Portfolio management under stress: a Bayesian-net approach to coherent asset allocation
Portfolio Management under Stress offers a novel way to apply the well-established Bayesian-net methodology to the important problem of asset allocation under conditions of market distress or, more generally, when an investor believes that a particular scenario (such as the break-up of the Euro) may...
Gespeichert in:
| 1. Verfasser: | |
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| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Cambridge
Cambridge University Press
2013
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| Schlagworte: | |
| Online-Zugang: | BSB01 FHN01 UBG01 URL des Erstveröffentlichers |
| Zusammenfassung: | Portfolio Management under Stress offers a novel way to apply the well-established Bayesian-net methodology to the important problem of asset allocation under conditions of market distress or, more generally, when an investor believes that a particular scenario (such as the break-up of the Euro) may occur. Employing a coherent and thorough approach, it provides practical guidance on how best to choose an optimal and stable asset allocation in the presence of user specified scenarios or 'stress conditions'. The authors place causal explanations, rather than association-based measures such as correlations, at the core of their argument, and insights from the theory of choice under ambiguity aversion are invoked to obtain stable allocations results. Step-by-step design guidelines are included to allow readers to grasp the full implementation of the approach, and case studies provide clarification. This insightful book is a key resource for practitioners and research academics in the post-financial crisis world |
| Beschreibung: | Title from publisher's bibliographic system (viewed on 05 Oct 2015) |
| Beschreibung: | 1 online resource (xxvi, 491 pages) |
| ISBN: | 9781107256736 |
| DOI: | 10.1017/CBO9781107256736 |
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| 505 | 8 | |a Machine generated contents note: Part I. Our Approach in Its Context: 1. How this book came about; 2. Correlation and causation; 3. Definitions and notation; Part II. Dealing with Extreme Events: 4. Predictability and causality; 5. Econophysics; 6. Extreme value theory; Part III. Diversification and Subjective Views; 7. Diversification in modern portfolio theory; 8. Stability: a first look; 9. Diversification and stability in the Black-Litterman model; 10. Specifying scenarios: the Meucci approach; Part IV. How We Deal with Exceptional Events: 11. Bayesian nets; 12. Building scenarios for causal Bayesian nets; Part V. Building Bayesian Nets in Practice: 13. Applied tools; 14. More advanced topics: elicitation; 15. Additional more advanced topics; 16. A real-life example: building a realistic Bayesian net; Part VI. Dealing with Normal-Times Returns: 17. Identification of the body of the distribution; 18. Constructing the marginals; 19. Choosing and fitting the copula; Part VII. Working with the Full Distribution: 20. Splicing the normal and exceptional distributions; 21. The links with CAPM and private valuations; Part VIII. A Framework for Choice: 22. Applying expected utility; 23. Utility theory: problems and remedies; Part IX. Numerical Implementation: 24. Optimizing the expected utility over the weights; 25. Approximations; Part X. Analysis of Portfolio Allocation: 26. The full allocation procedure: a case study; 27. Numerical analysis; 28. Stability analysis; 29. How to use Bayesian nets: our recommended approach; 30. Appendix I. The links with the Black-Litterman approach; 31. Appendix II. Marginals, copulae and the symmetry of return distributions; Index | |
| 520 | |a Portfolio Management under Stress offers a novel way to apply the well-established Bayesian-net methodology to the important problem of asset allocation under conditions of market distress or, more generally, when an investor believes that a particular scenario (such as the break-up of the Euro) may occur. Employing a coherent and thorough approach, it provides practical guidance on how best to choose an optimal and stable asset allocation in the presence of user specified scenarios or 'stress conditions'. The authors place causal explanations, rather than association-based measures such as correlations, at the core of their argument, and insights from the theory of choice under ambiguity aversion are invoked to obtain stable allocations results. Step-by-step design guidelines are included to allow readers to grasp the full implementation of the approach, and case studies provide clarification. This insightful book is a key resource for practitioners and research academics in the post-financial crisis world | ||
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Datensatz im Suchindex
