** Automatic strategy optimization based on market personality
- **Anti-Spam Signal Protection:** Mathematical prevention of signal clustering
- **Component Performance Tracking:** Real-time monitoring of algorithmic component success
- **Field-Strength Position Sizing:** Mathematical volatility integration for risk management
---
## ⚖️ RESPONSIBLE USAGE AND LIMITATIONS
### Mathematical Model Limitations
**Understanding Model Boundaries:**
While the TMAE implements sophisticated mathematical concepts, traders must understand fundamental limitations:
- **Markets Are Not Purely Mathematical:** Human psychology, news events, and fundamental factors create unpredictable elements
- **Past Performance Limitations:** Mathematical relationships that worked historically may not persist indefinitely
- **Model Risk:** Complex models can fail during unprecedented market conditions
- **Overfitting Potential:** Highly optimized parameters may not generalize to future market conditions
### Proper Implementation Guidelines
**Risk Management Requirements:**
- **Never Risk More Than 2% Per Trade:** Regardless of signal quality
- **Diversification Mandatory:** Don't rely solely on mathematical signals
- **Position Sizing Discipline:** Use mathematical field strength for sizing, not confidence
- **Stop Loss Non-Negotiable:** Every trade must have predefined risk parameters
**Realistic Expectations:**
- **Mathematical Edge, Not Certainty:** The indicator provides probabilistic advantages, not guaranteed outcomes
- **Learning Curve Required:** Complex mathematical concepts require time to master
- **Market Adaptation Necessary:** Parameters must evolve with changing market conditions
- **Continuous Education Important:** Understanding underlying mathematics improves application
### Ethical Trading Considerations
**Market Impact Awareness:**
- **Information Asymmetry:** Advanced mathematical analysis may provide advantages over other market participants
- **Position Size Responsibility:** Large positions based on mathematical signals can impact market structure
- **Sharing Knowledge:** Consider educational contributions to trading community
- **Fair Market Participation:** Use mathematical advantages responsibly within market framework
### Professional Development Path
**Skill Development Sequence:**
1. **Basic Mathematical Literacy:** Understand fundamental concepts before advanced application
2. **Risk Management Mastery:** Develop disciplined risk control before relying on complex signals
3. **Market Psychology Understanding:** Combine mathematical analysis with behavioral market insights
4. **Continuous Learning:** Stay updated on mathematical finance developments and market evolution
---
## 🔮 CONCLUSION
The Tensor Market Analysis Engine represents a quantum leap forward in technical analysis, successfully bridging the gap between advanced pure mathematics and practical trading applications. By integrating multi-dimensional volatility analysis, fractal market theory, and information flow dynamics, the TMAE reveals market structure invisible to conventional analysis while maintaining visual clarity and practical usability.
### Mathematical Innovation Legacy
This indicator establishes new paradigms in technical analysis:
- **Tensor analysis for market volatility understanding**
- **Stochastic self-excitation for event clustering prediction**
- **Information theory for causality-based trade generation**
- **Democratic algorithmic consensus for signal quality enhancement**
- **Mathematical field visualization for intuitive market understanding**
### Practical Trading Revolution
Beyond mathematical innovation, the TMAE transforms practical trading:
- **Quality-rated signals replace binary buy/sell decisions**
- **Regime-adaptive strategies automatically optimize for market personality**
- **Multi-dimensional risk management integrates mathematical volatility measures**
- **Visual mathematical concepts make complex analysis immediately interpretable**
- **Educational value creates lasting improvement in trading understanding**
### Future-Proof Design
The mathematical foundations ensure lasting relevance:
- **Universal mathematical principles transcend market evolution**
- **Multi-dimensional analysis adapts to new market structures**
- **Regime detection automatically adjusts to changing market personalities**
- **Component democracy allows for future algorithmic additions**
- **Mathematical visualization scales with increasing market complexity**
### Commitment to Excellence
The TMAE represents more than an indicator—it embodies a philosophy of bringing rigorous mathematical analysis to trading while maintaining practical utility and visual elegance. Every component, from the multi-dimensional tensor fields to the democratic signal generation, reflects a commitment to mathematical accuracy, trading practicality, and educational value.
