Coherent Stress Testing : A Bayesian Approach to the Analysis of Financial Stress

by
Format: eBook
Pub. Date: 2010-05-01
Publisher(s): Wiley
Availability: This title is currently not available.
  • Free Shipping Icon

    This Item Qualifies for Free Shipping!*

    *Excludes marketplace orders.

List Price: $78.75

Rent Textbook

Select for Price
There was a problem. Please try again later.

New Textbook

We're Sorry
Sold Out

Used Textbook

We're Sorry
Sold Out

eTextbook

We're Sorry
Not Available

Summary

In Coherent Stress Testing: A Bayesian Approach, industry expert Riccardo Rebonato presents a groundbreaking new approach to this important but often undervalued part of the risk management toolkit.Based on the author's extensive work, research and presentations in the area, the book fills a gap in quantitative risk management by introducing a new and very intuitively appealing approach to stress testing based on expert judgement and Bayesian networks. It constitutes a radical departure from the traditional statistical methodologies based on Economic Capital or Extreme-Value-Theory approaches.The book is split into four parts. Part I looks at stress testing and at its role in modern risk management. It discusses the distinctions between risk and uncertainty, the different types of probability that are used in risk management today and for which tasks they are best used. Stress testing is positioned as a bridge between the statistical areas where VaR can be effective and the domain of total Keynesian uncertainty. Part II lays down the quantitative foundations for the concepts described in the rest of the book. Part III takes readers through the application of the tools discussed in part II, and introduces two different systematic approaches to obtaining a coherent stress testing output that can satisfy the needs of industry users and regulators. In part IV the author addresses more practical questions such as embedding the suggestions of the book into a viable governance structure.

Table of Contents

Acknowledgements
Introduction
Why We Need Stress Testing
Plan of the Book
Suggestions for Further Reading
Data, Models and Reality
Risk and Uncertainty - or, Why Stress Testing is Not Enough
The Limits of Quantitative Risk Analysis
Risk or Uncertainty?
Suggested Reading
The Role of Models in Risk Management and Stress Testing
How Did We Get Here?
Statement of the Two Theses of this Chapter
Defence of the First Thesis (Centrality of Models)
Models as Indispensable Interpretative Tools
The Plurality-of-Models View
Defence of the Second Thesis (Coordination)
Traders as Agents
Agency Brings About Coordination
From Coordination to Positive Feedback
The Role of Stress and Scenario Analysis
Suggestions for Further Reading
What Kind of Probability Do We Need in Risk Management?
Frequentist versus Subjective Probability
Tail Co-dependence
From Structural Models to Co-dependence
Association or Causation?
Suggestions for Further Reading
The Probabilistic Tools and Concepts
Probability with Boolean Variables I: Marginal and Conditional Probabilities
The Set-up and What We are Trying to Achieve
(Marginal) Probabilities
Deterministic Causal Relationship
Conditional Probabilities
Time Ordering and Causation
An Important Consequence: Bayes' Theorem
Independence
Two Worked-Out Examples
Dangerous Running
Rare and Even More Dangerous Diseases
Marginal and Conditional Probabilities: A Very Important Link
Interpreting and Generalizing the Factors xk i
Conditional Probability Maps
Probability with Boolean Variables II: Joint Probabilities
Conditioning on More Than One Event
Joint Probabilities
A Remark on Notation
From the Joint to the Marginal and the Conditional Probabilities
From the Joint Distribution to Event Correlation
From the Conditional and Marginal to the Joint Probabilities?
Putting Independence to Work
Conditional Independence
Obtaining Joint Probabilities with Conditional Independence
At a Glance
Summary
Suggestions for Further Reading
Creating Probability Bounds
The Lay of the Land
Bounds on Joint Probabilities
How Tight are these Bounds in Practice?
Bayesian Nets I: An Introduction
Bayesian Nets: An Informal Definition
Defining the Structure of Bayesian Nets
More About Conditional Independence
What Goes in the Conditional Probability Tables?
Useful Relationships
A Worked-Out Example
A Systematic Approach
What Can We Do with Bayesian Nets?
Unravelling the Causal Structure
Estimating the Joint Probabilities
Suggestions for Further Reading
Bayesian Nets II: Constructing Probability Tables
Statement of the Problem
Marginal Probabilities - First Approach
Starting from a Fixed Probability
Starting from a Fixed Magnitude of the Move
Marginal Probabilities - Second Approach
Handling Events of Different Probability
Conditional Probabilities: A Reasonable Starting Point
Conditional Probabilities: Checks and Constraints
Necessary Conditions
Triplet Conditions
Independence
Deterministic Causation
Incompatibility of Events
Internal Compatibility of Conditional Probabilities: The Need for a Systematic Approach
Applications
Obtaining a Coherent Solution I: Linear Programming
Plan of the Work Ahead
Coherent Solution with Conditional Probabilities Only
The Methodology in Practice: First Pass
The CPU Cost of the Approach
Illustration of the Linear Programming Technique
What Can We Do with this Information?
Extracting Information with Conditional Probabilities Only
Extracting Information with Conditional and Marginal Probabilities
Obtaining a Coherent Solution II: Bayesian Nets
Solution with Marginal and n -conditioned Probabilities
Generalizing the Results
An 'Automatic' Prescription to Build Joint Probabilities
What Can We Do with this Information?
Risk-Adjusting Returns
Making It Work In Practice
Overcoming Our Cognitive Biases
Cognitive Shortcomings and Bounded Rationality
How Pervasive are Cognitive Shortcomings?
The Social Context
Adaptiveness
Representativeness
Quantification of the Representativeness Bias
Causal/Diagnostic and Positive/Negative Biases
Conclusions
Suggestions for Further Reading
Selecting and Combining Stress Scenarios
Bottom Up or Top Down?
Relative Strengths and Weaknesses of the Two Approaches
Possible Approaches to a Top-Down Analysis
Sanity Checks
How to Combine Stresses - Handling the Dimensionality Curse
Combining the Macro and Bottom-Up Approaches
Governance
The Institutional Aspects of Stress Testing
Transparency and Ease of Use
Challenge by Non-specialists
Checks for Completeness
Interactions among Different Specialists
Auditability of the Process and of the Results
Lines of Criticism
The Role of Subjective Inputs
The Complexity of the Stress-testing Process
Simple Introduction to Linear Programming
Plan of the Appendix
Linear Programming - A Refresher
The Simplex Method
References
Index
Table of Contents provided by Publisher. All Rights Reserved.

An electronic version of this book is available through VitalSource.

This book is viewable on PC, Mac, iPhone, iPad, iPod Touch, and most smartphones.

By purchasing, you will be able to view this book online, as well as download it, for the chosen number of days.

Digital License

You are licensing a digital product for a set duration. Durations are set forth in the product description, with "Lifetime" typically meaning five (5) years of online access and permanent download to a supported device. All licenses are non-transferable.

More details can be found here.

A downloadable version of this book is available through the eCampus Reader or compatible Adobe readers.

Applications are available on iOS, Android, PC, Mac, and Windows Mobile platforms.

Please view the compatibility matrix prior to purchase.