3 MAY 2011 MODELING Modeling Commercial Real Estate Loan METHODOLOGY FROM MOODY’S ANALYTICS Credit Risk: An Overview QUANTITATIVE RESEARCH Version 2.0 Authors Abstract Jun Chen Commercial real estate (CRE) exposures represent a large share of credit portfolios for many Jing Zhang banks, insurance companies, and asset managers. It is critical that these institutions properly measure and manage the credit risk of these portfolios. In this paper, we present the Moody’s Contact Us Analytics framework for measuring commercial real estate loan credit risk, which is the model at the core of our Commercial Mortgage Metrics (CMM)™ product. We describe our modeling Americas approaches for default probability, loss given default (LGD), Expected Loss (EL), and other +1-212-553-1653 related risk measures.
[email protected] Europe Our framework first models the CRE collateral stochastic process, as driven by both +44.20.7772.5454 market-wide and idiosyncratic factors. We then apply a Monte Carlo technique to simulate the
[email protected] future paths of the collateral net operating income (NOI) and market value. A CRE loan credit Asia (Excluding Japan) event is doubly triggered by the collateral financial condition at the time of default: both the +85 2 2916 1121 sustainable NOI falls below the total debt service, and the property market value falls below
[email protected] the total outstanding loan balance. Japan +81 3 5408 4100 Moreover, in order to capture the actual observed borrower default behavior, we empirically
[email protected] calibrate the conditional probability of default (PD) function to large historical datasets.