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.
