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as Djt. Djt is the focus of hypothesis one. In the application of the Corrado’s rank
statistic, Hl is rejected. That is, the GLB legislative event is associated with various
positive and negative share price reactions.
One-tail t-tests are used to assess hypothesis two. As a result, the H2 is rejected.
That is, there is a raise in the trading volume due to the GLB announcement.
Based upon a t-test, H3 is rejected as well. In other words, GLB event disclosures
caused significantly different share price reactions for both life and property-liability
insurers.
For hypothesis four, a GLS cross-sectional rank regression model is used. The in-
dependent variables include the standardized rank of firms’ size, liquidity, premiums-
written-to-surplus ratio and variance of abnormal returns. The results show that
the GLB has a greater impact on life insurers than on property-liability insurers.
Therefore, H4 is rejected.
In summary, smaller life insurers with high liquidity and more leverage seemed to
have the most positive share price reactions.
Mamun et al. (2004)
Mamun et al. (2004) examines the impact of GLB Act across three main sectors of
the financial services industry: commercial banks, insurance companies and brokerage
firms, taking into account the wealth effect associated with the announcement.
The four hypotheses tested in this paper are: