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Evolutionary support vector machine for RMB exchange rate forecasting

文献类型：期刊论文

作者Fu, Sibao6; Li, Yongwu5; Sun, Shaolong2,3,4; Li, Hongtao1
刊名PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
出版日期2019-05-01
卷号521页码:692-704
关键词Exchange rate forecasting Evolutionary support vector regression Particle swarm optimization Genetic algorithm Phase space reconstruction
ISSN号0378-4371
DOI10.1016/j.physa.2019.01.026
英文摘要The volatility of exchange rate is very important to a country's trading. Accurately forecasting exchange rate time series appears to be a challenging task for the scientific community on account of its nonstationary and nonlinear structural nature. In order to improve the performance of exchange rate forecasting, this study develops two evolutionary support vector regression models to forecast four typical RMB exchange rates (CNY against USD, EUR, JPY and GBP), and employs four evaluation criteria to assess the performance of outof-sample exchange rate forecasting. In this study, the evolutionary algorithm optimizes the SVR parameters by balancing search between the global and local optima. However, the inputs of models are selected though phase space reconstruction method from historical data of exchange rate series. The empirical results demonstrate that our proposed evolutionary support vector regression outperforms all other benchmark models in terms of level forecasting accuracy, directional forecasting accuracy and statistical accuracy. As it turns out, our proposed evolutionary support vector regression is a promising approach for RMB exchange rate forecasting. (C) 2019 Elsevier B.V. All rights reserved.
资助项目National Natural Science Foundation of China[71501176] ; National Natural Science Foundation of China[11361031] ; Beijing Natural Science Foundation[9192001] ; Great Wall Scholar Training Program of Beijing Municipality[CITTCD20180305] ; International Research Cooperation Seed Fund of Beijing University of Technology[2018B25] ; Humanities and Social Sciences Fund of Beijing University of Technology, Lanzhou Jiaotong University-Tianjin University Innovation Fund Project[2018064]
WOS研究方向Physics
语种英语
WOS记录号WOS:000464090700059
出版者ELSEVIER SCIENCE BV
源URL[http://ir.amss.ac.cn/handle/2S8OKBNM/34525]  
专题中国科学院数学与系统科学研究院
通讯作者Li, Yongwu
作者单位1.Lanzhou Jiaotong Univ, Sch Traff & Transportat, Lanzhou 730070, Gansu, Peoples R China
2.City Univ Hong Kong, Sch Data Sci, Kowloon, Tat Chee Ave, Hong Kong, Peoples R China
3.Univ Chinese Acad Sci, Sch Econ & Management, Beijing 100190, Peoples R China
4.Chinese Acad Sci, Acad Math & Syst Sci, Beijing 100190, Peoples R China
5.Beijing Univ Technol, Coll Econ & Management, Res Base Beijing Modern Mfg Dev, Beijing 100124, Peoples R China
6.Beijing Univ Posts & Telecommun, Sch Econ & Management, Beijing 100876, Peoples R China
推荐引用方式
GB/T 7714		 Fu, Sibao,Li, Yongwu,Sun, Shaolong,et al. Evolutionary support vector machine for RMB exchange rate forecasting[J]. PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS,2019,521:692-704.
APA Fu, Sibao,Li, Yongwu,Sun, Shaolong,&Li, Hongtao.(2019).Evolutionary support vector machine for RMB exchange rate forecasting.PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS,521,692-704.
MLA Fu, Sibao,et al."Evolutionary support vector machine for RMB exchange rate forecasting".PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS 521(2019):692-704.

入库方式： OAI收割

来源：数学与系统科学研究院

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