Peter Árendáš

Given the current turbulences on the European capital markets, as well as the expectations of a new recession, it is possible to expect that the risk of individual countries and their capital markets will increase significantly. This is particularly the case of those countries, which have long-term problems with economic instability and imbalances. The basis for country risk quantification is the country credit rating and credit risk of the government bonds. The market-based methods react often differently, as their reactions to the actual market developments are more flexible. The purpose of this paper is to compare various methods of country risk measurement. The study is focused on the country risk of Italy, a country that experienced a turbulent economic development over the last two decades. The results show that the CPFER method and sovereign ratings show a similar level of country risk, while the market-based methods show a higher level of country risk.

Numerous studies show that stock markets are often impacted by various calendar anomalies that disrupt the “random walk” behavior of stock prices. These anomalies contradict the Efficient markets theory and can be exploited to generate abnormal returns. This paper investigates the presence of two of them, namely the January effect and the January barometer, on the stock markets of 12 Central and Eastern European (CEE) countries. The paper examines the statistical significance of differences in returns recorded over the month of January and returns recorded over the other months (the January effect), as well as the statistical significance of differences between returns recorded during the remainder of year after a positive January return and after a negative January return (the January barometer). The results show, among other things, that the statistically significant January effect affects the Estonian, Lithuanian, Czech, Romanian, and Latvian stock markets. On the Romanian and Lithuanian stock markets, statistically significantly higher January returns are accompanied by statistically significantly higher January price volatility. On the other hand, we can speak of a statistically significant January barometer only in the case of the Latvian, Lithuanian, and Ukrainian stock markets. The presence of these anomalies is contrary to the Efficient market theory. It can be assumed that proper investment strategies based on these calendar anomalies should be able to generate abnormal returns.

Acknowledgment
This paper is an outcome of the science projects VEGA (1/0613/18) and VEGA (1/0221/21).