Continuous-time Identification of Exponential-Affine Term Structure Models

Arianto Wibowo

    Research output: ThesisPhD Thesis - Research UT, graduation UT

    71 Downloads (Pure)


    This thesis addresses the problem of parameter estimation of the exponentialaffine class of models, which is a class of multi-factor models for the short rate. We propose a continuous-time maximum likelihood estimation method to estimate the parameters of a short rate model, given set of observations that are linear with respect to the interest rate factors. We assume that observations are corrupted by Gaussian noise with a known covariance, which lead to a maximum likelihood estimation method for partially observed systems. Unlike other approaches in the literature, we do not discretize either the interest rate model or the observation model.
    Original languageEnglish
    Awarding Institution
    • University of Twente
    • Bagchi, A., Supervisor
    Award date6 Dec 2006
    Place of PublicationEnschede
    Print ISBNs90-365-2442-3
    Publication statusPublished - 6 Dec 2006


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