PT - JOURNAL ARTICLE AU - Rod E. Jensen AU - Jonathan Reifler TI - Automated Valuation Models and Non-Agency RMBS Property Evaluation and Analysis AID - 10.3905/JSF.2010.15.4.043 DP - 2010 Jan 31 TA - The Journal of Structured Finance PG - 43--57 VI - 15 IP - 4 4099 - https://pm-research.com/content/15/4/43.short 4100 - https://pm-research.com/content/15/4/43.full AB - This article explores various applications of automated valuation models (AVMs) in the evaluation and analysis of both loans and associated properties underlying non-agency residential mortgage-backed transactions and securities. In relation to available information only a few years ago, structured finance investors are now equipped to take a deeper and increasingly granular look into non-agency RMBS pools. In particular, the article discusses AVM property valuations in conjunction with ZIP indices as they relate to current and forward-looking surveillance activities on active, securitized loans. And it introduces the idea of a dealspecific home price time series, where such an index would track and aggregate property prices of active loans in a given transaction and could be used as a quantitative gauge of dealproperty over-, under-, or fair-valuation. Another analysis compares the results of current property valuations using ABSNet Loan HomeVal AVMs with those based on the FHFA and S&P/Case-Shiller indexes to show how substantial differences can be between the approaches. Finally, the article examines the relative statistical efficiency of the relationship between loan-level delinquency performance by ZIP code aggregation and state- and CBSA-level home price index time-adjusted valuations versus AVM-generated valuations.TOPICS: MBS and residential mortgage loans, big data/machine learning, statistical methods