Forecasting Realized Volatility: A Review
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.
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Published
2018-02-25
How to Cite
BUCCI, Andrea.
Forecasting Realized Volatility: A Review.
Journal of Advanced Studies in Finance, [S.l.], v. 8, n. 2, p. 94-138, feb. 2018.
ISSN 2068-8393.
Available at: <https://journals.aserspublishing.eu/jasf/article/view/1782>. Date accessed: 25 apr. 2024.
doi: https://doi.org/10.14505//jasf.v8.2(16).02.
Section
Journal of Advanced Studies in Finance
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