This project leverages data analytics and machine learning models to gain insights into financial markets. The analysis focuses on the historical daily returns of five selected stocks over a three-year period. The objective is to understand the performance of these stocks relative to market indices and to apply various analytical and modeling techniques to uncover actionable insights.
The repository includes the following components:
- Data: Historical daily returns data for the five stocks.
- Notebook: Jupyter notebook containing data analysis and machine learning models.
The dataset consists of:
- Historical daily returns for 5 stocks over a 3-year period.
- Data is obtained using QuantStats.
This project was inspired by and builds upon concepts and methodologies from the Kaggle Data Science for Financial Markets project.
Clone the repository:
git clone https://github.com/hazelglaine/financial-algorithms