Information Asymmetry, Market Segmentation and Cross-Listing: Implicatons for Event Study Methodology

This paper connects three subjects related to international financial markets -- (i) information asymmetry, (ii) market segmentation, and (iii) cross-listings -- and highlights their implication for event study methodology. When firms list equities on more than one exchange, and the exchanges are characterized by different information sets, a problem arises as to which exchange(s) to include in the event study sample. If market segmentation impedes the arbitrage of these multiple responses, then the use of a single listing (for a firm that is cross-listed) can yield abnormal return estimates that are biased. In such circumstances, using re-turns from all the markets in which a firm’s securities are listed not only increases the sample size (often an important consideration when undertaking event studies in emerging markets), but also enables full-information abnormal return estimates to be obtained. What is required is a method that extracts the independent information from each listing while counting the com-mon information only once. In this paper, we develop an estimation procedure that achieves these twin objectives. We then apply our approach to an event study of Chinese OMAs and compare results from alternative samples and estimators. We demonstrate that including re-turn data from cross-listings of the same firm can result in substantially different conclusions.