This paper addresses the open debate about the effectiveness and practical relevance of highfrequency (HF) data in portfolio allocation. Our results demonstrate that when used with proper econometric models, HF data offers gains over daily data and more importantly these gains are maintained...

This paper addresses the open debate about the usefulness of high-frequency (HF) data in large-scale portfolio allocation. Daily covariances are estimated based on HF data of the S&P 500 universe employing a blocked realized kernel estimator. We propose forecasting covariance matrices using a...

This article evaluates the predictability of the equity risk premium in the United States by comparing the individual and complementary predictive power of macroeconomic variables which are popular in academia and technical indicators which are widely used by practitioners in the market using a...

This article attempts to examine whether the equity premium in the United States can be predicted from a com-prehensive set of 18 economic and financial predictors over a monthly out-of-sample period of 2000:2 to 2011:12, using an in-sample period of 1990:2-2000:1. To do so, we consider, in...

This article attempts to examine whether the equity premium in the United States can be predicted from a comprehensive set of 18 economic and financial predictors over a monthly out-of-sample period of 2000:2 to 2011:12, using an in-sample period of 1990:2-2000:1. To do so, we consider, in...

In this paper we analyse the information content of correlations between daily changes in CDS spreads. Using factor analysis, we can break down the variance of CDS spreads into global, regional and country-specific components. Our results confirm the finding of other studies, namely that there...

We examine possible accuracy gains from using factor models, quantile regression and forecast averaging for computing interval forecasts of electricity spot prices. We extend the Quantile Regression Averaging (QRA) approach of Nowotarski and Weron (2014) and use principal component analysis to...

We show that incorporating the intra-day relationships of electricity prices improves the accuracy of forecasts of daily electricity spot prices. We use half-hourly data from the UK power market to model the spot prices directly (via ARX and Vector ARX models) and indirectly (via factor models)....

We show that incorporating the intra-day and inter-zone relationships of electricity prices in the Pennsylvania--New Jersey--Maryland (PJM) Interconnection improves the accuracy of short- and medium-term forecasts of average daily prices for a major PJM market hub -- the Dominion Hub in...