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Forecasting model of Shanghai and CRB commodity indexes

机译:上海和CRB商品指数的预测模型

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This paper examines the long-run relationship between the Shanghai index and CRB commodity index. We run our vector error correction model (VECM) for two sub-samples as pre-crisis period and post-crisis period. In pre-crisis period, there is strong bidirectional causality link between the Shanghai and CRB. In post-crisis period, there is no causality between the indices. In the second part of the article, we employ Fuzzy System Modeling (FSM) to increase the performances of root mean-square error, R~2 and Adjusted R~2. We show the results of our analysis for both Shanghai and CRB indexes. We have demonstrated the results for a good number of our investigations ANFIS, GENFIS, Classical LSE and three versions of support vector regression. For both Shanghai and CRB indexes, our FSMIFF with LSE obtains better results than all other models we have investigated and thus are more suitable for forecasting stable and unstable stock market behavior.
机译:本文研究了上海指数和CRB商品指数之间的长期关系。我们针对两个子样本(危机前期和危机后期)运行矢量错误校正模型(VECM)。在危机前时期,上海与CRB之间存在强烈的双向因果关系。在危机后时期,指标之间没有因果关系。在本文的第二部分,我们使用模糊系统建模(FSM)来提高均方根误差R〜2和调整后的R〜2的性能。我们展示了我们对上海和CRB指数的分析结果。我们已经对许多研究ANFIS,GENFIS,Classical LSE和支持向量回归的三种版本证明了结果。对于上海指数和CRB指数,带有LSE的FSMIFF均比我们研究的所有其他模型获得更好的结果,因此更适合于预测稳定和不稳定的股市行为。

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