Ankit_1618

Ocs Ai Trader

Ankit_1618 Aktualisiert   
This script perform predictive analytics from a virtual trader perspective!

It acts as an AI Trade Assistant that helps you decide the optimal times to buy or sell securities, providing you with precise target prices and stop-loss level to optimise your gains and manage risk effectively.


System Components
The trading system is built on 4 fundamental layers :

  1. Time series Processing layer
  2. Signal Processing layer
  3. Machine Learning
  4. Virtual Trade Emulator

Time series Processing layer
This is first component responsible for handling and processing real-time and historical time series data.
In this layer Signals are extracted from
averages such as : volume price mean, adaptive moving average
Estimates such as : relative strength stochastics estimates on supertrend

Signal Processing layer
This second layer processes signals from previous layer using sensitivity filter comprising of an Probability Distribution Confidence Filter
The main purpose here is to predict the trend of the underlying, by converging price, volume signals and deltas over a dominant cycle as dimensions and generate signals of action.
Key terms
  • Dominant cycle is a time cycle that has a greater influence on the overall behaviour of a system than other cycles.
    The system uses Ehlers method to calculate Dominant Cycle/ Period.
    Dominant cycle is used to determine the influencing period for the underlying.
    Once the dominant cycle/ period is identified, it is treated as a dynamic length for considering further calculations

    Predictive Adaptive Filter to generate Signals and define Targets and Stops
    An adaptive filter is a system with a linear filter that has a transfer function controlled by variable parameters and a means to adjust those parameters according to an optimisation algorithm. Because of the complexity of the optimisation algorithms, almost all adaptive filters are digital filters. Thus Helping us classify our intent either long side or short side
    The indicator use Adaptive Least mean square algorithm, for convergence of the filtered signals into a category of intents, (either buy or sell)

    Machine Learning
    The third layer of the System performs classifications using KNN K-Nearest Neighbour is one of the simplest Machine Learning algorithms based on Supervised Learning technique.
    K-NN algorithm assumes the similarity between the new case/data and available cases and put the new case into the category that is most similar to the available categories.
    K-NN algorithm stores all the available data and classifies a new data point based on the similarity. This means when new data appears then it can be easily classified into a well suite category by using K- NN algorithm. K-NN algorithm can be used for Regression as well as for Classification but mostly it is used for the Classification problems.

    Virtual Trade Emulator
    In this last and fourth layer a trade assistant is coded using trade emulation techniques and the Lines and Labels for Buy / Sell Signals, Targets and Stop are forecasted!


    How to use
    The system generates Buy and Sell alerts and plots it on charts
    Buy signal
    Buy signal constitutes of three targets {namely T1, T2, T3} and one stop level

    Sell signal
    Sell signal constitutes of three targets {namely T1, T2, T3} and one stop level

    What Securities will it work upon ?
    Volume Informations must be present for the applied security
    The indicator works on every liquid security : stocks, future, forex, crypto, options, commodities

    What TimeFrames To Use ?
    You can use any Timeframe, The indicator is Adaptive in Nature,
    I personally use timeframes such as : 1m, 5m 10m, 15m, ..... 1D, 1W

    This Script Uses Tradingview Premium features for working on lower timeframes
    In case if you are not a Tradingview premium subscriber you should tell the script that after applying on chart, this can be done by going to settings and unchecking "Is your Tradingview Subscription Premium or Above " Option

    How To Get Access ?
    You will need to privately message me for access mentioning you want access to "Ocs Ai Trader" Use comment box only for constructive comments. Thanks !


Versionshinweise:
Updates

  • Adds Regime Filter and Volatility Probability Scalper
  • Adds Quadratic Regression Filters
  • Adds Gaussian Lorentiz Normalisation and Daten Scaling
  • Adds Volume Float based Support and Resistance
  • Removes Dependencies from second based data unless necessarily forced by user!
Versionshinweise:
some links updated
Versionshinweise:
Adds Alert Passcode
Adds Marubozu Abnormality Detection
Adds Probability Average and Probability variable Filtering
Adds Historical Buy Sell Positions by Algo

Get Quality Free-mium Indicators (bit.ly/31Lzq7z)
On Scripts Section of myProfile

About me
I Wake Trade Eat Sleep Daily!
Skript nur auf Einladung

Der Zugriff auf dieses Skript ist auf vom Autor autorisierte User beschränkt und normalerweise kostenpflichtig. Sie können es zu Ihren Favoriten hinzufügen, aber Sie können es nur verwenden, nachdem Sie die Erlaubnis angefordert und vom Autor erhalten haben. Kontaktieren Sie Ankit_1618 für weitere Informationen oder folgen Sie den Anweisungen des Autors unten.

TradingView rät davon ab, für ein Skript zu bezahlen und es zu verwenden, bis Sie dem Autor zu 100% vertrauen und verstehen wie das Skript funktioniert. In vielen Fällen können Sie eine gute Open-Source-Alternative kostenlos in unserer öffentlichen Bibliothek finden.

Haftungsausschluss

Die Informationen und Veröffentlichungen sind nicht als Finanz-, Anlage-, Handels- oder andere Arten von Ratschlägen oder Empfehlungen gedacht, die von TradingView bereitgestellt oder gebilligt werden, und stellen diese nicht dar. Lesen Sie mehr in den Nutzungsbedingungen.

Hinweise des Autors

You will need to privately message me for access mentioning you want access to "Ocs Ai Trader" OR Also You can fill on the google forms here! bit.ly/4cdKMQm Use comment box only for constructive comments and criticism.

Möchten Sie dieses Skript auf einem Chart verwenden?

Warnung: Bitte lesen Sie dies, bevor Sie Zugriff anfordern.