Lewis Ranieri is famous for bringing securitization to the market in the 1980s at Salomon Brothers with the team of “fat guys.” You can read about him in Michael Lewis’ 1989 book Liar’s Poker. One reason he comes up in the context of NIM Optimization is mortgage prepayment models, we will get to that. Here is Ranieri’s Harvard GSD talk “Revolution in Mortgage Finance” on the Credit Crisis aftermath. Since the 80’s there has been a liquid two way market in mortgage backed securities meaning that there are buyers and sellers for MBS securities. Look at the 2014 Fed Notes from Campbell, Li, and Im Measuring Agency MBS Market Liquidity with Transaction Data, they show $7.5T outstanding MBS notional in 2013 trading at spreads between 5 and 7.5 bps between 2011 and 2013 using TRACE data. For comparison U.S. Treasuries traded at around a 2 bps spread in the same period versus Corporate bonds at 80 to 160 bps. For the MBS spreads to be that tight in that large a market it is plausible to assume the underlying quantitative modeling, if not perfect, is at least tradable. The mortgage prepayment models are part of that story.
Here is John Geanakoplos, James Tobin Professor of Economics at Yale discussing mortgage prepayment models in his lecture Modeling Mortgage Prepayments and Valuing Mortgages. Lakhbir Hayre is one of the original and main contributors to the development of prepayment models: see Anatomy of Prepayments 2000, Salomon Smith Barney Guide to Mortgage-Backed and Asset-Backed Securities, and Citigroup 2004 Hayre and Young’s Guide to Mortgage-Backed Securities. Why is this relevant to NIM Optimization? Prepayment models are the MBS market’s quantitative method for determining the expected loss write-downs (in addition to optional accelerated pay-downs) from market data and econometric data. They are tradable expectations of mortgage loan losses that are applicable to stochastic programming approaches to NIM Optimization. YieldBook and Intex are commercial suppliers of analytics for MBS and ABS valuation and cashflow analytics for liquid two-way structured finance markets. Certainly you could argue that the Credit Crisis showed that the prepayment models are not perfect. On the other hand, the accrual portfolio loan loss provisions in the $15T BHC assets are hardly modeled as rigorously as the $7.5T MBS, so it is better to do nothing and hope the VAR reserve levels capture the autocorrelation of write downs? Perhaps not.