A hybrid approach for forecasting of oil prices volatility

Akbar Komijani; Esmaeil Naderi; Nadiya Gandali Alikhani

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A hybrid approach for forecasting of oil prices volatility

机译：预测油价波动的混合方法

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This study aims to introduce an ideal model for forecasting crude oil price volatility. For this purpose, the 'predictability' hypothesis was tested using the variance ratio test, BDS test and the chaos analysis. Structural analyses were also carried out to identify possible non-linear patterns in this series. On this basis, Lyapunov exponents confirmed that the return series of crude oil price is chaotic. Moreover, according to the findings, the rate of return series has the long memory property rejecting the efficient market hypothesis and affirming the fractal markets hypothesis. The results of the Geweke and Porter-Hudak test verified that both the rate of return and volatility series of crude oil price have the long memory property. Besides, according to both mean square error (MSE) and root mean square error (RMSE) criteria, wavelet-decomposed data improve the performance of the model significantly. Therefore, a hybrid model was introduced based on the long memory property which uses wavelet decomposed data as the most relevant model.

机译：这项研究旨在为预测原油价格波动提供一个理想的模型。为此，使用方差比检验，BDS检验和混沌分析对“可预测性”假设进行了检验。还进行了结构分析，以确定该系列中可能的非线性模式。在此基础上，李雅普诺夫指数证实了原油价格的回报序列是混乱的。而且，根据研究结果，收益率序列具有拒绝有效市场假说并确认分形市场假说的长期记忆特性。 Geweke和Porter-Hudak检验的结果证明，原油价格的收益率和波动率系列都具有长期记忆性。此外，根据均方误差（MSE）和均方根误差（RMSE）准则，小波分解数据可显着提高模型的性能。因此，引入了基于长存储特性的混合模型，该模型使用小波分解数据作为最相关的模型。

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来源
《OPEC energy review》 |2014年第3期|323-340|共18页
作者
Akbar Komijani; Esmaeil Naderi; Nadiya Gandali Alikhani;
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作者单位

Faculty of Economic, University of Tehran, Tehran, Iran;

Faculty of Economic, University of Tehran, Tehran 4651835857, Iran;

Science and Research Branch, Islamic Azad University, Khouzestan, Iran;

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机译：一种预测油价波动的混合方法

A hybrid approach for forecasting of oil prices volatility

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