Residential Non-Agency MBS

Non-agency Mortgage-backed Securities are securities issued by private institutions in contract with the agency MBS which is issued by governmental or quasi-governmental agencies. The underlying collateral for non-agency MBS usually consists of mortgages which do not conform to the requirements, such as size, documentation, loan-to-value ratios, etc., of MBS issued by government agencies such as Ginnie Mae, Fannie Mae or Freddie Mac.

The mortgages in non-agency MBS can be prime mortgages, Alternative-A mortgages, Option Adjustable rate Mortgages (option ARMS), or Subprime mortgages.

Even though non-agency mortgage pass-throughs lack a government guarantee, many retain a high credit rating through the use of credit enhancement techniques.

In order to “conform” to agency standards, mortgages have loan size limits, loan to value limits, and debt to income ratio limits for the borrower.

Because borrowers can exceed these limits or may wish to have customized loan terms, many mortgages are non-conforming.

Non-agency mortgage securities are commonly structured as CMOs.

Given that the underlying mortgages of non-agency security pools have different characteristics from those of agency conforming security pools, prepayment patterns for the two types will differ.

For example, given the larger size of mortgages in a non-agency MBS security, borrowers have a high incentive to refinance whenever rates fall, so non-agency prepayment rates can be higher in a declining interest rate environment.

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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.