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
- 4 Predictability and causality
- 5 Econophysics
- 6 Extreme Value Theory
- 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
- Part IX Numerical implementation
- Part X Analysis of portfolio allocation
- Appendix I The links with the Black–Litterman approach
- References
- Index
4 - Predictability and causality
from Part II - Dealing with extreme events
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
- 4 Predictability and causality
- 5 Econophysics
- 6 Extreme Value Theory
- 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
- Part IX Numerical implementation
- Part X Analysis of portfolio allocation
- Appendix I The links with the Black–Litterman approach
- References
- Index
Summary
Effect, n. The second of two phenomena which always appear together in the same order. The first, called a Cause, is said to generate the other – which is no more sensible than it would be for one who has never seen a dog except in pursuit of a rabbit to declare the rabbit the cause of the dog. – Ambrose Bierce, The Devil's Dictionary
The purpose of this chapter
Extreme events or, more generally, user-specified scenarios that describe atypical market conditions play a central role in the approach to asset allocation described in this book. As we shall see, our procedure requires the portfolio manager to assign conditional probabilities to the events that connect causes and effects. However, before assigning probabilities, one must identify the potential consequences of a certain conjunction of events. In particular, in order to get the procedure started, the asset manager must be able to specify what the potential consequences of a given extreme or unusual event might be. This brings into play the vexed questions both of predictability and causation, and of what an extreme event is. We briefly look at both questions in this chapter.
Before delving into a discussion of predictability and forecasting, it is important to clarify one aspect of our approach.
- Type
- Chapter
- Information
- Portfolio Management under StressA Bayesian-Net Approach to Coherent Asset Allocation, pp. 31 - 39Publisher: Cambridge University PressPrint publication year: 2014