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Optimizing Optimization: The Next Generation of Optimization Applications and Theory: Quantitative Finance

Autor Stephen Satchell
en Limba Engleză Hardback – 10 noi 2009
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
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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


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