FATL, SATL, RFTL, & RSTL Digital Signal Filter Smoother [Loxx]FATL, SATL, RFTL, & RSTL Digital Signal Filter (DSP) Smoother is is a baseline indicator with DSP processed source inputs
What are digital indicators: distinctions from standard tools, types of filters.
To date, dozens of technical analysis indicators have been developed: trend instruments, oscillators, etc. Most of them use the method of averaging historical data, which is considered crude. But there is another group of tools - digital indicators developed on the basis of mathematical methods of spectral analysis. Their formula allows the trader to filter price noise accurately and exclude occasional surges, making the forecast more effective in comparison with conventional indicators. In this review, you will learn about their distinctions, advantages, types of digital indicators and examples of strategies based on them.
Two non-standard strategies based on digital indicators
Basic technical analysis indicators built into most platforms are based on mathematical formulas. These formulas are a reflection of market behavior in past periods. In other words, these indicators are built based on patterns that were discovered as a result of statistical analysis, which allows one to predict further trend movement to some extent. But there is also a group of indicators called digital indicators. They are developed using mathematical analysis and are an algorithmic spectral system called ATCF (Adaptive Trend & Cycles Following). In this article, I will tell you more about the components of this system, describe the differences between digital and regular indicators, and give examples of 2 strategies with indicator templates.
ATCF - Market Spectrum Analysis Method
There is a theory according to which the market is chaotic and unpredictable, i.e. it cannot be accurately analyzed. After all, no one can tell how traders will react to certain news, or whether some large investor will want to play against the market like George Soros did with the Bank of England. But there is another theory: many general market trends are logical, and have a rationale, causes and effects. The economy is undulating, which means it can be described by mathematical methods.
Digital indicators are defined as a group of algorithms for assessing the market situation, which are based exclusively on mathematical methods. They differ from standard indicators by the form of analysis display. They display certain values: price, smoothed price, volumes. Many standard indicators are built on the basis of filtering the minute significant price fluctuations with the help of moving averages and their variations. But we can hardly call the MA a good filter, because digital indicators that use spectral filters make it possible to do a more accurate calculation.
Simply put, digital indicators are technical analysis tools in which spectral filters are used to filter out price noise instead of moving averages.
The display of traditional indicators is lines, areas, and channels. Digital indicators can be displayed both in the form of lines and in digital form (a set of numbers in columns, any data in a text field, etc.). The digital display of the data is more like an additional source of statistics; for trading, a standard visual linear chart view is used.
All digital models belong to the category of spectral analysis of the market situation. In conventional technical indicators, price indications are averaged over a fixed period of time, which gives a rather rough result. The use of spectral analysis allows us to increase trading efficiency due to the fact that digital indicators use a statistical data set of past periods, which is converted into a “frequency” of the market (period of fluctuations).
Fourier theory provides the following spectral ranging of the trend duration:
low frequency range (0-4) - a reflection of a long trend of 2 months or more
medium frequency range (5-40) - the trend lasts 10-60 days, thus it is referred to as a correction
high frequency range (41-130) - price noise that lasts for several days
The ATCF algorithm is built on the basis of spectral analysis and includes a set of indicators created using digital filters. Its consists of indicators and filters:
FATL: Built on the basis of a low-frequency digital trend filter
SATL: Built on the basis of a low-frequency digital trend filter of a different order
RFTL: High frequency trend line
RSTL: Low frequency trend line
Inclucded:
4 DSP filters
Bar coloring
Keltner channels with variety ranges and smoothing functions
Bollinger bands
40 Smoothing filters
33 souce types
Variable channels
"algo"に関するスクリプトを検索
Ehlers Autocorrelation Periodogram [Loxx]Ehlers Autocorrelation Periodogram contains two versions of Ehlers Autocorrelation Periodogram Algorithm. This indicator is meant to supplement adaptive cycle indicators that myself and others have published on Trading View, will continue to publish on Trading View. These are fast-loading, low-overhead, streamlined, exact replicas of Ehlers' work without any other adjustments or inputs.
Versions:
- 2013, Cycle Analytics for Traders Advanced Technical Trading Concepts by John F. Ehlers
- 2016, TASC September, "Measuring Market Cycles"
Description
The Ehlers Autocorrelation study is a technical indicator used in the calculation of John F. Ehlers’s Autocorrelation Periodogram. Its main purpose is to eliminate noise from the price data, reduce effects of the “spectral dilation” phenomenon, and reveal dominant cycle periods. The spectral dilation has been discussed in several studies by John F. Ehlers; for more information on this, refer to sources in the "Further Reading" section.
As the first step, Autocorrelation uses Mr. Ehlers’s previous installment, Ehlers Roofing Filter, in order to enhance the signal-to-noise ratio and neutralize the spectral dilation. This filter is based on aerospace analog filters and when applied to market data, it attempts to only pass spectral components whose periods are between 10 and 48 bars.
Autocorrelation is then applied to the filtered data: as its name implies, this function correlates the data with itself a certain period back. As with other correlation techniques, the value of +1 would signify the perfect correlation and -1, the perfect anti-correlation.
Using values of Autocorrelation in Thermo Mode may help you reveal the cycle periods within which the data is best correlated (or anti-correlated) with itself. Those periods are displayed in the extreme colors (orange) while areas of intermediate colors mark periods of less useful cycles.
What is an adaptive cycle, and what is the Autocorrelation Periodogram Algorithm?
From his Ehlers' book mentioned above, page 135:
"Adaptive filters can have several different meanings. For example, Perry Kaufman’s adaptive moving average ( KAMA ) and Tushar Chande’s variable index dynamic average ( VIDYA ) adapt to changes in volatility . By definition, these filters are reactive to price changes, and therefore they close the barn door after the horse is gone.The adaptive filters discussed in this chapter are the familiar Stochastic , relative strength index ( RSI ), commodity channel index ( CCI ), and band-pass filter.The key parameter in each case is the look-back period used to calculate the indicator.This look-back period is commonly a fixed value. However, since the measured cycle period is changing, as we have seen in previous chapters, it makes sense to adapt these indicators to the measured cycle period. When tradable market cycles are observed, they tend to persist for a short while.Therefore, by tuning the indicators to the measure cycle period they are optimized for current conditions and can even have predictive characteristics.
The dominant cycle period is measured using the Autocorrelation Periodogram Algorithm. That dominant cycle dynamically sets the look-back period for the indicators. I employ my own streamlined computation for the indicators that provide smoother and easier to interpret outputs than traditional methods. Further, the indicator codes have been modified to remove the effects of spectral dilation.This basically creates a whole new set of indicators for your trading arsenal."
How to use this indicator
The point of the Ehlers Autocorrelation Periodogram Algorithm is to dynamically set a period between a minimum and a maximum period length. While I leave the exact explanation of the mechanic to Dr. Ehlers’s book, for all practical intents and purposes, in my opinion, the punchline of this method is to attempt to remove a massive source of overfitting from trading system creation–namely specifying a look-back period. SMA of 50 days? 100 days? 200 days? Well, theoretically, this algorithm takes that possibility of overfitting out of your hands. Simply, specify an upper and lower bound for your look-back, and it does the rest. In addition, this indicator tells you when its best to use adaptive cycle inputs for your other indicators.
Usage Example 1
Let's say you're using "Adaptive Qualitative Quantitative Estimation (QQE) ". This indicator has the option of adaptive cycle inputs. When the "Ehlers Autocorrelation Periodogram " shows a period of high correlation that adaptive cycle inputs work best during that period.
Usage Example 2
Check where the dominant cycle line lines, grab that output number and inject it into your other standard indicators for the length input.
Mikolaj Zakrzowski - Adjusted Mayer MultipleAuthor - Publication: Mikołaj Zakrzowski, Marek Zatwarnicki
Author - Algorithm: Mikołaj Zakrzowski
Author - Code: Marek Zatwarnicki, Derek Gruening
Inspired by: Mayer Multiple by Trace Mayer
Category: Technical Analysis
Type: Indicator
Timeframe: 1D Only
Index: INDEX:BTCUSD Only
About:
According to Willy Woo Mayer Multiple is "A way to gauge the current price of Bitcoin against its long range historical price movements (200 day moving average), the Mayer Multiple highlights when Bitcoin is overbought or oversold in the context of longer time frames".
My friend, Mikolaj Zakrzowski, decided to modify and adjust this indicator so that it could be normalized. This procedure allows for easier interpretation, and clear signals of the end of the ups and downs of a given Bitcoin cycle.
How to use:
BUY - Buy some Bitcoin , when label on last candle shows "Buy".
SELL- Sell some Bitcoin , when label on last candle shows "Sell".
Formula:
- Mayer Multiple - Close / ta. sma (close, 200)
- Formula for normalization is an intellectual property of Mikolaj Zakrzowski.
Overfitting: The presented algorithm is characterized by log regresion determined as of 01/01/2022. Tests with historical data show that the algorithm is very likely to work equally well the following years.
Disclaimer: Past good results do not guarantee future trading success. Please use the algorithm with caution and support it with your knowledge. Published algorithm decisions are not financial advice.
Market Maker Volatility Diameter V2 by Hawkeye Charting***German Description below***
Hey guys,
we are proud to publish the Market Maker Volatility Diameter V2!
Our goal with this indicator is to provide an All-in-one indicator, combining some special tools of open source scripts as well as some of our own developments and the algorithm of our MMVD V1.
We will create a video series very soon, where we will explain each aspect of the tool, your options and of course our trading strategies with this indicator.
You have the following technical tools and information combined in this indicator, which can each be shown and hidden:
- Psychological Ranges (Weekly Opening High/ Low for Crypto and Forex)
- Market Maker Sessions (Sydney, Asia, London, NY)
- Trade Cloud (algorithm developed by Hawkeye Charting)
- Fibonacci Cloud (inspired by watching paid offerings, coded by Hawkeye Charting)
- Display Moving Averages (select the visualization of up to 6 moving averages. You can change for each of these 6 MA's the type and the length.)
- Display Major Trend Cloud (developed by Hawkeye Charting)
- PVSRA Candle Colors
- Vector Candle Zones
- Pivots
- Pivot Fibonacci Levels (developed by Hawkeye Charting)
- OHLC-Levels
- Average Daily, Weekly, Monthly Ranges
- Volume Profile for Intraday Trading for up to 8 days.
We hope especially for people, who can not afford the Pro offering from TradingView, to give access to a good indicator, which includes many tools and alerts.
Our goal is to lower the barriers for new entrants and of course to protect people, to pay for indicators, which are completely insane priced.
Only, that you get an idea: the whole indicator has only cost me about 100 h of work (for a single person!), and I'm no Pine script expert, so don't get fooled when someone offers you insane amounts for an indicator...
There is no holy grail. Each indicator works only with calculations on previous data.
