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  • The impact of trading volume, number of trades and overnight returns on forecasting the daily realized range

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    Author(s)
    Todorova, Neda
    Soucek, Michael
    Griffith University Author(s)
    Todorova, Neda
    Year published
    2014
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    Abstract
    Intraday data of 26 German stocks are used to investigate whether the information contained in trading volume and number of trades as well as in various specifications of overnight returns can improve one-step-ahead volatility forecasts. For this purpose, a HAR model of the realized range adjusted for discrete trading is augmented by each of these variables and compared with the model's default form. The results show that the considered liquidity measures lead to very modest improvements in forecasting performance. The overnight returns exhibit some in-sample forecasting power. However, the accuracy improvement of out-of-sample ...
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    Intraday data of 26 German stocks are used to investigate whether the information contained in trading volume and number of trades as well as in various specifications of overnight returns can improve one-step-ahead volatility forecasts. For this purpose, a HAR model of the realized range adjusted for discrete trading is augmented by each of these variables and compared with the model's default form. The results show that the considered liquidity measures lead to very modest improvements in forecasting performance. The overnight returns exhibit some in-sample forecasting power. However, the accuracy improvement of out-of-sample forecasts is unequivocally non-significant.
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    Journal Title
    Economic Modelling
    Volume
    36
    DOI
    https://doi.org/10.1016/j.econmod.2013.10.003
    Copyright Statement
    © 2014 Elsevier Inc. This is the author-manuscript version of this paper. Reproduced in accordance with the copyright policy of the publisher. Please refer to the journal's website for access to the definitive, published version.
    Subject
    Applied economics
    Econometrics
    Banking, finance and investment
    Finance
    Publication URI
    http://hdl.handle.net/10072/62941
    Collection
    • Journal articles

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