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CRE Finance World, Winter 2013

The Timing of CMBS Losses studies focused on loans with strong amortization schedules, and observation does not negate the need for sound exit strategies in the Lancaster study spanned a time of increasing liquidity in the terms of leverage, amortization and loan structure. It is only to say CMBS market. that the probability of refinance default is heavily influenced by the probability of economic duress at the first scheduled maturity date. The figure below depicts the proportion of term versus refinance CMBS refinance risk was (prior to the Great Recession) masked defaults by vintage, limiting the dataset only to those loans that due to the steadily declining interest rate environment and relative have reached their original scheduled maturity date. absence of acutely adverse economic events occurring in conjunction with a significant concentration of scheduled loan maturities. Figure 13 Going forward it is hard to predict what the make-up of term versus refinance defaults will be for CMBS, because such estimation would rely on an ability to predict the trajectory of the economic recovery (or lack thereof). This question is especially important due to the fact that many special servicers are extending loans in hopes of more favorable loan workouts. If they are right, we may see refinance defaults comprise less of the total defaulted universe come 2017. If they are wrong, the level of refinance defaults will likely match if not surpass the historical range of roughly 50% to 70% (by vintage) of all defaults. For this research, we used DBRS’ CMBS Advisor research tool, which tracks over 90,000 fixed-rate conduit loans originated from the mid-1990s through to September 2012. Term vs. Refinance Default Counts — Original Maturities Prior to Q3 2012 For these loans refinance risk was more influential than term risk. 1 Lancaster, Brian P., Anthony G. Butler, Stephen P. Mayeux, Landon C. These results demonstrate how correlated CMBS loans tend to be Frerich. The CMBS Default and Loss Study: 1995–2005. April 17, 2006, as vintages are underwritten with the same standards and subject Wachovia Securities, Page 3. to the same market conditions. 2 Our construction of its default timing curve has important differences to the aforementioned past studies. Esaki/Snyderman results spanned It therefore follows that predicting the proportion of term versus a thirty-year time period that allowed for ample measurement of the balloon defaults in a specific vintage is in large part an exercise in complete lifecycle of loans. The Lancaster study used modeling predicting the probability of economic duress (or lack thereof) at techniques to artificially complete the lifecycle of loans thus expanding various points in the loans’ original scheduled terms. their dataset. We did not have the luxury of an extended time period, nor did we use modeling techniques to project future loan performance. Conclusion We therefore expect our curve to evolve as the CMBS loans that we Loan seasoning in itself likely provides a gradual positive impact on measure complete their lifecycle. probability of default and severity of loss. But timing of defaults in 3 Esaki, Howard. Commercial Mortgage Defaults: An Update. February 4, terms of years since origination is importantly driven by the timing 1999. of adverse economic events relative to loan issuance (and maturities). This was true for our data set and we believe that it would likely 4 Snyderman, Mark P. Commercial Mortgages: Default Occurrence and hold true for past and future data sets. Estimated Yield Impact. 5 Excludes the years 2008–2012 from the sample set. Likewise, the proportion of refinance defaults relative to term defaults also seems to be heavily influenced by the scheduled 6 Snyderman, Mark P. Commercial mortgages: Default occurrence and maturity date in relation to periods of economic duress. This estimated yield impact. 1991. A publication of Winter issue 2013 sponsored by CRE Finance World Winter 2013 63


CRE Finance World, Winter 2013
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