A nonparametric data mining approach for risk prediction in car insurance: a case study from the Montenegrin market

For prediction of risk in car insurance we used the nonparametric data mining techniques such as clustering, support vector regression (SVR) and kernel logistic regression (KLR). The goal of these techniques is to classify risk and predict claim size based on data, thus helping the insurer to assess the risk and calculate actual premiums. We proved that used data mining techniques can predict claim sizes and their occurrence, based on the case study data, with better accuracy than the standard methods. This represents the basis for calculation of net risk premium. Also, the article discusses advantages of data mining methods compared to standard methods for risk assessment in car insurance, as well as the specificities of the obtained results due to small insurance market, such as Montenegrin

Analysis of investors’ preferences in the Montenegro stock market using data mining techniques

This article analyses the preferences of different types of investors to stock characteristics in the Montenegrin stock market. The majority of papers deal with stock portfolio analysis of the institutional investors. Since the number of individual investors in the Montenegrin market is much higher, the analysis of their trading behaviour is also very significant. In this article, using data mining techniques, we tested trading behaviour with stocks for both types of investors. We prove that data mining techniques, such as logistic regression, clustering and ecision trees, provide good results in this type of analysis. The analysis may be useful to the future investors, brokers and stock exchange

Smart governments, regions and cities

Znanstvena monografija sadrži znanstvene radove sudionika međunarodne znanstvene konferencije pod naslovom Economics of digital transformation - Smart Governments, Regions and Cities u organizaciji Ekonomskog fakulteta u Rijeci. Rezultati istraživanja se odnose na razvoj i perspektive pametnih gradova i regija te ostale izazove digitalizacije i digitalne transformacije gospodarstva i društva