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Can home-owners benefit from stochastic programming models? A study of mortgage choice in Denmark

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  • Kourosh Rasmussen
  • Claus Madsen
  • Rolf Poulsen

Abstract

The Danish mortgage market is large and sophisticated. However, most Danish mortgage banks advise private home-owners based on simple, if sensible, rules of thumb. In recent years a number of papers (from Nielsen and Poulsen in J Econ Dyn Control 28:1267–1289, 2004 over Rasmussen and Zenios in J Risk 10:1–18, 2007 to Pedersen et al. in Ann Oper Res, 2013 ) have suggested a model-based, stochastic programming approach to mortgage choice. This paper gives an empirical comparison of performance over the period 2000–2010 of the rules of thumb to the model-based strategies. While the rules of thumb slightly outperform a passive benchmark on average and are less risky than pure adjustable rate loans, we find considerable gains from using the model-based strategies. Using a strategy that minimizes conditional-value-at-risk lowers average effective yearly interest rate over a 10-year horizon by 0.3–0.9 %-points (depending on the borrower’s level of conservatism) compared to the rules of thumb without increasing the risk. The answer to the question in the title is thus affirmative. Copyright Springer-Verlag Berlin Heidelberg 2014

Suggested Citation

  • Kourosh Rasmussen & Claus Madsen & Rolf Poulsen, 2014. "Can home-owners benefit from stochastic programming models? A study of mortgage choice in Denmark," Computational Management Science, Springer, vol. 11(1), pages 5-23, January.
    • Handle: RePEc:spr:comgts:v:11:y:2014:i:1:p:5-23
    DOI: 10.1007/s10287-013-0170-x
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    References listed on IDEAS

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    1. S. Nielsen, Soren & Poulsen, Rolf, 2004. "A two-factor, stochastic programming model of Danish mortgage-backed securities," Journal of Economic Dynamics and Control, Elsevier, vol. 28(7), pages 1267-1289, April.
    2. Christensen, Jens H.E. & Diebold, Francis X. & Rudebusch, Glenn D., 2011. "The affine arbitrage-free class of Nelson-Siegel term structure models," Journal of Econometrics, Elsevier, vol. 164(1), pages 4-20, September.
    3. John Y. Campbell, 2013. "Mortgage Market Design," Review of Finance, European Finance Association, vol. 17(1), pages 1-33.
    4. Allen Frankel & Jacob Gyntelberg & Kristian Kjeldsen & Mattias Persson, 2004. "The Danish mortgage market," BIS Quarterly Review, Bank for International Settlements, March.
    5. Mikkel Svenstrup & Soren Willemann, 2006. "Reforming Housing Finance - Perspectives from Denmark," Journal of Real Estate Research, American Real Estate Society, vol. 28(2), pages 105-130.
    6. Anne Pedersen & Alex Weissensteiner & Rolf Poulsen, 2013. "Financial planning for young households," Annals of Operations Research, Springer, vol. 205(1), pages 55-76, May.
    7. repec:bla:jfinan:v:44:y:1989:i:2:p:375-92 is not listed on IDEAS
    8. Ferstl, Robert & Weissensteiner, Alex, 2011. "Asset-liability management under time-varying investment opportunities," Journal of Banking & Finance, Elsevier, vol. 35(1), pages 182-192, January.
    9. Philippe Artzner & Freddy Delbaen & Jean‐Marc Eber & David Heath, 1999. "Coherent Measures of Risk," Mathematical Finance, Wiley Blackwell, vol. 9(3), pages 203-228, July.
    10. Shiller Robert J., 2009. "Unlearned Lessons from the Housing Bubble," The Economists' Voice, De Gruyter, vol. 6(7), pages 1-2, July.
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    Cited by:

    1. Ran Sun Lyng & Jie Zhou, 2019. "Household Portfolio Choice Before and After a House Purchase," Economics Working Papers 2019-01, Department of Economics and Business Economics, Aarhus University.
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