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Estimating Affine Multifactor Term Structure Models Using Closed-Form Likelihood Expansions

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  • Yacine Aït-Sahalia
  • Robert Kimmel

Abstract

We develop and implement a technique for closed-form maximum likelihood estimation (MLE) of multifactor affine yield models. We derive closed-form approximations to likelihoods for nine Dai and Singleton (2000) affine models. Simulations show our technique very accurately approximates true (but infeasible) MLE. Using US Treasury data, we estimate nine affine yield models with different market price of risk specifications. MLE allows non-nested model comparison using likelihood ratio tests; the preferred model depends on the market price of risk. Estimation with simulated and real data suggests our technique is much closer to true MLE than Euler and quasi-maximum likelihood (QML) methods.

Suggested Citation

  • Yacine Aït-Sahalia & Robert Kimmel, 2002. "Estimating Affine Multifactor Term Structure Models Using Closed-Form Likelihood Expansions," NBER Technical Working Papers 0286, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberte:0286
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    References listed on IDEAS

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    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing

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