Eurozone Stock Market Research Articles

Eurozone Stock Market Integration and the Base-Bank Money Divergence

Eurozone Stock Market Integration and the Base-Bank Money Divergence

21st Century Evidence on the Effect of Terror Attacks on Eurozone Stock Markets

ABSTRACT This paper uses the event study methodology to examine whether ‘significant’ terror attacks that occurred in the Eurozone in the 21st century affect stock markets. We find that such events do have a negative effect both on the market of the country suffering the attack, and on the general Eurozone market index. Depending on the method and the market index used, this effect ranges between −0.3% and −0.62% and is concentrated entirely on the day of the attack. We moreover find that this effect is more pronounced and of significance during the first decade of the 21st century. Regression analysis revealed that the most important factor affecting the magnitude of the effect is economic damage resulting from the attack.

Causal coupling between European and UK markets triggered by announcements of monetary policy decisions.

We investigate high-frequency reactions in the Eurozone stock market and the UK stock market during the time period surrounding European Central Bank (ECB) and the Bank of England (BoE)’s interest rate decisions, assessing how these two markets react and co-move influencing each other. The effects are quantified by measuring linear and nonlinear transfer entropy combined with a bivariate empirical mode decomposition from a dataset of 1 min prices for the Euro Stoxx 50 and the FTSE 100 stock indices. We uncover that central banks’ interest rate decisions induce an upsurge in intraday volatility that is more pronounced on ECB announcement days and there is a significant information flow between the markets with prevalent direction going from the market where the announcement is made towards the other.

Eurozone Stock Market Reaction to Monetary Policy Interventions and Other Covariates

The joint effect of the global economic and sovereign debt crisis forced the European Central Bank (ECB) to apply conventional and non-standard expansionary monetary policy interventions in order to stabilize eurozone economies. We conducted a panel regression econometric analysis to study the influence of euro area monetary authority policy interventions, along with two main macroeconomic variables and a sentiment indicator, on market equity returns of eurozone countries for the period January 2007 to December 2017. Our findings suggest that conventional and non-standard monetary policy innovations had a positive lagged impact on equity returns of euro area monetary markets. More specifically, interest rate cuts evenly influenced market indices while non-conventional actions mainly affected core eurozone countries that were less affected by the crisis. We also document a strong negative relationship between inflation rates and market returns. In addition, the sentiment indicator produces positive effects on returns because it contains information that is not incorporated into other macro variables.

An Empirical Investigation on the Relationship Between the Eurozone Zew Index and the Eurozone Stock Markets

Abstract The aim of this study is to investigate the long and short term impact of the Euro ZEW index (ZEW) on the DAX (GDAXI) Germany, FTSE 100 (FTSE) the UK, CAC 40 (FCHI) France, OMXS30 Sweden and CROBEX (CRBEX) Croatia stock market indices using monthly data for the period between February 2008 and December 2020. The Euro ZEW Index was taken as the independent variable, and the index values of Eurozone stock markets were taken as the dependent variables. As a result of the study, the Euro ZEW index was found to have a positive (increasing) statistical significant effect on the DAX, FTSE, OMXS and CRBEX variables. Of the stock markets studied, Croatia CROBEX (CRBEX) index was the most affected index by the change in the Euro ZEW index. The least affected stock market was Germany DAX (GDAXI) index. The effect of the Euro ZEW Index on Euro stock markets was higher in the short-term, and gradually decreasing in the long term. The research findings are discussed in the conclusion section.

Quantile Risk–Return Trade-Off

We investigate the risk–return trade-off on the US and European stock markets. We investigate the non-linear risk–return trade-off with a special eye to the tails of the stock returns using quantile regressions. We first consider the US stock market portfolio. We find that the risk–return trade-off is significantly positive at the upper tail (0.9 quantile), where the upper tail is large positive excess returns. The positive trade-off is as expected from asset pricing models. For the lower tail (0.1 quantile), that is for large negative stock returns, the trade-off is significantly negative. Additionally, for the median (0.5 quantile), the risk–return trade-off is insignificant. These results are recovered for the US industry portfolios and for Eurozone stock market portfolios.

