Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/8447
Title: Intraday volume and volatility relations with and without public news
Authors: Darrat, AF
Zhong, M
Cheng, LTW 
Keywords: Overconfidence
Public news
Return volatility
Sample partitioning
Sequential information arrival
Trading volume
Issue Date: 2007
Publisher: Elsevier
Source: Journal of banking and finance, 2007, v. 31, no. 9, p. 2711-2729 How to cite?
Journal: Journal of banking and finance 
Abstract: This paper reexamines the dynamic relation between intraday trading volume and return volatility of large and small NYSE stocks in two partitioned samples, with and without identifiable public news. We argue that the sequential information arrival hypothesis (SIAH) can be tested only in periods containing public news. After partitioning the sample into periods with and without public news, we find bi-directional Granger-causality between volume and volatility in the presence of public information as hypothesized by the SIAH. Our analysis further suggests that return volatility is higher in the periods with public news, while trading volume is significantly higher in the no-news period; perhaps owing to the importance of private information for trading stocks. Using the sample without public news, we find evidence that volume Granger-causes volatility without feedback. These results are broadly consistent with behavioral models like the overconfidence and biased self-attribution model of [Daniel, K., Hirshleifer, D., Subrahmanyam, A., 1998. Investor psychology and security market under- and over-reactions. Journal of Finance 53, 1839-1885]. It appears that overconfident investors overrate the precision of their private news signals and therefore trade too aggressively in the absence of public news; when public news arrives, investors' biased self-attribution triggers excessive return volatility.
URI: http://hdl.handle.net/10397/8447
ISSN: 0378-4266
EISSN: 1872-6372
DOI: 10.1016/j.jbankfin.2006.11.019
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