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
- 20 Splicing the normal and exceptional distributions
- 21 The links with CAPM and private valuations
- Part VIII A framework for choice
- Part IX Numerical implementation
- Part X Analysis of portfolio allocation
- Appendix I The links with the Black–Litterman approach
- References
- Index
20 - Splicing the normal and exceptional distributions
from Part VII - Working with the full distribution
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
- 20 Splicing the normal and exceptional distributions
- 21 The links with CAPM and private valuations
- Part VIII A framework for choice
- Part IX Numerical implementation
- Part X Analysis of portfolio allocation
- Appendix I The links with the Black–Litterman approach
- References
- Index
Summary
Purpose of the chapter
In the previous chapters we have obtained the joint distribution of changes in market risk factors that applies to the ‘normal’ times. As a next step, we want to obtain the joint probabilities of the changes in market risk factors derived from the events described by our Bayesian net. We are a small step away from this, and we will show how to do it in the next section.
Once this is done, the task at hand will be to conjoin these two distributions into an overall (‘spliced’) joint distribution of changes in market risk factors. And once this spliced distribution is available, given a set of weights (asset allocations) we will be able to create the full joint distribution of portfolio returns. As the distribution of portfolio returns will be a function of the assigned weights, in the next step (Chapter 24) we shall vary these weights so as to optimize some target function – typically, our chosen utility function.
Before embarking on this project, however, the preliminary step alluded to in the opening paragraph must be undertaken: we must turn the joint distribution of events produced by the Bayesian nets into a joint distribution of changes in market risk factors. This is accomplished in the next section.
Reducing the joint probability distribution
In the Bayesian nets we have built so far, only some of the nodes are directly associated with changes in market risk factors events.
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- Portfolio Management under StressA Bayesian-Net Approach to Coherent Asset Allocation, pp. 295 - 315Publisher: Cambridge University PressPrint publication year: 2014