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Prequential forecasting in the presence of structure breaks in natural gas spot markets

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Abstract

The natural gas sector has undergone major regulatory and technological changes. These changes may induce structural changes in price relationships among natural gas markets. Tests for structural breaks suggest two potential structural breaks, around 2000 and 2009. Previous forecasting studies on natural gas prices/returns largely are point forecasts and focus on a single spot market; unlike those, this study undertakes simultaneous probabilistic forecasts of eight spot markets. Prequential forecasting analysis examines: (1) whether differences exist in the ability to probabilistically forecast returns among various natural gas markets and (2) how the presence of structural breaks in the natural gas sector influences the probability forecasts. The ability to forecast natural gas markets differs based on the different criteria. Disparities may be explained by each market’s role in price discovery, the alteration of the market’s participation, and whether the market is located in an excess supply or demand region. Irrespective of the models, Henry Hub and AECO returns appear to be easier to forecast, as they generally have the smaller root-mean-squared error, Brier score, and ranked probability score, while Dominion South and Chicago returns appear to be more difficult to forecast. Models using longer periods of data appear to forecast returns better than models using data starting after the breaks; the latter always produces the largest root-mean-squared error, Brier score, and ranked probability score.

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Notes

  1. Many different techniques are available for forecasting. In the empirical literature, there is no consensus which methods provide better forecasts. The goal here is not to compare different techniques but rather examine how structural breaks may affect probabilistic forecasting ability of multiple markets. As such, the VAR methodology is used because of its ability to model multiple markets and provide probabilistic forecasts.

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Authors and Affiliations

  1. Faculty of Economics, Chiang Mai University, Chiang Mai, 50200, Thailand

    Kannika Duangnate

  2. Department of Agricultural Economics, Texas A&M University, College Station, TX, USA

    James W. Mjelde

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  1. Kannika Duangnate
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  2. James W. Mjelde
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Correspondence to Kannika Duangnate.

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Duangnate, K., Mjelde, J.W. Prequential forecasting in the presence of structure breaks in natural gas spot markets. Empir Econ 59, 2363–2384 (2020). https://doi.org/10.1007/s00181-019-01706-4

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