Valuation Commentary

Measuring and Managing Prepay Model Risk
by Alex Levin

AD&Co develops, maintains, and licenses OAS models, and strives to make the models as accurate and useful as possible, but the assumptions behind these models should not be taken for granted. The OAS method is highly dependent on modeling assumptions, most notably, the prepay model. Other problems could stem from improper interest rate distribution or volatility assumptions. With most, if not all, attention focused on controlling the interest rate risk that an OAS model can explain, mortgage companies and banks operating on an accrual accounting basis often regard OAS instability as “spread risk.” They view this risk as a ghost, a mathematical residual, something not concerning them or realized by them as long as they don’t intend to sell assets. A closer look at the spread risk reveals a “real” component that, if not quantified, hedged, and supported by capital, may dominate the bank’s exposure and even run a “well-hedged” firm into troubles.

Consider this: Spread Risk = Real Bias + Imaginary Forces

If a prepay model systematically drifts away from market expectations of prepayments, OAS levels will drift too. Hence, “spread risk” may simply reflect prepay model inadequacy which can be termed “real model’s bias”. If the model (or the market expectations) differs from the true realized prepayments, then spread risk can translate into actual losses. If, for example, the refinancing model is too slow, then the net income generated by premium MBS and IOs will be overstated – it can easily be positive on paper and negative in the real world. If the prepay model overstates housing turnover rate, then the same becomes true about discount and current-coupon MBS.

 

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