We appreciate seeing that you guys like this work, so please leave a like and a follow and share this indicator.
*****German Description*****
Hey Leute,
wir sind stolz, unsere 2. Version des Market Maker Volatility Diameter zu veröffentlichen!
Unser Ziel ist es, mit diesem Indikator eine All-In-One Lösung anzubieten, welche einige nicht ganz geläufige Tools sowie unsere eigenen Entwicklungen und natürlich den Algorithmus des MMVD V1 vereinen.
Wir werden in naher Zukunft eine Video Serie veröffentlichen, in welcher wir Stück für Stück jeden Aspekt des Werkzeugs, die Einstellungsmöglichkeiten sowie unsere Trading Strategien mit diesem Indikator erklären werden.
Ihr habt die folgenden technischen Werkzeuge und Informationen in diesem Indikator vereint, welche jede einzeln an- oder abgewählt und eingestellt werden können:
- Psychological Ranges (Weekly Opening High/ Low für Krypto and Forex)
- Market Maker Sessions (Sydney, Asia, London, NY)
- Trade Cloud (Algorithmus von Hawkeye Charting entwickelt)
- Fibonacci Cloud (inspiriert von der Beobachtung eines Paid-Indikators, Code geschrieben von Hawkeye Charting)
- Moving Averages (Ihr könnt die Darstellung von bis zu 6 Gleitenden Durchschnitten auswählen und für jeden dieser Durchschnitte den Typ und die Länge ändern.)
- Display Major Trend Cloud (entwickelt von Hawkeye Charting)
- PVSRA Candle Colors
- Vector Candle Zones
- Pivots
- Pivot Fibonacci Levels (entwickelt von Hawkeye Charting)
- OHLC-Levels
- Average Daily, Weekly, Monthly Ranges
- Volume Profile für Intraday Trading, Darstellungsmöglichkeit für 3-8 Tage
Wir hoffen, dass wir speziell für Leute, die sich nicht das PRO-Abo aufwärts von TradingView leisten können, Zugang zu einem guten Indikator, welche viele Werkzeuge und Alarme vereint gewährleisten zu können.
Unser Ziel ist es, die Eintrittsbarrieren für neue Marktteilnehmer senken und natürlich Leute vor wahnsinnigen Paid-Angeboten beschützen zu können.
Nur, damit ihr eine Vorstellung bekommt: den gesamten Indikator hat mich lediglich 100h Arbeit gekostet (für eine einzelne Person!), und ich bin kein Pine Script Experte. Also lasst euch bitte nicht verar******, wenn euch Paid-Angebote erreichen, mit dem Versprechen, den "zu 95% erfolgreich" Indikator erwerben zu können.
Es gibt keinen heiligen Gral, jeder Indikator arbeitet nur mit Berechnung von Vergangenheitswerten.
Wir würden uns riesig freuen, wenn euch diese Arbeit gefällt und ihr uns Likes und Follows hinterlasst und ihr diesen Indikator teilt.
Trend Daddy Bitcoin Strategy - Optimized For Automated TradingOverview:
This algorithm is the end result of years of trading both bitcoin and traditional markets. Over the years I've learned that trying to catch a top or bottom of a move is nearly impossible and results in a lot of pain. Instead, I've learned the money is made somewhere in the middle trading the momentum. That is how I came up with the Trend Daddy algo. Combining multiple different indicators, this script is able to pick up on large trending moves while at the same time avoiding sideways chop.
Signals:
The signals this algorithm produces are simple long and short signals. Keep in mind, this script will NOT attempt to short the top of the market nor will it attempt to catch knives. The signals that are thrown out attempt to play the momentum of the market, not reversals. Always wait for a candle to confirm in order to enter a trade.
Time Frame:
Bitcoin markets are extremely volatile and it is not recommended using this script on any time frame lower than 4 hours, with daily or above being the recommended time frame.
Backtesting:
I have run hundreds of backtests on this algorithm but also keep in mind that backtests do not show future results. I try to be as realistic in my backtests and do not account for any compounding. In the published backtest I ran an account size of $10k USD, only trading $10k USD per trade with no compounding. With this extremely conservative strategy, from day one of Bitcoin being listed on an exchange, this strategy would return roughly 1535% or $15,351 over the past 9 years.
Disclaimer:
Trading in any markets, especially cryptocurrencies involves taking on a great magnitude of risk. Do not trade any money that you are not willing to lose. Furthermore, past performance does not guarantee future results. The best trading device is your mind. Hopefully, this algorithm is the next best thing.
Machine Learning: kNN-based StrategykNN-based Strategy (FX and Crypto)
Description:
This strategy uses a classic machine learning algorithm - k Nearest Neighbours (kNN) - to let you find a prediction for the next (tomorrow's, next month's, etc.) market move. Being an unsupervised machine learning algorithm, kNN is one of the most simple learning algorithms.
To do a prediction of the next market move, the kNN algorithm uses the historic data, collected in 3 arrays - feature1, feature2 and directions, - and finds the k-nearest
neighbours of the current indicator(s) values.
The two dimensional kNN algorithm just has a look on what has happened in the past when the two indicators had a similar level. It then looks at the k nearest neighbours,
sees their state and thus classifies the current point.
The kNN algorithm offers a framework to test all kinds of indicators easily to see if they have got any *predictive value*. One can easily add cog, wpr and others.
Note: TradingViews's playback feature helps to see this strategy in action.
Warning: Signals ARE repainting.
Style tags: Trend Following, Trend Analysis
Asset class: Equities, Futures, ETFs, Currencies and Commodities
Dataset: FX Minutes/Hours+++/Days
PowerBot Binary Backtest FrameworkHello Traders,
This is the backtest framework for testing the Powerbot algorithm before activating alerts which can be used for precise Trading.
Powerbot can be used across any timeframe and across any expiration based on the performance
This backtest comes with some features to help traders make a decision on the following:
When using the indicator itself.
1. We use our proprietary algorithm - "Powerbot binary algorithm script", which is Public but can only be accessed based on request. If you would like to use the algorithm please ensure you have tested different assets and varying expiration for your trades through the backtest - if you don't know how to do that please contact us by sending a message.
EXPLORE YOUR OPTIONS FOR TRADING THROUGH VARIED ITERATION.
2. You can choose any expiration time by changing the expiration time period from the 'settings' button, this will display new results. example; on a 5 minutes chart timeframe, 6 bars would be 30 minutes, which means 5 minutes times 6, which is 30 and minutes because your timeframe is set to minutes. Another example is that on a 1-hour timeframe, 12 bars would be 12 hours, given 1 * 12 is 12hours, because your timeframe is set to hours.
3. You can choose the trading session you want, please note that we have included the three most active sessions - ASIAN, EU/UK, & US Session, by default, the scripts checks for performance on 24/7, which means it does not omit trades outside of the trading session. The Tradingview time is in UTC (or GMT -4). The best times to trade are during sessions most active times.
This backtesting indicator is free to add to the chart if you would like to use the algorithm during your trading session you need to contact us. After which you can use the algorithm for as long as you want.
Please note that no signal can work in all timeframe across all markets that is why backtesting to search for algorithms with at least 50% performance ratio is excellent for trading. All you need is to diversify alerts across to assets or more to rake in profits.
If you require assistance in understanding what session would work best, you can send us a message to work through the process together.
Thank you for you support. This script is free to use to see potential of the indicator itself.
We are NOT allowed to advertise any script on sale based on tradingview house rules.
Wishing you all the best.
Relative Strength(RSMK) + Perks - Markos KatsanosIf you are desperately looking for a novel RSI, this isn't that. This is another lesser known novel species of indicator. Hot off the press, in multiple stunning color schemes, I present my version of "Relative Strength (RSMK)" employing PSv4.0, originally formulated by Markos Katsanos for TASC - March 2020 Traders Tips. This indicator is used to compare performance of an asset to a market index of your choosing. I included the S&P 500 index along side the Dow Jones and the NASDAQ indices selectively by an input() in "Settings". You may comparatively analyze other global market indices by adapting the code, if you are skilled enough in Pine to do so.
With this contribution to the Tradingview community, also included is MY twin algorithmic formulation of "Comparative Relative Strength" as a supplementary companion indicator. They are eerily similar, so I decided to include it. You may easily disable my algorithm within the indicator "Settings". I do hope you may find both of them useful. Configurations are displayed above in multiple scenarios that should be suitable for most traders.
As always, I have included advanced Pine programming techniques that conform to proper "Pine Etiquette". For those of you who are newcomers to Pine Script, this script may also help you understand advanced programming techniques in Pine and how they may be utilized in a most effective manner. Utilizing the "Power of Pine", I included the maximum amount of features I could surmise in an ultra small yet powerful package, being less than a 60 line implementation at initial release.
Unfortunately, there are so many Pine mastery techniques included, I don't have time to write about all of them. I will have to let you discover them for yourself, excluding the following Pine "Tricks and Tips" described next. Of notable mention with this release, I have "overwritten" the Pine built-in function ema(). You may overwrite other built-in functions too. If you weren't aware of this Pine capability, you now know! Just heed caution when doing so to ensure your replacement algorithms are 100% sound. My ema() will also accept a floating point number for the period having ultimate adjustability. Yep, you heard all of that properly. Pine is becoming more impressive than `impressive` was originally thought of...
Features List Includes:
Dark Background - Easily disabled in indicator Settings->Style for "Light" charts or with Pine commenting
AND much, much more... You have the source!
The comments section below is solely just for commenting and other remarks, ideas, compliments, etc... regarding only this indicator, not others. 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. As always, "Like" it if you simply just like it with a proper thumbs up, and also return to my scripts list occasionally for additional postings. Have a profitable future everyone!
Trade Manager/Pnl and Risk-Reward Panel (Plug&Play)Hello traders
The Trade Manager Standalone is finally back and with many more built-in features.
I. 💎 SCRIPTS ACCESS AND TRIALS 💎
1. No TRIAL is available for that script. Available only with one-time payment on my website .
2. My website URL is in this script signature at the very bottom (you'll have to scroll down a bit and going past the long description) and in my profile status available here : Daveatt
Due to the new scripts publishing house rules, I won't mention the URL here directly. As I value my partnership with TradingView very much, I prefer showing you the way for finding them :)
3. Many video tutorials explaining clearly how all our indicators work are available on your website > guides section.
4. You may also contact me directly for more information
II. 🔎 What is a Trade Manager?🔎
2.1 Concept
Standalone Trade Manager compatible with any indicator.
Once connected, whenever you'll update your Algorithm Builders or your indicator, the Trade Manager Stop-loss, take-profit levels, and analytics get updated automatically. #bold #statement #but #actually #true
2.2 How hard is it to update your indicator?
We'll send to our customers, a comprehensive and easy tutorial, to make any indicator compatible.
