Videos

Lecture 2: Stylized Market Facts

This lecture goes through Chapter 2 of the Portfolio Construction and Risk Management book about stylized market facts.

Jul 10 •

1:04:52

Lecture 1: Intro and Python setup

The first lecture of the Applied Quantitative Investment Management course, including Python setup.

Jul 3 •

54:24

9. Time Series GANs

Walkthrough of the time series GAN functionality from the Investment Simulation module.

Apr 26 •

12:59

11. Time- and State-Dependent Resampling

A video walkthrough of the Time- and State-Dependent Resampling SSRN article and Python code.

Apr 19 •

15:25

8. Risk and Return Analysis

A video walkthrough of the risk and return analysis functionality from the Investment Analysis module.

Apr 12 •

31:21

Anton Vorobets, Next Generation Investment Framework

A replay of Quant Insider webinar from March 23, 2025, that carefully presents the next generation investment framework.

Apr 10 •

54:39

7. Bayesian Nets and Causal Stress-Tests

Video going through the Bayesian nets as well as causal and predictive views and stress-testing functionality.

Apr 5 •

45:46

6. Portfolio Optimization

This video post goes through the portfolio optimization functionality of the Investment Analysis module.

Mar 29 •

51:55

5. Sequential Entropy Pooling Theory and Examples

This video post carefully goes through the Sequential Entropy Pooling theory and presents many sophisticated Python case studies.

Mar 15 •

48:30

4. Time Series Variational Autoencoders

This video presents time series variational autoencoders (VAEs) and explores how they can be used for investment simulation and missing data imputation.

Mar 9 •

53:11

3. Investment Analysis Overview

This video post gives an overview of the Investment Analysis module's functionality, including the first Python example.

Mar 2 •

51:02

2. Investment Simulation, Stationary Transformations and Fully Flexible Resampling

This video post gives an overview of the Investment Simulation module as well as the stationary transformations and Fully Flexible Resampling examples.

Feb 23 •

45:55

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