Parameter estimation of parabolic type factor models and empirical study of US treasury bonds

ShinIchi Aihara, Arunabha Bagchi

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    Abstract

    In this paper we study the parameter estimation problem for stochastic distributed parameter systems by using the modified maximum likelihood method. More specifically, by using the US treasury bond data, the parameter estimation is performed for the stochastic hyperbolic and parabolic models describing the behavior of the term-structure of the US bond. From the prediction results, we can show that the parabolic factor models work better than the hyperbolic ones.
    Original languageUndefined
    Title of host publicationProceedings of the 22nd IFIP TC7 Conference
    EditorsF. Ceragioli, A. Dontchev, H. Futura, K. Marti, L. Pandolfi
    Place of PublicationBoston
    PublisherSpringer
    Pages207-217
    Number of pages11
    ISBN (Print)0-387-32774-6
    DOIs
    Publication statusPublished - 2006
    Event22nd International Federation for Information Processing (IFIP) TC7 Conference, Turin, Italy: System Modeling and Optimization - Boston
    Duration: 18 Jul 200522 Jul 2005

    Publication series

    NameIFIP International Federation for Information Processing
    PublisherSpringer Verlag
    Number199
    Volume199
    ISSN (Print)1571-5736

    Conference

    Conference22nd International Federation for Information Processing (IFIP) TC7 Conference, Turin, Italy
    CityBoston
    Period18/07/0522/07/05

    Keywords

    • EWI-6114
    • METIS-238661
    • IR-85721
    • US bonds
    • Factor model
    • Maximum likelihood estimate
    • Stochastic Parabolic Equation
    • MLE

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