Optimizing Optimization book cover

Optimizing Optimization

The Next Generation of Optimization Applications and Theory

The practical aspects of optimization rarely receive global, balanced examinations. Stephen Satchell’s nuanced assembly of technical presentations about optimization packages (by their developers) and about current optimization practice and theory (by academic researchers) makes available highly practical solutions to our post-liquidity bubble environment. The commercial chapters emphasize algorithmic elements without becoming sales pitches, and the academic chapters create context and explore development opportunities. Together they offer an incisive perspective that stretches toward new products, new techniques, and new answers in quantitative finance.

Audience
• 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.

Hardbound, 328 Pages

Published: October 2009

Imprint: Academic Press

ISBN: 978-0-12-374952-9

Contents

  • 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

Advertisement

advert image