TA Work

MGTF 405: Business Forecasting, Winter 22, Fall 22


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


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

Posted on:
October 2, 2022
1 minute read, 127 words
See Also: