  This study delves into the intra-industry effects following a firm-specific
scandal, with a particular focus on the Facebook data leakage scandal and its
associated events within the U.S. tech industry and two additional relevant
groups. We employ various metrics including daily spread, volatility,
volume-weighted return, and CAPM-beta for the pre-analysis clustering, and
subsequently utilize CAR (Cumulative Abnormal Return) to evaluate the impact on
firms grouped within these clusters. From a broader industry viewpoint,
significant positive CAARs are observed across U.S. sample firms over the three
days post-scandal announcement, indicating no adverse impact on the tech sector
overall. Conversely, after Facebook's initial quarterly earnings report, it
showed a notable negative effect despite reported positive performance. The
clustering principle should aid in identifying directly related companies and
thus reducing the influence of randomness. This was indeed achieved for the
effect of the key event, namely "The Effect of Congressional Hearing on Certain
Clusters across U.S. Tech Stock Market," which was identified as delayed and
significantly negative. Therefore, we recommend applying the clustering method
when conducting such or similar event studies.
