IMF Working Papers

Local Housing Market Cycle and Loss Given Default: Evidence from Sub-Prime Residential Mortgages

By Yanan Zhang, Lu Ji, Fei Liu

July 1, 2010

Download PDF

Preview Citation

Format: Chicago

Yanan Zhang, Lu Ji, and Fei Liu. Local Housing Market Cycle and Loss Given Default: Evidence from Sub-Prime Residential Mortgages, (USA: International Monetary Fund, 2010) accessed December 21, 2024
Disclaimer: This Working Paper should not be reported as representing the views of the IMF.The views expressed in this Working Paper are those of the author(s) and do not necessarily represent those of the IMF or IMF policy. Working Papers describe research in progress by the author(s) and are published to elicit comments and to further debate

Summary

This paper studies the impact of housing market cycles on loss given default (LGD). Previous studies have shown that the current loan-to-value ratio (CLTV) is the most important determinant of LGD. This paper establishes another linkage which is between the house price cycles before the time of mortgage origination and LGD. The empirical analysis is based on a large loan-level sub-prime residential mortgage loss dataset from 1998 to 2009. Results show that house price history has a long memory in explaining LGD. Its explanatory power far exceeds the original LTV and other loan characteristics. This paper offers a countercyclical view of LGD risk. The model can be combined with a default probability model to serve as a regulatory prudential tool. Such a tool provides a solution to the inherent procyclical bias in BASEL II capital requirements, and can contribute to the safety and soundness of banking institutions.

Subject: Collateral, Housing, Housing prices, Loans, Mortgages

Keywords: LGD model, LGD rate, LGDS relative, Lower-than-average LGD, Mortgage origination, Predicted LGD, WP

Publication Details

  • Pages:

    29

  • Volume:

    ---

  • DOI:

    ---

  • Issue:

    ---

  • Series:

    Working Paper No. 2010/167

  • Stock No:

    WPIEA2010167

  • ISBN:

    9781455201785

  • ISSN:

    1018-5941