The volatility effects of nontrading for stock market returns

Tyler J. VanderWeele

Applied Financial Economics, 2007, vol. 17, issue 13, 1037-1041

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.

Date: 2007
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.tandfonline.com/doi/abs/10.1080/09603100600749261 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:apfiec:v:17:y:2007:i:13:p:1037-1041

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/RAFE20

DOI: 10.1080/09603100600749261

Access Statistics for this article

Applied Financial Economics is currently edited by Anita Phillips

More articles in Applied Financial Economics from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().