Taylor's Library

Normal view MARC view ISBD view

Optimizing optimization [electronic resource] : the next generation of optimization applications and theory / [edited by] Stephen Satchell.

Contributor(s): Satchell, S. (Stephen) | ScienceDirect (Online service).
Series: Quantitative finance series: Publisher: Amsterdam ; Boston : Academic Press, c2010Description: xvi, 306 p. : ill. ; 24 cm.ISBN: 9780123749529; 0123749522.Subject(s): Portfolio management -- Data processing | Portfolio management -- Mathematical modelsGenre/Form: Electronic books.Additional physical formats: No titleDDC classification: 332.602853 Online resources: An electronic book accessible through the World Wide Web; click for information
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.
Item type Current location Call number Status Notes Date due Barcode
Main Collection Taylor's Library - Perpetual(TU)
332.602853 (Browse shelf) e-book TBSxx,44001,03,CL,PPT

Includes bibliographical references and index.

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.

Electronic reproduction. Amsterdam : Elsevier Science & Technology, 2010. Mode of access: World Wide Web. System requirements: Web browser. Title from title screen (viewed on Feb. 24, 2010). Access may be restricted to users at subscribing institutions.