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.

Potential Audience

Institutional portfolio managers, hedge FoF and multi-asset portfolio managers, risk managers, CIOs, advanced family offices.