Alternative beta risk estimators in cases of extreme thin trading: Canadian evidence
In this paper, an alternative method of estimating the systematic risk for Canadian stocks is presented and empirically investigated. The method proposed is applied to a set of data impacted by censoring - the presence of zero returns, which occurs in extreme cases of thin trading. The approach used is the sample selectivity model, which is a two-step procedure: with a selectivity component and a regression component. In addition, this study compares the new beta estimate to the standard OLS beta and the Dimson Beta. The results indicate that the selectivity-corrected beta does correct the downward bias of the OLS estimates and possesses desirable statistical properties.
Volume (Year): 15 (2005)
Issue (Month): 18 ()
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