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A new energy model to capture the behavior of energy price processes

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  • Xu, Weijun
  • Sun, Qi
  • Xiao, Weilin
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    Abstract

    Owing to the vague fluctuation of energy prices from time to time, a new energy model, which considers both the mean-reverting behavior and the long memory property, is proposed in this paper. Since the problem of estimating parameters, in discrete time for this model, plays a central role in forecast inference, the problem of estimating the unknown parameters has been dealt with for the fractional Ornstein–Uhlenbeck process observed discretely. The asymptotic properties of these estimates are also provided. The numerical simulation results confirm the theoretical analysis and show that our method is effective. To show how to apply our approach in realistic contexts, an empirical study of energy in China, namely Daqing crude oil, is presented. The empirical results seem reasonable when compared to the real data.

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    Bibliographic Info

    Article provided by Elsevier in its journal Economic Modelling.

    Volume (Year): 29 (2012)
    Issue (Month): 5 ()
    Pages: 1585-1591

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    Handle: RePEc:eee:ecmode:v:29:y:2012:i:5:p:1585-1591

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    Web page: http://www.elsevier.com/locate/inca/30411

    Related research

    Keywords: Energy model; Maximum likelihood estimation; Malliavin calculus; Fractional Ornstein–Uhlenbeck processes; Monte Carlo simulation;

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    References

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    Cited by:
    1. Zhang, Pu & Xiao, Wei-lin & Zhang, Xi-li & Niu, Pan-qiang, 2014. "Parameter identification for fractional Ornstein–Uhlenbeck processes based on discrete observation," Economic Modelling, Elsevier, vol. 36(C), pages 198-203.

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