Evaluating volatility and interval forecasts

Article Abstract:

A study was conducted to show that the associated test for bias in evaluating volatility forecasts is inappropriate. In line with this, the evaluation of interval forecasts was considered. Exchange rate data were utilized to characterize seven quantile estimators. An alternative procedure based on the test for bias in a conditional mean forecast was then presented. Results indicated that the alternative procedure provides novel information on the quality of quantile estimators.

Estimation theory

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Judgement in learning-curve forecasting: a laboratory study

Article Abstract:

A study was conducted to determine whether judgment can be of value to users of industrial learning curves, either alone or in combination with statistical models. Overall, findings showed that human judgment was better than the curve forecasts. In spite of their deficiency in field experience with the use of learning curves, 52 of the 79 subjects outperformed the curve on the set of 120 forecasts, based on mean absolute percentage error.

Learning curves, Experience curves

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A Fractionally Integrated Exponential Model for UK unemployment

Article Abstract:

Forecasting techniques and data regarding unemployment in the United Kingdom are given. Using fractionally integrated models with the disturbances following a Bloomfield exponential spectral model are proposed in this article for analyzing UK unemployment.

United Kingdom, Unemployment, Research

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