Scenario Modeling of Frontier Financial Market Development

Abstract

Purpose – Hypothesis verification and quantification of the relationship between drivers and the resulting factors for a lasting impact on the long-term ICT development, globalization, structural changes in the geo-economy and changes in socio-ethical standards in society in the frontier financial markets. Research methodology – Based on open source information, a database of almost 19,000 data was formed - 748 obser-vations by country on 25 indicators. The simulation was performed on the basis of a mixed-model, which is a statistical model that is an extended version of the General Linear Model (GLM), using SAS / STAT® 13.1 software. Findings – Based on the Solution for Fixed Effects and Solution for Random Effects and the test of fixed effects, glo-balization, economic dominance, economic growth and human development were identified as statistically significant patterns of transformation of frontier financial markets. Research limitations – The paper does not attempt a comprehensive coverage of the topic. However, it identifies main drivers of the development of frontier financial markets and makes calls for further research. Practical implications – The findings are likely to be useful for practitioners and researchers to gain knowledge about the main drivers of the frontier financial markets development. Originality/Value – The application of the technique of multidimensional ranking of drivers has identified globalization, geoeconomic changes and human development as the most influential drivers for the development of frontier financial markets.

Моделювання Взаємозв'язку Між Розвитком Роздрібної Торгівлі Та Економічними Показниками В Європейських Країнах

“…A clustering of European countries was developed according to factors such as: educational factors, income characteristics and indicators of income inequality (Gini coefficients), urbanisation factors, indicators reflecting the functioning of the healthcare system, quality of life factors and the impact of the (negative) environment [4]. Researchers have also modelled financial markets using mixedeffects models [5], and studied and modelled the Slovak retail market [6].…”