Omega Ratio Optimization: Theory And Practice
Portfolio optimization of hedge fund of funds is not a trivial task because of numerous reasons like non-normal distributions of returns, short return series, diverse risk-return profiles of underlying funds and so on. To solve these problems hedge fund investors need to employ more advanced optimization models capable to take into account tail risks and non-normal distributions. However, such models may fall into a complex area of non-convex objective functions that would require time consuming multi-extreme optimization. Though the Omega function (the Omega Ratio) presents a non-convex function, it has a great advantage - it it can be transformed to a convex model, which can be easily solved using the NLP optimization.
This tutorial discusses the practical aspects of the Omega optimization for optimization of portfolios of hedge funds or multi-asset portfolios. It compares Omega-optimal portfolios with other models (CVaR, Max Drawdown, LPM, the mean-variance optimization etc.) from a hedge fund investor's point of view and guides you through the steps of using Risk Shell to build robust Omega-optimal fund of funds.
Omega Optimization Basics
- Learn the basics of the Omega Ratio, its pros and cons for hedge fund risk assessment.
- Understand the fundamental problems of using the Omega function as an objective function.
- Understand why the Omega model should be tweaked for each hedge fund portfolio.
Omega Optimization for Hedge Fund of Funds - Step-by-step Tutorial
- Risk Shell Optimization: setting the Omega model. Application controls.
- Working with the Omega thresholds.
- Using soft and hard target returns for the Omega optimization.
- Omega optimization backtesting. Selecting best optimization time frames and rebalancing parameters.
- Practical tips: when to use the Omega optimization.
Potential Audience
Institutional portfolio managers, hedge FoF and multi-asset portfolio managers, CIOs, advanced family offices.
