This paper attempts to delineate from a theoretical of view the financial data series relative to other statistical data, starting from the financial econometrics’ models and from the resulting features of the specific descriptive statistics’ analysis of these characteristic series. From the analysis of these financial data during either very short and short or medium periods of time or from the information provided by the website of the Bucharest Stock Exchange (BVB), the trend of great values of kurtosis or eccentricity and skewness or asymmetry of series appears as a characteristic tendency. During a long period of time, between 1920 and 2008, this tendency seems to be more relevant, being confirmed by an excerpt from the author’s earlier paper written in 2009, concerning the statistical Dow Jones Industrial Average Index (DJIA Index). The skewness, kurtosis and normality of data distribution analysis, using Jarque Bera test, along with the identification of residual autocorrelation or serial correlation in the presence of significant residual values and heteroskedasticity are the major evaluated aspects. Finally, the author investigates the optimal way to ensure statistical comparability inflationary and deflationary method for financial series of data, and offers a solution to the selection of the appropriate indicator from the categories of the absolute values, absolute variation of the absolute values and the relative variation of the absolute values, expressed by percentages, with the finding of the latter alternative as the best alternative in the world of financial modelling of the economic and financial processes and phenomena.
