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6. Limitations of Our Model
The first limitation we can think about in our study is the sample size. In fact, for both studies we conducted in our thesis, the samples size are small due to the fact that we are working with a relative low number of presidential elections for both Taiwan and France. This number will increase with time and can be explained by the late arrival of direct presidential elections in Taiwan (1996) and the late automation of the CAC 40 (1987), main stock exchange in France.
The sample size is especially small for the indices where only mid or big-caps stocks are listed on, as this type of index appeared during the years 2000s.
As we previously mentioned, the statistical tests of significance (t-test, tcaar) need the sample to follow a normal distribution to show results with the least bias. Nevertheless, the tools to prove the normal distribution of our samples were not available during our research and the central limit theorem, stating that samples with a size higher than 30, are assumed to follow a normal distribution, could not be used, due to the small size samples used in this study. Nevertheless, the t-test remained the most robust tool to determine the significance of our results, after analyzing both parametrical and non-parametrical methods available. We may think to include several countries from Asia and several countries from Europe to conduct a research with a larger sample size and get even more robustness in our results.
It seems also clear that the event study methodology can lead to some bias. Indeed, the possibility that events, other than the presidential elections, influence the stock market exists.
Those events may influence the estimation window average returns, used to calculate the abnormal returns but also every event windows of our analysis. The presence of financial crisis such as the global financial crisis of 2007 or the Asian financial crisis had an impact, with
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different proportions and scales, on the stock markets in France and Taiwan. The relationship between Taiwan and China is also, due to the specific status of Taiwan, a factor that can directly influence the stock market. In fact, the elections organized by the Taiwanese government are directly seen as a threat by the PRC as the possibility of election of a political party in favor of the independence of Taiwan, against the unification, is possible. China had several times launched military activities before the elections occurring in Taiwan to threaten to citizen on the outcome of the election to come. The intimidation made by China against Taiwan could lead the stock market to reflect the investors’ fear toward this situation and this, before and after the election result, according to the outcome of this one...
Those events impacted the stock markets in the two countries of our study and definitely had an impact on the two studies we conducted. Our results cannot be explained only by the presidential elections and it is important to know which factors influence the most the stock markets. We can propose, for further study, the idea to take into account those factors in our analysis, to see what is the proportion of the influence of presidential elections on the stock markets compared to others events.
It is also important to mention that the t-test performed on the YAR (first study) shows only one significant result while when we consider daily returns for our second study, the number of significant results considerably increases. We may think that the period of one year (in average) to test the returns is not relevant as the time for the information to be reflected in market is definitely faster than a year. The higher volatility (standard deviation in the formula) during this period will definitely be the source of non-relevant results (not likely to be significant) and as a consequence, we can think that the first study does not require a t-test to be complete.
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Finally, the Fama-French model and the CAPM model are both very know to determine the estimated return of the estimation windows we are working with. The use of one of this model instead of the mean-adjusted one we used to conduct the event-study would bring more accuracy in our results. It would have also been relevant to plot the distribution of abnormal returns around the presidential election date so that we could have easily confirmed our results graphically.
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