In this liveProject, you’ll build a machine learning system based on the Arbitrage Pricing Theorem (APT) that can create a diversified investment portfolio designed to avoid risks. APT allows you to model the effects of different scenarios on an investment portfolio, and you’ll test this theorem on a portfolio of social media companies. You’ll run analysis to estimate coefficients, and conduct sensitivity analysis to determine important macroeconomic factors. Finally, you’ll interpret your results to find out what issues your portfolio is the most sensitive to.
This project is designed for learning purposes and is not a complete, production-ready application or solution.
This liveProject is for data analysts with an interest in financial services. Some knowledge of the finance industry will be useful. To begin this liveProject you will need to be familiar with:
- Basics of Python
- Basics of Jupyter Notebook
- Basics of finance
- Usage of APIs for data extraction
- Python for data cleaning and exploration
- Running linear regression via statsmodel in Python
you will learn
In this liveProject, you’ll learn to use one of the most reliable machine learning tools for finance and improve your understanding of financial data science.
- Risk management
- Financial risk estimation
- Financial modeling with multivariate case