I guarantee you, it should take no more than 2 minutes per indicator. We made it easy, fun, and awesome. #bolder #statement
III. The amazing benefits of our🔌&🕹️ (Plug&Play) system
Hope you're ready to be impressed. Because, what I'm about to introduce, is my best-seller feature - and available across many of my indicators.
In TradingView, there is a feature called "Indicator on Indicator" meaning you can use an external indicator as a data source for another indicator.
I'm using that feature to connect any external indicator to our Trade Manager (Plug & Play) - hence the plug and play name. Please don't make it a plug and pray :) it's supposed to help you out, not to stress you even more
Let's assume you want to connect your RSI divergence to your Trade Manager.
I mentioned an RSI divergence but you may connect any oscillator (MACD, On balance volume, stochastic RSI, True Strenght index, and many more..) or non-oscillator (divergence, trendline break, higher highs/lower lows, candlesticks pattern, price action, harmonic patterns, ...) indicators.
THE SKY IS (or more likely your imagination) is the limit :)
Fear no more. The Plug&Play technology allows you to connect it and use it the backtest calculations.
This is not magic ✨, neither is sorcery, but certainly is way beyond the most awesome thing I've ever developed on TradingView (even across all brokers I know). #bold #statement #level #9000
TradingView is the best trading platform by far and I'm very grateful to offer my indicators on their website.
To connect your external indicator to ours, we're using a native TradingView feature, which is not available for all users.
It depends on your TradingView subscription plan ( More info here )
If you intend to use our Algorithm Plug&Play indicator, and/or our Backtest Plug&Play suites, then you must upgrade your TradingView account to enjoy those features.
We value our relationship with our customers seriously, and that's why we're warning you that a compatible TradingView account type is required - at least PRO+ or PREMIUM to add more than 1 Plug&Play indicator per account.
We go in-depth on our website why the Plug&Play is an untapped opportunity for many traders out there - URL available on my profile status and signature
IV. 🧰 Features 🧰
4.1 Stop-Loss Management
For what's following, let's assume that 2 is the stop-loss value you inserted in the indicator, and the Algorithm Builder gives a BUY signal.
This is NOT a recommendation at all, only an example to explain how this feature works.
- %Trailing: The Stop-Loss starts 2% away from the entry price - and will move up (because we're on a BUY trade as per our example) every time your trade will gain 2% profit
- Percentage: The Stop-Loss stays static 2% away from the entry price. There is no trailing here
- TP Trailing: This is a very awesome feature. The stop-loss is set 2% away when the trades start.
When the TP1 is hit, the stop-loss will be moved to the Entry price (also called breakeven).
When the TP2 is hit, the SL is moved to the previous TP1 position
- Fixed: Set the Stop-Loss at a fixed position (value should be in currency/units)
4.2 Take Profits Management
You can manage up to 2 take profit levels defined as a percentage or price value.
The expected input is in percentage value (for instance, setting the % target of TP1 to 2% will set the TP1 level 2% away from the entry price
4.3 Built-in Trade Manager
This is very likely the most loved utility script that we shared on TradingView.
It's included in your Algorithm Builder - Single Trend+, and will certainly help you immensely to analyze your charts and your trades.
We made sure that all the graphical elements on the chart will be updated in real-time whenever our user change anything on the indicator configuration.
You'll also be able to change the Trade Manager labels positions as you wish :)
4.4 Built-in Risk-to-Reward Panel
The good stuff doesn't stop here.
You'll notice that this sometimes green (when in a LONG), sometimes red (when in a SHORT) panel at the right of your chart.
It displays for the selected trading algorithmic (see 2.3.2 above), a ton of useful real-time analytics.
- Entry Price: the price when the Algorithm Builder will give a signal.
- The Trade PnL in percentage.
- Entry Stop Loss: Distance (in currency/units) between the selected stop-loss algorithm (percent, trailing, TP trailing, etc.) and the entry price.
- Entry TP1: Distance (in currency/units) between the entry price and the first take profit
- Entry TP2: Distance (in currency/units) between the entry price and the second take profit
- Risk/Reward TP1: Using the Stop-loss distance at entry, and Take Profit 1 at entry to compute the risk-to-reward ratio.
- Risk/Reward TP2: Using the Stop-loss distance at entry, and Take Profit 2 at entry to compute the risk-to-reward ratio.
For more details, please check the guides section of my website. Links are in my signature and profile status.
4.5 Built-in PnL real-time calculations
YES!!!! you read it correctly
The panel displays the risk-to-reward ratios but also the PnL (Profit and Loss in percentage value) of the current and last trade
V. 🔔 Alerts 🔔
We enabled the alerts on the:
1. Stop-Loss
2. Take Profit 1
3. Take Profit 2
VI. 🤖 Compatible with trading bots? 🤖
I'm very aware of all existing solutions out there allowing us to capture the TradingView alerts (Instabot, ProfitView, ...) and forwarding them to the brokers to automatize your trading.
You'll find a more detailed answer on our website.
If you have any doubt or question, please hit me up directly or ask in the comments section of this script.
I'll never claim I have the best trading methodology or the best indicators.
You only will judge and I'll appreciate all the questions and feedback you're sending my way.
They help me a ton to develop indicators based on all the requests I received.
Kind regards,
Dave
MACD, backtest 2015+ only, cut in half and doubledThis is only a slight modification to the existing "MACD Strategy" strategy plugin!
found the default MACD strategy to be lacking, although impressive for its simplicity. I added "year>2014" to the IF buy/sell conditions so it will only backtest from 2015 and beyond ** .
I also had a problem with the standard MACD trading late, per se. To that end I modified the inputs for fast/slow/signal to double. Example: my defaults are 10, 21, 10 so I put 20, 42, 20 in. This has the effect of making a 30min interval the same as 1 hour at 10,21,10. So if you want to backtest at 4hr, you would set your time interval to 2hr on the main chart. This is a handy way to make shorter time periods more useful even regardless of strategy/testing, since you can view 15min with alot less noise but a better response.
Used on BTCCNY OKcoin, with the chart set at 45 min (so really 90min in the strategy) this gave me a percent profitable of 42% and a profit factor of 1.998 on 189 trades.
Personally, I like to set the length/signals to 30,63,30. Meaning you need to triple the time, it allows for much better use of shorter time periods and the backtests are remarkably profitable. (i.e. 15min chart view = 45min on script, 30min= 1.5hr on script)
** If you want more specific time periods you need to try plugging in different bar values: replace "year" with "n" and "2014" with "5500". The bars are based on unix time I believe so you will need to play around with the number for n, with n being the numbers of bars.
Adaptive Kalman Trend Filter (Zeiierman)█ Overview
The Adaptive Kalman Trend Filter indicator is an advanced trend-following tool designed to help traders accurately identify market trends. Utilizing the Kalman Filter—a statistical algorithm rooted in control theory and signal processing—this indicator adapts to changing market conditions, smoothing price data to filter out noise. By focusing on state vector-based calculations, it dynamically adjusts trend and range measurements, making it an excellent tool for both trend-following and range-based trading strategies. The indicator's adaptive nature is enhanced by options for volatility adjustment and three unique Kalman filter models, each tailored for different market conditions.
█ How It Works
The Kalman Filter works by maintaining a model of the market state through matrices that represent state variables, error covariances, and measurement uncertainties. Here’s how each component plays a role in calculating the indicator’s trend:
⚪ State Vector (X): The state vector is a two-dimensional array where each element represents a market property. The first element is an estimate of the true price, while the second element represents the rate of change or trend in that price. This vector is updated iteratively with each new price, maintaining an ongoing estimate of both price and trend direction.
⚪ Covariance Matrix (P): The covariance matrix represents the uncertainty in the state vector’s estimates. It continuously adapts to changing conditions, representing how much error we expect in our trend and price estimates. Lower covariance values suggest higher confidence in the estimates, while higher values indicate less certainty, often due to market volatility.
⚪ Process Noise (Q): The process noise matrix (Q) is used to account for uncertainties in price movements that aren’t explained by historical trends. By allowing some degree of randomness, it enables the Kalman Filter to remain responsive to new data without overreacting to minor fluctuations. This noise is particularly useful in smoothing out price movements in highly volatile markets.
⚪ Measurement Noise (R): Measurement noise is an external input representing the reliability of each new price observation. In this indicator, it is represented by the setting Measurement Noise and determines how much weight is given to each new price point. Higher measurement noise makes the indicator less reactive to recent prices, smoothing the trend further.
⚪ Update Equations:
Prediction: The state vector and covariance matrix are first projected forward using a state transition matrix (F), which includes market estimates based on past data. This gives a “predicted” state before the next actual price is known.
Kalman Gain Calculation: The Kalman gain is calculated by comparing the predicted state with the actual price, balancing between the covariance matrix and measurement noise. This gain determines how much of the observed price should influence the state vector.
Correction: The observed price is then compared to the predicted price, and the state vector is updated using this Kalman gain. The updated covariance matrix reflects any adjustment in uncertainty based on the latest data.
█ Three Kalman Filter Models
Standard Model: Assumes that market fluctuations follow a linear progression without external adjustments. It is best suited for stable markets.
Volume Adjusted Model: Adjusts the filter sensitivity based on trading volume. High-volume periods result in stronger trends, making this model suitable for volume-driven assets.
Parkinson Adjusted Model: Uses the Parkinson estimator, accounting for volatility through high-low price ranges, making it effective in markets with high intraday fluctuations.
These models enable traders to choose a filter that aligns with current market conditions, enhancing trend accuracy and responsiveness.
█ Trend Strength
The Trend Strength provides a visual representation of the current trend's strength as a percentage based on oscillator calculations from the Kalman filter. This table divides trend strength into color-coded segments, helping traders quickly assess whether the market is strongly trending or nearing a reversal point. A high trend strength percentage indicates a robust trend, while a low percentage suggests weakening momentum or consolidation.
█ Trend Range
The Trend Range section evaluates the market's directional movement over a specified lookback period, highlighting areas where price oscillations indicate a trend. This calculation assesses how prices vary within the range, offering an indication of trend stability or the likelihood of reversals. By adjusting the trend range setting, traders can fine-tune the indicator’s sensitivity to longer or shorter trends.
█ Sigma Bands
The Sigma Bands in the indicator are based on statistical standard deviations (sigma levels), which act as dynamic support and resistance zones. These bands are calculated using the Kalman Filter's trend estimates and adjusted for volatility (if enabled). The bands expand and contract according to market volatility, providing a unique visualization of price boundaries. In high-volatility periods, the bands widen, offering better protection against false breakouts. During low volatility, the bands narrow, closely tracking price movements. Traders can use these sigma bands to spot potential entry and exit points, aiming for reversion trades or trend continuation setups.
