# Calculating Interval Forecasts

@article{Chatfield1993CalculatingIF, title={Calculating Interval Forecasts}, author={Chris Chatfield}, journal={Journal of Business \& Economic Statistics}, year={1993}, volume={11}, pages={121-135} }

The importance of interval forecasts is reviewed. Several general approaches to calculating such forecasts are described and compared. They include the use of theoretical formulas based on a fitted probability model (with or without a correction for parameter uncertainty), various “approximate” formulas (which should be avoided), and empirically based, simulation, and resampling procedures. The latter are useful when theoretical formulas are not available or there are doubts about some model…

## 352 Citations

Prediction Intervals for Time-Series Forecasting

- Environmental Science
- 2001

PIs tend to be too narrow because out-of-sample forecast accuracy is often poorer than would be expected from within-sample fit, particularly for PIs calculated conditional on a model fitted to past data.

Model uncertainty and forecast accuracy

- Economics
- 1996

Alternative approaches to forecasting, which avoid conditioning on a single model, include Bayesian model averaging and using a forecasting method which is not model-based but which is designed to be adaptable and robust.

Evaluating the Forecasts of Risk Models

- Economics
- 1999

An new approach to evaluating interval and density forecasts requires evaluation of the entire forecast distribution, rather than a value-at-risk quantity, which is enough to construct a powerful test even with sample sizes as small as 100.

Multiple forecasts with autoregressive time series models: case studies

- EconomicsMath. Comput. Simul.
- 2004

Prediction intervals for growth curve forecasts

- Mathematics
- 1995

Since growth curves are often used to produce medium- to long-term forecasts for planning purposes, it is obviously of value to be able to associate an interval with the forecast trend. The problems…

WK1 Model: Prediction Intervals for Your Forecasts

- Computer Science
- 2011

This paper sets forth a synergy of existing statistical theories to obtain a clear-cut model for calculating forecasts with prediction intervals, named the “WK1 model,” which increases the power of a single discrete point forecast by adding its probable accuracy with top and bottom limits.

WK1 Model: Prediction Intervals for Your Forecasts

- Computer Science
- 2011

This paper sets forth a synergy of existing statistical theories to obtain a clear-cut model for calculating forecasts with prediction intervals, named the “WK1 model,” which increases the power of a single discrete point forecast by adding its probable accuracy with top and bottom limits.

A Quantile Regression Approach to Generating Prediction Intervals

- Business
- 1999

Exponential smoothing methods do not involve a formal procedure for identifying the underlying data generating process. The issue is then whether prediction intervals should be estimated by a…

Testing Interval Forecasts: a GMM-Based Approach

- Economics
- 2013

This paper proposes a new evaluation framework for interval forecasts. Our model free test can be used to evaluate intervals forecasts and High Density Regions, potentially discontinuous and/or…

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