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produce large reductions in the out-of-sample prediction mean squared error and provides a useful alternative to forecasting …
Persistent link: https://www.econbiz.de/10005342193
produce large reductions in the out-of-sample prediction mean squared error and provides a useful alternative to forecasting …
Persistent link: https://www.econbiz.de/10005124019
We address some of the key questions that arise in forecasting the price of crude oil. What do applied forecasters need … in forecasting the price of oil? How useful are survey forecasts? How does one evaluate the sensitivity of a baseline oil …
Persistent link: https://www.econbiz.de/10009643504
and easy-to-use forecasting methods such as the no-change forecast. This does not mean that there is no useful information …
Persistent link: https://www.econbiz.de/10005792183
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...
Persistent link: https://www.econbiz.de/10005124232
It is standard in applied work to select forecasting models by ranking candidate models by their prediction mean square …
Persistent link: https://www.econbiz.de/10011604260
It is standard in applied work to select forecasting models by ranking candidate models by their prediction mean square …
Persistent link: https://www.econbiz.de/10009639853
It is standard in applied work to select forecasting models by ranking candidate models by their PMSE in simulated out …
Persistent link: https://www.econbiz.de/10013320039
Long-horizon regression tests are widely used in empirical finance, despite evidence of severe size distortions. This paper introduces a new bootstrap method for small-sample inference in long-horizon regressions. A Monte Carlo study shows that this bootstrap test has much smaller size...
Persistent link: https://www.econbiz.de/10014072162
It is standard in applied work to select forecasting models by ranking candidate models by their prediction mean …
Persistent link: https://www.econbiz.de/10005504404