Risk Model Validation (3rd edition)
First published:
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References
References
Introduction
Basics of quantitative risk models
Usage of statistics in quantitative risk models
How can a risk model fail?
The concepts of model risk and validation
Model risk frameworks
Validation tools
Regulation
Stylised facts and classical approaches
Benchmarking with machine learning
Extending the risk horizon
Modelling and simulation
Data
Model results
Impact of machine learning, outlook and conclusions
References
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American Academy of Actuaries, 2019, “Model Risk Management: A Public Policy Practice Note”, May (available at https://www.actuary.org/sites/default/files/2019–05/ModelRiskManagementPracticeNote_May2019.pdf).
American Institute of Aeronautics and Astronautics, 1998, “Guide for the Verification and Validation of Computational Fluid Dynamics Simulations”, AIAA-G-077–1998e.
Andersen, L., J. Sidenius and S. Basu, 2003, “All Your Hedges in One Basket”, Risk,16(11), pp 67–72.
Aragonés, J. R., C. Blanco and K. Dowd, 2005, “Keeping All Eyes on Model Risk”, Futures and Options World, 412, pp 57–60.
Arnoldi, J., 2009, Risk (Cambridge, England: Polity).
Artzner, P., F. Delbaen, J. M. Eber and D. Heath, 1999, “Coherent Measures of Risk”, Mathematical Finance,9(3), pp 203–28.
Barone-Adesi, G. and K. Giannopoulos, 2001, “Non-parametric VaR Techniques: Myths and Realities”, Econ
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