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The volatility effects of nontrading for stock market returns

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  • Tyler J. VanderWeele

Abstract

The effect of periods of nontrading on volatility is examined. The empirical evidence suggests that volatility is higher on days which follow a period of nontrading. A nonparametric kernel regression is used to estimate a diffusion model with a volatility term dependent on the number of days of prior nontrading. The nonparametric estimates suggest that the presence of a prior period of nontrading may increase the volatility as much as 35%. A moving blocks bootstrap, taking into account the dependence in observations, is used in conjunction with the nonparametric regression to show that the differences estimated are statistically significant.

Suggested Citation

  • Tyler J. VanderWeele, 2007. "The volatility effects of nontrading for stock market returns," Applied Financial Economics, Taylor & Francis Journals, vol. 17(13), pages 1037-1041.
    • Handle: RePEc:taf:apfiec:v:17:y:2007:i:13:p:1037-1041
    DOI: 10.1080/09603100600749261
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