Pricing Of Credit-Sensitivity Residential Mortgage Asset Backed Securities Tranches

The main objective of this paper is to lay out a methodology for optimal sizing, or subordination, and pricing of the credit-sensitive Residential Mortgage Backed Securities (RMBS). To that end, we combine a Monte Carlo simulation framework with a model of cash flow waterfalls across multiple credit tranches defined within a security. The developed model is used in a two-stage sequential sizing pricing analysis: that is, first, generating an internally-consistent tranching given an empirically-fit loss distribution along with a set of stress scenarios defined a priori; and, next, estimating a riskneutral pricing of credit risk embedded in each tranche. Our preliminary results show that: the sizing differences between ARM and FRM are negligible, implying that, as long as loan- and borrower specific idiosyncratic risks factors being equal, the effects of systematic risk drivers (i.e., home price and interest rate scenarios) should be similar to both loan types; in terms of risk-adjusted return, mean IRR increases as rating goes to lower grades, and so does its dispersion across economic scenarios and, the subordination level (the sizing) for AAA decreases (increases) under a more geographically diversified mortgage pools, but not so in the NR (non-rated) tranches, implying that the diversification benefit is shown in the tail size, but not necessarily in the mean, of the loss distribution. Going forward, we will add more empirical results and will also elaborate policy implications thereof.