GEOGRAPHICAL INFORMATIONAL SYSTEMS - APPLICABILITY IN INVESTMENTS AND BANKING

Supported by information systems, the regional or world economy transformed itself in a global economy. Taking fast and optimal decisions is needed for each step an individual or an organization makes in order to support competitiveness in the context of radical evolution of the world economy. When dealing with fundamental decisions, spatial information plays an important role because it allows integration of data from various domains, having multiple connections, as well as their visualization and analysis in a useful, suggestive and efficient manner. Decision support systems (DSS) are spatially based computer applications and data which assists managers in making decisions. Since Geographical Informational Systems technology has a great deal to offer to the mortgage finance industry the goal of this paper is to analyze the main theoretical and practical approaches regarding the role of the geographic location and spatial relationships over the outcomes of the banking, housing and mortgage market.Investment, Banking, GIS Modeling, Decision Making System, Spatial Analysis

TESTING THE LONG RANGE-DEPENDENCE FOR THE CENTRAL EASTERN EUROPEAN AND THE BALKANS STOCK MARKETS

Abstract: In this study we tested the existence of long memory in the return series for major Central Eastern European and Balkans stock markets, using the following statistical methods: Hurst Exponent, GPH method, Andrews and Guggenberger method, Reisen method, Willinger, Taqqu and Teverovsky method and ARFIMA model. The results obtained are mixed. The Hurst Exponent showed the existence of long memory in all indices, except PX. After applying the GPH method, the results showed that BET, ATHEX, SOFIX and CROBEX have a predictable behavior. The ARFIMA model results support the existence of long memory for BUX, SAX and BELEX. The predictable behavior of index returns may suggest that the CEE and Balkans stock markets are not weak form efficient