This dissertation focuses on the behavior of security returns around certain events that occurred in the Saudi stock market. In the first study, we measure and analyze the reaction of security returns around a major horizontal merger that occurred in the banking industry in Saudi Arabia. The objective of this study is to illustrate a method that can forecast the economic effect of a merger on market competition. We investigate whether the merger increases market power or economic efficiency using an event study methodology. Using the standardized cross-sectional test statistic, we test three hypotheses, namely the market power hypothesis, the productivity hypothesis, and the information hypothesis. When the actual merger date is chosen as the event date, the results support the productivity hypothesis. When the announcement date is chosen instead, we find that the results are consistent with the information hypothesis. The results did not show any support for the market power hypothesis. The overall results suggest that the merger is believed to increase the economic efficiency of the industry.
In the second study, we introduce a new technique that measures any misvaluation in the overall stock market. The objective of this study is to propose a method that can forecast financial bubbles. Various techniques have been used to identify the existence of stock market bubbles. All of them are based on the standard present value models. The success of those techniques in identifying bubbles depends on how good the underlying models are in detecting asset price misvaluation. In general, those techniques have not been satisfactory in detecting asset price bubbles. This study introduces a new technique that is based on a recently developed model called the composite-error model, which deviates from the traditional present value models. The approach generates a new index called "Market Valuation Index" - an index that measures the extent to which the overall stock market is over, under, or correctly valued. This new index helps identify financial bubbles and may help avoid financial crashes in the future. The capability of the new index to identify bubbles is tested on two historical crashes that occurred in the Saudi stock market during the years 2006 and 2008. In each case, this approach finds that the market was persistently overvalued during the pre-crash period, which indicates the existence of a bubble. The results also show that in each case the market was correctly valued during the post-crash period showing the disappearance of the bubble after the crash. In addition, this study runs various sensitivity analyses and finds that the results in general are not sensitive to changes in the length of estimation period, the level of significance, and the weighting scheme used to calculate the average of the estimated misvaluation.
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