This paper explores the profitability of portfolio-based momentum strategies. The data consists of all NYSE, AMEX, and NASDAQ stocks on the CRSP database. The analysis considers the period July 1963 to December 2002 and the tests are performed on portfolios formed on industry, size and...

In this paper, we add new evidence to a long-debated macroeconomic question, namely whether money growth has predictive power for inflation or, put differently, whether money growth Granger causes inflation. We use a historical dataset - consisting of annual Swedish data on money growth and...

We assess the bivariate relation between money growth and inflation in the euro area and the United States using hybrid time-varying parameter Bayesian VAR models. Model selection based on marginal likelihoods suggests that the relation is statistically unstable across time in both regions. The...

This paper examines the effect of FDI on job creation in the Chinese manufacturing sector. As one of the world's largest recipients of FDI, China has arguably benefited from foreign multinational enterprises in various respects. However, one of the main challenges for China, and other developing...

We consider forecast combination and, indirectly, model selection for VAR models when there is uncertainty about which variables to include in the model in addition to the forecast variables. The key difference from traditional Bayesian variable selection is that we also allow for uncertainty...

In this paper, we assess whether key relations between US interest rates have been stable over time. This is done by estimating trivariate hybrid time-varying parameter Bayesian VAR models with stochastic volatility for the three-month Treasury bill rate, the slope of the Treasury yield curve...

The increasing availability of data and potential predictor variables poses new challenges to forecasters. The task of formulating a single forecasting model that can extract all the relevant information is becoming increasingly difficult in the face of this abundance of data. The two leading...

Large scale Bayesian model averaging and variable selection exercises present, despite the great increase in desktop computing power, considerable computational challenges. Due to the large scale it is impossible to evaluate all possible models and estimates of posterior probabilities are...

We consider forecast combination and, indirectly, model selection for VAR models when there is uncertainty about which variables to include in the model in addition to the forecast variables. The key di erence from traditional Bayesian variable selection is that we also allow for uncertainty...

The multivariate reduced rank regression model plays an important role in econo- metrics. Examples include co-integration analysis and models with a factor struc- ture. Geweke (1996) provided the foundations for a Bayesian analysis of this model. Unfortunately several of the full conditional...