DATA 690 Financial Data Science

Description: The aim of the course is to introduce apply data science tools to model financial phenomenon. This course is a first step towards better understanding financial issue with the help of data science. The topics to be covered are accessing financial data via APIs, regression analysis for finance, time series analysis, net present value, simulation, and modern portfolio theory.

Tentative Schedule

  • Week 1 – Introduction to Financial Data Science and Financial Data Sources
  • Week 2- Data Cleaning with Financial Data: First Step
  • Week 3 – Data Cleaning with Financial Data: Advanced
  • Week 4 – Data Visualization with Matplotlib, Seaborn, and Plotly
  • Week 5 – Making sense of Supervised Learning in Finance: A Quick Overview
  • Week 6 – Capital Asset Pricing Model and Arbitrage Pricing Theorem
  • Week 7 – Predicting Default with Logistic Regression
  • Week 8 – Predicting Default with Tree-based models
  • Week 9 – Time Series Analysis: Theoretical Background
  • Week 10 – Time Series Analysis: Stock Price Prediction
  • Week 11- Making Sense of Unsupervised Learning in Finance: A Quick Overview
  • Week 12- Dimension Reduction and Clustering in Finance
  • Week 13 – Anomaly Detection in Finance
  • Week 14 – Review