Efficient asset management: a practical guide to stock portfolio optimization and asset allocation [[electronic resource] /] / Richard O. Michaud and Robert O. Michaud

• Record Nr.: UNINA9910451508403321
• Autore: Michaud Richard O. <1941->
• Pubbl/distr/stampa: New York, : Oxford University Press, 2008
• ISBN: 0-19-988719-5; 1-281-16231-0; 9786611162313; 0-19-971579-3; 1-4356-3890-5
• Edizione: [2nd ed.]
• Descrizione fisica: 1 online resource (145 p.)
• Collana: Financial management association survey and synthesis series
• Altri autori (Persone): MichaudRobert O
• Disciplina: 332.6
• Soggetti: Investment analysis - Mathematical models; Portfolio management - Mathematical models; Electronic books.
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Note generali: Description based upon print version of record.
• Nota di bibliografia: Includes bibliographical references (p. ) and index.
• Nota di contenuto: Contents; 1 Introduction; Markowitz Efficiency; An Asset Management Tool; Traditional Objections; The Most Important Limitations; Resolving the Limitations of Mean-Variance Optimization; Illustrating the Techniques; 2 Classic Mean-Variance Optimization; Portfolio Risk and Return; Defining Markowitz Efficiency; Optimization Constraints; The Residual Risk-Return Efficient Frontier; Computer Algorithms; Asset Allocation Versus Equity Portfolio Optimization; A Global Asset Allocation Example; Reference Portfolios and Portfolio Analysis; Return Premium Efficient Frontiers; Appendix: Mathematical Formulation of MV Efficiency3 Traditional Criticisms and Alternatives; Alternative Measures of Risk; Utility Function Optimization; Multiperiod Investment Horizons; Asset-Liability Financial Planning Studies; Linear Programming Optimization; 4 Unbounded MV Portfolio Efficiency; Unbounded MV Optimization; The Fundamental Limitations of Unbounded MV Efficiency; Repeating Jobson and Korkie; Implications of Jobson and Korkie Analysis; ; Statistical MV Efficiency and Implications; 5 Linear Constrained MV Efficiency; Linear Constraints; Efficient Frontier Variance; Rank-Associated Efficient PortfoliosHow Practical an Investment Tool?; 6 The Resampled Efficient FrontierTM; Efficient Frontier Statistical Analysis; Properties of Resampled Efficient Frontier Portfolios; True and Estimated Optimization Inputs; Simulation Proofs of Resampled Efficiency Optimization; Why Does It Work; Certainty Level and RE Optimality; FC Level Applications; The REF Maximum Return Point (MRP); Implications for Asset Management; Conclusion; Appendix A: Rank- Versus λ-Associated RE Portfolios; Appendix B: Robert's Hedgehog; 7 Portfolio Rebalancing, Analysis, and Monitoring; Resampled Efficiency and Distance FunctionsPortfolio Need-to-Trade Probability; Meta-Resampling Portfolio Rebalancing; Portfolio Monitoring and Analysis; Conclusion; Appendix: Confidence Region for the Sample Mean Vector; 8 Input Estimation and Stein Estimators; Admissible Estimators; Bayesian Procedures and Priors; Four Stein Estimators; James-Stein Estimator; James-Stein MV Efficiency; Out-of-Sample James-Stein Estimation; Frost-Savarino Estimator; Covariance Estimation; Stein Covariance Estimation; Utility Functions and Input Estimation; Ad Hoc Estimators; Stein Estimation Caveats; ConclusionsAppendix: Ledoit Covariance Estimation; 9 Benchmark Mean-Variance Optimization; Benchmark-Relative Optimization Characteristics; Tracking Error Optimization and Constraints; Constraint Alternatives; Roll's Analysis; Index Efficiency; A Simple Benchmark-Relative Framework; Long-Short Investing; Conclusion; 10 Investment Policy and Economic Liabilities; Misusing Optimization; Economic Liability Models; Endowment Fund Investment Policy; Pension Liabilities and Benchmark Optimization; Limitations of Actuarial Liability Estimation; Current Pension Liabilities; Total and Variable Pension Liabilities
• Sommario/riassunto: In spite of theoretical benefits, Markowitz mean-variance (MV) optimized portfolios often fail to meet practical investment goals of marketability, usability, and performance, prompting many investors to seek simpler alternatives. Financial experts Richard and Robert Michaud demonstrate that the limitations of MV optimization are not the result of conceptual flaws in Markowitz theory but unrealistic representation of investment information. What is missing is a realistic treatment of estimation error in the optimization and rebalancing process. The text provides a non-technical review of class