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Optimal Recursive Refinancing and the Valuation of Mortgage-Backed Securities

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  • Francis A. Longstaff

Abstract

We study the optimal recursive refinancing problem where a borrower minimizes his lifetime mortgage costs by repeatedly refinancing when rates drop sufficiently. Key factors affecting the optimal decision are the cost of refinancing and the possibility that the mortgagor may have to refinance at a premium rate because of his credit. The optimal recursive strategy often results in prepayment being delayed significantly relative to traditional models. Furthermore, mortgage values can exceed par by much more than the cost of refinancing. Applying the recursive model to an extensive sample of mortgage-backed security prices, we find that the implied credit spreads that match these prices closely parallel borrowers' actual spreads at the origination of the mortgage. These results suggest that optimal recursive models may provide a promising alternative to the reduced-form prepayment models widely used in practice.

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Bibliographic Info

Paper provided by National Bureau of Economic Research, Inc in its series NBER Working Papers with number 10422.

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Date of creation: Apr 2004
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Publication status: published as Longstaff, Francis A. "Borrower Credit And The Valuation Of Mortgage-Backed Securities," Real Estate Economics, 2005, v33(4,Winter), 619-661.
Handle: RePEc:nbr:nberwo:10422

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Cited by:
  1. Merino Maestre, María & Pérez Sainz de Rozas, Gloria & Escudero Bueno, Laureano F. & Garín Martín, María Araceli, 2005. "A two-stage stochastic integer programming approach," BILTOKI 2005-01, Universidad del País Vasco - Departamento de Economía Aplicada III (Econometría y Estadística).
  2. John Y. Campbell, 2006. "Household Finance," Journal of Finance, American Finance Association, vol. 61(4), pages 1553-1604, 08.
  3. Xavier Gabaix & Arvind Krishnamurthy & Olivier Vigneron, 2005. "Limits of Arbitrage: Theory and Evidence from the Mortgage-Backed Securities Market," NBER Working Papers 11851, National Bureau of Economic Research, Inc.

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