Do Terror Attacks Affect the Euro? Evidence from the 21st Century

The objective of this paper is to examine whether terror attacks that took place in the Eurozone in the 21st century had a significant effect on the price of the Euro. Its novelty is twofold: it is the first study that assesses the impact of such events on the price of the Euro and employs a relatively large number of these events. The event-study methodology is used to deduce whether, after a terror event, the value of the Euro declines vs. other major currencies. We found that it does not, since following such an event, the decline was seldom over 0.5%. We also found, however, evidence of some diversion to safe-haven currencies, such as the Swiss Franc. Regression analysis revealed that factors such as the ‘number of attacks’, the ‘type of target’ and the ‘type of attack’, but not the number of casualties, affected the price of the Euro.

Euro, dollar or Swiss franc: which currency had the greatest impact on the Hungarian, Polish and Czech economies during the global financial crisis?

The article presents an analysis of the impact of foreign currency dynamics on the fundamentals (basic indices of the economic performance) of the Czech Republic, Hungary and Poland during the financial crisis of 2007/2008 and its aftermath until 2017. The subject of the analysis are three currencies: the US dollar, the euro and the Swiss franc. The assessment of their impact on the fundamentals of the three above-mentioned economies is based on the joint volatilities of bond spreads and currencies. A series of copula-GARCH models was estimated. The research demonstrates that the impact of foreign currencies was the strongest in the case of Poland and Hungary, as these two countries were more dependent on loans in foreign currencies than the Czech Republic. Another finding shows that the impact decreased significantly in Hungary after its government introduced loan conversion.

Financial Crises, Macroeconomic Variables, and Long-Run Risk: An Econometric Analysis of Stock Returns Correlations (2000 to 2019)

This paper focuses on four major aggregate stock price indexes (SP 500, Stock Europe 600, Nikkei 225, Shanghai Composite) and two “safe-haven” assets (Gold, Swiss Franc), and explores their return co-movements during the last two decades. Significant contagion effects on stock markets are documented during almost all financial crises; moreover, in line with the recent literature, the defensive role of gold and the Swiss Franc in asset portfolios is highlighted. Focusing on a new set of macroeconomic and financial series, a significant impact of these variables on stock returns correlations is found, notably in the case of the world equity risk premium. Finally, long-run risks are detected in all asset portfolios including the Chinese stock market index. Overall, this empirical evidence is of interest for researchers, financial risk managers and policy makers.

The predictive capacity of GARCH-type models in measuring the volatility of crypto and world currencies

This paper provides a thorough overview and further clarification surrounding the volatility behavior of the major six cryptocurrencies (Bitcoin, Ripple, Litecoin, Monero, Dash and Dogecoin) with respect to world currencies (Euro, British Pound, Canadian Dollar, Australian Dollar, Swiss Franc and the Japanese Yen), the relative performance of diverse GARCH-type specifications namely the SGARCH, IGARCH (1,1), EGARCH (1,1), GJR-GARCH (1,1), APARCH (1,1), TGARCH (1,1) and CGARCH (1,1), and the forecasting performance of the Value at Risk measure. The sampled period extends from October 13th 2015 till November 18th 2019. The findings evidenced the superiority of the IGARCH model, in both the in-sample and the out-of-sample contexts, when it deals with forecasting the volatility of world currencies, namely the British Pound, Canadian Dollar, Australian Dollar, Swiss Franc and the Japanese Yen. The CGARCH alternative modeled the Euro almost perfectly during both periods. Advanced GARCH models better depicted asymmetries in cryptocurrencies’ volatility and revealed persistence and “intensifying” levels in their volatility. The IGARCH was the best performing model for Monero. As for the remaining cryptocurrencies, the GJR-GARCH model proved to be superior during the in-sample period while the CGARCH and TGARCH specifications were the optimal ones in the out-of-sample interval. The VaR forecasting performance is enhanced with the use of the asymmetric GARCH models. The VaR results provided a very accurate measure in determining the level of downside risk exposing the selected exchange currencies at all confidence levels. However, the outcomes were far from being uniform for the selected cryptocurrencies: convincing for Dash and Dogcoin, acceptable for Litecoin and Monero and unconvincing for Bitcoin and Ripple, where the (optimal) model was not rejected only at the 99% confidence level.

Shaping Facebook and Twitter Public Spheres: The Case of Swiss Franc Mortgage Holders in Poland

The article focuses on the online communication on Polish Facebook and Twitter around issues related to mortgage loans in Swiss francs. Based on 20k posts retrieved from both Facebook and Twitter, we found the most active actors and the most common topics appearing on those micro-public spheres. It was revealed that actors with institutional affiliation and those who are not affiliated discuss different problems and share dissimilar content related to Swiss franc debts. It was also found that certain categories of actors may influence online discussions on both social networking sites by promoting specific content in order to pursue their institutional interests. Finally, the diversity of topics and problems discussed by the two categories of actors identified on Facebook and Twitter suggest that Swiss franc mortgage holders are a good example of “connective action” with no clear identity or community traits that led to favourable judgment of the European Court of Justice.