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I have some trouble in choosing the right method/model for the valuation a prepayment option on a loan (in General). So far I had some ideas about valuatiing it via a simple PV-method but there should be better ways. According to my Research theory about ABS/MBS, in particular calculating the Option Adjusted Spread of the security, provides me the answer to my solution, as far as I understood. I read something about binomial trees or monte-carlo as a method of valuation? Is there any literature you could recommend regarding this topic?

Thanks,

Konstantin

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I've been analysing the same problem and i think that the way to go it's calibrating an interest rate model. Think of it as an option on a bond, there is plenty of literature about that.

Also you can look at Quantlib implementation of callable bonds to get an idea of how can it be implemented.

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prepayment model could be very complicated as there are so many variables could affect the prepayment rates, such as demographic, seasonality, location etc. My experience on this was I knew many companies just directly use some prepayment data from SIFMA instead of building their own model. Typical text bool models are CPR, PSA, SMM. Nowdays, machine learning should be a good tool for modeling prepayment rate

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BlackRock has the best commercially available prepayment model and Yield Book is basically the industry standard for trading and is decent.

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