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| contents | Machine generated contents note: Part I. Our Approach in Its Context: 1. How this book came about; 2. Correlation and causation; 3. Definitions and notation; Part II. Dealing with Extreme Events: 4. Predictability and causality; 5. Econophysics; 6. Extreme value theory; Part III. Diversification and Subjective Views; 7. Diversification in modern portfolio theory; 8. Stability: a first look; 9. Diversification and stability in the Black-Litterman model; 10. Specifying scenarios: the Meucci approach; Part IV. How We Deal with Exceptional Events: 11. Bayesian nets; 12. Building scenarios for causal Bayesian nets; Part V. Building Bayesian Nets in Practice: 13. Applied tools; 14. More advanced topics: elicitation; 15. Additional more advanced topics; 16. A real-life example: building a realistic Bayesian net; Part VI. Dealing with Normal-Times Returns: 17. Identification of the body of the distribution; 18. Constructing the marginals; 19. Choosing and fitting the copula; Part VII. Working with the Full Distribution: 20. Splicing the normal and exceptional distributions; 21. The links with CAPM and private valuations; Part VIII. A Framework for Choice: 22. Applying expected utility; 23. Utility theory: problems and remedies; Part IX. Numerical Implementation: 24. Optimizing the expected utility over the weights; 25. Approximations; Part X. Analysis of Portfolio Allocation: 26. The full allocation procedure: a case study; 27. Numerical analysis; 28. Stability analysis; 29. How to use Bayesian nets: our recommended approach; 30. Appendix I. The links with the Black-Litterman approach; 31. Appendix II. Marginals, copulae and the symmetry of return distributions; Index |
| ctrlnum | (ZDB-20-CBO)CR9781107256736 (OCoLC)907964480 (DE-599)BVBBV043695676 |
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| dewey-ones | 332 - Financial economics |
| dewey-raw | 332.601/519542 |
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| dewey-tens | 330 - Economics |
| discipline | Wirtschaftswissenschaften |
| doi_str_mv | 10.1017/CBO9781107256736 |
| format | Electronic eBook |
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| id | DE-604.BV043695676 |
| illustrated | Not Illustrated |
| indexdate | 2024-07-10T07:32:44Z |
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| isbn | 9781107256736 |
| language | English |
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| spelling | Rebonato, Riccardo Verfasser aut Portfolio management under stress a Bayesian-net approach to coherent asset allocation Riccardo Rebonato and Alexander Denev Cambridge Cambridge University Press 2013 1 online resource (xxvi, 491 pages) txt rdacontent c rdamedia cr rdacarrier Title from publisher's bibliographic system (viewed on 05 Oct 2015) Machine generated contents note: Part I. Our Approach in Its Context: 1. How this book came about; 2. Correlation and causation; 3. Definitions and notation; Part II. Dealing with Extreme Events: 4. Predictability and causality; 5. Econophysics; 6. Extreme value theory; Part III. Diversification and Subjective Views; 7. Diversification in modern portfolio theory; 8. Stability: a first look; 9. Diversification and stability in the Black-Litterman model; 10. Specifying scenarios: the Meucci approach; Part IV. How We Deal with Exceptional Events: 11. Bayesian nets; 12. Building scenarios for causal Bayesian nets; Part V. Building Bayesian Nets in Practice: 13. Applied tools; 14. More advanced topics: elicitation; 15. Additional more advanced topics; 16. A real-life example: building a realistic Bayesian net; Part VI. Dealing with Normal-Times Returns: 17. Identification of the body of the distribution; 18. Constructing the marginals; 19. Choosing and fitting the copula; Part VII. Working with the Full Distribution: 20. Splicing the normal and exceptional distributions; 21. The links with CAPM and private valuations; Part VIII. A Framework for Choice: 22. Applying expected utility; 23. Utility theory: problems and remedies; Part IX. Numerical Implementation: 24. Optimizing the expected utility over the weights; 25. Approximations; Part X. Analysis of Portfolio Allocation: 26. The full allocation procedure: a case study; 27. Numerical analysis; 28. Stability analysis; 29. How to use Bayesian nets: our recommended approach; 30. Appendix I. The links with the Black-Litterman approach; 31. Appendix II. Marginals, copulae and the symmetry of return distributions; Index Portfolio Management under Stress offers a novel way to apply the well-established Bayesian-net methodology to the important problem of asset allocation under conditions of market distress or, more generally, when an investor believes that a particular scenario (such as the break-up of the Euro) may occur. Employing a coherent and thorough approach, it provides practical guidance on how best to choose an optimal and stable asset allocation in the presence of user specified scenarios or 'stress conditions'. The authors place causal explanations, rather than