文章基本信息

标题：Forecasting daily exchange rates: A comparison between SSA and MSSA
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作者：Rahim Mahmoudvand ; Paulo Canas Rodrigues ; Masoud Yarmohammadi. 等
期刊名称：RevStat : Statistical Journal
印刷版ISSN：1645-6726
出版年度：2019
卷号：17
期号：4
页码：599-616
出版社：Instituto Nacional de Estatística
摘要：In this paper, daily exchange rates in four of the BRICS emerging economies: Brazil, India, China and South Africa, over the period 2001 to 2015 are considered. In order to predict the future of exchange rate in these countries, it is possible to use both univariate and multivariate time series techniques. Among different time series analysis methods, we choose singular spectrum analysis (SSA), as it is a relatively powerful non-parametric technique and requires the fewest assumptions to be hold in practice. Both multivariate and univariate versions of SSA are considered to predict the daily currency exchange rates. The results show the superiority of MSSA, when compared with univariate SSA, in terms of mean squared error.
关键词：multivariate singular spectrum analysis; univariate singular spectrum analysis; forecasting; exchange rates