This paper investigates the relationship between foreign direct investment (FDI) and institutional quality measures (control of corruption, political stability, and rule of law) in the Western Balkans. The empirical study is based on panel techniques (unit root tests and causality) in the period 2002–2017. The results indicate that control of corruption, political stability, and rule of law cause an inflow of FDI at the Western Balkans. The bidirectional relationship has been found between political stability and rule of low, control of corruption and rule of law, and control of corruption and inflow of FDI. Thus, the study recommended that stronger institutional measures cause a higher inflow of foreign direct investments.

This paper examines the impact of illiquidity and liquidity risk on expected asset returns in the Serbian stock market. For this market we estimate the conditional Liquidity-adjusted Capital Asset Pricing Model (LCAPM) of Acharya and Pedersen (2005). We use daily data for the period from 2005-2009. While the method developed is applicable in other markets this is the first paper that tests the LCAPM model in the case of Serbia. Liquidity risks are allowed to be timevarying. We find that for the Serbian market as a frontier market illiquidity and liquidity risk significantly impact price formation. For such a market the LCAPM may indeed be a good tool for realistic assessment of the expected asset returns.

This article examines the following models: Capital Asset Pricing Model (CAPM) (Sharpe, 1964), and Liquidity CAPM (Hearn, Piesse and Strange, 2009) in the Croatian stock market. We used daily data for the period 2005–2009. The goal of this article is to examine the impact of an overall market factor, factor related to the firm size, and factor of liquidity risk on expected asset returns in the Croatian stock market. We found that Liquidity Capital Asset Pricing Model (LCAPM) model performs better in explaining stock returns than the standard CAPM. Additionally, LCAPM may indeed be a good tool for realistic assessment of the expected asset returns. The combination of company size and illiquidity in asset pricing in the context of the Fama and French cross-sectional framework can improve the description of equilibrium in the Croatian stock market.

One of the most challenging endeavors of contemporary research is to describe and analyze the dynamic behavior of time series arising from real-world systems. To address the need for analyzing long-range correlations and multifractal properties of multivariate time series, we generalize the multifractal detrended moving average algorithm (MFDMA) to the multivariate case and propose a multivariate MFDMA algorithm (MV-MFDMA). The validity and performance of the proposed algorithm are tested by conducting numerical simulations on synthetic multivariate monofractal and multifractal time series. The MV-MFDMA algorithm is then utilized to analyze raw, seasonally adjusted, and remainder components of five air pollutant time series. Results from all three cases reveal multifractal properties with persistent long-range correlations.

In this paper we analysed liquidity of the Croatian stock market. Low level of liquidity is one of the key problem areas facing this small market. As the measures of liquidity we used the Zero Rates return by Lesmond et al. (1999), Price Pressure of non-trading as in Bekaert et al. (2007), and Turnover. For calculating the Zero Rates return, and Price Pressure measures we used prices of all stocks listed at the the Zagreb Stock Exchange in the period: 2005 - 2009. Results showed that the level of liquidity for the Croatian market is very low. For this market the least illiquid year was 2007 (the pre-crises year), and most illiquid year for Croatia was 2009. We showed that illiquidity is persistent in this market. The first measures of correlation between all illiquidity measure are given. Particularly, we demonstrated that the Croatian market is less illiquid than the Serbian market.

Geopolitical risks and conflicts wield substantial influence on the global economy and financial markets, fostering uncertainty and volatility. This study investigates the intricate relationship between gold and representatives of green and sustainable stocks in the US and EU during the Russia-Ukraine conflict, employing multifractal detrended cross-correlation analysis (MF-DCCA) and nonlinear Granger causality. MF-DCCA reveals significant multifractal properties and nonlinear cross-correlations across all time series pairs. Notably, conflict weakened the multifractal cross-correlations between US stocks and gold, except for the TESLA/gold pair. A similar significant change in the EU market’s multifractal properties was observed during the conflict. In conjunction with MF-DCCA, Granger causality tests indicate bidirectional nonlinear relationships between gold and green/sustainable stock markets in the USA and EU. Gold’s past movements significantly influence changes in all the considered green and sustainable stocks, enabling predictions of their behavior. These findings shed light on multifractal dynamics during geopolitical crises and emphasize the bidirectional relationships between gold and green and sustainable stock markets. This comprehensive analysis informs investors and policy makers, enhancing their understanding of financial market behavior amid geopolitical instability.