Abstract This paper uses three euro exchange rates – the US dollar, sterling and yen – to test for the presence of volatility spillovers and time-varying correlations using the realised variance approach, which has significant advantages over the multivariate-GARCH methodology. Our results suggest that the three currencies do exhibit some degree of volatility spillover and hence commonality in the driving force behind volatility movement. With regard to the nature of time-variation within the correlation coefficients, there is substantial evidence that correlations are time-varying but that the strength of correlation coefficients has not increased over the sample period. Furthermore, there is evidence that correlations themselves are predictable and interrelated. These results support the view that the three rates do exhibit interrelationships, commonality and time-varying correlation, factors that are important to portfolio managers. 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As trading in the foreign exchange market is continuous, i.e. the trading day is 24 h long, we follow convention and mark a day beginning and ending at 21:00 GMT. Previous studies that have used Granger causality to tests for volatility spillovers in stock markets include Chow and Lawler (2003) Chow, G. C. and Lawler, C. C. 2003. A time series analysis of the Shanghai and New York stock prices indices. Annals of Economics and Finance, 4(May): 17–35. [Google Scholar] and Ramasamy and Yeung (2005) Ramasamy, B. and Yeung, M. 2005. The causality between stock returns and exchange rates: Revisited. Australian Economic Papers, 44: 162–9. [Crossref] , [Google Scholar]. More specifically, we calculate unconditional variances as the square of each series return and the covariance as the multiple of cross series returns. This introduces time-variation into the calculation of the unconditional variances and covariances. Moreover, we could compare the realised approach with a GARCH approach, however, we refrain from doing this, first, we wanted to compare methodologies that are simple in construction and hence of use for practitioners, second, as noted in the introduction the GARCH model can become cumbersome (especially when there are more than two assets) and there is no commonly accepted specification for the covariance matrix. Nonetheless, a study by McMillan, Speight, and Evans (2008) McMillan, D. G., Speight, A. E.H. and Evans, K. 2008. How useful is intraday data for evaluating daily value-at-risk? Evidence from three euro rates. Journal of Multinational Financial Management, 18: 488–503. [Crossref] , [Google Scholar] does make comparison between the realised and GARCH approaches to portfolio construction.