Auto Harmonic Pattern - Screener [Trendoscope]At Trendoscope, we take pride in offering a wide range of indicators on Harmonic Patterns, including both free and premium options. While we have successfully developed various advanced tools, we recognize that creating a Harmonic Pattern screener is an audacious endeavor that few have ventured into.
Creating a harmonic pattern screener presents a formidable challenge. The intricate nature of the algorithm, coupled with the limitations of cloud-based processing and platform memory, makes it exceedingly difficult to implement the screener functionality without encountering runtime errors.
Today marks a historic achievement as we overcome numerous challenges to unveil our groundbreaking harmonic pattern-based screener. This significant leap signifies our commitment to innovation in the field.
Without further delay, let's dive right into the new Auto Harmonic Pattern - Screener algorithm
🎲 Features Overview
🎯 Primary Functionality
We prefer not to categorize this as a traditional indicator, as it goes beyond that scope. Instead, it's a unique amalgamation of both a screener and an indicator, designed to achieve primarily two essential functions.
Firstly, it efficiently scans multiple tickers, up to 20, for harmonic pattern formations and presents them on a user-friendly dashboard
Secondly, it provides harmonic pattern drawings on the chart, but only if the current chart ticker is part of the screener and exhibits a harmonic pattern formation.
🎯 Secondary Features
In addition to its primary functionalities, our revolutionary algorithm offers an array of secondary features that cater to traders' diverse needs
Users have the privilege of accessing enhanced settings, providing limitless customization options for the zigzag and pattern detection algorithm
The platform empowers traders to effortlessly customize stop entry target ratios, facilitating automatic calculations and display of suggestions
The freedom to personalize the visualization and display of patterns and dashboard ensures a seamless and intuitive user experience
And finally, the algorithm leaves no stone unturned, keeping traders well-informed through timely alerts on every bar, highlighting tickers exhibiting Harmonic Pattern formations.
🎯 Limitations
Our innovative screener harnesses the power of the recursive zigzag algorithm to deliver efficient and accurate harmonic pattern detections. While the deep search algorithm, present in our other Harmonic Pattern algorithms, offers unparalleled precision, its resource-intensive nature makes it unsuitable for simultaneous scanning of 20 tickers. By focusing on the recursive zigzag approach, we strike the perfect balance between performance and functionality, ensuring seamless scanning across multiple tickers without compromising on accuracy. This strategic decision allows us to deliver a powerful and reliable screener that meets the diverse needs of traders and empowers them with real-time harmonic pattern insights.
🎲 Chart Components
Upon loading the indicator and configuring your tickers, our user-friendly interface offers two key components seamlessly integrated into the chart:
A color-coded screener dashboard : The dashboard presents a clear visualization of tickers with bullish and bearish harmonic patterns. This intuitive display allows you to quickly identify potential trading opportunities based on pattern formations.
Dynamic pattern display : As you interact with the chart, our algorithm dynamically highlights possible harmonic patterns based on the latest zigzag pivots. Please note that patterns may not always be visible on the chart, especially in cases where higher-level zigzags take time to form pivots. However, rest assured that our sophisticated algorithm ensures real-time updates, providing you with accurate and timely harmonic pattern insights.
🎯 Screener Dashboard
In our screener dashboard, you will find a wealth of information at your fingertips:
Bullish patterns : Tickers exhibiting bullish harmonic patterns are prominently highlighted with a refreshing green background
Bearish patterns : Similarly, tickers featuring bearish harmonic patterns stand out with a striking red background
Dual patterns : Tickers displaying both bullish and bearish patterns are cleverly highlighted in a captivating purple background, providing a comprehensive view of the harmonic pattern landscape.
Tickers without current patterns : Tickers lacking any current patterns are elegantly displayed with a silver background. These tickers do not trigger tooltips, streamlining your focus on actionable pattern-related data.