### Trading with Mathematical Precision
In an era where markets grow increasingly complex and computational, the TMAE provides traders with mathematical tools previously available only to institutional quantitative research teams. Yet unlike academic mathematical models, the TMAE translates complex concepts into intuitive visual representations and practical trading signals.
By combining the mathematical rigor of tensor analysis, the statistical power of multi-dimensional volatility modeling, and the information-theoretic insights of transfer entropy, traders gain unprecedented insight into market structure and dynamics.
### Final Perspective
Markets, like nature, exhibit profound mathematical beauty beneath apparent chaos. The Tensor Market Analysis Engine serves as a mathematical lens that reveals this hidden order, transforming how traders perceive and interact with market structure.
Through mathematical precision, visual elegance, and practical utility, the TMAE empowers traders to see beyond the noise and trade with the confidence that comes from understanding the mathematical principles governing market behavior.
Trade with mathematical insight. Trade with the power of tensors. Trade with the TMAE.
*"In mathematics, you don't understand things. You just get used to them." - John von Neumann*
*With the TMAE, mathematical market understanding becomes not just possible, but intuitive.*
— Dskyz, Trade with insight. Trade with anticipation.
VWAP/VOL [Extension] | FractalystWhat's the indicator's purpose and functionality?
The VWAP/VOL Extension is designed specifically as a bias identification system for the Quantify Trading Model.
This extension uses volume-weighted average price analysis combined with institutional volume classification to automatically detect market bias without requiring optimization periods that lead to overfitting.
The system provides real-time bias signals (bullish/bearish/neutral) that integrate directly with Quantify's machine learning algorithms, enabling institutional-level backtesting and automated entry/exit identification based on genuine market structure rather than curve-fitted parameters.
How does this extension work with the Quantify Trading Model?
The VWAP/VOL Extension serves as the bias detection engine for Quantify's automated trading system.
Instead of manually selecting bias direction, this extension automatically identifies market bias using:
- Volume-weighted VWAP analysis with three-state detection (bullish/bearish/neutral)
- Institutional volume classification using relative volume thresholds without optimization
- Non-repainting architecture ensuring consistent bias signals for Quantify's machine learning
The extension outputs bias signals that Quantify uses as input through the `input.source()` function, allowing the Trading Model to focus on optimal entry/exit timing while the extension handles bias identification.
Why doesn't this use optimization periods like other indicators?
The VWAP/VOL Extension deliberately avoids optimization periods to prevent overfitting bias that destroys out-of-sample performance. The system uses:
- Fixed mathematical thresholds based on market structure principles rather than optimized parameters
- Relative volume analysis using standard 2.0x/0.5x ratios that work across all market conditions
- VWAP distance calculations based on percentage thresholds without curve-fitting
- Gap enforcement using fixed 5-bar minimums for disciplined bias detection
This approach ensures the bias signals remain robust across different market regimes without the performance degradation typical of over-optimized systems.
Can this extension be used independently for discretionary trading?
No, the VWAP/VOL Extension is specifically engineered to work as a component within the Quantify ecosystem. The extension is designed to:
- Provide bias input for Quantify's machine learning algorithms
- Enable automated backtesting through systematic bias identification
- Support institutional-level analysis when combined with Quantify's ML entry model
Using this extension independently would miss the primary value proposition of systematic entry/exit optimization that Quantify provides.
The extension handles bias detection so Quantify can focus on probability-based trade timing and risk management.
How does this enable institutional-level backtesting?
The extension transforms discretionary bias identification into systematic institutional analysis by:
- Eliminating subjective bias selection through automated VWAP/volume analysis
- Providing consistent historical signals with non-repainting architecture for accurate backtesting
- Integrating with Quantify's algorithms to identify optimal entry patterns based on objective bias states
- Enabling performance analysis across multiple market regimes without optimization bias
This combination allows Quantify to run institutional-grade backtests with consistent bias identification, generating reliable performance statistics and risk metrics that reflect genuine market edge rather than curve-fitted results.
How do I integrate this with the Quantify Trading Model?
Integration enables institutional-grade systematic trading through advanced machine learning and statistical validation:
- Add both VWAP/VOL Extension and Quantify Trading Model to your chart
- Select VWAP/VOL Extension as the bias source using input.source()
- Quantify automatically uses the extension's bias signals for entry/exit analysis
- The built-in machine learning algorithms score optimal entry and exit levels based on trend intensity, volume conviction, and market structure patterns identified by the extension
The extension handles all bias detection complexity while Quantify focuses on optimal trade timing, position sizing, and risk management along with PineConnector automation
What markets and assets does the VWAP/VOL Extension work best on?
