Forecast-error-based estimation of forecast uncertainty when the horizon is increased
نویسندگان
چکیده
منابع مشابه
Modeling Time-Varying Uncertainty of Multiple-Horizon Forecast Errors
We develop uncertainty measures for point forecasts from surveys such as the Survey of Professional Forecasters, Blue Chip, or the Federal Open Market Committee’s Summary of Economic Projections. At a given point of time, these surveys provide forecasts for macroeconomic variables at multiple horizons. To track time-varying uncertainty in the associated forecast errors, we derive a multiple-hor...
متن کاملExploitation of particle filter for forecast error covariance structure estimation
The paper presents a scheme for estimation of spatio–temporal evolution of a quantity with unknown model error. Model error is estimated on basis of measured–minus– observed residuals evaluated upon measured and modeled values. Methods of Bayesian filtering are applied to the problem. The main contribution of this paper is application of general marginalized particle filter algorithm to the lin...
متن کاملComment on 'forecast Rationality Tests Based on Multi-horizon Bounds'
I enjoyed reading yet another paper by Patton and Timmermann (PT hereinafter) and feel that it has broken new ground in testing the rationality of a sequence of multi-horizon fixed target forecasts. Rationality tests are not new in the forecasting literature, but the idea of testing the monotonicity properties of second moment bounds across several horizons is novel and can suggest possible sou...
متن کاملForecast Rationality Tests Based on Multi-Horizon Bounds
Forecast rationality under squared error loss implies various bounds on second moments of the data across forecast horizons. For example, the mean squared forecast error should be increasing in the horizon, and the mean squared forecast should be decreasing in the horizon. We propose rationality tests based on these restrictions, including new ones that can be conducted without data on the targ...
متن کاملA General Forecast-error Taxonomy
We consider the sources of forecast errors and their consequences in an evolving economy subject to structural breaks,forecasting from mis-specified, data-based models. A model-free taxonomy of forecast errors highlights that deterministic shifts are a major cause of systematic forecast failure. Other sources seem to pose fewer problems. The taxonomy embeds several previous model-based taxonomi...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: International Journal of Forecasting
سال: 2018
ISSN: 0169-2070
DOI: 10.1016/j.ijforecast.2017.08.006