Book contents
- Frontmatter
- Dedication
- Contents
- List of figures
- List of tables
- Acknowledgements
- Part I Our approach in its context
- Part II Dealing with extreme events
- Part III Diversification and subjective views
- Part IV How we deal with exceptional events
- Part V Building Bayesian nets in practice
- Part VI Dealing with normal-times returns
- Part VII Working with the full distribution
- Part VIII A framework for choice
- 22 Applying expected utility
- 23 Utility theory: problems and remedies
- Part IX Numerical implementation
- Part X Analysis of portfolio allocation
- Appendix I The links with the Black–Litterman approach
- References
- Index
22 - Applying expected utility
from Part VIII - A framework for choice
Published online by Cambridge University Press: 18 December 2013
- Frontmatter
- Dedication
- Contents
- List of figures
- List of tables
- Acknowledgements
- Part I Our approach in its context
- Part II Dealing with extreme events
- Part III Diversification and subjective views
- Part IV How we deal with exceptional events
- Part V Building Bayesian nets in practice
- Part VI Dealing with normal-times returns
- Part VII Working with the full distribution
- Part VIII A framework for choice
- 22 Applying expected utility
- 23 Utility theory: problems and remedies
- Part IX Numerical implementation
- Part X Analysis of portfolio allocation
- Appendix I The links with the Black–Litterman approach
- References
- Index
Summary
The purpose of this chapter
Chapter 24 will show how to obtain an optimal allocation across the asset classes over which the portfolio manager has a mandate to invest. The result of the optimization will, of course, depend on her choice of utility function. We therefore discuss this important topic in the present chapter. We also make an important distinction between ‘proper’ and what we call ‘reduced-form’ utility functions. The latter should be used with care, but can prove useful in practical applications.
In the next chapter we discuss some alternatives to traditional expected utility maximization (either in its ‘proper’ or in its reduced form). Some of these extensions come from ‘within the theory’ (such as the family of Epstein-Zinn recursive utilities), and some from ‘outside’, such as some forms of Robust-Decision-Making theory. We briefly discuss these topics not because we want to wade into the deep waters of the utility debate – tempting and interesting as doing so might be. Rather we touch on some alternative choice strategies because we find that for our purposes the results provided by ‘straight’ utility maximization display some very undesirable features: in primis, the instability of the optimal allocation weights to small changes in the expected returns. (This feature, as we shall see, is intimately linked to the way utility functions have to be ‘calibrated’.) This instability of the allocation weights is a worrisome feature of virtually any asset-allocation technique based on the maximization of expected utility reasonably calibrated to risk aversion.
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- Portfolio Management under StressA Bayesian-Net Approach to Coherent Asset Allocation, pp. 343 - 352Publisher: Cambridge University PressPrint publication year: 2014