Causal coupling between European and UK markets triggered by announcements of monetary policy decisions

We investigate high-frequency reactions in the Eurozone stock market and the UK stock market during the time period surrounding the European Central Bank (ECB) and the Bank of England (BoE)'s interest rate decisions assessing how these two markets react and co-move influencing each other. The dynamic multiscale interaction between these markets and the spillover effect on monetary policy announcement days are quantified by measuring linear and non-linear transfer entropy combined with a Bivariate Empirical Mode Decomposition (BEMD) from a dataset of 1-minute prices for the Euro Stoxx 50 and the FTSE 100 stock indices. We draw the following conclusions. First, central banks' interest rate decisions induce an upsurge in intraday volatility that is more pronounced on ECB announcement days. Second, there is a clear and significant information flow between the markets surrounding the time interest rates are released with prevalent direction going from the market where the announcement is made towards the other. Third, the coupling between the two markets describing the spillover effects is sufficiently well modeled with the linear approach to transfer entropy. %appears to be sufficient in detecting the spillover.

Quantile Risk-Return Trade-Off

We investigate the risk-return trade-off on the US and European stock markets. We investigate the non-linear risk-return trade-off with a special eye to the tails of the stock returns using quantile regressions. We first consider the US stock market portfolio. We find that the risk-return trade-off is significantly positive at the upper tail (0.9 quantile), where the upper tail is large positive excess returns. The positive trade-off is as expected from asset pricing models. For the lower tail (0.1 quantile), that is for large negative stock returns, the trade-off is significantly negative. And for the median (0.5 quantile), the risk-return trade-off is insignificant. These results are recovered for the US industry portfolios as well as for Eurozone stock market portfolios.

A Dynamic Correlation Analysis of Financial Contagion: Evidence from the Eurozone Stock Markets

Objective: In this article, we try to determine whether there are contagion effects across the Greek stock market and the Belgian, French, Portuguese, Irish, Italian and Spanish stock markets during both crises periods. Research Design & Methods: To reach our aim, we used a bivariate Dynamic Conditional Correlation-Generalized Autoregressive Conditional Heteroscedasticity (DCC-GARCH) model to measure the extent of dynamic correlations between stock returns of our sample. Findings: Our results point to the presence of a contagion effect between all market pairs during the subprime crisis and between the Greek and Portuguese stock markets during the European sovereign debt crisis. Implications & Recommendations: The obtained results are useful for investors, in particular for their portfolio diversification strategies. They are also useful for the monetary and financial authorities in their efforts to absorb shocks resulting from crises. Contribution & Value Added: The originality of this work lies in studying contagion effect across the Eurozone stock markets through the bivariate DCC-GARCH model which is an original dynamic estimation of conditional correlations in Multivariate GARCH models. The measures of contagion effects following the valuation of countries induced by the massive negative sovereign rating signals during the crisis period would also be interesting to study. The methods might also be applicable to this kind of contagion type and for contagions effects across European stock market returns.

Time-Localized Wavelet Multiple Regression and Correlation: Eurozone Stock Markets Across Scales and Time

This paper extends wavelet methodology to handle co-movement dynamics of multivariate time series via moving weighted regression on wavelet coefficients. The concept of wavelet local multiple correlation is used to produce one single set of multi-scale correlations along time, in contrast with the large number of wavelet correlation maps that need to be compared when using standard pairwise wavelet correlations with rolling windows. Also, the spectral properties of weight functions are investigated and it is argued that some common time windows, such as the usual rectangular rolling window, are not satisfactory on these grounds. The method is illustrated with a multi-scale analysis of the co-movements of Eurozone stock markets during this century. It is shown how the evolution of the correlation structure in these markets has been far from homogeneous both along time and across timescales featuring an acute divide across timescales at about the quarterly scale. At longer scales, evidence from the long-term correlation structure can be interpreted as stable perfect integration among Euro stock markets. On the other hand, at intramonth and intraweek scales, the short-term correlation structure has been clearly evolving along time, experiencing a sharp increase during financial crises which may be interpreted as evidence of financial ‘contagion’.

