Extent:
Online-Ressource (256 S.)
Series:
Type of publication: Book / Working Paper
Language: English
Notes:
Description based upon print version of record
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
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
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
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
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
9.3 Composition Based on Additional Factors
ISBN: 1-118-79726-4 ; 1-118-79737-X ; 978-1-118-79737-2 ; 978-1-118-79726-6
Source:
ECONIS - Online Catalogue of the ZBW
Persistent link: https://www.econbiz.de/10011682091