The statistical analysis of financial time series is a rich and diversified research field whose inherent complexity requires an interdisciplinary approach, gathering together several disciplines, such as statistics, economics, and computational sciences. This special issue of the Journal of...

In this paper bilateral models formalizing monthly growth of US imports and exports are employed to investigate the potential of nonlinear relationships linking exchange rate uncertainty and trade growth. Parametric linear and nonlinear as well as semiparametric time series models are evaluated...

Most multivariate variance or volatility models suffer from a common problem, the “curse of dimensionality”. For this reason, most are fitted under strong parametric restrictions that reduce the interpretation and flexibility of the models. Recently, the literature has focused on...

The energy sector is one of the most important in the world, so that time series fluctuations in leading energy sources have been analysed widely. As the leading energy commodities are traded on international stock exchanges, the analysis of the fluctuations in stock and financial derivatives...

Several market and macro-level variables influence the evolution of equity risk in addition to the well-known volatility persistence. However, the impact of those covariates might change depending on the risk level, being different between low and high volatility states. By combining equity risk...

The simultaneous occurrence of jumps in several stocks can be associated with major financial news, triggers short-term predictability in stock returns, is correlated with sudden spikes of the variance risk premium, and determines a persistent increase (decrease) of stock variances and...