Hedge Fund Style Analysis: Advanced Techniques
The is the 2nd installment of our Hedge Fund Style Analysis webinars, a continuation of the 'Introduction to Style Analysis' tutorial. This tutorial discusses two main topics: how to improve the factor model using advanced techniques (the Elastic-net, LASSO, Kalman filter etc) and how to enhance the explanatory power of factor subsets, i.e. to create the best-fit factor subsets for a particular investment vehicle.
Advanced Regression Models for Hedge Fund Style Analysis
- Understand the limitations and drawbacks of the traditional multiple regression models: direct, stepwise, backward, forward and split regression.
- Learn how the Elastic-Net models can help you improve the factor model for hedge fund style analysis.
- Understand the LASSO and Rigid regression models.
- Learn the concept of the Kalman filter for Dynamic Style Analysis of hedge funds.
How To Find The Best-Fit Factor Subsets for Style Analysis - Step-by-step Tutorial
- Using Principal Component Analysis to enhance factor subsets.
- Using the Akaike Information Criterion (AIC) and Elastic-Net models for selecting explanatory factors.
Hedge Fund Style Analysis in Risk Shell: Practical Examples
- Risk Shell controls, options and settings for Static and Dynamic Style Analysis.
- Style Analysis examples: hedge funds, fund of funds, traditional long-only funds and equities.
Institutional portfolio managers, hedge FoF and multi-asset portfolio managers, risk managers, CIOs, advanced family offices.