This paper intends to harmonize two different approaches to the analysis of the business cycle and in doing so it retrieves the stylized facts of the business cycle in Europe. We start with the ‘classical’ approach proposed in Burns and Mitchell (1946) of dating and analyzing the business cycle; we then adopt the ‘modern’ alternative: the Markov-switching time series model proposed in Hamilton ...

Article history: Received 11 October 2012 Received in revised form 3 November 2014 Accepted 3 November 2014 Available online 11 November 2014 In this paper, we investigate the dynamic response of stock market volatility to changes in monetary policy. Using a vector autoregressive model, our findings reveal a significant response of stock returns and volatility to monetary policy shocks. While t...

We investigate non-linearities in the stock return trading volume relationship by using daily data for 16 European countries in an asymmetric vector autoregressive model. In this framework, we test for asymmetries and analyze the dynamic relationship using a simulation based procedure for computing asymmetric impulse response functions. We find that stock returns have a significant influence on...

We model the conditional mean and volatility of stock returns as a latent vector autoregressive (VAR) process to study the contemporaneous and intertemporal relationship between expected returns and risk in a flexible statistical framework and without relying on exogenous predictors. We find a strong and robust negative correlation between the innovations to the conditional moments that leads t...

This paper asks how well a general equilibrium agency cost model describes the dynamic relationship between credit variables and the business cycle. A Bayesian VAR is used to obtain probability intervals for empirical correlations. The agency cost model is found to predict the leading, countercyclical correlation of spreads with output when shocks arising from the credit market contribute to ou...

Within the approaches that have been applied to assess the impact of public capital on economic growth, this paper estimates the dynamic effects of public infrastructures using a structural vector autoregressive (SVAR) methodology for the Spanish regions. From a methodological point of view, our work contains different innovative features with respect to the previous studies using VAR models. T...

Article history: Received 20 June 2014 Received in revised form 25 September 2014 Accepted 26 September 2014 Available online 5 October 2014 This paper investigates the time-varying impact of oil price uncertainty on stock prices in China using weekly data on ten sectoral indices over the period January 1997–February 2014. The estimation of a bivariate VAR-GARCH-in-mean model suggests that oil ...

Article history: Received 17 September 2014 Received in revised form 23 March 2015 Accepted 24 March 2015 Available online 31 March 2015 This paper investigates the dynamic effects of common macroeconomic shocks in shaping business cycle fluctuations in a group of Euro-area countries. In particular, by using the structural (near) VAR methodology, we investigate the effect of area-wide shocks, w...

The identification of a VAR requires differentiating between correlation and causation. This paper presents a method to deal with this problem. Graphical models, which provide a rigorous language to analyze the statistical and logical properties of causal relations, associate a particular set of vanishing partial correlations to every possible causal structure. The structural form is described ...

This paper focuses on portfolio risk forecasting in an asymmetrical framework. Risk is defined by two factors; the dependence structure and the volatility. In order to account for asymmetric dependencies, the return series’ interdependence is estimated via a Copula approach rather than the correlation matrix. This allows to capture tightening dependence during market turmoils and loose dependen...