Stephen Satchell

Optimizing Optimization

The Next Generation of Optimization Applications and Theory

• Gebundenes Buch

Produktbeschreibung

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.

Presents a unique "confrontation" between software engineers and academics Highlights a global view of common optimization issues Emphasizes the research and market challenges of optimization software while avoiding sales pitches Accentuates real applications, not laboratory results

Produktdetails

• Elsevier Finance
• Verlag: Elsevier Science & Technology
• Seitenzahl: 328
• Erscheinungstermin: 6. April 2010
• Englisch
• Abmessung: 234mm
• Gewicht: 660g
• ISBN-13: 9780123749529
• ISBN-10: 0123749522
• Artikelnr.: 27347422

Autorenporträt

Satchell, StephenStephen Satchell is a Fellow of Trinity College, the Reader in Financial Econometrics at the University of Cambridge and Visiting Professor at Birkbeck College, City University Business School and University of Technology, Sydney. He provides consultancy for a range of city institutions in the broad area of quantitative finance. He has published papers in many journals and has a particular interest in risk.

Inhaltsangabe

Optimizing Optimization
Stephen Satchell

Section 1: Practitioners and Products
1. Robust Portfolio Optimization Using Second Order Cone Programming
Fiona Kolbert and Laurence Wormald
2. Novel Approaches to Portfolio Construction: Multiple Risk Models and Multi-Solution Generation
Sebastian Ceria, Francis Margot, Anthony Renshaw, and Anureet Saxena
3. Bitter Lessons Learned from Practical Optimization or A Holding Hand Through the Dark Valley of Infeasibility
Daryl Roxburgh, Katja Scherer, and Tim Matthews
4. The Windham Portfolio Advisor
Mark Kritzman

Section 2: Theory
5. Modeling, Estimation, and Optimization of Equity Portfolios with Heavy-tailed Distributions
Amira Biglova, Sergio Ortobelli, Svetlozar Rachev, and Frank J. Fabozzi
6. Staying Ahead on Downside Risk
Giuliano De Rossi
7. Optimization and Portfolio Selection
Hal Forsey and Frank Sortino
8. Computing Optimal Mean/Downside Risk Frontiers: the Role of Ellipticity
A.D. Hall and Stephen Satchell
9. Portfolio Optimization with 'Threshold Accepting': A Practical Guide
Manfred Gilli and Enrico Schumann
10. Some Properties Averaging Simulated Optimization Methods
J. Knight and Stephen Satchell
11. Heuristic Portfolio Optimization: Bayesian Updating with the Johnson Family of Distributions
Richard Louth
12. More Than You Ever Wanted to Know about Conditional Value at Risk-Optimization
Bernd Scherer