When to refinance mortgage loans in a stochastic interest rate environment

Jin Zheng*, Siwei Gan, Xiaoxia Feng, Dejun Xie*

*Corresponding author for this work

Research output: Chapter in Book or Report/Conference proceedingConference Proceedingpeer-review

4 Citations (Scopus)

Abstract

Refinancing refers to the replacement of an existing debt obligation with another debt obligation to take the advantage of a lower interest rate. This paper reflects our ongoing work to find a desirable refinancing time for mortgage borrowers to minimize the total payments in a dynamic interest rate environment. To simulate the alternative financial service that the market may offer, it is assumed that the future interest rate follows a stochastic model with mean-reverting property, which is essentially the only required market condition to implement our method. To make it more applicable to the real financial practice, two balance settlement schemes are considered and compared. Numerical simulations with varying samplings lead to several interesting characteristics pertaining to the optimal mortgage refinancing period. Our method is robust and user friendly, thus is useful for financial institutions and individual property investors.

Original languageEnglish
Title of host publicationInternational MultiConference of Engineers and Computer Scientists, IMECS 2012
PublisherNewswood Limited
Pages1678-1683
Number of pages6
ISBN (Print)9789881925190
Publication statusPublished - 2012
Event2012 International MultiConference of Engineers and Computer Scientists, IMECS 2012 - Kowloon, Hong Kong
Duration: 14 Mar 201216 Mar 2012

Publication series

NameLecture Notes in Engineering and Computer Science
Volume2196
ISSN (Print)2078-0958

Conference

Conference2012 International MultiConference of Engineers and Computer Scientists, IMECS 2012
Country/TerritoryHong Kong
CityKowloon
Period14/03/1216/03/12

Keywords

  • Financial optimization
  • Loan valuation
  • Monte-Carlo simulation
  • Mortgage refinancing
  • Stochastic interest rate model

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