Tails of Cross-Sectional Return Distributions at High Frequencies

Torben G. Andersen (), Yi Ding () and Viktor Todorov ()
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Torben G. Andersen: Finance Department, Kellogg School of Management, Northwestern University
Yi Ding: Faculty of Business Administration, University of Macau
Viktor Todorov: Finance Department, Kellogg School of Management, Northwestern University

No 202530, Working Papers from University of Macau, Faculty of Business Administration

Abstract: We develop nonparametric estimates for tail risk in the cross-section of asset prices at high frequencies. We show that the tail behavior of the crosssectional return distribution depends on whether the time interval contains a systematic jump event. If so, the cross-sectional return tail is governed by the assets’ exposures to the systematic event while, otherwise, it is determined by the idiosyncratic jump tails of the stocks. We develop an estimator for the tail shape of the cross-sectional return distribution that display distinct properties with and without systematic jumps. Empirically, we provide evidence for symmetric cross-sectional return tails at high-frequency that exhibit nontrivial and persistent time series variation. A hypothesis of equal cross-sectional return tail shapes during periods with and without systematic jump events is strongly rejected by the data.

Keywords: Cross-sectional return distribution; extreme value theory; highfrequency data; tail risk (search for similar items in EconPapers)
Pages: 44 pages
Date: 2025-06
New Economics Papers: this item is included in nep-ecm, nep-ifn and nep-rmg
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Published in UM-FBA Working Paper Series

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Persistent link: https://EconPapers.repec.org/RePEc:boa:wpaper:202530

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