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《Journal of Dalian Maritime University》 2006-02
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Forecasting the Baltic dry index using neural networks

LIU Jian-lin~(1,2),XU Guo-ping~2(1.Mathematics & Information Sciences College,Jiangxi Normal Univ.,Nanchang 330027,China;2.Transportation Dept.,Shanghai Maritime Univ.,Shanghai 200135,China)  
This paper investigated the potential of neural networks for medium-term monthly dry bulk freight rates.A comparative study of predictive performance among neural networks,multivariate regression models and ARCH time series models were conducted.Our conclusions show that neural networks can significantly outperform multivariate regression models and ARCH time series models in forecasting performance.
【Fund】: 上海市高校科技发展基金资助项目(021K02)
【CateGory Index】: F224
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