Forecasting economic and financial time series with non-linear models

Clements, M. P. ORCID: https://orcid.org/0000-0001-6329-1341, Franses, P. H. and Swanson, N. R. (2004) Forecasting economic and financial time series with non-linear models. International Journal of Forecasting, 20 (2). pp. 169-183. ISSN 0169-2070 doi: 10.1016/j.ijforecast.2003.10.004

Abstract/Summary

In this paper we discuss the current state-of-the-art in estimating, evaluating, and selecting among non-linear forecasting models for economic and financial time series. We review theoretical and empirical issues, including predictive density, interval and point evaluation and model selection, loss functions, data-mining, and aggregation. In addition, we argue that although the evidence in favor of constructing forecasts using non-linear models is rather sparse, there is reason to be optimistic. However, much remains to be done. Finally, we outline a variety of topics for future research, and discuss a number of areas which have received considerable attention in the recent literature, but where many questions remain.