association-based measures such as correlations, at the core of their argument, and insights from the theory of choice under ambiguity aversion are invoked to obtain stable allocations results. Step-by-step design guidelines are included to allow readers to grasp the full implementation of the approach, and case studies provide clarification. This insightful book is a key resource for practitioners and research academics in the post-financial crisis world Mathematisches Modell Portfolio management / Mathematical models Investments / Mathematical models Financial risk / Mathematical models Wertpapierportefeuille (DE-588)4276973-5 gnd rswk-swf Aktienportefeuille (DE-588)4141737-9 gnd rswk-swf Portfolio Selection (DE-588)4046834-3 gnd rswk-swf Wertpapierportefeuille (DE-588)4276973-5 s Aktienportefeuille (DE-588)4141737-9 s Portfolio Selection (DE-588)4046834-3 s 1\p DE-604 Denev, Alexander Sonstige oth Erscheint auch als Druckausgabe 978-1-107-04811-9 https://doi.org/10.1017/CBO9781107256736 Verlag URL des Erstveröffentlichers Volltext 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Rebonato, Riccardo Portfolio management under stress a Bayesian-net approach to coherent asset allocation Machine generated contents note: Part I. Our Approach in Its Context: 1. How this book came about; 2. Correlation and causation; 3. Definitions and notation; Part II. Dealing with Extreme Events: 4. Predictability and causality; 5. Econophysics; 6. Extreme value theory; Part III. Diversification and Subjective Views; 7. Diversification in modern portfolio theory; 8. Stability: a first look; 9. Diversification and stability in the Black-Litterman model; 10. Specifying scenarios: the Meucci approach; Part IV. How We Deal with Exceptional Events: 11. Bayesian nets; 12. Building scenarios for causal Bayesian nets; Part V. Building Bayesian Nets in Practice: 13. Applied tools; 14. More advanced topics: elicitation; 15. Additional more advanced topics; 16. A real-life example: building a realistic Bayesian net; Part VI. Dealing with Normal-Times Returns: 17. Identification of the body of the distribution; 18. Constructing the marginals; 19. Choosing and fitting the copula; Part VII. Working with the Full Distribution: 20. Splicing the normal and exceptional distributions; 21. The links with CAPM and private valuations; Part VIII. A Framework for Choice: 22. Applying expected utility; 23. Utility theory: problems and remedies; Part IX. Numerical Implementation: 24. Optimizing the expected utility over the weights; 25. Approximations; Part X. Analysis of Portfolio Allocation: 26. The full allocation procedure: a case study; 27. Numerical analysis; 28. Stability analysis; 29. How to use Bayesian nets: our recommended approach; 30. Appendix I. The links with the Black-Litterman approach; 31. Appendix II. Marginals, copulae and the symmetry of return distributions; Index Mathematisches Modell Portfolio management / Mathematical models Investments / Mathematical models Financial risk / Mathematical models Wertpapierportefeuille (DE-588)4276973-5 gnd Aktienportefeuille (DE-588)4141737-9 gnd Portfolio Selection (DE-588)4046834-3 gnd |
| subject_GND | (DE-588)4276973-5 (DE-588)4141737-9 (DE-588)4046834-3 |
| title | Portfolio management under stress a Bayesian-net approach to coherent asset allocation |
| title_auth | Portfolio management under stress a Bayesian-net approach to coherent asset allocation |
| title_exact_search | Portfolio management under stress a Bayesian-net approach to coherent asset allocation |
| title_full | Portfolio management under stress a Bayesian-net approach to coherent asset allocation Riccardo Rebonato and Alexander Denev |
| title_fullStr | Portfolio management under stress a Bayesian-net approach to coherent asset allocation Riccardo Rebonato and Alexander Denev |
| title_full_unstemmed | Portfolio management under stress a Bayesian-net approach to coherent asset allocation Riccardo Rebonato and Alexander Denev |
| title_short | Portfolio management under stress |
| title_sort | portfolio management under stress a bayesian net approach to coherent asset allocation |
| title_sub | a Bayesian-net approach to coherent asset allocation |
| topic | Mathematisches Modell Portfolio management / Mathematical models Investments / Mathematical models Financial risk / Mathematical models Wertpapierportefeuille (DE-588)4276973-5 gnd Aktienportefeuille (DE-588)4141737-9 gnd Portfolio Selection (DE-588)4046834-3 gnd |
| topic_facet | Mathematisches Modell Portfolio management / Mathematical models Investments / Mathematical models Financial risk / Mathematical models Wertpapierportefeuille Aktienportefeuille Portfolio Selection |
| url | https://doi.org/10.1017/CBO9781107256736 |
| work_keys_str_mv | AT rebonatoriccardo portfoliomanagementunderstressabayesiannetapproachtocoherentassetallocation AT denevalexander portfoliomanagementunderstressabayesiannetapproachtocoherentassetallocation |