We propose a new approach to model high and low frequency components of equity correlations. Our framework combines a factor asset pricing structure with other specifications capturing dynamic properties of volatilities and covariances between a single common factor and idiosyncratic returns....

Bayesian inference in a time series model provides exact, out-of-sample predictive distributions that fully and coherently incorporate parameter uncertainty. This study compares and evaluates Bayesian predictive distributions from alternative models, using as an illustration five alternative...

We use a Panel Smooth Transition Regression (STR) model to study nonlinearities in the expectationformation process in the US stock market. To this end, we use data from the Livingston survey to investigate how the importance of regressive and extrapolative expectations fluctuates over time as...

Density forecasts have become quite important in economics and finance. For example, such forecasts play a central role in modern financial risk management techniques like Value at Risk. This paper suggests a regression based density forecast evaluation framework as a simple alternative to other...

Density forecasts have become quite important in economics and finance. For example, such forecasts play a central role in modern financial risk management techniques like Value at Risk. This paper suggests a regression based density forecast evaluation framework as a simple alternative to other...

This paper investigates whether the HML, the SMB along with the short-term reversal, the long-term reversal and the momentum factors exhibit both in-sample and out-of-sample forecasting ability for the US stock returns. Our findings suggest that these factors contain significantly more...

We propose a comprehensive empirical examination of the time-varying leading properties of two high yield spreads in the United States and compare them with the leading properties of the term spread between the mid-1980s and the end of 2011. We show that high yield spreads are not reliable...

When do financial markets help in predicting economic activity? With incomplete markets, the link between financial and real economy is state-dependent and financial indicators may turn out to be useful particularly in forecasting "tail" macroeconomic events. We examine this conjecture by...

Dynamic Time Warping (DTW) is a widely used algorithm in speech recognition for measuring similarity between two time series. This non-parametric technique overcomes the problems associated with Pearson's correlation coefficient by allowing a non-linear mapping of one sequence to another...