Aggregational Gaussianity and barely infinite variance in financial returns

Antonios Antypas, Phoebe Koundouri () and Nikolaos Kourogenis

Journal of Empirical Finance, 2013, vol. 20, issue C, 102-108

Abstract: This paper aims at reconciling two apparently contradictory empirical regularities of financial returns, namely, the fact that the empirical distribution of returns tends to normality as the frequency of observation decreases (aggregational Gaussianity) combined with the fact that the conditional variance of high frequency returns seems to have a (fractional) unit root, in which case the unconditional variance is infinite. We provide evidence that aggregational Gaussianity and infinite variance can coexist, provided that all the moments of the unconditional distribution whose order is less than two exist. The latter characterizes the case of Integrated and Fractionally Integrated GARCH processes. Finally, we discuss testing for aggregational Gaussianity under barely infinite variance. Our empirical motivation derives from commodity prices and stock indices, while our results are relevant for financial returns in general.

Keywords: Aggregational Gaussianity; Infinite variance; FIGARCH; Financial returns (search for similar items in EconPapers)
JEL-codes: C10 G12 Q14 (search for similar items in EconPapers)
Date: 2013
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Citations: View citations in EconPapers (6)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:empfin:v:20:y:2013:i:c:p:102-108

DOI: 10.1016/j.jempfin.2012.11.003

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