INVITE-ONLY SCRIPT

Ocs Ai Trader

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

    Sell signal snapshot
    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 timeframesIn 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
    snapshotHow 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 !


Release Notes
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!
Release Notes
some links updated
Release Notes
Adds Alert Passcode
Adds Marubozu Abnormality Detection
Adds Probability Average and Probability variable Filtering
Adds Historical Buy Sell Positions by Algo
Release Notes
Adds Trimean based Quantitative Test
Adds Hyperbolic Trend Tests
Adds Obv based Learnings
Adds Marubozu extremes
Adds Dynamic Target 4 and Target 5
Adds Signal Improvements
Release Notes
Minor update for Stop Taking
Release Notes
removes target text bugs
adds triple impulse of balance volume
Release Notes
Adds Pivotal points and Lines
Fixes issues in target booking
Release Notes
Adds Fisher Transform to Result in a variable with an approximately normally distributed variance, stable across different values of the sample correlation coefficient.
Release Notes
Does Minor Fixes in replay mode
Release Notes
Adds Fine tuning surrounding false volume negatives
Release Notes
Adds Tolerance to Fisher Transforms and * Minor Bug Fixes
Release Notes
Adds cumulative vol delta Regime filtering !
Release Notes
Adds Volatility Derivative Filters, inspired by elder's method!
Release Notes
*minor bug fixes -in -<datum plane of volatility reference>
Release Notes
Adds Filters based on Impulsive ATR's in order to Identify/Filter periods of increased market activity
Release Notes
Adds TRIX Filter's Strength and Weakness Analyser
Release Notes
Adds Smoothness and Marubozu Considerations in TRIX Regime Based Signals
Release Notes
Adds Work around over Exponential Probability Squeeze for managing random fuzzyness
Release Notes
minor FLT plot bugs updates
Release Notes
Adds Refined Retrained Weights for machine learning models
ai_trade_assistantforecastingocs_ai_traderPivot points and levelsvolumedelta

Invite-only script

Access to this script is restricted to users authorized by the author and usually requires payment. You can add it to your favorites, but you will only be able to use it after requesting permission and obtaining it from its author. Contact Ankit_1618 for more information, or follow the author's instructions below.

TradingView does not suggest paying for a script and using it unless you 100% trust its author and understand how the script works. In many cases, you can find a good open-source alternative for free in our Community Scripts.

Author's instructions

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

Want to use this script on a chart?

Warning: please read before requesting access.

Get Ocs Ai Trader, Your personal Ai Trade Assistant here
ocstrader.com
bit.ly/ocs_ai_trader

About me
AlgoTrading Certification, (University of Oxford, Säid Business School)
PGP Research Analysis, (NISM)
Electronics Engineer
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