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The effect of non-trading days on volatility forecasts in equity markets

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LYÓCSA Štefan MOLNÁR Peter

Rok publikování 2017
Druh Článek v odborném periodiku
Časopis / Zdroj Finance Research Letters
Fakulta / Pracoviště MU

Ekonomicko-správní fakulta

Citace
www https://www.sciencedirect.com/science/article/pii/S1544612317300181?via%3Dihub
Doi http://dx.doi.org/10.1016/j.frl.2017.07.002
Obor Řízení, správa a administrativa
Klíčová slova realized volatility; volatility forecasting; non-trading days
Popis Weekends and holidays lead to gaps in daily financial data. Standard models ignore these irregularities. Because this issue is particularly important for persistent time series, we focus on volatility modelling, specifically modelling of realized volatility. We suggest a simple way of adjusting volatility models, which we illustrate on an AR(1) model and the HAR model of Corsi (2009). We investigate daily series of realized volatilities for 21 equity indices around the world, covering more than 15 years, and we find that our extension improves the volatility models—both in sample and out of sample. For HAR models and for consecutive trading days, the mean squared error decreased by 2.34% in average and for the QLIKE loss function by 1.41%.

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