Abstract
This paper regards the dynamics of gas spot prices on one of European energy exchanges—EEX. A detailed description of the price dynamics is provided alongside with several multi-factor models for daily gas prices. An original approach to the development of such multi-factor daily price models is proposed. Specifically, daily price models taking into account non-integer power of time variable tend perform relatively well on the horizon of several weeks despite the heteroskedasticity of the daily prices.
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Asche, F., Misund, B., Sikveland, M.: The relationship between spot and contract gas prices in Europe. Energy Econ. 38, 212–217 (2013)
Emery, G.W., Liu, Q.W.: An analysis of the relationship between electricity and natural gas futures prices. J. Futur. Mark. 22(2), 95–122 (2002)
Gujarati, D.N.: Basic Econometrics. Tata McGraw-Hill Education, New York, NY (2009)
Hamilton, J.D.: Oil and the macroeconomy since World War II. J. Polit. Econ. 91(2), 228–248 (1983)
Hamilton, J.D.: Understanding Crude Oil Prices (No. w14492). National Bureau of Economic Research, Cambridge (2008)
Irvin J.O.: On a criterion for the rejection of outlying observation. Biometrika 17, 238–250 (1925)
Kimenta, J.: Elements of Econometrics. University of Michigan Press, Ann Arbor (1986)
Mohammadi, H., Su, L.: International evidence on crude oil price dynamics: applications of ARIMA-GARCH models. Energy Econ. 32(5), 1001–1008 (2010)
Morana, C.: A semiparametric approach to short-term oil price forecasting. Energy Econ. 23(3), 325–338 (2001)
Narayan, P.K., Gupta, R.: Has oil price predicted stock returns for over a century? Energy Econ. 48, 18–23 (2015)
Narayan, P.K., Liu, R.: A unit root model for trending time-series energy variables. Energy Econ. 50, 391–402 (2015)
Schmidt, T.: Modelling energy markets with extreme spikes. In: Mathematical Control Theory and Finance, pp. 359–375. Springer, Berlin (2008)
Villar, J.A., Joutz, F.L.: The relationship between crude oil and natural gas prices. Energy Information Administration, Office of Oil and Gas, 1–43 (2006)
Xie, W., Yu, L., Xu, S., Wang, S.: A new method for crude oil price forecasting based on support vector machines. In: International Conference on Computational Science, pp. 444–451. Springer, Berlin (2006)
Yu, L., Wang, S., Lai, K.K.: Forecasting crude oil price with an EMD-based neural network ensemble learning paradigm. Energy Econ. 30(5), 2623–2635 (2008)
Acknowledgements
The research was partially carried out while this author Ivan P. Yamshchikov was in UAS Zittau, Germany. This research is supported by the European Union in the FP7-PEOPLE-2012-ITN Program under Grant Agreement Number 304617 (FP7 Marie Curie Action, Project Multi-ITN STRIKE—Novel Methods in Computational Finance). Short reference for contract: PITN-GA-2012-304617 STRIKE.
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Khrushch, Y., Rudolf, S., Detkova, A., Yamshchikov, I.P. (2019). European Gas Prices Dynamics: EEX Ad-Hoc Study. In: Faragó, I., Izsák, F., Simon, P. (eds) Progress in Industrial Mathematics at ECMI 2018. Mathematics in Industry(), vol 30. Springer, Cham. https://doi.org/10.1007/978-3-030-27550-1_16
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DOI: https://doi.org/10.1007/978-3-030-27550-1_16
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