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Everything that I have been doing in the AI for trading nanodegree program by Udacity

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prakharrathi25/artificial-intelligence-for-trading

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Artificial Intelligence For Trading.

This repository contains all the quizzes and projects that I have completed for the Udacity AI for Trading Nanodegree.

Course Overview

Learnt the basics of quantitative analysis, including data processing, trading signal generation, and portfolio management. Used Python to work with historical stock data, develop trading strategies, and construct a multi-factor model with optimization.

  1. Basic Quantitative Trading : Learnt about market mechanics and how to generate signals with stock data. Work on developing a momentum-trading strategy in your first project.

  2. Advanced Quantitative Trading : Picked up the quant workflow for signal generation, and apply advanced quantitative methods commonly used in trading.

  3. Stocks, Indices, and ETFs : Learnt about portfolio optimization, and financial securities formed by stocks, including market indices, vanilla ETFs, and Smart Beta ETFs.

  4. Factor Investing and Alpha Research : Learnt the fundamentals of text processing, and analyze corporate filings to generate sentiment-based trading signals.

After learning about these concepts, I also implemented them and the projects can be found here.

Learnt how to analyze alternative data and use machine learning to generate trading signals. I also ran backtests to evaluate and combine top performing signals.

  1. Sentiment Analysis with Natural Language Processing : Studied the fundamentals of text processing, and analyze corporate filings to generate sentiment-based trading signals.

  2. Advanced Natural Language Processing with Deep Learning : Applied deep learning in quantitative analysis and used recurrent neural networks and long short-term memory to generate trading signals.

  3. Combining Multiple Signals : Advanced techniques to select and combine the factors generated from both traditional and alternative data.

  4. Simulating Trades with Historical Data : Refine trading signals by running rigorous back tests and tracking P&L while my algorithm buys and sells.

After learning about these concepts, I also implemented them and the projects can be found here.

Contact

For any queries and suggestions, please reach out to me on prakharrathi25@gmail.com

How to contribute

  1. You can open an issue and let me know what you're working. We can discuss it and approve it.
  2. You can also fork this repository and submit a pull request. Do add details of what your PR does to get it approved faster.

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Everything that I have been doing in the AI for trading nanodegree program by Udacity

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