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Improving the accuracy of predictions in multivariate time series using dynamic vine copulas

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985556%3A_____%2F24%3A00599051" target="_blank" >RIV/67985556:_____/24:00599051 - isvavai.cz</a>

  • Result on the web

    <a href="https://www.tandfonline.com/doi/full/10.1080/03081079.2024.2350542" target="_blank" >https://www.tandfonline.com/doi/full/10.1080/03081079.2024.2350542</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1080/03081079.2024.2350542" target="_blank" >10.1080/03081079.2024.2350542</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Improving the accuracy of predictions in multivariate time series using dynamic vine copulas

  • Original language description

    In this work, we deal with non-stationary multivariate time series, proposing a method which uses copulas to produce more accurate forecasting. The idea is to apply a copula-based approach to identify change points and then split the time series into consecutive segments based on these change points. In each segment, we define the best-fitting copula family and forecast values of the time series of each segment using the corresponding fitting copula. We apply our model to a financial data set to test the predictive power of our approach. A simulation study is also presented for a detailed illustration and assessment of our proposed methodology. Based on the results of numerical analysis, we observed that our proposed approach will help us to improve the accuracy of forecasting in comparison with other existing methods such as traditional time series forecasting as well as neural network forecasting.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    10103 - Statistics and probability

Result continuities

  • Project

  • Continuities

    I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Others

  • Publication year

    2024

  • Confidentiality

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

Data specific for result type

  • Name of the periodical

    International Journal of General Systems

  • ISSN

    0308-1079

  • e-ISSN

    1563-5104

  • Volume of the periodical

    53

  • Issue of the periodical within the volume

    7-8

  • Country of publishing house

    GB - UNITED KINGDOM

  • Number of pages

    15

  • Pages from-to

    1146-1160

  • UT code for WoS article

    001233832100001

  • EID of the result in the Scopus database

    2-s2.0-85194565565