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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 a tree with an interest rate model. OAS as far as i know, its better for determining the value of a portfolio of mortages or loans, if you can get the probability of prepayment and that kind of data and if you have an observed market price.

If you want to price a particular mortage with a prepayment option, you need to discount the cashflows of the option. In this case, will matter the type of option (american, bermudean, european,) when choosing a pricing engine (tree ,finite difference or monte-carlo).

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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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