The main goal of this article is to compare data-mining clustering methods (k-means and fuzzy c-means) based on a sample of banking and energy companies on the Gulf Cooperation Council (GCC) stock markets. We examined these companies for a pattern that reflected the effect of news on the bank sector’s stocks throughout October, November, and December 2012. Correlation coefficients and t-statistics for the good news indicator (GNI) and the bad news indicator (BNI) and financial factors, such as PER, PBV, DY and rate of return, were used as diagnostic variables for the clustering methods.
One of the most important group of assets in the balance sheet of an enterprise is the group of intangible assets. The asset situation of a sport enterprise is particularly complicated as such a company has an unusual type of intangible assets-players' performance rights. There are many problems with the valuation of such assets. This article presents the econometric approach to solving a valuation problem. Much research takes into account the possibilities of using econometric tools for valuation of the economic value of a professional football player's performance rights. The most important methods were presented in the paper of Trequattrini, Lombardi and Nappo (Trequattrini et al., 2012). The main goal of this article is to build econometric spatial models to explain the market value of footballer's performance rights according to players' sports results divided into homogeneous groups: goalkeepers, defenders, midfielders and forwards. The hypothesis of this research is that sports results influence the market value of footballers' performance rights. Hence, there are four additional hypotheses. For example, one of them concerning forwards will be as follows-the market value of a footballer's performance rights is dependent on the number of goals, the number of assists and the market value of the team. The following independent variables will be used: goals, assists, performance, yellow cards, red cards, club position in the league and the market value of the club in the whole research. Linear and non-linear models are used to test these hypotheses. The data set includes information about all players' game activity, taken from the Bundesliga (professional association football league in Germany) from the 2013/2014 season. The result of the analysis will identify variables closely tied to the market value of the football player's performance rights (footballers) and measure the goodness of fit of a statistical model. The study refers to the research conducted in 1999 and indicates new possibilities for the use of common tools, such as spatial econometric models. It is also a contribution to further research on the properties of the models.
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