Original paper
Naı̈ve, ARIMA, nonparametric, transfer function and VAR models: A comparison of forecasting performance
Abstract
We examine the forecasting performance of a number of parametric and nonparametric models based on a training–validation sample approach and the use of rolling short-term forecasts to compute root mean-squared errors. We find that the performance of these models is better than that of the naı̈ve, no-change model. The use of bivariate models (like VAR and transfer functions) provides additional root mean-squared error reductions. In many cases...
Paper Details
Title
Naı̈ve, ARIMA, nonparametric, transfer function and VAR models: A comparison of forecasting performance
Published Date
Jan 1, 2004
Volume
20
Issue
1
Pages
53 - 67
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