Skip to main content Accessibility help
×
Hostname: page-component-586b7cd67f-gb8f7 Total loading time: 0 Render date: 2024-11-30T19:10:15.616Z Has data issue: false hasContentIssue false

4 - Beyond Exceedance-Based Backtesting of Value-at-Risk Models: Methods for Backtesting the Entire Forecasting Distribution Using Probability Integral Transform

Published online by Cambridge University Press:  02 March 2023

David Lynch
Affiliation:
Federal Reserve Board of Governors
Iftekhar Hasan
Affiliation:
Fordham University Graduate Schools of Business
Akhtar Siddique
Affiliation:
Office of the Comptroller of the Currency
Get access

Summary

This chapter assesses the accuracy and possible misspecification of VaR models and offers a comparison of backtesting results using PITs over exceedances for the same sample of real portfolios. It investigates results from a set of tests used to assess unconditional coverage, conditional coverage, and independence properties of the realized VaR exceptions. This also presents a comprehensive overview of tests used to assess the uniformity and independence properties of a series of PIT estimates generated from real-world risk models. The analysis includes tests based on the empirical CDF (e.g., Kolmogorov–Smirnov; Cramér–Von Mises; and Anderson–Darling) as well as tests of dependence based on regression analysis of observed PITs.

Type
Chapter
Information
Publisher: Cambridge University Press
Print publication year: 2023

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Berkowitz, J. (2001). Testing density forecasts, with applications to risk management. Journal of Business and Economic Statistics, 19(4), 465474.Google Scholar
Berkowitz, J. and O’Brien, J. (2002). How Accurate Are Value-at-Risk Models at Commercial Banks. Journal of Finance, 57(3), 1093–1111.CrossRefGoogle Scholar
Berkowitz, J., Christoffersen, P. and Pelletier, D. (2016). Evaluating Value-at-Risk models with desk-level data. Management Science, 57(12), 22132227.Google Scholar
Campbell, S. (2006). A review of backtesting and backtesting procedures. Journal of Risk, 9(2), 117.CrossRefGoogle Scholar
Christoffersen, P. (1998). Evaluating interval forecasts. International Economic Review, 39, 841862.Google Scholar
Christoffersen, P., Hahn, J. and Inoue, A. (2001). Testing and comparing Value-at-Risk measures. Journal of Empirical Finance, 8, 325342.Google Scholar
Christoffersen, P. and Pelletier, D. (2004). Backtesting Value-at-Risk: A duration-based approach. Journal of Financial Econometrics, 2(1), 84108.Google Scholar
Diebold, F., Gunther, T., and Tay, A. (1998). Evaluating density forecasts with applications to financial risk management. International Economic Review, 39(4), 863883.CrossRefGoogle Scholar
Federal Register (2013). Market Risk Capital Rule; Vol. 78 No. 198.Google Scholar
Jorion, P. (2002). How informative are Value-at-Risk disclosures. The Accouting Review, 77(4), 911931.Google Scholar
Kupiec, P. (1995). Techniques for verifying the accuracy of risk management models. Journal of Derivatives, 3, 7384.CrossRefGoogle Scholar
Ljung, G. and Box, G. (1978). On a measure of a lack of fit in time series models. Biometrika, 65(2), 297303.Google Scholar
Marshall, C. and Siegel, M. (1997). Value-at-Risk: Implementing a risk measurement standard. Journal of Derivatives, 4, 91111.Google Scholar
Noceti, P., Smith, J., and Hodges, S. (2003). An evaluation of tests of distributional forecasts. Journal of Forecasting, 22(6–7), 447455.Google Scholar
Pritsker, M. (1997). Evaluating Value-at-Risk methodologies: Accuracy versus computational time. Journal of Financial Services Research, 12, 201242.Google Scholar
Rosenblatt, M. (1952). Remarks on a multivariate transformation. Annals of Mathematical Statistics, 23, 470472.Google Scholar

Save book to Kindle

To save this book to your Kindle, first ensure [email protected] is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

Available formats
×

Save book to Dropbox

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Dropbox.

Available formats
×

Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

Available formats
×