基于Boosting-ARMA的碳价预测 |
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引用本文: | 王娜. 基于Boosting-ARMA的碳价预测[J]. 统计与信息论坛, 2017, 0(3): 28-34. DOI: 10.3969/j.issn.1007-3116.2017.03.004 |
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作者姓名: | 王娜 |
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作者单位: | 厦门大学 经济学院,福建 厦门,361005 |
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摘 要: | 自回归滑动平均(ARMA)模型是最流行的预测模型之一,而模型选择却是使用ARMA进行预测的难点,尤其是当真实模型的阶数较高时,因此提出Boosting-ARMA预测算法,利用Boosting算法进行最优子集ARMA寻找,自动且高效地完成ARMA模型的识别。模拟实验显示,Boosting-ARMA优于其他方法,用新算法预测碳价实证分析发现,Boosting-ARMA算法可以获得较高的碳价预测准确性并且方便快捷。
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关 键 词: | 子集ARMA选择 Boosting 碳价预测 |
Forecasting of Carbon Price Based on Boosting-ARMA Model |
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Abstract: | Autoregressive moving average (ARMA) model is one of the most popular models in forecasting, but model selection is a difficult point of ARMA modeling, especially when the orders of true model are high.Hence, this paper proposes Boosting-ARMA forecasting algorithm, this algorithm identifies the optimal subset ARMA model via Boosting, finish the identification automatically and efficiently.Simulation results show that Boosting-ARMA is better than other methods.At last, we forecast the carbon price with new algorithm;the empirical results find that Boosting-ARMA can get high forecasting accuracy for carbon price conveniently and efficiently. |
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Keywords: | subset ARMA selection Boosting carbon price forecasting |
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