Trend Based
Volatility Based
█ How to Use
Trend Following:
When the Kalman Filter is green, it signals a bullish trend, and when it’s red, it indicates a bearish trend. The Sigma Cloud provides additional insights into trend strength. In a strong bullish trend, the cloud remains below the Kalman Filter line, while in a strong bearish trend, the cloud stays above it. Expansion and contraction of the Sigma Cloud indicate market momentum changes. Rapid expansion suggests an impulsive move, which could either signal the continuation of the trend or be an early sign of a possible trend reversal.
Mean Reversion: Watch for prices touching the upper or lower sigma bands, which often act as dynamic support and resistance.
Volatility Breakouts: Enable volatility-adjusted sigma bands. During high volatility, watch for price movements that extend beyond the bands as potential breakout signals.
Trend Continuation: When the Kalman Filter line aligns with a high trend strength, it signals a continuation in that direction.
█ Settings
Measurement Noise: Adjusts how sensitive the indicator is to price changes. Higher values smooth out fluctuations but delay reaction, while lower values increase sensitivity to short-term changes.
Kalman Filter Model: Choose between the standard, volume-adjusted, and Parkinson-adjusted models based on market conditions.
Band Sigma: Sets the standard deviation used for calculating the sigma bands, directly affecting the width of the dynamic support and resistance.
Volatility Adjusted Bands: Enables bands to dynamically adapt to volatility, increasing their effectiveness in fluctuating markets.
Trend Strength: Defines the lookback period for trend strength calculation. Shorter periods result in more responsive trend strength readings, while longer periods smooth out the calculation.
Trend Range: Specifies the lookback period for the trend range, affecting the assessment of trend stability over time.
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Disclaimer
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!
ML Supply Zone Strategy - ETHOverview
The ML (Machine Learning) Supply Zone Strategy for ETH is an advanced trading tool designed for traders looking to capitalize market movements in Ethereum (ETH). This strategy employs sophisticated machine learning techniques to identify supply zones by analyzing historical price data and calculating the statistical likelihood of price movements in specific directions. Our proprietary Python scripts perform monthly analyses to update these probabilities, ensuring the strategy adapts to evolving market conditions.
Key Features
Machine Learning-Derived Supply Zones-
Data-Driven Identification: Utilizes ML algorithms to process extensive historical price data of ETH, pinpointing supply zones where significant price reversals or continuations are statistically probable.
Probability Assessment: Breaks down the percentage chance of the price moving up or down upon reaching these zones, based on patterns recognized by the ML (machine learning) models.
Monthly Updates: Refreshes supply zones and probabilities every month through new data analysis, keeping the strategy current with market trends.
Proprietary Python Script Integration-
Advanced Algorithms: Our custom Python scripts employ clustering algorithms (e.g., K-means, DBSCAN) and statistical analysis to detect meaningful patterns in ETH price action.
Seamless Strategy Integration: The outputs from the Python analysis are directly incorporated into the trading script, providing actionable insights without the need for external tools.
Comprehensive Risk Management-
Precise Entry and Exit Points: Based on ML-derived supply zones and associated probabilities, the strategy sets exact entry and exit points to optimize trade outcomes.
Risk-to-Reward Optimization: Implements stop-loss and take-profit levels designed to achieve a favorable risk-to-reward ratio, typically aiming for 1:3 (0.7% SL / 2.1% TP).
Versatility Across Timeframes: While the strategy works well across various timeframes, it performs particularly effectively on the 1-minute timeframe, capturing short-term market movements.
How the Strategy Works
Data Collection and ML Analysis-
Historical Price Data Processing: The proprietary Python scripts analyze large datasets of historical ETH price movements, focusing on identifying zones where supply exceeds demand, leading to potential price drops.
Feature Extraction: ML models extract features such as price levels, volume spikes, and volatility measures that influence supply zone formations.
Probability Calculation-
Statistical Modeling: Uses statistical techniques to calculate the probability of price moving in a particular direction after reaching a supply zone.
Pattern Recognition: Identifies recurring patterns and correlations that have historically led to significant price movements.
Integration into Trading Script-
Supply Zone Mapping: The identified supply zones and their associated probabilities are embedded into the trading script as key levels.
Signal Generation:
Entry Signals: Triggered when the current price approaches a supply zone with a high probability of a downward move.
Choppiness Index (CI) and Volume Filtering-
Trade Quality Enhancement: To prevent excessive trading on determined supply zones, the strategy incorporates the Choppiness Index and volume filters.
Market Condition Assessment: The CI helps determine whether the market is trending or ranging, ensuring trades are taken in optimal conditions.
Liquidity Confirmation: Volume filters ensure that trades are only executed when there is sufficient market activity, improving execution and reliability.
Setup and Configuration
Access the Strategy: Add the ML Supply Zone Probability Strategy for ETH to your TradingView chart.
Select the Correct Chart: Apply it to the Pionex ETH/USDT Perpetual chart for optimal performance.
Select Timeframe: For best results, use the 1-minute timeframe (although almost all timeframes work).
Customize Settings: Adjust parameters such as risk tolerance, position sizing, and probability thresholds to suit your trading preferences.
Backtesting Recommendations
Sufficient Trade Sample Size: To generate around 100+ trades in backtesting, it is recommended to extend the backtesting period to at least three months.
Statistical Significance: A larger number of trades provides a more reliable assessment of the strategy's performance, enhancing confidence in its effectiveness.
MeanRevert Matrix [StabTrading]MeanRevert Matrix is a sophisticated trading tool designed to detect when prices significantly deviate from their historical averages, signalling potential market trends and reversals.
Leveraging complex algorithms that incorporate human emotions and mean reversion theory, this indicator is the first stage in a comprehensive system for identifying market entry points. Its versatility allows it to be applied across all charts and timeframes, providing traders with clear visual cues for trend analysis and decision-making.
This indicator is purposefully straightforward, allowing traders to observe how the different algorithms work in confluence. The MeanRevert Matrix can be customized to fit individual trading styles, particularly in terms of aggressiveness, making it adaptable to various market conditions. Working in tandem with the FloWave Oscillator, it offers an additional layer of confluence, ensuring that trading signals are more reliable.
💡 Features
Reversal Zones - These zones are integral to the MeanRevert Matrix, highlighting areas where trader emotions and money flow suggest potential longer-term reversals. The lighter shaded zones indicate early-stage reversals, while darker shades signal stronger reversal potential. This feature is designed to help traders anticipate market shifts and prepare for them accordingly.
Localized Mean Reversion Signals - These signals are triggered when the price deviates significantly from the mean, unaffected by longer-term price movements. This localized algorithm helps traders focus on short-term market fluctuations without being influenced by broader trends.
Yellow Signals - These signals identify isolated overbought or oversold conditions. While they often indicate reversal points, they can also signal the beginning of accelerated buying or selling, giving traders early warning of potential market shifts.
Trading Style Customization - The MeanRevert Matrix allows traders to tailor their strategy by adjusting the indicator’s aggressiveness. A more aggressive setting will produce more frequent reversal signals, offering flexibility based on the trader’s risk tolerance and market outlook.
Noise Eliminator - This feature helps traders filter out market noise or manipulation by increasing the noise value. By removing unwanted or misleading signals, it ensures that traders are acting on the most reliable data.
📈 Implementing the System
Step 1 - Begin by observing the localized blue trend to identify reversal points below the mean. Green or red signals within this trend indicate that the price remains within the current market parameters, suggesting that a reversal may occur more quickly. Yellow signals, however, indicate that the trend is likely to continue, so it’s advisable to wait for clearer reversal zones to develop. To avoid misleading signals, consider using higher noise values.
Step 2 - Wait for the reversal zone algorithm to indicate a potential market reversal by showing either light or dark red/green colour. A lighter zone suggests that the overall trend is beginning to reverse, while a darker zone indicates a higher likelihood of reversal.
Step 3 - Once a reversal zone is identified, monitor the trend line for signals that the price is moving significantly away from the mean. This indicates a strong localized price movement that is poised for a reversal. At this stage, you can reduce the noise value and increase the aggressiveness of the trading style to capture more reversal signals.
🛠️ Usage/Practice
In the example above, the indicator is set with neutral aggression for buy signals and lower aggression for sell signals, reflecting the current bull market cycle
Red Reversal Zone - A bearish reversal zone emerges, followed by a darker bearish zone, indicating an increased probability of a trend reversal. The red signals show price reversion from the localized mean, but the absence of yellow signals suggests the reversion isn't abnormally aggressive, making this a good area to consider a short position.
Strong Reversal Opportunity - Similar to point 1, but this time a green signal appears within the bullish dark green zone, highlighting a strong reversal potential. Subsequent red signals suggest opportunities to take profits as the trend faces resistance.
Opportunity to Strengthen Long Position - Once again, the indicator shows a bullish reversal zone without yellow signals. This suggests an area of increased resistance at this price point, offering traders another chance to increase their long positions before the market enters the long bull cycle.
Excessive Buying Pressure - The price has deviated significantly from the mean, triggering a yellow signal. This indicates excessive buying pressure, suggesting the trend is likely to continue upward. Although not an immediate bearish area, the red sell signals suggest it could be a time to conservatively take partial profits.
Trend Weakening - As the trend slows down, bearish zones appear, indicating potential reversal points. As the market shows signs of losing upward momentum, this suggests an opportunity to reduce their long exposure or enter a short trade and take advantage of the correction in the bull cycle.
Potential for Additional Long Position - Despite the earlier sell signals, the overall uptrend remains strong. This presents an opportunity either to add to the long position or to take profits from a previous sell position. The strength of the upward trend suggests that the market may continue higher.
Abnormal Upward Momentum - Similar to points 4 and 5, the yellow signals indicate abnormal price action with aggressive upward momentum. As the trend corrects to a normal range, the price hitting a resistance level is confirmed by the appearance of red reversal zones, suggesting a potential pullback.
Sideways Market Signals - In a sideways market, the indicator shows signals that remain within the normal mean reversion range. These signals are not abnormal and suggest potential entry points for trades within a sideways market, indicating periods where the market lacks strong directional momentum.
🔶 Conclusion
With its seamless integration into various charts and timeframes, the MeanRevert Matrix stands as a reliable and adaptable tool, essential for navigating the complexities of modern markets. By following the implementation guidelines and leveraging its features, traders have the potential to effectively anticipate market movements and optimize their entry and exit points.
We developed this indicator to help traders enhance their understanding of market trends and achieve their trading objectives with greater precision.
Multiple Naked LevelsPURPOSE OF THE INDICATOR
This indicator autogenerates and displays naked levels and gaps of multiple types collected into one simple and easy to use indicator.
VALUE PROPOSITION OF THE INDICATOR AND HOW IT IS ORIGINAL AND USEFUL
1) CONVENIENCE : The purpose of this indicator is to offer traders with one coherent and robust indicator providing useful, valuable, and often used levels - in one place.
