£68.46

Wiley Investing in Mortgage-Backed and Asset-Backed Securities, + Website: Financial Modeling with R and Open Source Analytics (Wiley Finance)

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£68.46 £65.04 £66.41 £67.78 £69.14 £70.51 £71.88 25 January 2026 25 January 2026 26 January 2026 27 January 2026 28 January 2026

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Description

A complete guide to investing in and managing a portfolio of mortgage- and asset-backed securities Mortgage- and asset-backed securities are not as complex as they might seem. In fact, all of the information, financial models, and software needed to successfully invest in and manage a portfolio of these securities are available to the investment professional through open source software. Investing in Mortgage and Asset-Backed Securities + Website shows you how to achieve this goal. The book draws entirely on publicly available data and open source software to construct a complete analytic framework for investing in these securities. The analytic models used throughout the book either exist in the quantlib library, as an R package, or are programmed in R and incorporated into the analytic framework used. Examines the valuation of fixed-income securities―metrics, valuation framework, and return analysis Covers residential mortgage-backed securities―security cash flow, mortgage dollar roll, adjustable rate mortgages, and private label MBS Discusses prepayment modeling and the valuation of mortgage credit Presents mortgage-backed securities valuation techniques―pass-through valuation and interest rate models Engaging and informative, this book skillfully shows you how to build, rather than buy, models and proprietary analytical platforms that will allow you to invest in mortgage- and asset-backed securities.

Key Features

Investing in Mortgage-Backed and Asset-Backed Securities, + Website: Financial Modeling with R and Open Source Analytics (Wiley Finance)

Brand: Wiley

Product Specifications

Brand
Wiley
Format
hardcover
Domain
Amazon UK
Release Date
24 February 2016
Listed Since
01 April 2014

Barcode

No barcode data available

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