The VWAP/VOL Extension performs optimally on markets with consistent, high-volume participation since the system relies on institutional volume analysis for bias detection. Futures markets provide the most reliable performance due to their centralized volume data and continuous institutional participation.
Recommended Futures Markets:
- ES (S&P 500 E-mini) - Over 2 million contracts daily volume, excellent liquidity depth
- NQ (NASDAQ-100 E-mini) - Around 600,000 contracts daily, strong tech sector representation
- YM (Dow Jones E-mini) - Consistent institutional flow and volume patterns
- RTY (Russell 2000 E-mini) - Small-cap exposure with reliable volume data
- GC (Gold Futures) - High volume commodity with institutional participation
- CL (Crude Oil Futures) - Energy sector representation with strong volume consistency
Why Futures Markets Excel:
- Futures markets provide centralized volume reporting, ensuring the extension's volume classification system receives accurate institutional participation data. The standardized contract specifications and continuous trading hours create consistent volume patterns that the extension's algorithms can analyze effectively.
Acceptable Timeframes and Portfolio Integration:
- Any timeframe that can be evaluated within Quantify Trading Model's backtesting engine is acceptable for live trading implementation.
The extension is specifically designed to integrate with Quantify's portfolio management system, allowing multiple strategies across different timeframes and assets to operate simultaneously while maintaining consistent bias identification methodology across the entire automated trading portfolio.
Legal Disclaimers and Risk Acknowledgments
Trading Risk Disclosure
The VWAP/VOL Extension is provided for informational, educational, and systematic bias detection purposes only and should not be construed as financial, investment, or trading advice. The extension provides volume-weighted institutional analysis but does not guarantee profitable outcomes, accurate bias predictions, or positive investment returns.
Trading systems utilizing bias detection algorithms carry substantial risks including but not limited to total capital loss, incorrect bias identification, market regime changes, and adverse conditions that may invalidate volume-based analysis. The extension's performance depends on accurate volume data, TradingView infrastructure stability, and proper integration with Quantify Trading Model, any of which may experience data errors, technical failures, or service interruptions that could affect bias detection accuracy.
System Dependency Acknowledgment
The extension requires continuous operation of multiple interconnected systems: TradingView charts and real-time data feeds, accurate volume reporting from exchanges, Quantify Trading Model integration, and stable platform connectivity. Any interruption or malfunction in these systems may result in incorrect bias signals, missed transitions, or unexpected analytical behavior.
Users acknowledge that neither Fractalyst nor the creator has control over third-party data providers, exchange volume reporting accuracy, or TradingView platform stability, and cannot guarantee data accuracy, service availability, or analytical performance. Market microstructure changes, volume reporting delays, exchange outages, and technical factors may significantly affect bias detection accuracy compared to theoretical or backtested performance.
Intellectual Property Protection
The VWAP/VOL Extension, including all proprietary algorithms, volume classification methodologies, three-state bias detection systems, and integration protocols, constitutes the exclusive intellectual property of Fractalyst. Unauthorized reproduction, reverse engineering, modification, or commercial exploitation of these proprietary technologies is strictly prohibited and may result in legal action.
Liability Limitation
By utilizing this extension, users acknowledge and agree that they assume full responsibility and liability for all trading decisions, financial outcomes, and potential losses resulting from reliance on the extension's bias detection signals. Fractalyst shall not be liable for any unfavorable outcomes, financial losses, missed opportunities, or damages resulting from the development, use, malfunction, or performance of this extension.
Past performance of bias detection accuracy, volume classification effectiveness, or integration with Quantify Trading Model does not guarantee future results. Trading outcomes depend on numerous factors including market regime changes, volume pattern evolution, institutional behavior shifts, and proper system configuration, all of which are beyond the control of Fractalyst.
User Responsibility Statement
Users are solely responsible for understanding the risks associated with algorithmic bias detection, properly configuring system parameters, maintaining appropriate risk management protocols, and regularly monitoring extension performance. Users should thoroughly validate the extension's bias signals through comprehensive backtesting before live implementation and should never base trading decisions solely on automated bias detection.