🎲 Settings in Detail
🎯 Tickers
Our platform currently allows users to select up to 20 tickers for the harmonic pattern screener. We understand the importance of flexibility and scalability, and while we are excited to accommodate more tickers in the future, our present focus is to ensure optimal performance within the CPU and memory limitations. Rest assured, we are continuously working on enhancing our capabilities to provide you with an even more comprehensive experience. Stay tuned for updates as we strive to meet your evolving needs.
🎯 Zigzag and Harmonic Pattern
In this section, we present a range of essential settings that play a pivotal role in the calculation of the zigzag and the scanning of patterns. These parameters share similarities with other premium indicators associated with Harmonic patterns. These settings serve as building blocks for our advanced algorithms' suite.
This include
Zigzag length and depth settings for calculation of the multi level recursive zigzag
Pattern scanning settings to filter patterns based on preferences of category, pattern name, accuracy of calculation, and other considerations.
User preference of pattern trading ratios that are used for calculating entry, stop and target prices.
🎯 Screener Dashboard and Alerts
In this section, we introduce the parameters that define the format and content of alerts and the screener dashboard, offering you maximum flexibility in customizing their display. These settings encompass the following key aspects:
Screener dashboard position, layout and size that influence the display of screener dashboard.
List of parameters that can be shown on dashboard tooltips as well as on alerts.
Format of alert and tooltip data
🎯 Pattern Display
These are the settings related to pattern display on the chart and to limit calculation to last n bars
Will soon make video tutorials on this soon.
Buscar en scripts para "algo"
Recursive Micro Zigzag🎲 Overview
Zigzag is basic building block for any pattern recognition algorithm. This indicator is a research-oriented tool that combines the concepts of Micro Zigzag and Recursive Zigzag to facilitate a comprehensive analysis of price patterns. This indicator focuses on deriving zigzag on multiple levels in more efficient and enhanced manner in order to support enhanced pattern recognition.
The Recursive Micro Zigzag Indicator utilises the Micro Zigzag as the foundation and applies the Recursive Zigzag technique to derive higher-level zigzags. By integrating these techniques, this indicator enables researchers to analyse price patterns at multiple levels and gain a deeper understanding of market behaviour.
🎲 Concept:
Micro Zigzag Base : The indicator utilises the Micro Zigzag concept to capture detailed price movements within each candle. It allows for the visualisation of the sequential price action within the candle, aiding in pattern recognition at a micro level.
Basic implementation of micro zigzag can be found in this link - Micro-Zigzag
Recursive Zigzag Expansion : Building upon the Micro Zigzag base, the indicator applies the Recursive Zigzag concept to derive higher-level zigzags. Through recursive analysis of the Micro Zigzag's pivots, the indicator uncovers intricate patterns and trends that may not be evident in single-level zigzags.
Earlier implementations of recursive zigzag can be found here:
Recursive Zigzag
Recursive Zigzag - Trendoscope
And the libraries
rZigzag
ZigzagMethods
The major differences in this implementation are
Micro Zigzag Base - Earlier implementation made use of standard zigzag as base whereas this implementation uses Micro Zigzag as base
Not cap on Pivot depth - Earlier implementation was limited by the depth of level 0 zigzag. In this implementation, we are trying to build the recursive algorithm progressively so that there is no cap on the depth of level 0 zigzag. But, if we go for higher levels, there is chance of program timing out due to pine limitations.
These algorithms are useful in automatically spotting patterns on the chart including Harmonic Patterns, Chart Patterns, Elliot Waves and many more.
Channel Based Zigzag [HeWhoMustNotBeNamed]🎲 Concept
Zigzag is built based on the price and number of offset bars. But, in this experiment, we build zigzag based on different bands such as Bollinger Band, Keltner Channel and Donchian Channel. The process is simple:
🎯 Derive bands based on input parameters
🎯 High of a bar is considered as pivot high only if the high price is above or equal to upper band.
🎯 Similarly low of a bar is considered as pivot low only if low price is below or equal to lower band.
