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Portfolio management under stress : = a Bayesian-net approach to coherent asset allocation /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Portfolio management under stress :/ Riccardo Rebonato and Alexander Denev.
其他題名:	a Bayesian-net approach to coherent asset allocation /
作者:	Rebonato, Riccardo,
其他作者:	Denev, Alexander,
面頁冊數:	1 online resource (xxvi, 491 pages) :digital, PDF file(s). :
附註:	Title from publisher's bibliographic system (viewed on 05 Oct 2015).
標題:	Financial risk - Mathematical models. -
電子資源:	https://doi.org/10.1017/CBO9781107256736
ISBN:	9781107256736 (ebook)

Portfolio management under stress : = a Bayesian-net approach to coherent asset allocation /
Rebonato, Riccardo,

Portfolio management under stress :a Bayesian-net approach to coherent asset allocation /Riccardo Rebonato and Alexander Denev. - 1 online resource (xxvi, 491 pages) :digital, PDF file(s).

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.

ISBN: 9781107256736 (ebook)Subjects--Topical Terms:

997101
Financial risk
--Mathematical models.

LC Class. No.: HG4529.5 / .R43 2013

Dewey Class. No.: 332.601/519542

Portfolio management under stress : = a Bayesian-net approach to coherent asset allocation /
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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.
650 0 $a Financial risk $x Mathematical models. $3 997101
650 0 $a Investments $x Mathematical models. $3 566107
650 0 $a Portfolio management $x Mathematical models. $3 557706
700 1 $a Denev, Alexander, $e author. $3 1440998
776 0 8 $i Print version: $z 9781107048119
856 4 0 $u https://doi.org/10.1017/CBO9781107256736