Evolutionary support vector machine for RMB exchange rate forecasting

doi:10.1016/j.physa.2019.01.026

CSpace

	Evolutionary support vector machine for RMB exchange rate forecasting
	Fu, Sibao 1; Li, Yongwu 2; Sun, Shaolong 3,4,5; Li, Hongtao 6
	2019-05-01
发表期刊	PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
ISSN	0378-4371
卷号	521 页码:692-704
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.
关键词	Exchange rate forecasting Evolutionary support vector regression Particle swarm optimization Genetic algorithm Phase space reconstruction
DOI	10.1016/j.physa.2019.01.026
语种	英语
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
WOS类目	Physics, Multidisciplinary
WOS记录号	WOS:000464090700059
出版者	ELSEVIER SCIENCE BV
引用统计
文献类型	期刊论文
条目标识符	http://ir.amss.ac.cn/handle/2S8OKBNM/34526
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.Beijing Univ Posts & Telecommun, Sch Econ & Management, Beijing 100876, Peoples R China 2.Beijing Univ Technol, Coll Econ & Management, Res Base Beijing Modern Mfg Dev, Beijing 100124, Peoples R China 3.Chinese Acad Sci, Acad Math & Syst Sci, Beijing 100190, Peoples R China 4.Univ Chinese Acad Sci, Sch Econ & Management, Beijing 100190, Peoples R China 5.City Univ Hong Kong, Sch Data Sci, Kowloon, Tat Chee Ave, Hong Kong, Peoples R China 6.Lanzhou Jiaotong Univ, Sch Traff & Transportat, Lanzhou 730070, Gansu, 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.