2) CLUSTERS OF CONFLUENCES : With this indicator it is easy to identify levels and zones on the chart with multiple confluences increasing the likelihood of a potential reversal zone.
THE TYPES OF LEVELS AND GAPS INCLUDED IN THE INDICATOR
The types of levels include the following:
1) PIVOT levels (Daily/Weekly/Monthly) depicted in the chart as: dnPIV, wnPIV, mnPIV.
2) POC (Point of Control) levels (Daily/Weekly/Monthly) depicted in the chart as: dnPoC, wnPoC, mnPoC.
3) VAH/VAL STD 1 levels (Value Area High/Low with 1 std) (Daily/Weekly/Monthly) depicted in the chart as: dnVAH1/dnVAL1, wnVAH1/wnVAL1, mnVAH1/mnVAL1
4) VAH/VAL STD 2 levels (Value Area High/Low with 2 std) (Daily/Weekly/Monthly) depicted in the chart as: dnVAH2/dnVAL2, wnVAH2/wnVAL2, mnVAH1/mnVAL2
5) FAIR VALUE GAPS (Daily/Weekly/Monthly) depicted in the chart as: dnFVG, wnFVG, mnFVG.
6) CME GAPS (Daily) depicted in the chart as: dnCME.
7) EQUILIBRIUM levels (Daily/Weekly/Monthly) depicted in the chart as dnEQ, wnEQ, mnEQ.
HOW-TO ACTIVATE LEVEL TYPES AND TIMEFRAMES AND HOW-TO USE THE INDICATOR
You can simply choose which of the levels to be activated and displayed by clicking on the desired radio button in the settings menu.
You can locate the settings menu by clicking into the Object Tree window, left-click on the Multiple Naked Levels and select Settings.
You will then get a menu of different level types and timeframes. Click the checkboxes for the level types and timeframes that you want to display on the chart.
You can then go into the chart and check out which naked levels that have appeared. You can then use those levels as part of your technical analysis.
The levels displayed on the chart can serve as additional confluences or as part of your overall technical analysis and indicators.
In order to back-test the impact of the different naked levels you can also enable tapped levels to be depicted on the chart. Do this by toggling the 'Show tapped levels' checkbox.
Keep in mind however that Trading View can not shom more than 500 lines and text boxes so the indocator will not be able to give you the complete history back to the start for long duration assets.
In order to clean up the charts a little bit there are two additional settings that can be used in the Settings menu:
- Selecting the price range (%) from the current price to be included in the chart. The default is 25%. That means that all levels below or above 20% will not be displayed. You can set this level yourself from 0 up to 100%.
- Selecting the minimum gap size to include on the chart. The default is 1%. That means that all gaps/ranges below 1% in price difference will not be displayed on the chart. You can set the minimum gap size yourself.
BASIC DESCRIPTION OF THE INNER WORKINGS OF THE INDICTATOR
The way the indicator works is that it calculates and identifies all levels from the list of levels type and timeframes above. The indicator then adds this level to a list of untapped levels.
Then for each bar after, it checks if the level has been tapped. If the level has been tapped or a gap/range completely filled, this level is removed from the list so that the levels displayed in the end are only naked/untapped levels.
Below is a descrition of each of the level types and how it is caluclated (algorithm):
PIVOT
Daily, Weekly and Monthly levels in trading refer to significant price points that traders monitor within the context of a single trading day. These levels can provide insights into market behavior and help traders make informed decisions regarding entry and exit points.
Traders often use D/W/M levels to set entry and exit points for trades. For example, entering long positions near support (daily close) or selling near resistance (daily close).
Daily levels are used to set stop-loss orders. Placing stops just below the daily close for long positions or above the daily close for short positions can help manage risk.
The relationship between price movement and daily levels provides insights into market sentiment. For instance, if the price fails to break above the daily high, it may signify bearish sentiment, while a strong breakout can indicate bullish sentiment.
The way these levels are calculated in this indicator is based on finding pivots in the chart on D/W/M timeframe. The level is then set to previous D/W/M close = current D/W/M open.
In addition, when price is going up previous D/W/M open must be smaller than previous D/W/M close and current D/W/M close must be smaller than the current D/W/M open. When price is going down the opposite.
POINT OF CONTROL
The Point of Control (POC) is a key concept in volume profile analysis, which is commonly used in trading.
It represents the price level at which the highest volume of trading occurred during a specific period.
The POC is derived from the volume traded at various price levels over a defined time frame. In this indicator the timeframes are Daily, Weekly, and Montly.
It identifies the price level where the most trades took place, indicating strong interest and activity from traders at that price.
The POC often acts as a significant support or resistance level. If the price approaches the POC from above, it may act as a support level, while if approached from below, it can serve as a resistance level. Traders monitor the POC to gauge potential reversals or breakouts.
The way the POC is calculated in this indicator is by an approximation by analysing intrabars for the respective timeperiod (D/W/M), assigning the volume for each intrabar into the price-bins that the intrabar covers and finally identifying the bin with the highest aggregated volume.
The POC is the price in the middle of this bin.
The indicator uses a sample space for intrabars on the Daily timeframe of 15 minutes, 35 minutes for the Weekly timeframe, and 140 minutes for the Monthly timeframe.
The indicator has predefined the size of the bins to 0.2% of the price at the range low. That implies that the precision of the calulated POC og VAH/VAL is within 0.2%.
This reduction of precision is a tradeoff for performance and speed of the indicator.
This also implies that the bigger the difference from range high prices to range low prices the more bins the algorithm will iterate over. This is typically the case when calculating the monthly volume profile levels and especially high volatility assets such as alt coins.
Sometimes the number of iterations becomes too big for Trading View to handle. In these cases the bin size will be increased even more to reduce the number of iterations.
In such cases the bin size might increase by a factor of 2-3 decreasing the accuracy of the Volume Profile levels.
Anyway, since these Volume Profile levels are approximations and since precision is traded for performance the user should consider the Volume profile levels(POC, VAH, VAL) as zones rather than pin point accurate levels.
VALUE AREA HIGH/LOW STD1/STD2
The Value Area High (VAH) and Value Area Low (VAL) are important concepts in volume profile analysis, helping traders understand price levels where the majority of trading activity occurs for a given period.
The Value Area High/Low is the upper/lower boundary of the value area, representing the highest price level at which a certain percentage of the total trading volume occurred within a specified period.
The VAH/VAL indicates the price point above/below which the majority of trading activity is considered less valuable. It can serve as a potential resistance/support level, as prices above/below this level may experience selling/buying pressure from traders who view the price as overvalued/undervalued
In this indicator the timeframes are Daily, Weekly, and Monthly. This indicator provides two boundaries that can be selected in the menu.
The first boundary is 70% of the total volume (=1 standard deviation from mean). The second boundary is 95% of the total volume (=2 standard deviation from mean).
The way VAH/VAL is calculated is based on the same algorithm as for the POC.
However instead of identifying the bin with the highest volume, we start from range low and sum up the volume for each bin until the aggregated volume = 30%/70% for VAL1/VAH1 and aggregated volume = 5%/95% for VAL2/VAH2.
Then we simply set the VAL/VAH equal to the low of the respective bin.
FAIR VALUE GAPS
Fair Value Gaps (FVG) is a concept primarily used in technical analysis and price action trading, particularly within the context of futures and forex markets. They refer to areas on a price chart where there is a noticeable lack of trading activity, often highlighted by a significant price movement away from a previous level without trading occurring in between.
FVGs represent price levels where the market has moved significantly without any meaningful trading occurring. This can be seen as a "gap" on the price chart, where the price jumps from one level to another, often due to a rapid market reaction to news, events, or other factors.
These gaps typically appear when prices rise or fall quickly, creating a space on the chart where no transactions have taken place. For example, if a stock opens sharply higher and there are no trades at the prices in between the two levels, it creates a gap. The areas within these gaps can be areas of liquidity that the market may return to “fill” later on.
FVGs highlight inefficiencies in pricing and can indicate areas where the market may correct itself. When the market moves rapidly, it may leave behind price levels that traders eventually revisit to establish fair value.
Traders often watch for these gaps as potential reversal or continuation points. Many traders believe that price will eventually “fill” the gap, meaning it will return to those price levels, providing potential entry or exit points.
This indicator calculate FVGs on three different timeframes, Daily, Weekly and Montly.
In this indicator the FVGs are identified by looking for a three-candle pattern on a chart, signalling a discrete imbalance in order volume that prompts a quick price adjustment. These gaps reflect moments where the market sentiment strongly leans towards buying or selling yet lacks the opposite orders to maintain price stability.
The indicator sets the gap to the difference from the high of the first bar to the low of the third bar when price is moving up or from the low of the first bar to the high of the third bar when price is moving down.
CME GAPS (BTC only)
CME gaps refer to price discrepancies that can occur in charts for futures contracts traded on the Chicago Mercantile Exchange (CME). These gaps typically arise from the fact that many futures markets, including those on the CME, operate nearly 24 hours a day but may have significant price movements during periods when the market is closed.
CME gaps occur when there is a difference between the closing price of a futures contract on one trading day and the opening price on the following trading day. This difference can create a "gap" on the price chart.
Opening Gaps: These usually happen when the market opens significantly higher or lower than the previous day's close, often influenced by news, economic data releases, or other market events occurring during non-trading hours.
Gaps can result from reactions to major announcements or developments, such as earnings reports, geopolitical events, or changes in economic indicators, leading to rapid price movements.
The importance of CME Gaps in Trading is the potential for Filling Gaps: Many traders believe that prices often "fill" gaps, meaning that prices may return to the gap area to establish fair value.
This can create potential trading opportunities based on the expectation of gap filling. Gaps can act as significant support or resistance levels. Traders monitor these levels to identify potential reversal points in price action.
The way the gap is identified in this indicator is by checking if current open is higher than previous bar close when price is moving up or if current open is lower than previous day close when price is moving down.
EQUILIBRIUM
Equilibrium in finance and trading refers to a state where supply and demand in a market balance each other, resulting in stable prices. It is a key concept in various economic and trading contexts. Here’s a concise description:
Market Equilibrium occurs when the quantity of a good or service supplied equals the quantity demanded at a specific price level. At this point, there is no inherent pressure for the price to change, as buyers and sellers are in agreement.
Equilibrium Price is the price at which the market is in equilibrium. It reflects the point where the supply curve intersects the demand curve on a graph. At the equilibrium price, the market clears, meaning there are no surplus goods or shortages.
In this indicator the equilibrium level is calculated simply by finding the midpoint of the Daily, Weekly, and Montly candles respectively.
