Estimating Loan‐to‐Value Distributions

Korteweg, Arthur G.; Sørensen, Morten

doi:10.1111/1540-6229.12086

Cited by 31 publications

(12 citation statements)

References 52 publications

(48 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…For retail properties, the average implied volatility is 18.84%, and for multifamily properties it is 17.05%. Although these volatilities are higher than the values that appeared in the early literature, they are consistent with more recent estimates, including Korteweg and Sørensen ()…”

Section: Structural Modeling Evidencesupporting

confidence: 91%

CMBS Subordination, Ratings Inflation, and Regulatory‐Capital Arbitrage

Stanton¹,

Wallace

2017

Financial Management

View full text Add to dashboard Cite

Using detailed origination and performance data on a comprehensive sample of CMBS deals, along with their underlying loans and a set of similarly rated residential MBS, we apply reduced-form and structural modeling strategies to test for regulatorycapital arbitrage and ratings inflation in the CMBS market. We find that the spread between AAA CMBS yields and AAA corporate bond yields fell significantly following a loosening of capital requirements for highly rated CMBS in 2002, while no comparable drop occurred for lower-rated bonds (which experienced no similar regulatory change). We also find that AA-rated CMBS upgraded to AAA significantly faster than comparable AA-rated residential RMBS (for which there was also no change in risk-based capital requirements). We use a structural model to investigate these results in more detail, and find that little else changed in the CMBS market over this period except for the rating agencies' subordination levels.

show abstract

Section: Structural Modeling Evidencesupporting

confidence: 91%

CMBS Subordination, Ratings Inflation, and Regulatory‐Capital Arbitrage

Stanton¹,

Wallace

2017

Financial Management

View full text Add to dashboard Cite

show abstract

“…As LTV ratios are a convex function of asset valuations, we expect the effect of using the average local HPI rather than the actual, unobserved heterogeneous property-level house price to lead to an underestimate of CLTV ratios (see e.g. Korteweg and Sorensen 2016). 14 In addition, previous research indicates that underwater borrowers reduce their housing maintenance and investment, suggesting that our procedure may overestimate home values for borrowers at or near the underwater mark (Melzer 2013, Haughwout et al 2013.…”

Section: Definitions and Datasetsmentioning

confidence: 94%

Tracking and Stress-Testing U.S. Household Leverage

2018

View full text Add to dashboard Cite

Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. AbstractBorrowers' housing equity is an important component of their wealth and a critical determinant of their vulnerability to shocks. In this paper, we create a unique data set that allows us to provide a comprehensive look at the ratio of housing debt to housing values-what we refer to as household leverage-at the micro level. An advantage of our data is that we are able to study the evolution of household leverage over time and across locations in the United States. We find that leverage was at a very low point just prior to the large declines in house prices that began in 2006, but it rose very quickly thereafter, despite reductions in housing debt. As of late 2015, leverage statistics are approaching their pre-crisis levels, as house prices have risen over 30 percent nationally since 2012. We use our borrower-level leverage measures and another unique feature of our data-updated borrower credit scores-to conduct "stress tests": projecting leverage and defaults under various adverse house price scenarios. We find that while the riskiness of the household sector has declined significantly since 2012, it remains vulnerable to very severe declines in house prices.

show abstract

“…Our contribution is analyzing how di↵erent measures of CLT V a↵ect predicted outcomes. 28 Korteweg and Sorensen (2016) show that current approaches to updating LTV, including the use of city-level indices, can seriously understate the number of houses that are underwater by up to 80%, which has been shown to significantly increase the likelihood of default. Yang, Lin, and Cho (2011) find that not fully accounting for the cross-sectional dispersion of house prices is a major source of this bias and can significantly a↵ect assessments of mortgage default risk.…”

Section: Credit Modelmentioning

confidence: 99%