In the article the author analyses the impact of the Financial Crisis, especially the Greek fiscal one, on the sCDS prices in Europe. The aim of the article is to assess the ability of the sCDS premia to price the risk of countries before and during the Greek crisis. The author analyses sCDS premia of maturity 10 years together with the so called bond-spreads, i.e. the spreadsbetween the countries’ bond indexes and the risk free rate of the region (in our case it was the yield of German bonds of corresponding maturity – 10 years).The idea was to check whether there occurred any discrepancies in the risk valuation via the two measures, as a consequence of the Greek crisis. The data is taken daily and covers the period of 2008‒2012. Based upon the results obtained in the research we conclude that the Greek crisis indeed influenced the relationships between the two measures of risk, however the degree of the influence was different in different countries. The relationships between the two measures of risk were totally broken only in the case of Greece, while in the other countries the relationships either were not distorted or had been broken already at the beginning of the financial crisis (2008/2009). The Greek problems were indeed reflected in volatilities of all analysed instruments; however triggering the credit event affected only Greek bonds dynamics.
The literature on exchange rate forecasting is vast. Many researchers have tested whether implications of theoretical economic models or the use of advanced econometric techniques can help explain future movements in exchange rates. The results of the empirical studies for major world currencies show that forecasts from a naive random walk tend to be comparable or even better than forecasts from more sophisticated models. In the case of the Polish zloty, the discussion in the literature on exchange rate forecasting is scarce. This article fills this gap by testing whether non-linear time series models are able to generate forecasts for the nominal exchange rate of the Polish zloty that are more accurate than forecasts from a random walk. Our results confirm the main findings from the literature, namely that it is difficult to outperform a naive random walk in exchange rate forecasting contest.