Prague Economic Papers - impact factor journal of the University of Economics, Prague

Bad decisions have harmful effects on the quality of human life and an increase of their duration expands these undesirable effects. Systematic bad decisions related to dividend policy can affect the investors’ quality of life in the long-term. We propose an agent-based model for the estimation of the duration of systematically making bad decisions, with an application on dividend policy. We propose an algorithm that can be used in modelling the interaction between different classes of shareholders and for predicting this duration. We perform numerical simulations based on this model using NetLogo 6.0.4. We prove that, as a result of agents’ interaction, in some conditions, the duration of systematically making bad decisions can be very long: some numerical simulations suggest that, in some circumstances, this duration can significantly exceed the human lifetime. Additionally, in some conditions, the company can fail before the power is switched. This duration can increase dramatically if the shareholders have a great level of trust in the management’s decisions. As an implication, a greater concern for the quality of financial education, and more performant instruments for controlling the power’s decisions are required.

International portfolio management is influenced by the existence of “frictions”, factors or events that interfere with trade, which are linked in financial literature to market-specific factors, such as available information, restrictions, investor protection, or market liquidity. Given the wide variety of factors that can be included in these categories, scientific studies typically focus on a reduced number of indicators at a time in order to offer an in depth analysis of their impact. We offer a consolidated view of the perspectives observed in financial literature by proposing a novel index for market frictions that includes all these four components and rank fifteen post-communist East European capital markets based on their index values. We then constructed various scenarios by assuming different levels of importance for the criteria used in index construction. By employing grey clustering analysis, we cluster these capital markets into three categories—strongly recommended, recommended with some reserve, and not recommended—based on the importance given by the decision maker to these factors. The results show that some of the studied markets are in the same cluster, irrespective of the chosen scenario. The only market always included in the “strongly recommended” category is Hungary, indicating that it is a good investment option for international participants. Bulgaria and Slovakia are always regarded as “recommended with reserve” markets, whereas the Republic of Moldova is part of the “not recommended” category. The other markets show a degree of variability that can be explained by different investor perspectives. This study contributes to the existing literature by combining the advantages of grey clustering and portfolio analysis. Investors can use this approach during the decision-making process related to their investments.