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DCC- and DECO-HEAVY: Multivariate GARCH models based on realized variances and correlations

Author

Listed:
  • Bauwens, Luc

    (Université catholique de Louvain, LIDAM/CORE, Belgium)

  • Xu, Yongdeng

Abstract

This paper introduces the scalar DCC-HEAVY and DECO-HEAVY models for conditional variances and correlations of daily returns based on measures of realized variances and correlations built from intraday data. Formulas for multi-step forecasts of conditional variances and correlations are provided. Asymmetric versions of the models are developed. An empirical study shows that in terms of forecasts the scalar HEAVY models outperform the scalar BEKK-HEAVY model based on realized covariances and the scalar BEKK, DCC, and DECO multivariate GARCH models based exclusively on daily data.

Suggested Citation

  • Bauwens, Luc & Xu, Yongdeng, 2025. "DCC- and DECO-HEAVY: Multivariate GARCH models based on realized variances and correlations," LIDAM Reprints CORE 3345, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    • Handle: RePEc:cor:louvrp:3345
    DOI: https://doi.org/10.1016/j.ijforecast.2022.03.005
    Note: In: International Journal of Forecasting, 2023, vol. 39(2), p. 938-955
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    Cited by:

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    2. Xu, Yongdeng & Guan, Bo & Lu, Wenna & Heravi, Saeed, 2024. "Macroeconomic shocks and volatility spillovers between stock, bond, gold and crude oil markets," Energy Economics, Elsevier, vol. 136(C).
    3. Virbickaitė, Audronė & Lopes, Hedibert F. & Zaharieva, Martina Danielova, 2025. "Multivariate dynamic mixed-frequency density pooling for financial forecasting," International Journal of Forecasting, Elsevier, vol. 41(3), pages 1184-1198.
    4. Bauwens, Luc & Dzuverovic, Emilija & Hafner, Christian, 2024. "Asymmetric Models for Realized Covariances," LIDAM Discussion Papers CORE 2024024, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    5. Yongdeng Xu, 2025. "The exponential HEAVY model: an improved approach to volatility modeling and forecasting," Review of Quantitative Finance and Accounting, Springer, vol. 65(2), pages 727-748, August.
    6. Bauwens, Luc & Xu, Yongdeng, 2025. "The contribution of realized variance–covariance models to the economic value of volatility timing," International Journal of Forecasting, Elsevier, vol. 41(3), pages 1165-1183.
    7. Bauwens, Luc & Otranto, Edoardo, 2023. "Realized Covariance Models with Time-varying Parameters and Spillover Effects," LIDAM Discussion Papers CORE 2023019, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    8. Xu, Yongdeng, 2024. "Extended multivariate EGARCH model: A model for zero†return and negative spillovers," Cardiff Economics Working Papers E2024/24, Cardiff University, Cardiff Business School, Economics Section.
    9. Samuel Tabot Enow, 2025. "Statistical properties, dynamic conditional correlation, and scaling analysis: evidence from international financial markets high-frequency data," International Journal of Research in Business and Social Science (2147-4478), Center for the Strategic Studies in Business and Finance, vol. 14(4), pages 251-255, June.
    10. Honig, Igor & Kircher, Felix, 2025. "Large dynamic covariance matrices and portfolio selection with a heterogeneous autoregressive model," Journal of Banking & Finance, Elsevier, vol. 178(C).
    11. Zaharieva, Martina Danielova & Virbickaitė, Audronė & Santos, André Portela, 2025. "Intraday volatility transmission in global energy markets: A Bayesian nonparametric approach," Journal of Commodity Markets, Elsevier, vol. 39(C).

    More about this item

    Keywords

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    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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