🎯 Adding the pivot high/low follows same logic as that of regular zigzag where pivot high is always followed by pivot low and vice versa.
🎯 If the new pivot added is of same direction as that of last pivot, then both pivots are compared with each other and only the extreme one is kept. (Highest in case of pivot high and lowest in case of pivot low)
🎯 If a bar has both pivot high and pivot low - pivot with same direction as previous pivot is added to the list first before adding the pivot with opposite direction.
🎲 Use Cases
Can be used for pattern recognition algorithms instead of standard zigzag. This will help derive patterns which are relative to bands and channels.
Example: John Bollinger explains how to manually scan double tap using Bollinger Bands in this video: www.youtube.com This modified zigzag base can be used to achieve the same using algorithmic means.
🎲 Settings
Few simple configurations which will let you select the band properties. Notice that there is no zigzag length here. All the calculations depend on the bands.
With bands display, indicator looks something like this
Note that pivots do not always represent highest/lowest prices. They represent highest/lowest price relative to bands.
As mentioned many times, application of zigzag is not for buying at lower price and selling at higher price. It is mainly used for pattern recognition either manually or via algorithms. Lets build new Harmonic, Chart patterns, Trend Lines using the new zigzag?
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
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.
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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
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.
ICT SIlver Bullet Trading Windows UK times🎯 Purpose of the Indicator
It’s designed to highlight key ICT “macro” and “micro” windows of opportunity, i.e., time ranges where liquidity grabs and algorithmic setups are most likely to occur. The ICT Silver Bullet concept is built on the idea that institutions execute in recurring intraday windows, and these often produce high-probability setups.
🕰️ Windows
London Macro Window
10:00 – 11:00 UK time
This aligns with a major liquidity window after the London equities open settles and London + EU traders reposition.
You’re looking for setups like liquidity sweeps, MSS (market structure shift), and FVG entries here.
New York Macro Window
15:00 – 16:00 UK time (10:00 – 11:00 NY time)
This is right after the NY equities open, a key ICT window for volatility and liquidity grabs.
Power Hour
Usually 20:00 – 21:00 UK time (3pm–4pm NY time), the last trading hour of NY equities.
ICT often refers to this as another manipulation window where setups can form before the daily close.
🔍 What the Indicator Does
Draws session boxes or shading: so you can visually see the London/NY/Power Hour windows directly on your chart.
Macro vs. Micro time frames:
Macro windows → The ones you set (London & NY) are the major daily algo execution windows.
Micro windows → Within those boxes, ICT expects smaller intraday setups (like a Silver Bullet entry from a sweep + FVG).
Guides your trade selection: it tells you when not to hunt trades everywhere, but instead to wait for price action confirmation inside those boxes.
🧩 How This Fits ICT Silver Bullet Trading
The ICT Silver Bullet strategy says:
Wait for one of the macro windows (London or NY).
Look for liquidity sweep → market structure shift → FVG.
Enter with defined risk inside that hour.
This indicator essentially does step 1 for you: it makes those high-probability windows visually obvious, so you don’t waste time trading random hours where algos aren’t active.
Harmonic Patterns + Fib [CRT Trader]Overview
The Harmonic Patterns Fibonacci indicator is an advanced technical analysis tool designed to automatically detect and visualize Fibonacci-based harmonic patterns on financial charts. This indicator helps traders identify high-probability reversal zones and potential entry/exit points based on precise mathematical relationships.
