For Skewness, ideally it should be zero indicating symmetry and normality. Positively skewed data are said to be right tailed and it is an indication that stocks carry on a likelihood of have a higher probability of earning positive returns. In this case, only FTSE MID 250 (1.690595) was seen to be positive and this is also because the company prides in having one of the leading share returns in the market over the recent period. On the other hand, negatively skewed data are referred to as left-tailed and this is reflected in the rest of the variable ranging from BRUSSELS ALL SHARE 0 (-0.25139) to MILAN COMIT GENERAL (-0.486624). It is however worth noting these values are relatively close to zero and they are therefore slightly left tailed. For Kurtosis, it is often used to estimate the clustering of scores and as such a value of zero reflects data that are clustered around the mean. On the other hand a value greater than 0 shows clustering around numbers other than the mean. On the other hand, a value less than 0 shows that the data is spread out and as such there is no clustering. Based on findings in Table 1, it can be concluded that the data used in the study are all clustered around numbers other than the mean as shown by the results which are 9.286315, 25.30415, and 8.49093 for MILAN COMIT GENERAL, FTSE MID 250, and BRUSSELS ALL SHARE respectively. It is important to mention that kurtosis is the relative flatness or peakedness of the distribution of the returns as compared to the normal distribution. A normal distribution is said to have a kurtosis of 3. Whenever the tails of a given data are thinner compared to those associated with the normal distribution, they are said to be platykurtic (Harvey, 1990). Nevertheless, market returns are often slightly leptokurtic, implying that dramatic market moves often take place at a frequency larger than that predicted by a normal distribution. (Poon & Granger, 2005) The results obtained can be said to affirm this assumption and hence tend to move towards confirmation of the concept being evaluated in this study. This is due to the fact that a kurtosis larger than 3 implies fatter tails and hence the respective model under-prices both out-of-the-money as well as in-the-money calls/puts. On the other hand, kurtoses lower than 3 imply thinner tails and consequently the market options are overpriced (Mian & Adam, 2001). Such stock valuations have also make way for kurtosis and skewness trading methods. Further test by looking at the histogram also reaffirm this sense of normality in the data as seen from Figure 1. Figure 1: Histograms Figure 2: Stock share price distribution The distribution of the stock share price further illustrates the samples as seen from Figure 2. It is important to note that graphs simply give a presentation of what has already been discussed in with regard to daily data statistics returns. Based on the descriptive statistics as detailed in Table I, the returns show that the mean return is for FTSE MID 250 daily stock return set at 0.000161 which is lower than MILAN COMIT GENERAL. However, MILAN COMIT GENERAL records a lower median returns. BRUSSELS ALL SHARE records lesser minimal returns as compared to the FTSE MID 250. To the contrary, the standard deviation for FTSE MID 250 is much lower as compared to that of MILAN COMIT GENERAL. Table 1: Descriptive Statistics of Daily Data This table
Share price evaluation Name: Institution: Date: Generally, descriptive statistics tells a lot about the stock returns as well as the indices data used in the study. The main descriptive statistics that helped in description of data are the mean, data skewness, kurtosis, standard deviation, data ranges, as well as the minimum and maximum values…
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