Hostname: page-component-78c5997874-8bhkd Total loading time: 0 Render date: 2024-11-15T15:20:29.401Z Has data issue: false hasContentIssue false
  • English
  • Français

Measuring Event Impacts in Thinly Traded Stocks

Published online by Cambridge University Press:  06 April 2009

Robert Heinkel  and
Alan Kraus
Get access Rights & Permissions [Opens in a new window]

Abstract

The purpose of this paper is to suggest simple procedures designed to cope with the effects of thin trading on event study tests. The procedures are directed at two central problems: (i) missing individual stock returns (i.e., days on which no trading is observed in a security), and (ii) the effect of a bid-ask spread on the time series behavior of daily stock return data. We attack these problems by explicitly incorporating them in the construction of a generating process for observed security returns. First, we develop a procedure for “filling in” missing returns. Then, we model a return-generating process of observed security returns that allows estimation of the variance of unobserved true security returns for use in hypothesis testing.

Type
Research Article
Information
Journal of Financial and Quantitative Analysis , Volume 23 , Issue 1 , March 1988 , pp. 71 - 88
Copyright
Copyright © School of Business Administration, University of Washington 1988

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Cohen, K. J.; Maier, S. F.; Schwartz, R. A.; and Whitcomb, D. K.. “On the Existence of Serial Correlation in an Efficient Securities Market.” TIMS Studies in the Management Sciences, 11b (1979), 151–168.Google Scholar
French, K. R., and Roll, R.. “Stock Return Variances: The Arrival of Information and the Reaction of Traders.” Journal of Financial Economics, 17 (09 1986), 5–26.Google Scholar
Glosten, L. R. “Estimating and Adjusting for the Bid-Ask Spread.” Working paper, Graduate School of Business, Univ. of Chicago (1984).Google Scholar
Glosten, L. R., and Harris, L. E.. “Estimating the Components of the Bid/Ask Spread.” Working Paper, Univ. of Southern California (07 1986).Google Scholar
Glosten, L. R., and Milgrom, P. R.. “Bid, Ask and Transaction Prices in a Specialist Market with Heterogeneously Informed Traders.” Journal of Financial Economics, 14 (03 1985), 71–100.Google Scholar
Harris, L. “Estimation of ‘True’ Stock Price Variances and Bid-Ask Spreads from Discrete Observation.” Working paper, School of Business Administration, Univ. of Southern California (1985).Google Scholar
Ho, T., and Stoll, H. R.. “Optimal Dealer Pricing under Transactions and Return Uncertainty.” Journal of Financial Economics, 9 (03 1981), 47–73.CrossRefGoogle Scholar
Ho, T., and Stoll, H. R.. “The Dynamics of Dealer Markets under Competition.” Journal of Finance, 38 (09 1983), 1053–1074.CrossRefGoogle Scholar
Holthausen, R.; Leftwich, R.; and Mayers, D.. “Block Trades of Securities and the Price Pressure Hypothesis.” Working paper, Graduate School of Business, Univ. of Chicago (1984).Google Scholar
Jaffee, J. “Special Information and Insider Trading.” Journal of Business, 47 (07 1974), 410–428.CrossRefGoogle Scholar
Kraus, A., and Stoll, H.. “Price Impacts of Block Trading on the New York Stock Exchange.” Journal of Finance, 27 (06 1972), 569–588.Google Scholar
Mandelker, G. “Risk and Return: The Case of Merging Firms.” Journal of Financial Economics, 1 (12 1974), 303–336.Google Scholar
Marshall, J. M. “Private Incentives and Public Information.” American Economic Review, 64 (06 1974), 373–390.Google Scholar
Rubinstein, M. “Securities Market Efficiency in an Arrow-Debreu Economy.” American Economic Review, 65 (12 1975), 812–824.Google Scholar
Scholes, M. “The Market for Securities: Substitution versus Price Pressure and the Effect of information of Share Price.” Journal of Business, 45 (04 1972), 179–211.CrossRefGoogle Scholar
Scholes, M., and Williams, J.. “Estimating Betas from Nonsynchronous Data.” Journal of Financial Economics, 5 (05 1977), 309–327.CrossRefGoogle Scholar