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  1. Forecasting realized volatility using machine learning and mixed-frequency data (the case of the Russian stock market)
    Author: Pyrlik, Vladimir; Elizarov, Pavel; Leonova, Aleksandra
    Published: Noember 2021
    Publisher:  Charles University, Center for Economic Research and Graduate Education, Prague

    Access:
    Verlag (kostenfrei)
    Verlag (kostenfrei)

    Location:
    ZBW - Leibniz-Informationszentrum Wirtschaft, Standort Kiel
    Signature:
    VS 823
    Inter-library loan:
    No inter-library loan
    Export to reference management software   RIS file
      BibTeX file
    Source: Union catalogues
    Language: English
    Media type: Ebook
    Format: Online
    ISBN: 9788073435202; 9788073446154
    Series: Working paper series / CERGE-EI ; 713
    Subjects: heterogeneous autoregressive model; machine learning; lasso; gradientboosting; random forest; long short-term memory; realized volatility; Russian stockmarket; mixed-frequency data
    Scope: 1 Online-Ressource (circa 37 Seiten), Illustrationen