MGTF 405: Business Forecasting, Winter 22, Fall 22

UCSD-Rady

I hold regular discussion sections to go over technical material covered in class. I present and discuss python code related to class material. Here is the Github page, where I keep lecture codes.

Here are some of the topics covered:

1. ARIMA
2. Model Selection Methods
3. Vector Autoregressions (VECM)
4. State Space Models
5. Regime Switching Models
6. Volatility Models (G/ARCH)
7. Neural Networks

MGTF 495: Data Science for Finance II, Spring 22, Spring 23

UCSD-Rady

This class covers supervised and unsupervised learning methods applied to financial data. I prepared assigments and lecture codes to support the lectures. Some topics covered in the class are:

1. Tree Based Methods
2. Logistic Models
3. Support Vector Machines
4. Time Series Clustering
5. Feed-Forward Neural Networks
6. Recurrent Neural Networks
7. Attention Networks