We propose new methods for comparing the out-of-sample forecasting performance of two competing models in the presence of possible instabilities. The main idea is to develop a measure of the relative local forecasting performance for the two models, and to investigate its stability over time by...

SUMMARY We develop a structural model of the global market for crude oil that for the first time explicitly allows for shocks to the speculative demand for oil as well as shocks to flow demand and flow supply. The speculative component of the real price of oil is identified with the help of data...

Despite their widespread use as predictors of the spot price of oil, oil futures prices tend to be less accurate in the mean-squared prediction error sense than no-change forecasts. This result is driven by the variability of the futures price about the spot price, as captured by the oil futures...

The use of a new bootstrap method for small-sample inference in long-horizon regressions is illustrated by analysing the long-horizon predictability of four major exchange rates, and the findings are reconciled with those of an earlier study by Mark (1995). While there is some evidence of...

We propose a measure of predictability based on the ratio of the expected loss of a short-run forecast to the expected loss of a long-run forecast. This predictability measure can be tailored to the forecast horizons of interest, and it allows for general loss functions, univariate or...

We propose a Bayesian framework in which the uncertainty about the half-life of deviations from purchasing power parity can be quantified. Based on the responses to a survey study, we propose a prior probability distribution for the half-life under the recent float intended to capture widely...