The stock exchanges are widely considered to be pivotal institutions providing the capital for companies and helping them to gain competitive advantage through economies of scale. This paper examines and sheds additional insight into the stock market behaviour of countries of Visegrad Group, namely the Czech Republic, Slovak Republic, Poland and Hungary, beyond the global financial crisis. The study uses data about official stock market indices of the four official stock exchanges in the Visegrad region, between the years 2010-2016. It applies the correlation analysis in attempt to find out whether the indices, namely the BUX Index, PX Index, SAX Index and WIG 20 Index, have similarities in their behaviour, beyond the crisis. The results indicate the V4 stock markets of geographically connected economics exhibit significant similarities in their behaviour, in the post-crisis period. The paper, inter alia, stresses the importance of the stock markets and provides a coherent overview on official V4 stock markets and their official stock market indices.

This paper aims to explore specific cross-asset market correlations over the past fifteen-yearperiod-from January 04, 1999 till April 01, 2015, and within four sub-phases covering both the crisis and the non-crisis periods. On the basis of multivariate statistical methods, we focus on investigating relations between selected well-known market indices-U.S. treasury bond yields-the 30-year treasury yield index (TYX) and the 10-year treasury yield (TNX); commodity futuresthe TR/J CRB; and implied volatility of S&P 500 index-the VIX. We estimate relative logarithmic returns by using monthly close prices adjusted for dividends and splits and run normality and correlation analyses. This paper indicates that the TR/J CRB can be adequately modeled by a normal distribution, whereas the rest of benchmarks do not come from a normal distribution. This paper, inter alia, points out some evidence of a statistically significant negative relationship between bond yields and the VIX in the past fifteen years and a statistically significant negative linkage between the TR/J CRB and the VIX since 2009. In rather general terms, this paper thereafter supports the a priori idea-financial markets are interconnected. Such knowledge can be beneficial for building and testing accurate financial market models, and particularly for the understanding and recognizing market cycles.

This paper examines the effectiveness of implementing carbon taxes to reduce carbon dioxide emissions from transport. Using the system Generalized Method of Moments estimator, we utilize cross-country analysis for the first time to study the impact of carbon taxes on the composition of petrol versus diesel passenger cars sold in 17 countries over the period 2013–2017. The results suggest that increasing carbon taxes affects consumer behavior, causing a significant shift from petrol to diesel fuel vehicles, controlling for factors such as the price of passenger cars, fuel price, interest rates, income level, population density, inflation, and vehicle stock.

This paper aims to explore which macroeconomic factors affect the volatility of the automakers stock prices by employing a multifactor model. The study uses quarterly panel data of 39 automakers quoted on the stock exchanges in the 11 countries. It studies the effects of 19 macroeconomic variables from January 2000 to December 2017, and proposes the mixed-effect model constructed based on employing genetic algorithm and AIC criterion, and compares its explanatory power with the existing multifactor model . This paper suggests that the proposed model can shed more light on explaining the variability of stock prices of the quoted automakers. The findings show there are positive linkages between automaker's stock return volatility and explanatory variables such as stock market development, GDP and unemployment. Conversely, an inverse linkage between the dependent variable and money supply and IPI was found. The study demonstrates that selected macroeconomic factors can also be used as predictors. ARTICLE HISTORY

Globalization of the capital markets increasingly leads the investors to understand the fundamentals and technicals of asset cross-correlations and the global asset allocation seems to be an important task. The paper measures product momentum correlations between the four leading global benchmarks Standard & Poor’s stock index, Thomson Reuters/Jefferies CRB index, 30-Year U.S. Treasury Bond Price index and Dollar Index and between these indices and the Czech stock PX index. Empirical results illustrate that statistically significant correlations between U.S. indices existed over some past period at the 95.0% confidence level. In addition, the significant relation between indices Standard & Poor’s stock index, Thomson Reuters/Jefferies CRB index and the Czech stock market PX during the past fifteen years has been detected. These conclusions were reached from an analysis of monthly data in the United States and the Czech Republic, from January 1999 to April 2014. The empirical results offer beneficial applications not only for investors to diversify their risk but also for policy-makers to allocate resources more efficiently.