The objective of this paper is to offer a methodology for sizing credit-sensitive Asset Backed Securities (ABS) used in the prime mortgage lending sector in the U.S. and then to evaluate their relative performance. Using a multi-factor Monte Carlo simulation framework, we perform a four-step analysis. First, we estimate scenario-specific credit losses from a given mortgage pool. We then structure the pool into a 6-pack subordination structure based on statistically-determined stress economic scenarios. Next, we estimate performance indicators of the tranches to compare risk-adjusted returns. Finally, we report our results in terms of tranche-specific risk-adjusted returns. The results indicate that the middle tranches of ABS, e.g., BBB and BB, possess the lowest risk-adjusted returns. We also find and explain a cliff phenomenon in the tranche-level principal cash flows.
| Identifer | oai:union.ndltd.org:ETSU/oai:dc.etsu.edu:etsu-works-15949 |
| Date | 01 December 2013 |
| Creators | Lin, Che Chun, Chang, Jow Ran, Chu, Ting Heng, Prather, Larry J. |
| Publisher | Digital Commons @ East Tennessee State University |
| Source Sets | East Tennessee State University |
| Detected Language | English |
| Type | text |
| Source | ETSU Faculty Works |
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