Optimizing Optimization, 1st Edition

Readership

• Portfolio managers in buy-side firms (hedge funds, mutual funds, pension funds) and investment houses
• CTOs who make purchasing decisions for financial optimization software.
• Research staff at top quantitative investing companies like BGI and SSgA.
• Masters and PhD students in financial engineering programs worldwide.

Optimizing Optimization, 1st Edition

Optimizing Optimization

Stephen Satchell

Section 1: Practitioners and Products

Chapter 1: Robust Portfolio Optimization Using Second Order Cone Programming

Fiona Kolbert and Laurence Wormald

Chapter 2: Novel Approaches to Portfolio Construction: Multiple Risk Models and Multi-Solution Generation

Sebastian Ceria, Francis Margot, Anthony Renshaw, and Anureet Saxena

Chapter 3: Bitter Lessons Learned from Practical Optimization or A Holding Hand Through the Dark Valley of Infeasibility

Daryl Roxburgh, Katja Scherer, and Tim Matthews

Chapter 4: The Windham Portfolio Advisor

Mark Kritzman

Section 2: Theory

Chapter 5: Modeling, Estimation, and Optimization of Equity Portfolios with Heavy-tailed Distributions

Amira Biglova, Sergio Ortobelli, Svetlozar Rachev, and Frank J. Fabozzi

Chapter 6: Staying Ahead on Downside Risk

Giuliano De Rossi

Chapter 7: Optimization and Portfolio Selection

Hal Forsey and Frank Sortino

Chapter 8: Computing Optimal Mean/Downside Risk Frontiers: the Role of Ellipticity

A.D. Hall and Stephen Satchell

Chapter 9: Portfolio Optimization with ‘Threshold Accepting’: A Practical Guide

Manfred Gilli and Enrico Schumann

Chapter 10: Some Properties Averaging Simulated Optimization Methods

J. Knight and Stephen Satchell

Chapter 11: Heuristic Portfolio Optimization: Bayesian Updating with the Johnson Family of Distributions

Richard Louth

Chapter 12: More Than You Ever Wanted to Know about Conditional Value at Risk-Optimization

Bernd Scherer