In this paper we assess the movements of euro area sovereign bond yield spreads vis-àvis the German Bund as processes specified across different levels of volatility and subject to movements in asset prices and economic conditions. The determinants we use are grouped into domestic and euro-area aggregates, thus allowing us to derive results on their relative explanatory power for movements in spreads and compare them across time and the spectrum of countries. We find that volatility influences the deterministic processes of the euro area sovereign spreads and that identical determinants have effects on spreads that vary considerably across countries. Furthermore, we find that economic sentiment indices are the most important determinants and their significance remains, to a large extent, even when controlling for the debt-to-GDP ratio.

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In this article we apply the Extreme Value Theory (EVT) in order to estimate the Value-at-Risk (VaR) and the correlation of extreme returns for two inherently unstable markets; the foreign exchange and the stock market. We also derive the corresponding VaR estimates from more ‘traditional’ methods of estimation on daily returns of the US dollar/Cyprus pound exchange rate and the Cyprus stock exchange general index. The main conclusion we reach is that the more heavy-tailed distributed a series is the more accurate the loss predictions are from the application of the EVT. We also show that the conditional correlation index of the extreme returns of those two markets remained almost constant throughout the backtesting period that was characterized by ‘bear’ market conditions.

In this paper we analyze the implications for the identification of common stochastic trends among stock price indices of using data transformed on a "real dollar" basis. By applying a "general" VAR model where all the relevant variables (stock indices, consumer price indices and the exchange rate) are included, we show that the expected results from the cointegration analysis differ substantially. In particular it is shown that if four common stochastic trends drive the system then cointegration between the indices transformed in nominal dollars should be the relevant test while the use of their "real dollars equivalent" is superfluous. In cases where three common stochastic trends exist then a reasonable specification of the model would imply that the Purchasing Power Parity condition accounts for one of them while the second one relates to a cointegrating relation between the stock indices in nominal domestic currency terms. We apply the testing methodology developed by Johansen (1992a, 1995a, 1997) and extended by Paruolo (1996) and Rahbek et al. (1999) to examine the presence of I(2) and I(1) components in a multivariate context using monthly data for the US, UK, Germany and Japan for the period 1980-2000. Four possible economic scenarios were considered in a bivariate setting and two of them were found to be statistically supported. By imposing linear restrictions on each cointegrating vector as suggested by Johansen and Juselius (1994), the order and rank conditions for statistical identification are satisfied while the test for economic identification was not significant for each bilateral case, namely US-UK, US-Germany, US-Japan. The main findings suggest that the policy to transform the data into a "real" dollar basis, which is often encountered in the literature, lacks empirical support. Furthermore, the stability results indicate that cointegration was established in the early 1990s which implies that some form of policy coordination between the G-7 countries was implemented in the aftermath of the October 1987 crisis.