Accuracy of Mortgage Portfolio Risk Forecasts During Financial Crises

European Journal of Operational Research 249 (2016), 440-456

Posted: 28 Feb 2018

See all articles by Yongwoong Lee

Yongwoong Lee

Department of International Finance, Hankuk University of Foreign Studies

Daniel Roesch

University of Regensburg

Harald (Harry) Scheule

University of Technology Sydney (UTS) - School of Finance and Economics; Financial Research Network

Date Written: February 19, 2018

Abstract

This paper explores whether factor based credit portfolio risk models are able to predict losses in severe economic downturns such as the recent Global Financial Crisis (GFC) within standard confidence levels. The paper analyzes (i) the accuracy of default rate forecasts, and (ii) whether forecast downturn percentiles (Value-at-Risk, VaR) are sufficient to cover default rate outcomes over a quarterly and an annual forecast horizon.Uninformative maximum likelihood and informative Bayesian techniques are compared as they imply different degrees of uncertainty.

We find that quarterly VaR estimates are generally sufficient but annual VaR estimates may be insufficient during economic downturns. In addition, the paper develops and analyzes models based on auto-regressive adjustments of scores, which provide a higher forecast accuracy. The consideration of parameter uncertainty and auto-regressive error terms mitigates the shortfall.

Keywords: Bayesian estimation, Maximum likelihood estimation, Model risk, Mortgage Value-at-risk

JEL Classification: C51

Suggested Citation

Lee, Yongwoong and Roesch, Daniel and Scheule, Harald, Accuracy of Mortgage Portfolio Risk Forecasts During Financial Crises (February 19, 2018). European Journal of Operational Research 249 (2016), 440-456, Available at SSRN: https://ssrn.com/abstract=3126280

Yongwoong Lee (Contact Author)

Department of International Finance, Hankuk University of Foreign Studies ( email )

81 Oedae-ro, Mohyeon-myeon, Cheoin-gu
Yongin-si, Gyeonggi-do
Korea, Republic of (South Korea)

Daniel Roesch

University of Regensburg ( email )

Chair of Statistics and Risk Management
Faculty of Business, Economics and BIS
Regensburg, 93040
Germany

HOME PAGE: http://www-risk.ur.de/

Harald Scheule

University of Technology Sydney (UTS) - School of Finance and Economics ( email )

P.O. Box 123
Broadway, NSW 2007
Australia

HOME PAGE: http://https://www.uts.edu.au/staff/harald.scheule

Financial Research Network ( email )

C/- University of Queensland Business School
St Lucia, 4071 Brisbane
Queensland
Australia

HOME PAGE: http://www.firn.org.au

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