Treatment of kurtosis in financial markets

Since Mandelbrot (1963) [2] highlighted the fact that data on the yield of financial assets exhibit leptokurtosis, different distributions have been presented as alternatives to the normal distribution. So far little consideration has been given to the capacity that these distributions have to recover the kurtosis of the sample data. Our work aims to present distributions which, given the broad range of their kurtosis, have the capacity to perform adjustment on many occasions where other distributions fail, while also being capable of recovering the peakedness of the empirical data. Another key characteristic of these distributions is that they are defined within a bounded domain in the same way as the sample data. An empirical application of these distributions is presented within the financial field by using daily returns.