Supported Patterns
5-Point Patterns (X-A-B-C-D Structure)
Gartley Pattern: The most common harmonic pattern with reliable reversal signals
AB/XA = 0.618, BC/AB = 0.618, CD/BC = 1.272, AD/XA = 0.786
Butterfly Pattern: Strong reversal pattern indicating potential trend changes
AB/XA = 0.786, BC/AB = 0.618, CD/BC = 1.618, AD/XA = 1.270
Bat Pattern: Medium-term reversal pattern with high accuracy
AB/XA = 0.382, BC/AB = 0.886, CD/BC = 1.618, AD/XA = 0.886
Crab Pattern: Aggressive reversal pattern with extended D point
AB/XA = 0.618, BC/AB = 0.886, CD/BC = 2.240, AD/XA = 1.618
Shark Pattern: Trend continuation or reversal pattern
AB/XA = 0.618, BC/AB = 1.130, CD/BC = 1.618, AD/XA = 0.886
4-Point Pattern (A-B-C-D Structure)
ABCD Pattern: Basic harmonic structure forming the foundation of all patterns
BC/AB = 0.382-0.886, CD/BC = 1.130-2.618
Key Features
Fibonacci Validation
Each pattern is validated against precise Fibonacci ratios with customizable tolerance
Mathematical accuracy ensures reliable pattern recognition
Eliminates false signals through strict ratio requirements
Performance Optimization
Pivot Detection: Automatically identifies significant highs and lows
Scan Frequency Control: Adjustable scanning intervals to optimize performance
Early Exit Algorithms: Efficient computation to reduce processing load
Pattern Limit: Control maximum number of patterns displayed
Visual Elements
Pattern Lines: Clear visualization of pattern structure with colored lines
Fill Areas: Highlighted zones between pattern legs
Point Labels: X, A, B, C, D markers for easy identification
Fibonacci Levels: Optional Fibonacci retracement/extension levels
Bullish/Bearish Colors: Green for bullish, red for bearish patterns
Customizable Settings
Pattern Selection: Enable/disable specific pattern types
Tolerance Adjustment: Fine-tune pattern recognition sensitivity (5-30%)
Color Customization: Personalize visual appearance
Information Table: Optional statistics display
Trading Applications
Entry Signals
Reversal Zones: Identify high-probability reversal areas at pattern completion
Confluence Trading: Combine with other technical indicators for confirmation
Risk Management: Use pattern structure to define stop-loss levels
Market Analysis
Support/Resistance: Pattern points often act as future S/R levels
Price Targets: Fibonacci extensions provide potential profit targets
Market Structure: Understand underlying market geometry and rhythm
Strategy Integration
Swing Trading: Ideal for medium-term position entries
Position Trading: Long-term trend reversal identification
Day Trading: Intraday reversal patterns on lower timeframes
How to Use
Add to Chart: Apply the indicator to any timeframe and instrument
Configure Settings: Adjust tolerance, colors, and pattern types as needed
Wait for Completion: Patterns are valid only when D point is formed
Confirm with Volume: Look for volume confirmation at pattern completion
Set Stop Loss: Place stops beyond X point for 5-point patterns, or A point for ABCD
Target Levels: Use Fibonacci extensions for profit targets
Important Notes
Pattern Completion: Wait for full pattern formation before taking action
Market Context: Consider overall market trend and conditions
Risk Management: Always use appropriate position sizing and stops
Backtesting: Test the indicator on historical data before live trading
Multiple Timeframes: Analyze patterns across different timeframes for confirmation
Technical Requirements
Lookback Period: Adjustable pivot detection sensitivity
Depth Setting: Controls how far back the algorithm searches for patterns
Memory Efficient: Optimized for real-time performance without lag
This indicator is suitable for all experience levels, from beginners learning harmonic patterns to advanced traders seeking automated pattern recognition. The combination of mathematical precision and visual clarity makes it an essential tool for harmonic trading strategies.
Auto-Fit Growth Trendline# **Theoretical Algorithmic Principles of the Auto-Fit Growth Trendline (AFGT)**
## **🎯 What Does This Algorithm Do?**
The Auto-Fit Growth Trendline is an advanced technical analysis system that **automates the identification of long-term growth trends** and **projects future price levels** based on historical cyclical patterns.
