Assessment of mortgage default risk via Bayesian reliability models

2010 ◽  
Vol 26 (3) ◽  
pp. 308-330 ◽  
Author(s):  
Refik Soyer ◽  
Feng Xu
Keyword(s):  
Default Risk ◽  
Mortgage Default ◽  
Reliability Models

Renter Mobility and Multifamily Mortgage Default Risk

2001 ◽  
Vol 10 (1) ◽  
pp. 21-40 ◽  
Author(s):  
Charles A. Capone ◽  
Lawrence Goldberg
Keyword(s):  
Default Risk ◽  
Mortgage Default

scholarly journals Assessment of mortgage default risk via Bayesian state space models

2013 ◽  
Vol 7 (3) ◽  
pp. 1450-1473 ◽  
Author(s):  
Tevfik Aktekin ◽  
Refik Soyer ◽  
Feng Xu
Keyword(s):  
State Space ◽  
Default Risk ◽  
State Space Models ◽  
Mortgage Default

scholarly journals "Measures of mortgage default risk and local house price dynamics "

2018 ◽  
Author(s):  
Damian Damianov ◽  
Cheng Yan ◽  
Xiangdong Wang
Keyword(s):  
Default Risk ◽  
House Price ◽  
Price Dynamics ◽  
Mortgage Default ◽  
House Price Dynamics

The Double Trigger for Mortgage Default: Evidence from the Fracking Boom

2020 ◽  
Author(s):  
Chris Cunningham ◽  
Kristopher Gerardi ◽  
Lily Shen
Keyword(s):  
Household Income ◽  
Default Risk ◽  
Credit Card ◽  
Natural Experiment ◽  
House Prices ◽  
Mortgage Default ◽  
Unemployment Benefits ◽  
Income Shock ◽  
Zip Code ◽  
Shed Light

This paper exploits a natural experiment afforded by the fracking boom in Pennsylvania to shed light on the determinants of mortgage default. Looking only at mortgages originated before fracking became viable, and using the underlying geology as a supply shifter, we find that mortgages on homes exposed to shale drilling experience a significant reduction in default risk. This effect is more than four times greater for borrowers who are underwater on their loans. Additional evidence shows that fracking activity does not raise house prices, but significantly increases household income through higher royalty payments, wages, and salaries. Furthermore, we find that fracking directly leads to employment increases in the drilling/mining and construction sectors at the county level and reduces income from unemployment benefits at the ZIP-code level. Finally, in addition to reducing mortgage-default risk, we show that fracking lowers credit card delinquencies. These results are most consistent with the “double-trigger” theory of mortgage default, where underwater borrowers subject to an adverse income shock are much more likely to lose their homes to foreclosure. This paper was accepted by David Simchi-Levi, finance.

Residential Mortgage Default Risk in Hong Kong

2004 ◽  
Author(s):  
Jim Wong ◽  
Laurence Fung ◽  
Tom Fong ◽  
Angela Sze
Keyword(s):  
Hong Kong ◽  
Default Risk ◽  
Mortgage Default ◽  
Residential Mortgage

Residential Mortgage Default Risk in Hong Kong

2008 ◽  
pp. 132-156 ◽  
Author(s):  
Jim Wong ◽  
Laurence Kang-Por Fung ◽  
Tom Pak-Wing Fong ◽  
Angela Sze
Keyword(s):  
Hong Kong ◽  
Default Risk ◽  
Mortgage Default ◽  
Residential Mortgage

scholarly journals Residential Mortgage Default Risk and Market Returns of Public Mortgage Originator Firms in Kenya

2020 ◽  
Vol 16 (31) ◽  
Author(s):  
Mwikamba Tumaini Mutugi ◽  
Willy M. Muturi ◽  
Oluoch J. Oluoch
Keyword(s):  
Default Risk ◽  
Credit Rating ◽  
Secondary Data ◽  
Vital Role ◽  
Mortgage Market ◽  
Mortgage Default ◽  
Rating Systems ◽  
Market Returns ◽  
Mortgage Loans ◽  
Residential Mortgage

The mortgage market plays a vital role in the development of the real estate sector. The mortgage industry in Kenya has experienced tremendous growth since the year 2000. Despite this growth, Kenya’s mortgage debt to GDP ratio is still relatively low when compared to other economies like South Africa. Default risk has been revealed as one of the risks that significantly impacts on the profitability of mortgagees. However, literature is inconclusive with reference to the relationship between default risk and the market returns of mortgage firms. Consequently, this study sought to determine the extent to which residential mortgage default risk influences the market returns of publicly listed mortgage firms in Kenya. Default risk in this case was measured using the non-performing loans ratio: the ratio of non-performing residential mortgage loans to total residential mortgage loans and advances. The study adopted descriptive and quantitative forms of research design. A census was conducted on the eleven NSE listed mortgage originating firms. A panel data regression model was utilized to draw inference from the secondary data collected. Descriptive statistical findings revealed a mean of 0.0796 with a standard deviation of 0.04219 for residential mortgage default risk. Inferential statistics revealed an R square value of 0.2794 between residential mortgage default risk and market returns of publicly listed mortgage originators. In addition, there was significant effect between default risk and the market returns of public mortgage originators. Consequently, mortgagees should develop strategies of reducing nonperforming loans. For instance, mortgage firms can improve their credit rating systems.

Sign in / Sign up

Export Citation Format

Share Document