Optimizing Optimization: The Next Generation of Optimization Applications and Theory: Quantitative Finance
Autor Stephen Satchellen Limba Engleză Hardback – 10 noi 2009
- 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
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Specificații
ISBN-13: 9780123749529
ISBN-10: 0123749522
Pagini: 328
Ilustrații: Illustrated
Dimensiuni: 152 x 229 x 22 mm
Greutate: 0.65 kg
Editura: ELSEVIER SCIENCE
Seria Quantitative Finance
ISBN-10: 0123749522
Pagini: 328
Ilustrații: Illustrated
Dimensiuni: 152 x 229 x 22 mm
Greutate: 0.65 kg
Editura: ELSEVIER SCIENCE
Seria Quantitative Finance
Public țintă
• 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.
Cuprins
Optimizing OptimizationStephen SatchellSection 1: Practitioners and Products1. Robust Portfolio Optimization Using Second Order Cone ProgrammingFiona Kolbert and Laurence Wormald2. Novel Approaches to Portfolio Construction: Multiple Risk Models and Multi-Solution GenerationSebastian Ceria, Francis Margot, Anthony Renshaw, and Anureet Saxena3. Bitter Lessons Learned from Practical Optimization or A Holding Hand Through the Dark Valley of InfeasibilityDaryl Roxburgh, Katja Scherer, and Tim Matthews4. The Windham Portfolio AdvisorMark KritzmanSection 2: Theory5. Modeling, Estimation, and Optimization of Equity Portfolios with Heavy-tailed DistributionsAmira Biglova, Sergio Ortobelli, Svetlozar Rachev, and Frank J. Fabozzi6. Staying Ahead on Downside RiskGiuliano De Rossi7. Optimization and Portfolio SelectionHal Forsey and Frank Sortino8. Computing Optimal Mean/Downside Risk Frontiers: the Role of EllipticityA.D. Hall and Stephen Satchell9. Portfolio Optimization with ‘Threshold Accepting’: A Practical GuideManfred Gilli and Enrico Schumann10. Some Properties Averaging Simulated Optimization MethodsJ. Knight and Stephen Satchell11. Heuristic Portfolio Optimization: Bayesian Updating with the Johnson Family of DistributionsRichard Louth12. More Than You Ever Wanted to Know about Conditional Value at Risk-OptimizationBernd Scherer