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…mehr
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
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
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
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