Machine Learning in Action: Live Demos for Investment Management

Many practitioners hesitate to adopt these techniques due to a lack of clarity on their practical applications or concerns about complexity. In this engaging presentation, we will explore why embracing quantitative finance and machine learning is critical, address the common challenges that hold professionals back, and demonstrate real-world applications of 3 machine learning models with accompanying code. This session is designed to bridge the gap between theory and practice, showing the power of ML to transform portfolio management.

### Agenda

1. Introduction
2. A brief description of the portfolio management workflow
3. A brief overview of machine learning in asset management
4. What obstacles do firms face in implementing machine learning and quantitative methods
5. Case Study 1: Using clustering algorithms in strategic asset allocation
6. Case Study 2: Predicting the daily return of the S&P 500.
7. Case Study 3: Assigning portfolio weights based on forecasted volatility
8. Summary and Q&A