Advanced stochastic models, risk assessment, and portfolio optimization : the ideal risk, uncertainty, and performance measures / by Svetlozar T. Rachev, Stoyan V. Stoyanov, Frank J. Fabozzi.

Format:

Book

Author/Creator:

Rachev, S. T. (Svetlozar Todorov)

Contributor:

Stoyanov, Stoyan V.

Fabozzi, Frank J.

Series:

Frank J. Fabozzi series.

The Frank J. Fabozzi series

Language:

English

Subjects (All):

Stochastic processes.

Mathematical optimization.

Risk assessment--Mathematical models.

Risk assessment.

Portfolio management--Mathematical models.

Portfolio management.

Physical Description:

1 online resource (39 p.)

Edition:

1st ed.

Place of Publication:

Hoboken, N.J. : Wiley ; [Chichester : John Wiley, distributor], 2008.

Language Note:

English

Summary:

This groundbreaking book extends traditional approaches of risk measurement and portfolio optimization by combining distributional models with risk or performance measures into one framework. Throughout these pages, the expert authors explain the fundamentals of probability metrics, outline new approaches to portfolio optimization, and discuss a variety of essential risk measures. Using numerous examples, they illustrate a range of applications to optimal portfolio choice and risk theory, as well as applications to the area of computational finance that may be useful to financial engineers.

Contents:

Advanced Stochastic Models, Risk Assessment, and Portfolio Optimization; Contents; Preface; Acknowledgments; About the Authors; Chapter 1 Concepts of Probability; 1.1 INTRODUCTION; 1.2 BASIC CONCEPTS; 1.3 DISCRETE PROBABILITY DISTRIBUTIONS; 1.4 CONTINUOUS PROBABILITY DISTRIBUTIONS; 1.5 STATISTICAL MOMENTS AND QUANTILES; 1.6 JOINT PROBABILITY DISTRIBUTIONS; 1.7 PROBABILISTIC INEQUALITIES; 1.8 SUMMARY; BIBLIOGRAPHY; Chapter 2 Optimization; 2.1 INTRODUCTION; 2.2 UNCONSTRAINED OPTIMIZATION; 2.3 CONSTRAINED OPTIMIZATION; 2.4 SUMMARY; BIBLIOGRAPHY; Chapter 3 Probability Metrics; 3.1 INTRODUCTION

3.2 MEASURING DISTANCES: THE DISCRETE CASE3.3 PRIMARY, SIMPLE, AND COMPOUND METRICS; 3.4 SUMMARY; 3.5 TECHNICAL APPENDIX; BIBLIOGRAPHY; Chapter 4 Ideal Probability Metrics; 4.1 INTRODUCTION; 4.2 THE CLASSICAL CENTRAL LIMIT THEOREM; 4.3 THE GENERALIZED CENTRAL LIMIT THEOREM; 4.4 CONSTRUCTION OF IDEAL PROBABILITY METRICS; 4.5 SUMMARY; 4.6 TECHNICAL APPENDIX; BIBLIOGRAPHY; Chapter 5 Choice under Uncertainty; 5.1 INTRODUCTION; 5.2 EXPECTED UTILITY THEORY; 5.3 STOCHASTIC DOMINANCE; 5.4 PROBABILITY METRICS AND STOCHASTIC DOMINANCE; 5.5 SUMMARY; 5.6 TECHNICAL APPENDIX; BIBLIOGRAPHY

Chapter 6 Risk and Uncertainty6.1 INTRODUCTION; 6.2 MEASURES OF DISPERSION; 6.3 PROBABILITY METRICS AND DISPERSION MEASURES; 6.4 MEASURES OF RISK; 6.5 RISK MEASURES AND DISPERSION MEASURES; 6.6 RISK MEASURES AND STOCHASTIC ORDERS; 6.7 SUMMARY; 6.8 TECHNICAL APPENDIX; BIBLIOGRAPHY; Chapter 7 Average Value-at-Risk; 7.1 INTRODUCTION; 7.2 AVERAGE VALUE-AT-RISK; 7.3 AVaR ESTIMATION FROM A SAMPLE; 7.4 COMPUTING PORTFOLIO AVaR IN PRACTICE; 7.5 BACKTESTING OF AVaR; 7.6 SPECTRAL RISK MEASURES; 7.7 RISK MEASURES AND PROBABILITY METRICS; 7.8 SUMMARY; 7.9 TECHNICAL APPENDIX; BIBLIOGRAPHY

Chapter 8 Optimal Portfolios8.1 INTRODUCTION; 8.2 MEAN-VARIANCE ANALYSIS; 8.3 MEAN-RISK ANALYSIS; 8.4 SUMMARY; 8.5 TECHNICAL APPENDIX; BIBLIOGRAPHY; Chapter 9 Benchmark Tracking Problems; 9.1 INTRODUCTION; 9.2 THE TRACKING ERROR PROBLEM; 9.3 RELATION TO PROBABILITY METRICS; 9.4 EXAMPLES OF r.d. METRICS; 9.5 NUMERICAL EXAMPLE; 9.6 SUMMARY; 9.7 TECHNICAL APPENDIX; BIBLIOGRAPHY; Chapter 10 Performance Measures; 10.1 INTRODUCTION; 10.2 REWARD-TO-RISK RATIOS; 10.3 REWARD-TO-VARIABILITY RATIOS; 10.4 SUMMARY; 10.5 TECHNICAL APPENDIX; BIBLIOGRAPHY; Index

Notes:

Description based upon print version of record.

Includes bibliographical references and index.

ISBN:

9786611217303

9786613272959

9781281217301

1281217301

9780470253601

0470253606

9781283272957

1283272954

9781118086148

1118086147

OCLC:

608622380