Scherer / Martin Modern Portfolio Optimization with NuOPT(TM), S-PLUS®, and S+Bayes(TM)

1. Auflage 2007
ISBN: 978-0-387-27586-4
Verlag: Springer US
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 406 Seiten

In recent years portfolio optimization and construction methodologies have become an increasingly critical ingredient of asset and fund management, while at the same time portfolio risk assessment has become an essential ingredient in risk management. This trend will only accelerate in the coming years. This practical handbook fills the gap between current university instruction and current industry practice. It provides a comprehensive computationally-oriented treatment of modern portfolio optimization and construction methods using the powerful NUOPT for S-PLUS optimizer.

Autoren/Hrsg.

Scherer, Bernd

Martin, R. Douglas

Inhaltsverzeichnis

1;Preface;6
1.1;Purpose of Book;6
1.2;Intended Audience;7
1.3;Organization of the Book;7
1.4;Downloading the Software and Data;10
1.5;Using the Scripts and Data;11
1.6;Acknowledgments;12
2;Contents;14
3;List of Code Examples;17
4;Linear and Quadratic Programming;20
4.1;1.1 Linear Programming: Testing for Arbitrage;20
4.2;1.2 Quadratic Programming: Balancing Risk and Return;25
4.3;1.3 Dual Variables and the Impact of Constraints;36
4.4;1.4 Analysis of the Efficient Frontier;43
4.5;Exercises;49
4.6;Endnotes;51
5;General Optimization with SIMPLE;53
5.1;2.1 Indexing Parameters and Variables;53
5.2;2.2 Function Optimization;63
5.3;2.3 Maximum Likelihood Optimization;68
5.4;2.4 Utility Optimization;72
5.5;2.5 Multistage Stochastic Programming;79
5.6;2.6 Optimization within S-PLUS;87
5.7;Exercises;97
5.8;Endnotes;98
6;Advanced Issues in Mean- Variance Optimization;99
6.1;3.1 Nonstandard Implementations;99
6.2;3.2 Portfolio Construction and Mixed-Integer Programming;108
6.3;3.3 Transaction Costs;116
6.4;Exercises;124
6.5;Endnotes;126
7;Resampling and Portfolio Choice;127
7.1;4.1 Portfolio Resampling;127
7.2;4.2 Resampling Long-Only Portfolios;132
7.3;4.3 Introduction of a Special Lottery Ticket;133
7.4;4.4 Distribution of Portfolio Weights;138
7.5;4.5 Theoretical Deficiencies of Portfolio Construction via Resampling;144
7.6;4.6 Bootstrap Estimation of Error in Risk- Return Ratios;147
7.7;Exercises;154
7.8;Endnotes;157
8;Scenario Optimization: Addressing Non- normality;159
8.1;5.1 Scenario Optimization;159
8.2;5.2 Mean Absolute Deviation;171
8.3;5.3 Semi-variance and Generalized Semi- variance Optimization;176
8.4;5.4 Probability-Based Risk/Return Measures;182
8.5;5.5 Minimum Regret;188
8.6;5.6 Conditional Value-at-Risk;192
8.7;5.7 CDO Valuation using Scenario Optimization;207
8.8;Exercises;211
8.9;Endnotes;212
9;Robust Statistical Methods for Portfolio Construction;213
9.1;6.1 Outliers and Non-normal Returns;213
9.2;6.2 Robust Statistics versus Classical Statistics;218
9.3;6.3 Robust Estimates of Mean Returns;220
9.4;6.4 Robust Estimates of Volatility;227
9.5;6.5 Robust Betas;236
9.6;6.6 Robust Correlations and Covariances;239
9.7;6.7 Robust Distances for Determining Normal Times versus Hectic Times;244
9.8;6.8 Robust Covariances and Distances with Different Return Histories;251
9.9;6.9 Robust Portfolio Optimization;256
9.10;6.10 Conditional Value-at-Risk Frontiers: Classical and Robust;279
9.11;6.11 Influence Functions for Portfolios;294
9.12;Exercises;312
9.13;Endnotes;315
10;Bayes Methods;317
10.1;7.1 The Bayesian Modeling Paradigm;317
10.2;7.2 Bayes Models for the Mean and Volatility of Returns;321
10.3;7.3 Bayes Linear Regression Models;364
10.4;7.4 Black-Litterman Models;377
10.5;7.5 Bayes-Stein Estimators of Mean Returns;393
10.6;7.6 Appendix 7A: Inverse Chi-Squared Distributions;398
10.7;7.7 Appendix 7B: Posterior Distributions for Normal Likelihood Conjugate Priors;402
10.8;7.8 Appendix 7C: Derivation of the Posterior for Jorion’s Empirical Bayes Estimate;402
10.9;Exercises;405
10.10;Endnotes;407
11;Bibliography;410
12;Index;417