I investigate the time variation in the integration of EU government bond markets. The integration is measured by the explanatory power of European factor portfolios for the individual bond markets for each year. The integration of the government bond markets is stronger for EMU than non-EMU members and stronger for old than new EU members. For EMU countries, the integration is weaker the lower the credit rating is. During the recent crisis periods, the integration is weaker, particularly for EMU countries.

The paper introduces and estimates a multivariate level-GARCH model for the long rate and the term-structure spread where the conditional volatility is proportional to the γth power of the variable itself (level effects) and the conditional covariance matrix evolves according to a multivariate GARCH process (heteroskedasticity effects). The long-rate variance exhibits heteroskedasticity effects and level effects in accordance with the square-root model. The spread variance exhibits heteroskedasticity effects but no level effects. The level-GARCH model is preferred above the GARCH model and the level model. GARCH effects are more important than level effects. The results are robust to the maturity of the interest rates.

Using a large panel data set containing detailed information on educational attainments as well as financial and socioeconomic variables for individual investors, we show that economists are more likely to hold stocks than otherwise identical investors. First, we consider the change in stockholdings associated with (i) completing an economics education and (ii) an economist moving into the household. Second, we model stock market participation using a probit model with unobserved individual heterogeneity. Third, instrumental variables estimation allows us to identify the causal effect of an economics education on stock market participation. Throughout, we focus explicitly on the effect of a change in educational status on the likelihood of holding stocks.

We analyze the financial integration of the new European Union (EU) member states’ stock markets using the negative (positive) coexceedance variable that counts the number of large negative (large positive) returns on a given day across the countries. A similar analysis is performed for the old EU countries. We use a multinomial logit model to investigate how persistence, asset classes, and volatility are related to the coexceedance variables. We find that the effects differ (a) between negative and positive coexceedance variables (b) between old and new EU member states, and (c) before and after the EU enlargement in 2004, suggesting a closer connection of new EU stock markets to those in Western Europe.

We explain the currency carry trade (CT) performance using an asset pricing model in which factor loadings are regime dependent rather than constant. Empirical results show that a typical CT strategy has much higher exposure to the stock market and is mean reverting in regimes of high foreign exchange volatility. The findings are robust to various extensions. Our regime-dependent pricing model provides significantly smaller pricing errors than a traditional model. Thus, the CT performance is better explained by a time-varying systematic risk that increases in volatile markets, suggesting a partial resolution of the uncovered interest parity puzzle.

In this study, we use an extension of the heterogeneous autoregressive model to investigate the influence of time-varying risk aversion and macroeconomic, financial, and economic policy uncertainty measures on stock market volatility and correlation. Based on the findings, there is a stronger predictive ability of these variables at the monthly frequency than at the daily frequency. We also highlight the importance of risk aversion, which, alongside fundamental factors, reflects investor sentiment in predicting stock market volatility. Meanwhile, although uncertainty variables, such as economic uncertainty and financial uncertainty, are important, the widely used variable, economic policy uncertainty, is not helpful for predicting stock market volatility. Moreover, there is evidence of higher economic value and reduced portfolio risk when including risk aversion and economic uncertainty in international portfolio analysis.

We study the role of sentiment variables as predictors for US recessions. We combine sentiment variables with either classical recession predictors or common factors based on a large panel of macroeconomic and financial variables. Sentiment variables hold vast predictive power for US recessions in excess of both the classical recession predictors and the common factors. The strong importance of the sentiment variables is documented both in-sample and out-of-sample.