Understanding temporal aggregation effects on kurtosis in financial indices
Publication Type
Journal Article
Publication Date
3-2022
Abstract
Indices of financial returns typically display sample kurtosis that declines towards the Gaussian value 3 as the sampling interval increases. This paper uses stochastic unit root (STUR) and continuous time analysis to explain the phenomenon. Limit theory for the sample kurtosis reveals that STUR specifications provide two sources of excess kurtosis, both of which decline with the sampling interval. Limiting kurtosis is shown to be random and is a functional of the limiting price process. Using a continuous time version of the model under no-drift, local drift, and drift inclusions, we suggest a new continuous time kurtosis measure for financial returns that assists in reconciling these models with the empirical kurtosis characteristics of returns. Simulations are reported and applications to several financial indices demonstrate the usefulness of this approach.
Keywords
Autoregression, Diffusion, Kurtosis, Stochastic unit root, Time-varying coefficients
Discipline
Econometrics
Research Areas
Econometrics
Publication
Journal of Econometrics
Volume
227
Issue
1
First Page
25
Last Page
46
ISSN
0304-4076
Identifier
10.1016/j.jeconom.2020.07.035
Publisher
Elsevier: 24 months
Citation
LIEBERMAN, Offer and PHILLIPS, Peter C. B..
Understanding temporal aggregation effects on kurtosis in financial indices. (2022). Journal of Econometrics. 227, (1), 25-46.
Available at: https://ink.library.smu.edu.sg/soe_research/2628
Additional URL
http://doi.org/10.1016/j.jeconom.2020.07.035