A new energy model to capture the behavior of energy price processes |
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Authors: | Weijun Xu Qi Sun Weilin Xiao |
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Institution: | 1. School of Business Administration, South China University of Technology, Guangzhou 510641, China;2. School of Business Administration, Zhejiang Gongshang University, Hangzhou 310018, China;3. School of Management, Zhejiang University, Hangzhou 310058, China |
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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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Keywords: | Energy model Maximum likelihood estimation Malliavin calculus Fractional Ornstein–Uhlenbeck processes Monte Carlo simulation |
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