In the paper, we document how conditional dependencies observed in the FOREX market change during a trading day. The analysis is performed for the pairs (GBP/EUR, USD/EUR) and (GBP/USD, EUR/USD) of exchange rates. We consider daily returns calculated using the exchange rates quoted at different hours of a day. The dynamics of the dependencies is modeled by means of 3-regime Markov regime switching copula models, and the strength of the linkages is described using dynamic Spearman’s rho and the dynamic coefficients of tail dependence. The established approach allows us to monitor the changes in the dependence structure.

We test whether the floating exchange rates of the EU New Member States against the euro are determined jointly within the panel VEC framework. We find that the exchange rates of the Czech koruna, the Polish zloty and the Hungarian forint follow the same long-run relationship, in which the real exchange rates are explained by the real interest rates parities and the spreads of the credit default risk premiums. In case of the Romanian leu, the common relationship is rejected, which is likely due to differences in the economic setting. The results confirm that the currency markets of these three countries are closely related, since the appreciation/depreciation of one currency leads to similar movements in the other currencies of the NMS. The estimated misalignments exhibit some common patterns in terms of time spans and percentage values of under/overvaluation.

In this work, the level of influence of the posts published by famous people on social networks on the formation of the cryptocurrency exchange rate is investigated. Celebrities who are familiar with the financial industry, especially with the cryptocurrency market, or are somehow connected to a certain cryptocurrency, such as Elon Musk with Dogecoin, are chosen as experts whose influence through social media posts on cryptocurrency rates is examined. This research is conducted based on statistical analysis. Real cryptocurrency exchange rate forecasts for the selected time period and predicted ones for the same period, obtained using three algorithms, are utilized as a dataset. This paper uses methods such as statistical hypotheses regarding the significance of Spearman’s rank correlation coefficient and Pearson’s correlation. It is confirmed that the posts by famous people on social networks significantly affect the exchange rates of cryptocurrencies.