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Forecasting realized volatility: a review

Andrea Bucci ()

MPRA Paper from University Library of Munich, Germany

Abstract: Modeling financial volatility is an important part of empirical finance. This paper provides a literature review of the most relevant volatility models, with a particular focus on forecasting models. We firstly discuss the empirical foundations of different kinds of volatility. The paper, then, analyses the non-parametric measure of volatility, named realized variance, and its empirical applications. A wide range of realized volatility models, both univariate and multivariate, is presented, such as time series models, MIDAS and GARCH-MIDAS models, Realized GARCH, and HEAVY models. We further discuss forecasting evaluation methods specifically suited for volatility models.

Keywords: Realized Volatility; Stochastic Volatility; Volatility Models (search for similar items in EconPapers)
JEL-codes: C22 C53 G10 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ecm, nep-ets, nep-for, nep-his and nep-rmg
Date: 2017-12
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https://mpra.ub.uni-muenchen.de/83232/1/MPRA_paper_83232.pdf original version (application/pdf)
https://mpra.ub.uni-muenchen.de/83738/1/MPRA_paper_83738.pdf revised version (application/pdf)

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Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:83232

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