### **Primary Functionality:**
- **Automatically detects** the most significant lows in regular periods (monthly, quarterly, semi-annually, annually)
- **Constructs a dynamic trendline** that connects these historical lows
- **Projects the trend into the future** with high mathematical precision
- **Generates Fibonacci bands** that act as dynamic support and resistance levels
- **Automatically adapts** to different timeframes and market conditions
### **Strategic Purpose:**
The algorithm is designed to identify **fundamental value zones** where price has historically found support, enabling traders to:
- Identify optimal entry points for long positions
- Establish realistic price targets based on mathematical projections
- Recognize dynamic support and resistance levels
- Anticipate long-term price movements
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## **🧮 Core Mathematical Foundations**
### **Adaptive Temporal Segmentation Theory**
The algorithm is based on **dynamic temporal partition theory**, where time is divided into mathematically coherent uniform intervals. It uses modular transformations to create bijective mappings between continuous timestamps and discrete periods, ensuring each temporal point belongs uniquely to a specific period.
**What does this achieve?** It allows the algorithm to automatically identify natural market cycles (annual, quarterly, etc.) without manual intervention, adapting to the inherent periodicity of each asset.
The temporal mapping function implements a **discrete affine transformation** that normalizes different frequencies (monthly, quarterly, semi-annual, annual) to a space of unique identifiers, enabling consistent cross-temporal comparative analysis.
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## **📊 Local Extrema Detection Theory**
### **Multi-Point Retrospective Validation Principle**
Local minima detection is founded on **relative extrema theory with sliding window**. Instead of using a simple minimum finder, it implements a cross-validation system that examines the persistence of the extremum across multiple historical periods.
**What problem does this solve?** It eliminates false minima caused by temporal volatility, identifying only those points that represent true historical support levels with statistical significance.
This approach is based on the **statistical confirmation principle**, where a minimum is only considered valid if it maintains its extremum condition during a defined observation period, significantly reducing false positives caused by transitory volatility.
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## **🔬 Robust Interpolation Theory with Outlier Control**
### **Contextual Adaptive Interpolation Model**
The mathematical core uses **piecewise linear interpolation with adaptive outlier correction**. The key innovation lies in implementing a **contextual anomaly detector** that identifies not only absolute extreme values, but relative deviations to the local context.
**Why is this important?** Financial markets contain extreme events (crashes, bubbles) that can distort projections. This system identifies and appropriately weights them without completely eliminating them, preserving directional information while attenuating distortions.
### **Implicit Bayesian Smoothing Algorithm**
When an outlier is detected (deviation >300% of local average), the system applies a **simplified Kalman filter** that combines the current observation with a local trend estimation, using a weight factor that preserves directional information while attenuating extreme fluctuations.
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## **📈 Stabilized Extrapolation Theory**
### **Exponential Growth Model with Dampening**
Extrapolation is based on a **modified exponential growth model with progressive dampening**. It uses multiple historical points to calculate local growth ratios, implements statistical filtering to eliminate outliers, and applies a dampening factor that increases with extrapolation distance.
**What advantage does this offer?** Long-term projections in finance tend to be exponentially unrealistic. This system maintains short-to-medium term accuracy while converging toward realistic long-term projections, avoiding the typical "exponential explosions" of other methods.
### **Asymptotic Convergence Principle**
For long-term projections, the algorithm implements **controlled asymptotic convergence**, where growth ratios gradually converge toward pre-established limits, avoiding unrealistic exponential projections while preserving short-to-medium term accuracy.
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## **🌟 Dynamic Fibonacci Projection Theory**
### **Continuous Proportional Scaling Model**
Fibonacci bands are constructed through **uniform proportional scaling** of the base curve, where each level represents a linear transformation of the main curve by a constant factor derived from the Fibonacci sequence.
**What is its practical utility?** It provides dynamic resistance and support levels that move with the trend, offering price targets and profit-taking points that automatically adapt to market evolution.
### **Topological Preservation Principle**
The system maintains the **topological properties** of the base curve in all Fibonacci projections, ensuring that spatial and temporal relationships are consistently preserved across all resistance/support levels.
