Sizing and performance of fixed-rate residential mortgage asset-backed securities tranches

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 tranchespecific 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.