Workshop: “Practical Machine Learning for Quantitative Finance”

We will focus on two concepts in machine learning that hold great promise for quant finance: regression models on Day 1, and generative models on Day 2. Each day, we will discuss theory during the first hour, and then use what we learned to solve practical quant finance problems during the second hour.

During the practice sessions, we will review, update and run code on Colab and AWS. Participants are welcome to just observe, or if desired also participate in writing or running the code (participation is strictly optional). The code will be available on GitHub after the workshop.

Day 1 – Regression Models

1. Regression model types
2. Feedforward networks
3. Autoencoders

Practice session: Estimation of Drift in Real-World Measure

Day 2 – Generative Models

1. Generative model types
2. Joint and Conditional Probabilities
3. Gibbs sampling

Practice session: Estimation of Probability in Real-World Measure

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