Trading Projects Repository

This repository contains all of my trading projects, divided into three sections: projects completed before the AI in Trading Nanodegree from Udacity (Interactive Broker API), those completed as part of the Nanodegree program and those after utilizing yFinance.

Projects Completed with Interactive Broker API

Interactive Broker Projects

These projects involve creating and testing trading strategies on the Interactive Brokers platform. The strategies are based on price analysis, shorting, and longing based on previous price movements and trends.

1. IB (Interactive Broker) Stocks Trading

   • In this project, I developed trading strategies for stocks using the Interactive Brokers platform. The strategies focus on taking short and long positions derived from analyzing historical price data and price trends.

2. IB (Interactive Broker) Crypto Trading

   • This project involves strategies that capitalize on the volatile nature of the crypto market by using shorting and longing techniques based on historical price movements and trend analysis.

3. IB (Interactive Broker) Forex Trading

   • The Forex trading project involves designing strategies for the currency markets. The strategies are based on shorting and longing positions driven by previous price data and trends, aiming to exploit fluctuations in currency prices.

Projects Completed During the AI in Trading Nanodegree

These projects were completed as part of the AI in Trading Nanodegree from Udacity. Each project focuses on a different aspect of quantitative trading, utilizing machine learning and data analysis techniques to build, test, and evaluate trading strategies.

AI in Trading Nanodegree Projects

1. Alpha Research and Factor Modeling

   • This project involves researching and creating alpha factors, which are signals that can predict stock returns. The project covers the development of custom factors, their evaluation, and their integration into a portfolio.

2. Backtesting

   • In this project, I developed and evaluated trading strategies using backtesting. The focus is on testing the robustness of strategies by simulating them on historical data, allowing for analysis of their performance and risk.

3. Breakout Strategy

   • The breakout strategy project explores the concept of momentum trading by implementing a strategy that captures price movements that break through predefined levels. The project includes performance analysis and optimization of the strategy parameters.

4. Combined Signals for Enhanced Alpha

   • This project combines multiple alpha factors to create a more robust and predictive trading signal. The emphasis is on blending different factors and optimizing their weights to maximize returns while controlling for risk.

5. NLP on Financial Statements

   • This project applies Natural Language Processing (NLP) techniques to analyze financial statements and extract meaningful insights that can be used in trading strategies. The focus is on sentiment analysis and its application in predicting stock movements.

6. Sentiment Analysis with Neural Networks

   • In this project, I built and trained a neural network model to perform sentiment analysis on financial news and social media data. The project explores the impact of sentiment on market prices and integrates the sentiment scores into trading strategies.

7. Smart Beta and Portfolio Optimization

   • This project focuses on smart beta strategies, which involve creating portfolios that aim to outperform traditional market-cap-weighted indices. The project includes techniques for portfolio optimization and risk management.

8. Trading with Momentum

   • The momentum trading project involves developing strategies that capitalize on the continuation of existing market trends. The project explores various momentum indicators and their application in creating profitable trading strategies.

How to Navigate the Projects

To view and explore the work I've done in each project, follow these steps:

1. Navigate to the project folder of interest.
2. Open the file named project_x_starter.ipynb, where x corresponds to the specific project you're interested in.

This will open the Jupyter notebook where the project work is documented, including the code, analysis, and results.

yFinance - Fetching Stocks

The yFinance library is specifically utilized in the "yFinance - Fetching Stocks" file within this repository. This file demonstrates how to fetch historical stock data directly from Yahoo Finance. The yFinance library provides a simple interface to retrieve stock prices, financial information, and other relevant data that can be used in trading strategies and analysis.

This file serves as a practical example of how to use the yFinance library to gather the data needed for stock analysis and strategy development.