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Tails of Cross-Sectional Return Distributions at High Frequencies

Author

Listed:
  • 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)

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.

Suggested Citation

  • Torben G. Andersen & Yi Ding & Viktor Todorov, 2025. "Tails of Cross-Sectional Return Distributions at High Frequencies," Working Papers 202530, University of Macau, Faculty of Business Administration.
    • Handle: RePEc:boa:wpaper:202530
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