The Pricing of Mortgage Insurance Premiums Under Systematic and Idiosyncratic Shocks

Authors

  • Ming Pu,

  • Gang-Zhi Fan,

  • Chunsheng Ban

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    • Ming Pu is at the School of Insurance and Collaborative Innovation Center of Financial Security, Southwestern University of Finance and Economics, 55 Guanghuacun Street, Chengdu, China. Gang-Zhi Fan is at the Department of Real Estate Studies, Konkuk University, 120 Neungdong-ro, Gwangjin-gu, Seoul 143-701, Korea. Gang-Zhi Fan can be contacted via e-mail: fan10@konkuk.ac.kr. Chunsheng Ban is at the Department of Mathematics, Ohio State University, 100 Math Tower, 231 West 18th Avenue, Columbus, OH 43210-1174. USA. We would like to thank Gene C. Lai, Sheng Xiao, two anonymous referees, and seminar participants at the 16th International Congress on Insurance: Mathematics and Economics and the 2012 Asian Real Estate Society-American Real Estate and Urban Economics Society Joint International Conference for helpful comments. This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korean government (NRF-2014S1A5A8012340).

  • We would like to thank Gene C. Lai, Sheng Xiao, and seminar participants at the 16th International Congress on Insurance: Mathematics and Economics and the 2012 Asian Real Estate Society-American Real Estate and Urban Economics Society Joint International Conference for helpful comments.

Abstract

The recent financial crisis has posed new challenges to the pricing issue of mortgage insurance premiums. By extending an option-based approach to this pricing issue, we attempt to tackle several key challenges including the clustering of mortgage defaults, the diversification effect of underlying property pools, and mortgage insurers' information advantages. Our model partitions the volatility of collateralized property prices into idiosyncratic volatility and systematic volatility. Our results demonstrate that although the rising number of pooled mortgage loans can reduce the volatility of average default losses, the increasing correlation between the collateralized properties can lead to the volatility clustering of these losses.

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