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|a UAMI
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|a Kim, Woo Chang.
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|a Robust portfolio management in equity markets :
|b formulations, implementations, and properties.
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260 |
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|a [Place of publication not identified] :
|b John Wiley & Sons Inc,
|c 2014.
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300 |
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|a 1 online resource
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336 |
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|a text
|b txt
|2 rdacontent
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|a computer
|b c
|2 rdamedia
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338 |
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|a online resource
|b cr
|2 rdacarrier
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490 |
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|a Frank J. Fabozzi Series
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|a Cover; Title Page; Copyright; Contents; Preface; Chapter 1 Introduction; 1.1 Overview of the Chapters; 1.2 Use of MATLAB; Notes; Chapter 2 Mean-Variance Portfolio Selection; 2.1 Return of Portfolios; 2.2 Risk of Portfolios; 2.3 Diversification; 2.4 Mean-Variance Analysis; 2.5 Factor Models; 2.6 Example; Key Points; Notes; Chapter 3 Shortcomings of Mean-Variance Analysis; 3.1 Limitations on the Use of Variance; 3.2 Difficulty in Estimating the Inputs; 3.3 Sensitivity of Mean-Variance Portfolios; 3.4 Improvements on Mean-Variance Analysis; Key Points; Notes.
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|a Chapter 4 Robust Approaches for Portfolio Selection4.1 Robustness; Uncertainty Aversion; 4.2 Robust statistics; Mean vs. Median; M-Estimators; L-Estimators; Estimators of Dispersion; 4.3 Shrinkage Estimation; 4.4 Monte Carlo Simulation; Portfolio Resampling; 4.5 Constraining Portfolio Weights; 4.6 Bayesian Approach; Black-Litterman Model; Equilibrium Model; Views of Investors; Combining the Equilibrium State with Investors' Views; 4.7 Stochastic Programming; 4.8 Additional Approaches; Key Points; Notes; Chapter 5 Robust Optimization; 5.1 Worst-Case Decision Making; 5.2 Convex Optimization.
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|a DualityLinear Programming; Quadratic Programming; Conic Programming; Second-Order Cone Programming; Semidefinite Programming; 5.3 Robust Counterparts; Uncertainty Sets; Robust Linear Programming; 5.4 Interior Point Methods; Key Points; Notes; Chapter 6 Robust Portfolio Construction; 6.1 Some Preliminaries; 6.2 Mean-Variance Portfolios; 6.3 Constructing Robust Portfolios; 6.4 Robust Portfolios with Box Uncertainty; Step 1. Formulate the Robust Problem by Defining the Box Uncertainty Set; Step 2. Reformulate the Robust Counterpart with Box Uncertainty.
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|a Step 3. Use Optimization Tools to Solve the Box Uncertainty Problem6.5 Robust Portfolios with Ellipsoidal Uncertainty; Step 1. Formulate the Robust Problem by Defining the Ellipsoidal Uncertainty Set; Step 2. Reformulate the Robust Counterpart with Ellipsoidal Uncertainty; Step 3. Use Optimization Tools to Solve the Ellipsoidal Uncertainty Problem; 6.6 Closing Remarks; Key Points; Notes; Chapter 7 Controlling Third and Fourth Moments of Portfolio Returns via Robust Mean-Variance Approach; 7.1 Controlling Higher Moments of Portfolio Return; 7.2 Why Robust Formulation Controls Higher Moments.
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|a 7.3 Empirical TestsKey Points; Notes; Chapter 8 Higher Factor Exposures of Robust Equity Portfolios; 8.1 Importance of Portfolio Factor Exposure; 8.2 Fundamental Factor Models in the Equity Market; 8.3 Factor Dependency of Robust Portfolios: Theoretical Arguments; 8.4 Factor Dependency of Robust Portfolios: Empirical Findings; 8.5 Factor Movements and Robust Portfolios; 8.6 Robust Formulations That Control Factor Exposure; Key Points; Notes; Chapter 9 Composition of Robust Portfolios; 9.1 Overview of Analyses; 9.2 Composition Based on Investment Styles.
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|a "This is a comprehensive book on robust portfolio optimization, which includes up-to-date developments and will interest readers looking for advanced material on portfolio optimization. The book will also attract introductory-level readers because it begins by reviewing the foundations of portfolio optimization. The material in this book emphasizes applications in equity portfolio management and includes MATLAB codes that can assist readers of all levels in implementing robust models. The book aims to help the reader fully understand formulations, performances, and properties of robust portfolios. Application in the equity market is described throughout the book and the implementation of robust models is explained in detail with example code"--
|c Provided by publisher.
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520 |
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|a "The book will be most helpful for readers who are interested in learning about the quantitative side of equity portfolio management, mainly portfolio optimization and risk analysis. Mean-variance portfolio optimization is covered in detail, leading to an extensive discussion on robust portfolio optimization. Nonetheless, readers without prior knowledge of portfolio management or mathematical modeling should be able to follow the presentation since basic concepts are covered in each chapter. Furthermore, the main quantitative approaches are presented with MATLAB examples, allowing readers to easily implement portfolio problems in MATLAB or similar modeling software. There is an online appendix that provides the MATLAB codes presented in the chapter boxes (www.wiley.com/go/robustequitypm)"--
|c Provided by publisher.
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590 |
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|a ProQuest Ebook Central
|b Ebook Central Academic Complete
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650 |
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|a Portfolio management.
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650 |
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|a Investments
|x Mathematical models.
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650 |
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|a Investment analysis
|x Mathematical models.
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650 |
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6 |
|a Gestion de portefeuille.
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650 |
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6 |
|a Investissements
|x Modèles mathématiques.
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650 |
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6 |
|a Analyse financière
|x Modèles mathématiques.
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650 |
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7 |
|a BUSINESS & ECONOMICS
|x Investments & Securities.
|2 bisacsh
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650 |
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7 |
|a Investment analysis
|x Mathematical models
|2 fast
|
650 |
|
7 |
|a Investments
|x Mathematical models
|2 fast
|
650 |
|
7 |
|a Portfolio management
|2 fast
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776 |
0 |
8 |
|i Print version:
|a Kim, Woo Chang.
|t Robust portfolio management in equity markets.
|d [Place of publication not identified] : John Wiley & Sons Inc, 2014
|z 1118797264
|z 9781118797266
|w (OCoLC)870409988
|
830 |
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0 |
|a Frank J. Fabozzi series.
|
856 |
4 |
0 |
|u https://ebookcentral.uam.elogim.com/lib/uam-ebooks/detail.action?docID=4182966
|z Texto completo
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938 |
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