NDLI: New HEAVY Models for Fat-Tailed Realized Covariances and Returns

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New HEAVY Models for Fat-Tailed Realized Covariances and Returns

Content Provider	Semantic Scholar
Author	Opschoor, Anne Janus, Pawel Lucas, André Dijk, Dick Van
Copyright Year	2017
Abstract	ABSTRACTWe develop a new score-driven model for the joint dynamics of fat-tailed realized covariance matrix observations and daily returns. The score dynamics for the unobserved true covariance matrix are robust to outliers and incidental large observations in both types of data by assuming a matrix-F distribution for the realized covariance measures and a multivariate Student's t distribution for the daily returns. The filter for the unknown covariance matrix has a computationally efficient matrix formulation, which proves beneficial for estimation and simulation purposes. We formulate parameter restrictions for stationarity and positive definiteness. Our simulation study shows that the new model is able to deal with high-dimensional settings (50 or more) and captures unobserved volatility dynamics even if the model is misspecified. We provide an empirical application to daily equity returns and realized covariance matrices up to 30 dimensions. The model statistically and economically outperforms competi...
Starting Page	643
Ending Page	657
Page Count	15
File Format	PDF HTM / HTML
DOI	10.1080/07350015.2016.1245622
Volume Number	36
Alternate Webpage(s)	https://repub.eur.nl/pub/99946/REPUB_99946-OA.pdf
Alternate Webpage(s)	https://doi.org/10.1080/07350015.2016.1245622
Language	English
Access Restriction	Open
Content Type	Text
Resource Type	Article

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