Elza Jurun

Comparative regional GDP analysis: case study of Croatia

The focus of this paper is the regional GDP analysis of Croatian Counties. It is a part of an extensive on-going scientific research about Croatian economic challenges within the global recession environment. Although, as EU accession country, Croatia is divided into three NUTS 2 regions, twenty one Croatian Counties show significant economic and social disproportions. In multiple regression model it is researched to what extent regional GDP per capita depends on a set of regional variables (employment, gross investment, production of more important agricultural products, GVA per person employed, construction works value, exports, imports, foreign tourists arrivals, foreign tourist nights, ecology...). Subsequently parameters are evaluated by Monte Carlo simulations which are used for the first time in comparative regional analysis. Also Croatian Counties are classified using Cluster analysis to make a comparative analysis with official spacing into three NUTS 2 regions which are geographical and political areas rather than real and homogenous socio-economic areas.

The significance of non-financial information flows in risk management

Risk management in this paper is focused on the concept of information efficiency. Information efficiency means that prices fully reflect all relevant information at every instant and therefore prices can not be predicted, i.e. prices are evolving randomly. When stock markets are not efficient, there are possibilities for speculation. Although neither the direction nor the magnitude of the price change can be specified without knowing the expectations model of investors, therefore Capital Asset Pricing Model (CAPM) will be used for removing the market wide effects, i.e. unspecified factors. By removing the effects from unspecified factors, unexpected price changes can be estimated, in period around the announcement day, due to the incoming information. The aim of this paper is to provide evidence of information which can affect investors strategies, and to compare the influence of bad news and good news to the price changes. Moreover, empirical analysis will show that there is significant correlation between information content of the incoming news and price volatility (unexpected price changes) based on data set of daily closing prices for 6 most traded stocks, all obtained form Zagreb Stock Exchange. It is expected that bad news have greater influence on price movements than the good news.