Theory and Practice in Finance
Authors: Bertrand K. Hassani
Proposes different solutions to address scenario analysis issues in financial institutions
Provides tutorials to help readers implement these solutions
Applies the solutions to stress testing scenarios
This book focuses on identifying and explaining the key determinants of scenario analysis in the context of operational risk, stress testing and systemic risk, as well as management and planning. Each chapter presents alternative solutions to perform reliable scenario analysis. The author also provides technical notes and describes applications and key characteristics for each of the solutions. In addition, the book includes a section to help practitioners interpret the results and adjust them to real-life management activities. Methodologies, including those derived from consensus strategies, extreme value theory, Bayesian networks, Neural networks, Fault Trees, frequentist statistics and data mining are introduced in such a way as to make them understandable to readers without a quantitative background. Particular emphasis is given to the added value of the implementation of these methodologies.
Table of contents
Front Matter
Introduction
Environment
The Information Set: Feeding the Scenarios
The Consensus Approach
Tilting Strategy: Using Probability Distribution Properties
Leveraging Extreme Value Theory
Fault Trees and Variations
Bayesian Networks
Artificial Neural Network to Serve Scenario Analysis Purposes
Forward-Looking Underlying Information: Working with Time Series
Dependencies and Relationships Between Variables
Back Matter
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