This extension is designed to provide systematic institutional flow analysis but does not replace the need for proper market understanding, risk management discipline, and comprehensive trading methodology. Users should maintain active oversight of bias detection accuracy and be prepared to implement manual overrides when market conditions invalidate volume-based analysis assumptions.
Terms of Service Acceptance
Continued use of the VWAP/VOL Extension constitutes acceptance of these terms, acknowledgment of associated risks, and agreement to respect all intellectual property protections. Users assume full responsibility for compliance with applicable laws and regulations governing automated trading system usage in their jurisdiction.
Trend Lines by CR86The basic construction algorithm:
1. The baseline trend line through the closing prices:
First, the best fit line (linear regression) is calculated for the closing prices for a given period.
The least squares method is used to find the optimal slope and intersection point.
2. Search for key deviation points:
For each bar in the period, the deviation of the maximum and minimum from the regression baseline is calculated.
The point with the maximum deviation of the maximum upward from the regression line (for the resistance line) is located
The point with the maximum deviation of the minimum is located down from the regression line (for the support line)
3. Optimizing the slope of the lines:
Lines with an optimized slope are drawn through the found key points.
The algorithm selects the slope so that the line best "bends around" the corresponding extremes (maxima for resistance, minima for support)
Numerical optimization is used to check the validity of the trend line.
4. The principle of validity:
For the support line: all points must be above or at the line level (with a tolerance of 1e-5)
For the resistance line: all points must be below or at the line level (with a tolerance of 1e-5)
Key Features
Adaptability: the lines automatically adjust to the actual price extremes
Mathematical precision: a rigorous mathematical approach with optimization is used
Logarithmic scaling: optional for dealing with highly volatile assets
The basic construction algorithm
1. The baseline trend line through the closing prices:
First, the best fit line (linear regression) is calculated for the closing prices for a given period.
The least squares method is used to find the optimal slope and intersection point.
2. Search for key deviation points:
For each bar in the period, the deviation of the maximum and minimum from the regression baseline is calculated.
The point with the maximum deviation of the maximum upward from the regression line (for the resistance line) is located
The point with the maximum deviation of the minimum is located down from the regression line (for the support line)
3. Optimizing the slope of the lines:
Lines with an optimized slope are drawn through the found key points.
The algorithm selects the slope so that the line best "bends around" the corresponding extremes (maxima for resistance, minima for support)
Numerical optimization is used to check the validity of the trend line.
4. The principle of validity:
For the support line: all points must be above or at the line level (with a tolerance of 1e-5)
For the resistance line: all points must be below or at the line level (with a tolerance of 1e-5)
Key Features
Adaptability: the lines automatically adjust to the actual price extremes
Mathematical precision: a rigorous mathematical approach with optimization is used
Logarithmic scaling: optional for dealing with highly volatile assets
***********************************************************************************************
Основной алгоритм построения:
1. Базовая линия тренда через цены закрытия:
Сначала вычисляется линия наилучшего соответствия (линейная регрессия) для цен закрытия за заданный период
Используется метод наименьших квадратов для нахождения оптимального наклона и точки пересечения
2. Поиск ключевых точек отклонения:
Для каждого бара в периоде вычисляется отклонение максимума и минимума от базовой линии регрессии
Находится точка с максимальным отклонением максимума вверх от линии регрессии (для линии сопротивления)
Находится точка с максимальным отклонением минимума вниз от линии регрессии (для линии поддержки)
3. Оптимизация наклона линий:
Через найденные ключевые точки проводятся линии с оптимизированным наклоном
Алгоритм подбирает такой наклон, чтобы линия наилучшим образом "огибала" соответствующие экстремумы (максимумы для сопротивления, минимумы для поддержки)
Используется численная оптимизация с проверкой валидности трендовой линии
4. Принцип валидности:
Для линии поддержки: все точки должны быть выше или на уровне линии (с допуском 1e-5)
Для линии сопротивления: все точки должны быть ниже или на уровне линии (с допуском 1e-5)
Ключевые особенности
Адаптивность: линии автоматически подстраиваются под фактические экстремумы цен
Математическая точность: используется строгий математический подход с оптимизацией
Логарифмическое масштабирование: опционально для работы с сильно волатильными активами
