This paper investigates whether oil prices have a reliable and stable out-of-sample relationship with the Canadian/U.S. dollar nominal exchange rate. Despite state-of-the-art methodologies, the authors find little systematic relation between oil prices and the exchange rate at the monthly and...

This paper proposes a framework to implement regression-based tests of predictive ability in unstable environments, including, in particular, forecast unbiasedness and efficiency tests, commonly referred to as tests of forecast rationality. Our framework is general: it can be applied to...

This paper investigates whether oil price shocks have a reliable and stable out-of-sample relationship with the Canadian/U.S Dollar nominal exchange rate. Despite state-of-the-art methodologies and clean data, we find paradoxically little systematic relation between oil prices and the exchange...

This paper proposes new methodologies for evaluating out-of-sample forecasting performance that are robust to the choice of the estimation window size. The methodologies involve evaluating the predictive ability of forecasting models over a wide range of window sizes. We show that the tests...

We propose a new methodology to identify the sources of models’ forecasting performance. The methodology decomposes the models’ forecasting performance into asymptotically uncorrelated components that measure instabilities in the forecasting performance, predictive content, and over-fitting....

In this paper the oil price-macroeconomy relationship is investigated from a global perspective, by means of a large scale macro-financial-econometric model. In addition to real activity, fiscal and monetary policy responses and labor and financial markets are considered as well. We find that...

In this study real oil price dynamics have been assessed over few important episodes since the 1990s. The evidence provides support to the demand side view: in this respect, macroeconomic shocks would appear to be the major upward driver of the real oil price over the whole period investigated,...

This paper, exploiting the properties of mixed causal and noncausal models, proposes strategies to detect time reversibility in stochastic processes. These novel strategies can be implemented to verify the time reversibility of stationary stochastic processes. We show that they can also be used...

This paper proposes new methodologies for evaluating out-of-sample forecasting performance that are robust to the choice of the estimation window size. The methodologies involve evaluating the predictive ability of forecasting models over a wide range of window sizes. The authors show that the...

We propose new methods for evaluating predictive densities. The methods include Kolmogorov-Smirnov and Cramér-von Mises-type tests for the correct specification of predictive densities robust to dynamic mis-specification. The novelty is that the tests can detect mis-specification in the...