NOTES
1) Performance. The algorithms are quite resource intensive and the time it takes the indicator to calculate all the levels could be 5 seconds or more, depending on the number of bars in the chart and especially if Montly Volume Profile levels are selected (POC, VAH or VAL).
2) Levels displayed vs the selected chart timeframe. On a timeframe smaller than the daily TF - both Daily, Weekly, and Monthly levels will be displayed. On a timeframe bigger than the daily TF but smaller than the weekly TF - the Weekly and Monthly levels will be display but not the Daily levels. On a timeframe bigger than the weekly TF but smaller than the monthly TF - only the Monthly levels will be displayed. Not Daily and Weekly.
CREDITS
The core algorithm for calculating the POC levels is based on the indicator "Naked Intrabar POC" developed by rumpypumpydumpy (https:www.tradingview.com/u/rumpypumpydumpy/).
The "Naked intrabar POC" indicator calculates the POC on the current chart timeframe.
This indicator (Multiple Naked Levels) adds two new features:
1) It calculates the POC on three specific timeframes, the Daily, Weekly, and Monthly timeframes - not only the current chart timeframe.
2) It adds functionaly by calculating the VAL and VAH of the volume profile on the Daily, Weekly, Monthly timeframes .
Volume Profile cheap copyIn the absence of TradingView's open-source Volume Profile (hereinafter referred to as VP) indicator code, I have replicated it. However, because this code is classified as an "indicator" rather than a "tool," it cannot allow users to define the range according to their preferences. In the code, I have set different periods, and users can input 0, 1, or 2 to let the indicator calculate the volume distribution from the earliest candle to the latest candle within the daily, weekly, or monthly range, respectively.
How can we prove that this code is consistent with TradingView's algorithm?
Firstly, the calculation or drawing process of VP starts from the earliest candle in the selected range. After calling TradingView's built-in "Fixed Range Volume Profile" (FRVP) tool, you can enter the settings interface of the tool and check both "developing POC" and "Value Area (VA)." The paths of POC, VAH, and VAL will appear in the chart. These paths are the changes in the values of POC, VAH, and VAL as the number of candles increases. If the paths shown by my indicator are the same as those shown by TradingView's VP indicator, then it proves the algorithms are consistent. Since VP itself is calculated based on volume, the high and low points of candles, and the opening and closing prices, if the data sources are consistent, the calculation results (the paths of POC, VAH, and VAL) will remain consistent over time. This can be used to infer that the algorithms are consistent. Additionally, the parameters of the two indicators (number of rows and value area ratio) must be the same to verify consistency. The number of rows in the indicator is usually set to 100 by default, and the value area ratio is 70. Therefore, the parameters in FRVP should also be set to 100 rows and a value area volume of 70.
Why is there a noticeable discrepancy?
When the start and end points of the VP remain unchanged, reducing the chart's time frame can improve accuracy. For example, when calculating the weekly VP, switching from a 1-hour time frame to a 5-minute time frame can make the indicator more closely match TradingView's native VP. Tests have shown that TradingView's native VP may not use the data displayed on the current chart for its calculations. For instance, the VP may use data from the 5-minute time frame even if the chart is displayed in the 1-hour time frame. However, my replicated VP calculates based on the chart's data, so differences in time frames will affect accuracy.
Current algorithm deficiencies
This replicated VP code is merely a demo and does not handle data updates. In other words, after the latest candle closes, the VP needs to be recalculated, but this recalculation step is not handled, which will cause errors. To resolve this issue, you only need to switch the time frame or delete the indicator and re-add it.
HilalimSBHilalimSB A Wedding Gift 🌙
HilalimSB - Revealing the Secrets of the Trend
HilalimSB is a powerful indicator designed to help investors analyze market trends and optimize trading strategies. Designed to uncover the secrets at the heart of the trend, HilalimSB stands out with its unique features and impressive algorithm.
Hilalim Algorithm and Fixed ATR Value:
HilalimSB is equipped with a special algorithm called "Hilalim" to detect market trends. This algorithm can delve into the depths of price movements to determine the direction of the trend and provide users with the ability to predict future price movements. Additionally, HilalimSB uses its own fixed Average True Range (ATR) value. ATR is an indicator that measures price movement volatility and is often used to determine the strength of a trend. The fixed ATR value of HilalimSB has been tested over long periods and its reliability has been proven. This allows users to interpret the signals provided by the indicator more reliably.
ATR Calculation Steps
1.True Range Calculation:
+ The True Range (TR) is the greatest of the following three values:
1. Current high minus current low
2. Current high minus previous close (absolute value)
3. Current low minus previous close (absolute value)
2.Average True Range (ATR) Calculation:
-The initial ATR value is calculated as the average of the TR values over a specified period
(typically 14 periods).
-For subsequent periods, the ATR is calculated using the following formula:
ATRt=(ATRt−1×(n−1)+TRt)/n
Where:
+ ATRt is the ATR for the current period,
+ ATRt−1 is the ATR for the previous period,
+ TRt is the True Range for the current period,
+ n is the number of periods.
Pine Script to Calculate ATR with User-Defined Length and Multiplier
Here is the Pine Script code for calculating the ATR with user-defined X length and Y multiplier:
//@version=5
indicator("Custom ATR", overlay=false)
// User-defined inputs
X = input.int(14, minval=1, title="ATR Period (X)")
Y = input.float(1.0, title="ATR Multiplier (Y)")
// True Range calculation
TR1 = high - low
TR2 = math.abs(high - close )
TR3 = math.abs(low - close )
TR = math.max(TR1, math.max(TR2, TR3))
// ATR calculation
ATR = ta.rma(TR, X)
// Apply multiplier
customATR = ATR * Y
// Plot the ATR value
plot(customATR, title="Custom ATR", color=color.blue, linewidth=2)
This code can be added as a new Pine Script indicator in TradingView, allowing users to calculate and display the ATR on the chart according to their specified parameters.
HilalimSB's Distinction from Other ATR Indicators
HilalimSB emerges with its unique Average True Range (ATR) value, presenting itself to users. Equipped with a proprietary ATR algorithm, this indicator is released in a non-editable form for users. After meticulous testing across various instruments with predetermined period and multiplier values, it is made available for use.
ATR is acknowledged as a critical calculation tool in the financial sector. The ATR calculation process of HilalimSB is conducted as a result of various research efforts and concrete data-based computations. Therefore, the HilalimSB indicator is published with its proprietary ATR values, unavailable for modification.
The ATR period and multiplier values provided by HilalimSB constitute the fundamental logic of a trading strategy. This unique feature aids investors in making informed decisions.
Visual Aesthetics and Clear Charts:
HilalimSB provides a user-friendly interface with clear and impressive graphics. Trend changes are highlighted with vibrant colors and are visually easy to understand. You can choose colors based on eye comfort, allowing you to personalize your trading screen for a more enjoyable experience. While offering a flexible approach tailored to users' needs, HilalimSB also promises an aesthetic and professional experience.
Strong Signals and Buy/Sell Indicators:
After completing test operations, HilalimSB produces data at various time intervals. However, we would like to emphasize to users that based on our studies, it provides the best signals in 1-hour chart data. HilalimSB produces strong signals to identify trend reversals. Buy or sell points are clearly indicated, allowing users to develop and implement trading strategies based on these signals.
For example, let's imagine you wanted to open a position on BTC on 2023.11.02. You are aware that you need to calculate which of the buying or selling transactions would be more profitable. You need support from various indicators to open a position. Based on the analysis and calculations it has made from the data it contains, HilalimSB would have detected that the graph is more suitable for a selling position, and by producing a sell signal at the most ideal selling point at 08:00 on 2023.11.02 (UTC+3 Istanbul), it would have informed you of the direction the graph would follow, allowing you to benefit positively from a 2.56% decline.
Technology and Innovation:
HilalimSB aims to enhance the trading experience using the latest technology. With its innovative approach, it enables users to discover market opportunities and support their decisions. Thus, investors can make more informed and successful trades. Real-Time Data Analysis: HilalimSB analyzes market data in real-time and identifies updated trends instantly. This allows users to make more informed trading decisions by staying informed of the latest market developments. Continuous Update and Improvement: HilalimSB is constantly updated and improved. New features are added and existing ones are enhanced based on user feedback and market changes. Thus, HilalimSB always aims to provide the latest technology and the best user experience.
Social Order and Intrinsic Motivation:
Negative trends such as widespread illegal gambling and uncontrolled risk-taking can have adverse financial effects on society. The primary goal of HilalimSB is to counteract these negative trends by guiding and encouraging users with data-driven analysis and calculable investment systems. This allows investors to trade more consciously and safely.
Quarterly H/L [Dango]Introducing the Quarterly High and Low Indicator, a powerful and original tool designed to enhance your understanding of price action by identifying key turning points within quarterly cycles. This innovative script accurately determines the most significant highs and lows in each quarter, providing valuable insights for traders.
Key Features:
- Identifies and displays quarterly highs and lows on 90-minute, daily, weekly, monthly, and yearly timeframes
- Employs advanced algorithms and a deep understanding of cycle theory to precisely pinpoint key turning points
- Accounts for subtle nuances in price action and market dynamics
- Intended to be used in conjunction with the Quarterly Cycles Indicator for further confluence
How It Works:
The Quarterly High and Low Indicator utilizes a proprietary algorithm to meticulously analyze price action within each quarter. This advanced formula takes into account multiple factors, such as price momentum, volatility, and volume, to accurately identify the most significant high and low points.
The script employs a multi-step process to determine the quarterly highs and lows:
1. Cycle Isolation: The indicator first isolates the price action within each quarter, focusing on the specific time frame being analyzed (90-minute, daily, weekly, monthly, or yearly).
2. Momentum Analysis: The script then analyzes the price momentum within each quarter, identifying periods of strong bullish or bearish sentiment. This helps to narrow down potential high and low points.
3. Volatility and Volume Confirmation: To further refine the identification of key turning points, the indicator assesses the volatility and volume characteristics surrounding potential highs and lows. Significant changes in volatility and volume often accompany important price reversals.
4. Proprietary Scoring System: The algorithm assigns scores to each potential high and low point based on a proprietary scoring system. This system takes into account the confluence of momentum, volatility, and volume factors to determine the most significant turning points within each quarter.
The Quarterly High and Low Indicator visually represents these key turning points on the chart, enabling traders to easily identify potential support and resistance levels, trend reversals, and optimal entry and exit points. By focusing on the most significant price levels within each quarter, the indicator helps traders cut through the noise and make more informed trading decisions.
Expected Usage:
The Quarterly High and Low Indicator is designed to be a valuable tool for traders seeking to gain a deeper understanding of price action and market dynamics. By mapping out the most significant high and low points within each quarter, the indicator provides users with key levels to watch for potential trend reversals, support, and resistance.
