Securitisation of Subprime Mortgage Credit

This reading is a part of the syllabus for FRM Part 2 Exam in the section ‘Credit Risk Measurement and Management

This paper covers the following:

  • An overview of the subprime mortgage securitization process and the seven key informational frictions which arise
  • How market participants work to minimize these frictions and speculate on how this process broke down
  • A complete picture of the subprime borrower and the subprime loan, discussing both predatory borrowing and predatory lending
  • The key structural features of a typical subprime securitization
  • How the rating agencies assign credit ratings to mortgagebacked securities
  • How the agencies monitor the performance of mortgage pools over time.
  • It uses the example of a mortgage pool securitized by New Century during 2006.

[gview file="http://www.ny.frb.org/research/economists/ashcraft/subprime.pdf" save=1]

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Data Science in Finance: 9-Book Bundle

Data Science in Finance Book Bundle

Master R and Python for financial data science with our comprehensive bundle of 9 ebooks.

What's Included:

  • Getting Started with R
  • R Programming for Data Science
  • Data Visualization with R
  • Financial Time Series Analysis with R
  • Quantitative Trading Strategies with R
  • Derivatives with R
  • Credit Risk Modelling With R
  • Python for Data Science
  • Machine Learning in Finance using Python

Each book comes with PDFs, detailed explanations, step-by-step instructions, data files, and complete downloadable R code for all examples.