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

• Record Nr.: UNINA9910789716503321
• Autore: Rachev S. T (Svetlozar Todorov)
• Pubbl/distr/stampa: Hoboken, N.J., : Wiley; [Chichester, : John Wiley, distributor], 2008
• ISBN: 1-281-21730-1; 0-470-25360-6; 9786611217303; 1-283-27295-4; 9786613272959; 1-118-08614-7
• Descrizione fisica: 1 online resource (39 p.)
• Collana: The Frank J. Fabozzi series
• Altri autori (Persone): StoyanovStoyan V; FabozziFrank J
• Disciplina: 332
• Soggetti: Stochastic processes; Mathematical optimization; Risk assessment - Mathematical models; Portfolio management - Mathematical models
• 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 and index.
• Nota di contenuto: 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
• Sommario/riassunto: 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.