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## **⚡ Adaptive Computational Optimization**
### **Multi-Scale Resolution Theory**
It implements **automatic multi-resolution analysis** where data granularity is dynamically adjusted according to the analysis timeframe. It uses the **adaptive Nyquist principle** to optimize the signal-to-noise ratio according to the temporal observation scale.
**Why is this necessary?** Different timeframes require different levels of detail. A 1-minute chart needs more granularity than a monthly one. This system automatically optimizes resolution for each case.
### **Adaptive Density Algorithm**
Calculation point density is optimized through **adaptive sampling theory**, where calculation frequency is adjusted according to local trend curvature and analysis timeframe, balancing visual precision with computational efficiency.
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## **🛡️ Robustness and Fault Tolerance**
### **Graceful Degradation Theory**
The system implements **multi-level graceful degradation**, where under error conditions or insufficient data, the algorithm progressively falls back to simpler but reliable methods, maintaining basic functionality under any condition.
**What does this guarantee?** That the indicator functions consistently even with incomplete data, new symbols with limited history, or extreme market conditions.
### **State Consistency Principle**
It uses **mathematical invariants** to guarantee that the algorithm's internal state remains consistent between executions, implementing consistency checks that validate data structure integrity in each iteration.
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## **🔍 Key Theoretical Innovations**
### **A. Contextual vs. Absolute Outlier Detection**
It revolutionizes traditional outlier detection by considering not only the absolute magnitude of deviations, but their relative significance within the local context of the time series.
**Practical impact:** It distinguishes between legitimate market movements and technical anomalies, preserving important events like breakouts while filtering noise.
### **B. Extrapolation with Weighted Historical Memory**
It implements a memory system that weights different historical periods according to their relevance for current prediction, creating projections more adaptable to market regime changes.
**Competitive advantage:** It automatically adapts to fundamental changes in asset dynamics without requiring manual recalibration.
### **C. Automatic Multi-Timeframe Adaptation**
It develops an automatic temporal resolution selection system that optimizes signal extraction according to the intrinsic characteristics of the analysis timeframe.
**Result:** A single indicator that functions optimally from 1-minute to monthly charts without manual adjustments.
### **D. Intelligent Asymptotic Convergence**
It introduces the concept of controlled asymptotic convergence in financial extrapolations, where long-term projections converge toward realistic limits based on historical fundamentals.
**Added value:** Mathematically sound long-term projections that avoid the unrealistic extremes typical of other extrapolation methods.
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## **📊 Complexity and Scalability Theory**
### **Optimized Linear Complexity Model**
The algorithm maintains **linear computational complexity** O(n) in the number of historical data points, guaranteeing scalability for extensive time series analysis without performance degradation.
### **Temporal Locality Principle**
It implements **temporal locality**, where the most expensive operations are concentrated in the most relevant temporal regions (recent periods and near projections), optimizing computational resource usage.
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## **🎯 Convergence and Stability**
### **Probabilistic Convergence Theory**
The system guarantees **probabilistic convergence** toward the real underlying trend, where projection accuracy increases with the amount of available historical data, following **law of large numbers** principles.
**Practical implication:** The more history an asset has, the more accurate the algorithm's projections will be.
### **Guaranteed Numerical Stability**
It implements **intrinsic numerical stability** through the use of robust floating-point arithmetic and validations that prevent overflow, underflow, and numerical error propagation.
**Result:** Reliable operation even with extreme-priced assets (from satoshis to thousand-dollar stocks).
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## **💼 Comprehensive Practical Application**
**The algorithm functions as a "financial GPS"** that:
1. **Identifies where we've been** (significant historical lows)
2. **Determines where we are** (current position relative to the trend)
3. **Projects where we're going** (future trend with specific price levels)
4. **Provides alternative routes** (Fibonacci bands as alternative targets)
This theoretical framework represents an innovative synthesis of time series analysis, approximation theory, and computational optimization, specifically designed for long-term financial trend analysis with robust and mathematically grounded projections.
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.
