Portfolio Management under Stress: A Bayesian-Net Approach to Coherent Asset Allocation
Cambridge University Press, 1/9/2014
EAN 9781107048119, ISBN10: 1107048117
Hardcover, 518 pages, 24.4 x 17 x 2.9 cm
Language: English
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.
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.
'Rebonato and Denev have demolished the status quo with their radical extension of best-practice portfolio management. The key is to integrate realistic 'extreme' scenarios into risk assessment, and they show how to use Bayesian networks to characterize precisely those scenarios. The book is rigorous yet completely practical, and reading it is a pleasure, with the 'Rebonato touch' evident throughout.' Francis X. Diebold, Paul F. and Warren S. Miller Professor of Economics, and Professor of Finance and Statistics, University of Pennsylvania