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On conditional covariance modelling: An approach using state space models

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F16%3A10329024" target="_blank" >RIV/00216208:11320/16:10329024 - isvavai.cz</a>

  • Result on the web

    <a href="http://dx.doi.org/10.1016/j.csda.2014.09.019" target="_blank" >http://dx.doi.org/10.1016/j.csda.2014.09.019</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1016/j.csda.2014.09.019" target="_blank" >10.1016/j.csda.2014.09.019</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    On conditional covariance modelling: An approach using state space models

  • Original language description

    A novel approach to conditional covariance modelling is introduced in the context of multivariate financial time series analysis. In particular, a class of multivariate generalized autoregressive conditional heteroscedasticity models is proposed. The suggested modelling technique is based on a specific dynamic orthogonal transformation derived by the LDL factorization of the conditional covariance matrix. An observed time series is transformed into a particular form that can be further treated by means of a discrete-time state space model under corresponding assumptions. The calibration can be performed by the associated Kalman recursive formulas, which are numerically effective. The introduced procedure has been investigated by extensive Monte Carlo experiments and empirical financial applications; it has been compared with other methods commonly used in this framework. The outlined methodology has demonstrated its capabilities, and it seems to be at least competitive in this field of research.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)

  • CEP classification

    BA - General mathematics

  • OECD FORD branch

Result continuities

  • Project

    <a href="/en/project/GBP402%2F12%2FG097" target="_blank" >GBP402/12/G097: DYME-Dynamic Models in Economics</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Others

  • Publication year

    2016

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    Computational Statistics and Data Analysis

  • ISSN

    0167-9473

  • e-ISSN

  • Volume of the periodical

    2016

  • Issue of the periodical within the volume

    100

  • Country of publishing house

    NL - THE KINGDOM OF THE NETHERLANDS

  • Number of pages

    14

  • Pages from-to

    304-317

  • UT code for WoS article

    000378368100019

  • EID of the result in the Scopus database

    2-s2.0-84979729497