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A Simplified Approach to modeling the credit-risk of CMO

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  • K. Rajaratnam

Abstract

The credit crisis of 2007 and 2008 has thrown much focus on the models used to price mortgage backed securities. Many institutions have relied heavily on the credit ratings provided by credit agency. The relationships between management of credit agencies and debt issuers may have resulted in conflict of interest when pricing these securities which has lead to incorrect risk assumptions and value expectations from institutional buyers. Despite the existence of sophisticated models, institutional buyers have relied on these ratings when considering the risks involved with these products. Institutional investors interested in non-agency MBS are particularly vulnerable due to both the credit risks as well as prepayment risks. This paper describes a simple simulation model that model non-agency MBS and CMO. The simulation model builds on existing models for agency MBS. It incorporates credit risks of mortgage buyers using existing models used in capital requirements as specified by the Basel II Accord.

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  • K. Rajaratnam, 2009. "A Simplified Approach to modeling the credit-risk of CMO," Papers 0903.1643, arXiv.org, revised Jan 2012.
  • Handle: RePEc:arx:papers:0903.1643
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    1. John C. Cox & Jonathan E. Ingersoll Jr. & Stephen A. Ross, 2005. "A Theory Of The Term Structure Of Interest Rates," World Scientific Book Chapters, in: Sudipto Bhattacharya & George M Constantinides (ed.), Theory Of Valuation, chapter 5, pages 129-164, World Scientific Publishing Co. Pte. Ltd..
    2. Robert Jarrow, 2017. "Derivatives," World Scientific Book Chapters, in: THE ECONOMIC FOUNDATIONS OF RISK MANAGEMENT Theory, Practice, and Applications, chapter 3, pages 19-28, World Scientific Publishing Co. Pte. Ltd..
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