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Mortgage Markets in the Age of AI
Paperback
Publisher: 2peanuts.com
Published: Aug 26 2026
Pages: 264
Weight: 1.02
Height: 0.55 Width: 7.00 Depth: 10.00
Language: English
A mortgage looks like the simplest contract in finance: someone borrows against a house and pays it back monthly. It isn't. The borrower can repay early at any time - because rates fell, because a job moved, because a marriage ended - and that one option is why a mortgage is not a bond, why it can lose value whether rates rise or fall, and why an industry exists to forecast when one borrower refinances.
This book explains the US mortgage market in plain language first, then the mathematics. It follows five people through the life of one loan: Jack the borrower, Maya the loan officer, Priya the servicer, Ben the dealer, and Elena the investor. Every formula arrives attached to whoever uses it, and all of it ties back to one object: a thirty-year payment stream.
Nine chapters carry that stream from a kitchen table to a trading desk. The early chapters build the mortgage itself: amortization, underwriting, pooling, and the prepayment conventions (SMM, CPR, PSA) that describe how fast a pool pays down. The middle chapters add the machinery a desk runs on: SOFR discounting, DV01, CV01, and key rate durations; Ito's lemma applied to the Vasicek and Hull-White short-rate models; the prepayment option as a receiver swaption on the mortgage rate; and option-adjusted spread as pricing by expected discounted payoff.
The final chapters are about what breaks: why prepayment forecasting sits at the center of pricing, servicing, and hedging, and how millions of loans collapse into priceable cohorts; why a hedge that is right at 9:30 is wrong by 9:31, why no traded instrument shares Jack's psychology, and how every desk hedging convexity the same way turns a small rate move into a large one. The last chapter brings the modern toolkit - hybrid ensembles, competing-risk survival trees, neural SDEs for joint rate and home-price paths, neural pricing surrogates for real-time OAS - plus the governance that makes it safe to run with money behind it.
For analysts, investors, quantitative developers, and practitioners.
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