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On the Modelling and Forecasting of Multivariate Realized Volatility: Generalized Heterogeneous Autoregressive (GHAR) Model

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985556%3A_____%2F17%3A00478479" target="_blank" >RIV/67985556:_____/17:00478479 - isvavai.cz</a>

  • Alternative codes found

    RIV/00216208:11230/17:10326547

  • Result on the web

    <a href="http://dx.doi.org/10.1002/for.2423" target="_blank" >http://dx.doi.org/10.1002/for.2423</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1002/for.2423" target="_blank" >10.1002/for.2423</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    On the Modelling and Forecasting of Multivariate Realized Volatility: Generalized Heterogeneous Autoregressive (GHAR) Model

  • Original language description

    Recent multivariate extensions of the popular heterogeneous autoregressive model (HAR) for realized volatility leave substantial information unmodelled in residuals. We propose to employ a system of seemingly unrelated regressions to model and forecast a realized covariance matrix to capture this information. We find that the newly proposed gener- alized heterogeneous autoregressive (GHAR) model outperforms competing approaches in terms of economic gains, providing better mean–variance trade-off, while, in terms of statistical precision, GHAR is not substantially dominated by any other model. Our results provide a comprehensive comparison of the performance when realized covariance, subsampled realized covariance and multivariate realized kernel estimators are used. We study the contribution of the estimators across different sampling frequencies, and show that the multivariate realized kernel and subsampled real- ized covariance estimators deliver further gains compared to realized covariance estimated on a 5-minute frequency. In order to show economic and statistical gains, a portfolio of various sizes is used.

  • 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

    50201 - Economic Theory

Result continuities

  • Project

    <a href="/en/project/GA13-32263S" target="_blank" >GA13-32263S: Multivariate spectral analysis of financial markets</a><br>

  • Continuities

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

Others

  • Publication year

    2017

  • Confidentiality

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

Data specific for result type

  • Name of the periodical

    Journal of Forecasting

  • ISSN

    0277-6693

  • e-ISSN

  • Volume of the periodical

    36

  • Issue of the periodical within the volume

    1

  • Country of publishing house

    US - UNITED STATES

  • Number of pages

    26

  • Pages from-to

    181-206

  • UT code for WoS article

    000394909900006

  • EID of the result in the Scopus database

    2-s2.0-84966539553