1. Identifying Pivots and Reversals: The quarterly highs and lows identified by the indicator serve as critical levels where price is more likely to pivot or reverse. Traders can use these levels to anticipate potential trend changes and adjust their trading strategies accordingly.
2. Backtesting and Historical Analysis: The indicator enables traders to analyze historical price action and assess how the market has reacted to quarterly high and low levels in the past. By backtesting their strategies using these key levels, traders can gain valuable insights into the effectiveness of their approach and make data-driven refinements.
3. Support and Resistance: Quarterly highs and lows often act as significant support and resistance levels. Traders can use the indicator to identify these key areas and plan their trades around them. For example, if price approaches a quarterly high, traders may watch for potential selling pressure and consider taking profits or initiating short positions.
4. Confirmation and Confluence: The Quarterly High and Low Indicator can be used in conjunction with other technical analysis tools to confirm trade setups and increase confidence in trading decisions. When multiple indicators or analysis techniques align with the quarterly highs and lows, it provides a stronger signal for potential trade entry or exit points.
5. Risk Management: By understanding the location of quarterly highs and lows, traders can make more informed decisions about stop-loss placement and position sizing. Setting stop-losses beyond these key levels can help mitigate the risk of getting stopped out prematurely due to short-term price fluctuations.
6. Combining with the Quarterly Cycles Indicator: The Quarterly High and Low Indicator is intended to be used alongside the Quarterly Cycles Indicator for further confluence and validation. By analyzing the relationship between the identified quarterly highs and lows and the underlying quarterly cycles, traders can gain a more comprehensive understanding of market dynamics and potential turning points. When the quarterly highs and lows align with the key phases of the quarterly cycles, it provides a stronger signal for potential trend changes and trading opportunities.
Incorporating the Quarterly High and Low Indicator into a trading strategy, along with the Quarterly Cycles Indicator, allows traders to develop a more comprehensive understanding of price action and make better-informed decisions. By backtesting and analyzing how price reacts around these key levels and cycles, traders can refine their approach and potentially improve their trading outcomes.
Limitations and Disclaimer:
While the Quarterly High and Low Indicator is a powerful tool, it should not be used in isolation. Traders should combine the insights gained from this indicator with other forms of analysis, such as the Quarterly Cycles Indicator, fundamental analysis, risk management, and sound trading psychology, to develop a well-rounded and effective trading approach.
Please note that the indicator's accuracy may be impacted by extreme market volatility or unusual events, and quarterly highs and lows should not be relied upon in isolation. As with any trading tool, individual results may vary, and past performance does not guarantee future outcomes. Traders should always exercise caution, use appropriate risk management techniques, and continuously educate themselves to adapt to changing market conditions.
This indicator is provided for educational purposes only and should not be considered financial advice. Always conduct your own due diligence and consult with a financial professional before making any trading decisions.
Privacy of Code:
The underlying logic and specific calculations used in the proprietary algorithm are not disclosed to protect the intellectual property of the script. The advanced formula and scoring system used to identify quarterly highs and lows are the result of extensive research, testing, and refinement. By keeping these details confidential, the script maintains its competitive edge and ensures the protection of its intellectual property.
ICT Concept [TradingFinder] Order Block | FVG | Liquidity Sweeps🔵 Introduction
The "ICT" style is one of the subsets of "Price Action" technical analysis. ICT is a method created by "Michael Huddleston", a professional forex trader and experienced mentor. The acronym ICT stands for "Inner Circle Trader".
The main objective of the ICT trading strategy is to combine "Price Action" and the concept of "Smart Money" to identify optimal entry points into trades. However, finding suitable entry points is not the only strength of this approach. With the ICT style, traders can better understand price behavior and adapt their trading approach to market structure accordingly.
Numerous concepts are discussed in this style, but the key practical concepts for trading in financial markets include "Order Block," "Liquidity," and "FVG".
🔵 How to Use
🟣Order Block
Order blocks are a specific type of "Supply and Demand" zones formed when a series of orders are placed in a block. These orders could be created by banks or other major players. Banks typically execute large orders in blocks during their trading sessions. If they were to enter the market directly with a small quantity, significant price movements would occur before the orders are fully executed, resulting in less profit. To avoid this, they divide their orders into smaller, manageable positions. Traders should look for "buy" opportunities in "demand order blocks" areas and "sell" opportunities in "supply order blocks".
🟣Liquidity
These levels are where traders aim to exit their trades. "Market Makers" or smart money usually collects or distributes their trading positions near levels where many retail traders have placed their "Stop Loss" orders. When the liquidity resulting from these losses is collected, the price often reverses direction.
A "Stop Hunt" is a move designed to neutralize liquidity generated by triggered stop losses. Banks often use significant news events to trigger stop hunts and acquire the liquidity released in the market. If, for example, they intend to execute heavy buy orders, they encourage others to sell through stop hunts.
As a result, if there is liquidity in the market before reaching the order block region, the credibility of that order block is higher. Conversely, if liquidity is near the order block, meaning the price reaches the order block before reaching the liquidity area, the credibility of that order block is lower.
🟣FVG (Fair Value Gap)
To identify the "Fair Value Gap" on the chart, one must analyze candle by candle. Focus on candles with large bodies, examining one candle and the one before it. The candles before and after this central candle should have long shadows, and their bodies should not overlap with the body of the central candle. The distance between the shadows of the first and third candles is called the FVG range.
These zone function in two ways :
•Supply and Demand zone: In this case, the price reacts to these zone, and its trend reverses.
•Liquidity zone: In this scenario, the price "fills" the zone and then reaches the order block.
Important Note: In most cases, FVG zone with very small width act as supply and demand zone, while zone with a significant width act as liquidity zone, absorbing the price.
🔵 Setting
🟣Order Block
Refine Order Block : When the option for refining order blocks is Off, the supply and demand zones encompass the entire length of the order block (from Low to High) in their standard state and remain unaltered. On the option for refining order blocks triggers the improvement of supply and demand zones using the error correction algorithm.
Refine Type : The enhancement of order blocks via the error correction algorithm can be executed through two methods: Defensive and Aggressive. In the Aggressive approach, the widest possible range is taken into account for order blocks.
Show High Levels : If major high levels are to be displayed, set the option for showing high level to Yes.
Show Low Levels : If major low levels are to be displayed, set the option for showing low level to Yes.
Show Last Support : If showing the last support is desired, set the option for showing last support to Yes.
Show Last Resistance : If showing the last resistance is desired, set the option for showing last resistance to Yes.
🟣 FVG
FVG Filter : When FVG filtering is activated, the number of FVG areas undergoes filtration based on the specified algorithm.
FVG Filter Types :
1. Very Aggressive : Apart from the initial condition, an additional condition is introduced. For an upward FVG, the maximum price of the last candle should exceed the maximum price of the middle candle. Similarly, for a downward FVG, the minimum price of the last candle should be lower than the minimum price of the middle candle. This mode eliminates a minimal number of FVGs.
2. Aggressive : In addition to the conditions of the Very Aggressive mode, this mode considers the size of the middle candle; it should not be small. Consequently, a larger number of FVGs are eliminated in this mode.
3. Defensive : Alongside the conditions of the Very Aggressive mode, this mode takes into account the size of the middle candle, which should be relatively large with the majority of it comprising the body. Furthermore, to identify upward FVGs, the second and third candles must be positive, whereas for downward FVGs, the second and third candles must be negative. This mode filters out a considerable number of FVGs, retaining only those of suitable quality.
4. Very Defensive : In addition to the conditions of the Defensive mode, the first and third candles should not be very small-bodied doji candles. This mode filters out the majority of FVGs, leaving only the highest quality ones. Show Demand FVG: Enables the display of demand-related boxes, which can be toggled between off and on. Show Supply FVG: Enables the display of supply-related boxes along the path, which can also be toggled between off and on.
🟣 Liquidity
Statics Liquidity Line Sensitivity : A value ranging from 0 to 0.4. Increasing this value reduces the sensitivity of the "Statics Liquidity Line Detection" function and increases the number of identified lines. The default value is 0.3.
Dynamics Liquidity Line Sensitivity : A value ranging from 0.4 to 1.95. Increasing this value enhances the sensitivity of the "Dynamics Liquidity Line Detection" function and decreases the number of identified lines. The default value is 1.
Statics Period Pivot : Default value is set to 8. By adjusting this value, you can specify the period for static liquidity line pivots.
Dynamics Period Pivot : Default value is set to 3. By adjusting this value, you can specify the period for dynamic liquidity line pivots.
You can activate or deactivate liquidity lines as necessary using the buttons labeled "Show Statics High Liquidity Line," "Show Statics Low Liquidity Line," "Show Dynamics High Liquidity Line," and "Show Dynamics Low Liquidity Line".
AB=CD [Real-Time] (Zeiierman)█ Overview
The AB=CD (Zeiierman) indicator is designed to automatically detect the ABCD pattern across any chart and timeframe as it unfolds. Activating when point C forms, it automatically draws the D line, giving traders immediate entry, stop-loss, and target signals.
The primary use of the ABCD pattern is to provide a structure to forecast where prices are likely to move next. It's grounded in the principle that history tends to repeat itself, and patterns in price movements are reflective of market psychology.
A simple yet powerful tool in the trader's toolkit, providing clear signals for entry, stop-loss, and profit-target levels, which are based on symmetrical price movements and Fibonacci mathematics. It is applicable in various markets including forex, stocks, and commodities.
█ How to Use
The ABCD pattern is one of the foundational chart patterns used in technical analysis. It's essentially a price structure where two price legs are equivalent in length. In other words, the distance price travels from A to B roughly equals the distance from C to D.
Trend Continuation: Suggests that after a pullback, the original market trend is likely to resume towards point D.
Entry Point: Typically at point C to capitalize on the movement towards D.
Profit Target: Set at point D, expected to mirror the length of the A to B leg.
Stop Loss: Placed just beyond point C to protect against pattern failure.
█ How It Works
The pattern is made up of three consecutive price swings:
AB: This is the first price leg. It can either be up or down.
BC: This is a corrective or retracement leg. If AB is up, BC will be down, and vice versa.
CD: This is the final price leg. It moves in the same direction as AB and is approximately equal in length.
The ABCD pattern algorithm identifies pivot points over a user-defined period, labeled as A, B, C, and D. These points are determined by finding the highest and lowest values (extremes) within the specified period. The direction of the pattern is then established based on the position of these extremes. Fibonacci retracement levels are calculated between these points to determine potential reversal zones (entry and stop levels) and extension levels (target zones). When the price crosses into these zones, the ABCD pattern becomes active, signaling potential trading opportunities.
█ Settings
Market Move: This setting allows traders to define the size of the market move they're interested in, ranging from small to traditional, to swing, or even a custom length. This adjusts the sensitivity and the period over which the ABCD pattern is detected.
