We investigate the evolution of co-movement and lead-lag relationships between the nominal effective European exchange rate and the largest European stock markets in the time and frequency dimension. We decompose the financial return series into different time scales and apply the cross-wavelet...

In this paper we provide a unified methodology for conducting likelihood-based inference on the unknown parameters of a general class of discrete-time stochastic volatility (SV) models, characterized by both a leverage effect and jumps in returns. Given the nonlinear/non-Gaussian state-space...

We show that a model where investors learn about the persistence of oil-price movements accounts well for the fluctuations in oil-price futures since the late 1990s. Using a DSGE model, we then show that this learning process alters the impact of oil shocks, making it time-dependent and...

In this study we investigate and identify the patterns of co-movement of interest rate, stock price and exchange rate in India in the period between July 1997 and December 2010 using the cross-wavelet power, the cross-wavelet coherency, and the phase difference methodologies. Our empirical...

We show that a model where investors learn about the persistence of oil-price movements accounts well for the fluctuations in oil-price futures since the late 1990s. Using a DSGE model, we then show that this learning process alters the impact of oil shocks, making it time-dependent and...

This paper investigates the nonlinearity in the effects of news shocks about technological innovations. In a maximally flexible logistic smooth transition vector autoregressive model, state-dependent effects of news shocks are identified based on medium-run restrictions. We propose a novel...

Ljungqvist and Sargent (2017) (LS) show that unemployment fluctuations can be understood in terms of a quantity they call the "fundamental surplus." However, their analysis ignores risk premia, a force that Hall (2017) shows is important in understanding unemployment fluctuations. We show how...