Value at Risk (VaR) Historical Approach: Could It Be More Historical and Representative of the Real Financial Risk Environment?

The purpose of this paper is to suggest a new approach that improves the conventional Historical Value-at-Risk (HVaR) estimations’ accuracy and can be easily applied by anyone. The main assumption for the newly suggested method is “the more representative to the financial conditions the data inputs are, the better the VaR estimations”. Volatility is assumed to be the criterion for the “representative to the financial conditions” definition. In practice, the newly suggested approach does not use the previous x days observations as data inputs in the estimation process (as the HVaR does), but the last x filtered volatility (fv) observations of a “representative to the current financial conditions dataset”. Depending on the volatility value, each observation is classified in several regimes, from which the VaR is estimated depending on the examined day’s volatility. This way the HVaR approach is more historical. The empirical findings using data from the US and the Eurozone stock market show that the newly suggested filtered volatility approach not only significantly improves the VaR estimations, but also makes these estimations much more representative of the real financial conditions. The results using the filtered volatility approach are comparable to some previously documented VaR estimations that adopt advanced econometric models. In this point, we should note advanced econometric models have the drawbacks that are not usually applied in financial markets industry because of their complexity. The newly suggested approach: (i) popularizes some of the most advanced econometric techniques, (ii) improves the VaR estimations accuracy, and (iii) enables financial risk analysts and portfolio managers to estimate the risk-return under several volatility regimes in order to help them to apply their desired investment strategy. Finally, this paper not only examines accuracy using the traditional/conventional tests [1], but also suggests some new measures for the comparison amongst different VaR models and their ability to accurately estimate the real financial risk.

The Determinants of Banks’ Capital Adequacy Ratio: Some Evidence from South Eastern European Countries

The legal authorities set the minimum capital level for the banks. Recent studies have shown that variables used to explain capital structure of non financial firms, such as size, profit, leverage, liquidity and risk, could also be helpful in understanding banks’ capital structure. This paper aims to evaluate the impact of bank-dimensional and environmental factors on bank’s capital adequacy ratio in South Eastern European (SEE) region. Size, profitability (ROA), leverage, liquidity, net interest margin (NIM), and risk are used as bank-dimensional explanatory variables in a feasible GLS regression model. On the other hand, economic growth rate, inflation, real interest rate, Eurozone stock market volatility index, deposit insurance coverage, and governance indicator are added to the original model to control for environmental factors. Annual data from 71 commercial banks belong to 10 different countries in SEE region for the period of 2007 – 2012 is used. This region mainly consists of the “transition economies” which are still experiencing the difficulties of turning into efficient market economies with high economic potentials. The results of our study show that among the bank dimensional explanatory variables size, ROA, leverage, liquidity, net interest margin and risk have statistically significant effects in determining CAR for the banks in the region. Among the environmental factors, economic growth rate, Eurozone stock market volatility index, deposit insurance coverage, and governance have statistically significant effects in determining CAR for the banks in the SEE region.

A Formal Test of Asymmetric Correlation in Stock Market Returns and the Relevance of Time Interval of Returns – a Case of Eurozone Stock Markets

A Formal Test of Asymmetric Correlation in Stock Market Returns and the Relevance of Time Interval of Returns – a Case of Eurozone Stock Markets

A Formal Test of Asymmetric Correlation in Stock Market Returns and the Relevance of Time Interval of Returns – a Case of Eurozone Stock Markets

A Formal Test of Asymmetric Correlation in Stock Market Returns and the Relevance of Time Interval of Returns – a Case of Eurozone Stock Markets

