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Optimizing optimization : the next generation of optimization applications and theory (2010)

Satchell, S.

Amsterdam :Academic,

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UID:

almahu_9948026424502882

Format: 1 online resource (323 p.)

ISBN: 1-282-66608-8 , 9786612666087 , 0-08-095920-2

Series Statement: Quantitative finance

Content: Optimization is the holy grail of portfolio management, creating a portfolio in which return is highest in light of the risk the client is willing to take. Portfolio optimization has been done by computer modeling for over a decade. The software providers are currently reworking their software to address shortcomings that became apparent during the meltdown. This book details how their new breed of software manages not only the meltdown problems, but also performs faster and better than ever before.This will be a must-read book for portfolio managers who need to know whether th

Note: Description based upon print version of record. , Front Cover; Optimizing Optimization: The Next Generation of Optimization Applications and Theory; Copyright Page; Contents; List of Contributors; Section One: Practitioners and Products; Chapter 1 Robust portfolio optimization using second-order cone programming; Executive Summary; 1.1 Introduction; 1.2 Alpha uncertainty; 1.3 Constraints on systematic and specific risk; 1.4 Constraints on risk using more than one model; 1.5 Combining different risk measures; 1.6 Fund of funds; 1.7 Conclusion; References , Chapter 2 Novel approaches to portfolio construction: multiple risk models and multisolution generationExecutive Summary; 2.1 Introduction; 2.2 Portfolio construction using multiple risk models; 2.2.1 Out-of-sample results; 2.2.2 Discussion and conclusions; 2.3 Multisolution generation; 2.3.1 Constraint elasticity; 2.3.2 Intractable metrics; 2.4 Conclusions; References; Chapter 3 Optimal solutions for optimization in practice; Executive Summary; 3.1 Introduction; 3.1.1 BITA Star(TM); 3.1.2 BITA Monitor(TM); 3.1.3 BITA Curve(TM); 3.1.4 BITA Optimizer(TM); 3.2 Portfolio optimization , 3.2.1 The need for optimization3.2.2 Applications of portfolio optimization; 3.2.3 Program trading; 3.2.4 Long-short portfolio construction; 3.2.5 Active quant management; 3.2.6 Asset allocation; 3.2.7 Index tracking; 3.3 Mean-variance optimization; 3.3.1 A technical overview; 3.3.2 The BITA optimizer-functional summary; 3.4 Robust optimization; 3.4.1 Background; 3.4.2 Introduction; 3.4.3 Reformulation of mean-variance optimization; 3.4.4 BITA Robust applications to controlling FE; 3.4.5 FE constraints; 3.4.6 Preliminary results; 3.4.7 Mean forecast intervals; 3.4.8 Explicit risk budgeting , 3.5 BITA GLO(TM) Gain/loss optimization3.5.1 Introduction; 3.5.2 Omega and GLO; 3.5.3 Choice of inputs; 3.5.4 Analysis and comparison; 3.5.5 Maximum holding = 100%; 3.5.6 Adding 25% investment constraint; 3.5.7 Down-trimming of emerging market returns; 3.5.8 Squared losses; 3.5.9 Conclusions; 3.6 Combined optimizations; 3.6.1 Introduction; 3.6.2 Discussion; 3.6.3 The model; 3.6.4 Incorporation of alpha and risk model information; 3.7 Practical applications: charities and endowments; 3.7.1 Introduction; 3.7.2 Why endowments matter; 3.7.3 Managing endowments; 3.7.4 The specification , 3.7.5 Trustees' attitude to risk3.7.6 Decision making under uncertainty; 3.7.7 Practical implications of risk aversion; 3.8 Bespoke optimization-putting theory into practice; 3.8.1 Request: produce optimal portfolio with exactly 50 long and 50 short holdings; 3.8.2 Request: how to optimize in the absence of forecast returns; 3.9 Conclusions; Appendix A: BITA Robust optimization; Appendix B: BITA GLO; References; Chapter 4 The Windham Portfolio Advisor; Executive Summary; 4.1 Introduction; 4.2 Multigoal optimization; 4.2.1 The problem; 4.2.2 The WPA solution; 4.2.3 Summary , 4.3 Within-horizon risk measurement , English

Additional Edition: ISBN 0-12-374952-2

Language: English

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Online Resource

Optimizing optimization : the next generation of optimization applications and theory (2010)

Satchell, Stephen 1949-

Amsterdam : Academic Press

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Details

UID:

gbv_1648908128

Format: Online-Ressource

ISBN: 9780123749529 , 0123749522 , 0080959202 , 9781282666085 , 9780080959207

Series Statement: Quantitative finance series

Content: Editor Stephen Satchell brings us a book that truly lives up to its title: optimizing optimization by taking the lessons learned about the failures of portfolio optimization from the credit crisis and collecting them into one book, providing a variety of perspectives from the leaders in both industry and academia on how to solve these problems both in theory and in practice. Industry leaders are invited to present chapters that explain how their new breed of optimization software addresses the faults of previous versions. Software vendors present their best of breed optimization software, demonstrating how it addresses the faults of the credit crisis. Cutting-edge academic articles complement the commercial applications to provide a well-rounded insight into the current landscape of portfolio optimization. Optimization is the holy grail of portfolio management, creating a portfolio in which return is highest in light of the risk the client is willing to take. Portfolio optimization has been done by computer modeling for over a decade, and several leading software companies make a great deal of money by selling optimizers to investment houses and hedge funds. Hedge funds in particular were enamored of heavily computational optimizing software, and many have been burned when this software did not perform as, er, expected during the market meltdown. The software providers are currently reworking their software to address any shortcomings that became apparent during the meltdown, and are eager for a forum to address their market and have the space to describe in detail how their new breed of software can manage not only the meltdown problems but also perform faster and better than ever before-that is, optimizing the optimizers!! In addition, there is a strong line of serious well respected research on portfolio optimization coming from the academic side of the finance world. Many different academic approaches have appeared toward optimization: some favor stochastic methods, others numerical methods, others heuristic methods. All focus on the same issues of optimizing performance at risk levels. This book will provide the forum that the software vendors are looking for to showcase their new breed of software. It will also provide a forum for the academics to showcase their latest research. It will be a must-read book for portfolio managers who need to know whether their current optimization software provider is up to snuff compared to the competition, whether they need to move to a competitor product, whether they need to be more aware of the cutting-edge academic research as well. 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

Note: Includes bibliographical references and index. - Print version record , Optimizing OptimizationStephen 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.

Additional Edition: ISBN 0123749522

Language: English

Subjects: Economics

RVK:

QK 810

Keywords: Portfoliomanagement

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URL: Volltext

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