Bias: Traders can set their bias to bullish, bearish, or both, which filters the patterns based on the anticipated market direction.
Entry Retracement: Defines the Fibonacci retracement level for potential entry points.
Stop Retracement: Sets the Fibonacci retracement level for stop loss placement.
Exit Retracement: Determines the Fibonacci extension level for the profit target.
Show Stoploss & Target: Toggles the display of stop loss and target lines on the chart.
Color Settings: Customize the colors for bullish and bearish patterns to improve visual distinction.
-----------------
Disclaimer
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!
Eternal Moving AverageA moving average with absolutely no* settings??? Now that is a challenge.
* The only setting is for the user to change the calculation method of the dataset.
A trader must have their mind on recent price action. At the same time they must not miss the bigger picture. Instead of creating a moving average that takes some data into account (like 200 days), I decided to take all data into account. Each chart is analyzed separately. A custom algorithm generates moving averages, some slower, some faster.
In the future I may tweak the lengths of the algorithm. It is a hard process and it will take user-feedback as well as personal research for future alterations of the algorithm. It is however a complete, working product at the time of writing.
The basis of this moving average is EMA. It has the responsiveness of EMA, that takes more recent data into account. Contrary to some MAs, it preserves long-term trends.
As a hidden extra, with this moving average no candle is lost. Everything is analyzed without repainting.
This indicator does not provide any signals. The meaning of any lines crossing is left to the trader for explanation. This indicator helps trend analysts retain perspective of past price action.
WinningWave By Sercan V1Winningwave is a hurricane algorithm that works in all time frames and all transactions (stock exchange-coin), is too comprehensive to be explained in detail and includes many strategies.
To explain briefly; It is a layered oracle algorithm that gives signals by filtering the formations (Normal and Harmonic formations) created by multiple account movements containing many calculations and algorithms, based on the instantaneous momentum of the price and the overbought or oversold levels in a certain time period. Of course, formations refer to situations in which price movements occur in a certain order in financial markets. These patterns are specific patterns seen on the price chart and can often provide clues about future movements of prices. For example; Reverse Shoulder, Head and Shoulder, Symmetrical Triangle etc. Dozens of formation formation conditions and targets were filtered and made suitable for signaling. It also creates bands using YDK3 with the channel algorithm it contains. This band is usually calculated using the standard deviation method to measure price movements and indicate a specific deviation. The upper and lower bands obtained as a result of standard deviation calculations are drawn on the price chart. After a certain band is created, automatic expansion is carried out in order to predict possible movements of future prices. Additionally, Winningwave includes Ema calculations and has identified stop points after the main entry signal to help you in case you miss the main exit signal or choose a different strategy.
STRATEGY 1: As I mentioned in the general statement, the signals that emerged after many formations were filtered in 2 stages (SMI and CCI values served as filters for the formations) and the false signal rate was reduced to a minimum. You can combine signals into your own strategy using oscillators and tactics you trust.
It is important to remember that no indicator or tactic works 100% accurately. That's why filters and combinations are the right methods for you.
STRATEGY 2: Channel programs often create bands using the standard deviation method to indicate price movements and a specific deviation. Standard deviations are a measure of how far prices are generally from the mean. Channel programs draw price charts by creating upper and lower bands using these standard deviation values.
These bands can become very narrow depending on the playability of the price and the strength of the trends. In this way it can change the normal range of movement of prices and indicate potential overbought or oversold.
Once the channel is created, it is automatically expanded and gives us some clues about the direction of price movements. This expansion automatically signals the change according to the price movements of the bands. This feature becomes a predictive tool to predict price movements on the indicator.
Thus, using channel updates and standard deviation, the bands show the normal range of prices and these bands expand or contract dynamically, giving an idea about possible changes in prices. This can help investors gain insight into potential trend reversals or overbought or oversold prices.
In channel band strategy . It is a second strategy in which we calculate the profit rate with the most logical calculations when the prices touch the channel bottoms and channel tops and move up or down.
STRATEGY 3: We aimed to create a stop zone by blending the most appropriate ema values with buy signals. In some cases where you don't want to follow the signals or are confident in the transaction (written to filter out successive sell signals where price action generally rises without correction), it has created a more reliable stopping point for your trading strategy. It gives you a stopping point.
*** Calculations and mathematical settings will be in the menu. For healthy signals and filters, do not play with the numbers. For your personal use, color options or On-Off settings of each feature are available in the menu.
LuxAlgo - Backtester (OSC)The OSC Backtester is an innovative strategy script that allows users to create a wide variety of strategies using various unique oscillators.
By utilizing our 'Step' and 'Match' algorithms, users can create custom and complex strategy entries from each of the supported oscillators and included conditions, as well as any external sources, allowing users to create entries from a sequence of conditions and/or multiple matching conditions.
We included a complete alert system that will send a notification for each action taken by the strategy and we also allow users to set custom messages for each action taken by a strategy.
🔶 Features
🔹 Step & Match Algorithm
More complex entry rules can be created by using multiple conditions together, this is done thanks to the Step dropdown setting on the right of each condition.
The Step setting is directly related to the Step & Match algorithm and works in two ways:
When two or more conditions have the same step number, both conditions are evaluated. Used to test matching conditions.
When two or more conditions have different step numbers, each conditions will be evaluated in order, testing for the first step and switching to the next step once the previous one is true. When the final step is true the strategy will open a market order. Used to create sequence of conditions.
This operation is complementary, as you can create a sequence of conditions with one step consisting of two or more matching conditions as long as they have the same step number.
🔹 Fully Customizable Entries From Various Oscillators And Conditions
We allow the users to set entries using our unique HyperWave, Smart Money Flow, and their derived conditions as entries.
The Hyper Wave is a normalized adaptive oscillator aiming to reflect price trends without returning a high amount of noise.
The Smart Money Flow aims to detect trends based on market activity, by doing a comparative analysis between current volume and historical volume. A Smart Money Flow above 50 suggest market participants are bullish, else bearish. Derived from this oscillator we have Overflow indications, this indicator detects when market is overbought or oversold based on participants activity.
Other entries include proprietary reversal signals, real-time divergence detection, oscillator confluence (indicating how aligned each oscillator is), as well as entries using external sources.
🔹 Complete Alert System
Users can get alerted for any action executed by a strategy, from opening positions to closing them.
The message field in the Alert Messages setting section allows for the strategy to send a custom alert message depending on the action taken by the strategy, if no messages are set the strategy will send default messages.
🔶 Usage
Users can create a wide variety of strategies from this script, whether they are trend-following or contrarian traders.
Let's see a contrarian (revesal-based) strategy example using the following entry conditions:
Long: Hyperwave bullish divergence and oversold Hyperwave (lower than 20).
Short: Hyperwave bearish divergence and overbought Hyperwave (greater than 20).
We can also introduce take-profit and stop-loss exit conditions based on external indicators, allowing more control over exits in our strategy. For example:
Long: Hyperwave crossing over 50 while money flow is bearish.
Short: Hyperwave crossing under 50 while money flow is bullish.
Exit Long on a profit (long exit tp): Hyperwave crossing 80.
Exit Short on a profit (short exit tp): Hyperwave crossing 20.
While this strategy script can be used as a standalone, we recommend using other indicators creatively to assist with entries and exits as well as TP/SLs.
Our Step & Match algorithm can magnify interoperability, allowing for way more complete strategies through complex conditions, let's demonstrate this using the following entries:
Long: Any bullish reversal occurring after the price crosses over the lowest upper reversal zone of the Signals & Overlays™.
Short: Any bearish reversal occurring after the price crosses under the highest lower reversal zone of the Signals & Overlays™.
Long TP/SL: 5 ATR's away from the entry price.
Short TP/SL: 5 ATR's away from the entry price.
🔶 Strategy Properties (Important)
This script backtest is done on daily EURGBP, using the following backtesting properties:
Balance (default): 10 000 (default base currency)
Order Size: 10% of the equity
Comission: 3.4 pips (average spread for EURGBP)
Slippage: 3 tick
Stop Loss: 0.02 points away from entry price
We use these properties to ensure a realistic preview of the backtesting system, do note that default properties can be different for various reasons described below:
Order Size: 1 contract by default, this is to allow the strategy to run properly on most instruments such as futures.
Comission: Comission can vary depending on the market and instrument, there is no default value that might return realistic results.
We strongly recommend all users to ensure they adjust the Properties within the script settings to be in line with their accounts & trading platforms of choice to ensure results from the strategies built are realistic.
🔶 How To Access
You can see the Author's Instructions below to learn how to get access.
Double AI Super Trend Trading - Strategy [PresentTrading]█ Introduction and How It is Different
The Double AI Super Trend Trading Strategy is a cutting-edge approach that leverages the power of not one, but two AI algorithms, in tandem with the SuperTrend technical indicator. The strategy aims to provide traders with enhanced precision in market entry and exit points. It is designed to adapt to market conditions dynamically, offering the flexibility to trade in both bullish and bearish markets.
*The KNN part is mainly referred from @Zeiierman.
BTCUSD 8hr performance
ETHUSD 8hr performance
█ Strategy, How It Works: Detailed Explanation
1. SuperTrend Calculation
The SuperTrend is a popular indicator that captures market trends through a combination of the Volume-Weighted Moving Average (VWMA) and the Average True Range (ATR). This strategy utilizes two sets of SuperTrend calculations with varying lengths and factors to capture both short-term and long-term market trends.
2. KNN Algorithm
The strategy employs k-Nearest Neighbors (KNN) algorithms, which are supervised machine learning models. Two sets of KNN algorithms are used, each focused on different lengths of historical data and number of neighbors. The KNN algorithms classify the current SuperTrend data point as bullish or bearish based on the weighted sum of the labels of the k closest historical data points.
3. Signal Generation
Based on the KNN classifications and the SuperTrend indicator, the strategy generates signals for the start of a new trend and the continuation of an existing trend.
4. Trading Logic
The strategy uses these signals to enter long or short positions. It also incorporates dynamic trailing stops for exit conditions.
Local picture
█ Trade Direction
The strategy allows traders to specify their trading direction: long, short, or both. This enables the strategy to be versatile and adapt to various market conditions.
█ Usage
ToolTips: Comprehensive tooltips are provided for each parameter to guide the user through the customization process.
Inputs: Traders can customize numerous parameters including the number of neighbors in KNN, ATR multiplier, and types of moving averages.
Plotting: The strategy also provides visual cues on the chart to indicate bullish or bearish trends.
Order Execution: Based on the generated signals, the strategy will execute buy or sell orders automatically.
█ Default Settings
The default settings are configured to offer a balanced approach suitable for most scenarios:
Initial Capital: $10,000
Default Quantity Type: 10% of equity
Commission: 0.1%
Slippage: 1
Currency: USD
These settings can be modified to suit various trading styles and asset classes.
