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Investing in Mortgage-Backed and Asset-Backed Securities Financial Modeling with R and Open Source Analytics von Schultz, Glenn M. (eBook)

  • Erscheinungsdatum: 07.01.2016
  • Verlag: Wiley
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Investing in Mortgage-Backed and Asset-Backed Securities

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. GLENN M. SCHULTZ is the Director of mortgage analytics for Performance Trust Capital Partners. He co-edited (with Frank Fabozzi) Structured Products and Related Credit Derivatives (Wiley), as well as authored several chapters in the Handbook of MBS Securities and The Handbook of Fixed Income Securities .

Produktinformationen

    Format: PDF
    Kopierschutz: AdobeDRM
    Seitenzahl: 416
    Erscheinungsdatum: 07.01.2016
    Sprache: Englisch
    ISBN: 9781119221531
    Verlag: Wiley
    Größe: 9716 kBytes
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