2009
DOI: 10.2139/ssrn.1436090
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Detecting Abnormal Returns of Infrequently Traded Stocks in an Event Study

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Cited by 3 publications
(3 citation statements)
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“…A potential methodological issue with conducting event studies in the small-cap resource sector is non-synchronous or thin trading biasing results (Brown and Warner, 1985;Kallunki, 1997;Leemakdej, 2009). To provide confidence that non-synchronous trading does drive or bias the main results we pro-rate allocate daily returns to any immediately preceding non-trading days, which produces consistent, although slightly weaker results (Kallunki, 1997).…”
Section: Robustness and Sensitivity Testingmentioning
confidence: 99%
See 1 more Smart Citation
“…A potential methodological issue with conducting event studies in the small-cap resource sector is non-synchronous or thin trading biasing results (Brown and Warner, 1985;Kallunki, 1997;Leemakdej, 2009). To provide confidence that non-synchronous trading does drive or bias the main results we pro-rate allocate daily returns to any immediately preceding non-trading days, which produces consistent, although slightly weaker results (Kallunki, 1997).…”
Section: Robustness and Sensitivity Testingmentioning
confidence: 99%
“…9 The resulting sub-sample produces similar, but stronger results. Fourth, as non-parametric rank tests can provide superior insight in samples prone to non-synchronous trading (Leemakdej, 2009), we compare whether there is a difference between the abnormal return on event day 0 relative to the 15 days before and after using the non-parametric Mann-Whitney U test and find significantly higher returns on event day 0 (z-score = 2.575). This result also holds in the sub-sample of firms that trade continuously.…”
Section: Robustness and Sensitivity Testingmentioning
confidence: 99%
“…Non-synchronous trading has been shown to cause a number of problems in event studies (Leemakdej, 2009). In particular, it introduces biases in the calculation of the abnormal returns associated with (i) the preponderance of zero returns assigned to stocks on non-trading days and (ii) biases that this introduces into the estimation of the expected return model (e.g.…”
Section: Event Study Methodologymentioning
confidence: 99%