A Study on the Shocks of Euro zone's Stock Market under the European Debt Crisis

A Study on the Shocks of Euro zone's Stock Market under the European Debt Crisis

The Impulse Response Function of Economic Policy Uncertainty and Stock Market Returns: A Look at the Eurozone

This paper examines the impulse response function of economic policy uncertainty (EPU) and stock market returns in the Eurozone. Using a vector autoregression analysis, this study explores how the Eurozone’s stock market responds to the impulse of economic policy uncertainty; a response feedback from the stock market is also examined. Using monthly data of the changes in economic policy uncertainty index and returns on the index of Eurozone stock market from 1993 to 2012, this study shows that Eurozone stock market returns respond positively to the changes in economic policy uncertainty; this response is statistically significant in the second, seventh and eighth months. However, the pooled OLS shows that the increase in the changes in economic policy uncertainty predicts lower stock market returns. The results also reveal a strong feedback from the stock market. The changes in economic policy uncertainty are significantly lower in the first, fourth and eighth months when the impulse is stock market returns.

Wavelet multiple correlation and cross-correlation: A multiscale analysis of Eurozone stock markets

Statistical studies that consider multiscale relationships among several variables use wavelet correlations and cross-correlations between pairs of variables. This procedure needs to calculate and compare a large number of wavelet statistics. The analysis can then be rather confusing and even frustrating since it may fail to indicate clearly the multiscale overall relationship that might exist among the variables. This paper presents two new statistical tools that help to determine the overall correlation for the whole multivariate set on a scale-by-scale basis. This is illustrated in the analysis of a multivariate set of daily Eurozone stock market returns during a recent period. Wavelet multiple correlation analysis reveals the existence of a nearly exact linear relationship for periods longer than the year, which can be interpreted as perfect integration of these Euro stock markets at the longest time scales. It also shows that small inconsistencies between Euro markets seem to be just short within-year discrepancies possibly due to the interaction of different agents with different trading horizons.

Eurozone Stock Market Reactions to Unexpected ECB Monetary Policy Announcements

To examine the Eurozone stock market reactions to European Central Bank (ECB) monetary policy announcement surprises, we study the effect of unexpected changes in the ECB's main refinancing rate on aggregate and sectorial Eurozone equity returns. We also analyse the results according to varying business conditions. We estimate unexpected changes on the basis of the market's expectations released in the financial press just before the monetary policy announcement. Using an event study methodology for the 1999-2008 period, we found that the impact of ECB monetary policy surprise is not significant for Euro-zone stock markets. However, we find a significant stock market reaction around unexpected ECB monetary policy announcements when we account for business conditions.

Correlation dynamics in European equity markets

We examine correlation dynamics using daily data from 1993 to 2002 on the five largest Euro-zone stock market indices. We also study, for comparison, the correlations of a sample of individual stocks. We employ both unconditional and conditional estimation methodologies, including estimation of the conditional correlations using the symmetric and asymmetric DCC-MVGARCH model, extended with the inclusion of a deterministic time trend. We confirm the presence of a structural break in market index correlations reported by previous researchers and, using an innovative likelihood-based search, we find that the it occurred at the beginning the process of monetary integration in the Euro-zone. We find mixed evidence of asymmetric correlation reactions to news of the type modelled by conventional asymmetric DCC-MVGARCH specifications.

Idiosyncratic Risk, Market Risk and Correlation Dynamics in European Equity Markets

We examine correlation dynamics using daily data from 1993 to 2002 on the 5 largest euro-zone stock market indices. We also study, for comparison, the correlations of a sample of individual stocks. We employ both unconditional and conditional estimation methodologies, including estimation of the conditional correlations using the symmetric and asymmetric DCC-MVGARCH model, extended with the inclusion of a deterministic time trend. We confirm the presence of a structural break in market index correlations reported by previous researchers and, using an innovative likelihood-based search, we find that it occurred at the beginning the process of monetary integration in the Euro-zone. We find mixed evidence of asymmetric correlation reactions to news of the type modelled by conventional asymmetric DCC-MVGARCH specifications.