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  <front>
    <journal-meta>
      <journal-id journal-id-type="publisher-id">JDS</journal-id>
      <journal-title-group>
        <journal-title>Journal of Data Science</journal-title>
      </journal-title-group>
      <issn pub-type="epub">1680-743X</issn>
      <issn pub-type="ppub">1680-743X</issn>
      <publisher>
        <publisher-name>SOSRUC</publisher-name>
      </publisher>
    </journal-meta>
    <article-meta>
      <article-id pub-id-type="publisher-id">100207</article-id>
      <article-id pub-id-type="doi">10.6339/JDS.2012.10(2).746
</article-id>
      <article-categories>
        <subj-group subj-group-type="heading">
          <subject>Research Article</subject>
        </subj-group>
      </article-categories>
      <title-group>
        <article-title>Bayesian Estimation of CIR Model</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <name>
            <surname>Feng</surname>
            <given-names>Xiaoxia</given-names>
          </name>
          <xref ref-type="aff" rid="j_JDS_aff_000"/>
        </contrib>
        <aff id="j_JDS_aff_000">Xi’an Jiaotong University</aff>
        <contrib contrib-type="author">
          <name>
            <surname>Xie</surname>
            <given-names>Dejun</given-names>
          </name>
          <xref ref-type="aff" rid="j_JDS_aff_001"/>
        </contrib>
        <aff id="j_JDS_aff_001">Xi’an Jiaotong-Liverpool University</aff>
      </contrib-group>
      <volume>10</volume>
      <issue>2</issue>
      <fpage>271</fpage>
      <lpage>280</lpage>
      <permissions>
        <ali:free_to_read xmlns:ali="http://www.niso.org/schemas/ali/1.0/"/>
      </permissions>
      <abstract>
        <p>Abstract: This article concerns the Bayesian estimation of interest rate mod els based on Euler-Maruyama approximation. Assume the short term inter est rate follows the CIR model, an iterative method of Bayesian estimation is proposed. Markov Chain Monte Carlo simulation based on Gibbs sam pler is used for the posterior estimation of the parameters. The maximum A-posteriori estimation using the genetic algorithm is employed for finding the Bayesian estimates of the parameters. The method and the algorithm are calibrated with the historical data of US Treasury bills.</p>
      </abstract>
      <kwd-group>
        <label>Keywords</label>
        <kwd>Bayesian estimation</kwd>
        <kwd>CIR model</kwd>
        <kwd>Gibbs sampler</kwd>
        <kwd>MCMC method</kwd>
      </kwd-group>
    </article-meta>
  </front>
</article>
