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The purpose of this paper then, is to add to the existing literature on financial contagion. While a vast amount of the debate has been made using data from the late 1990s, this paper differentiates itself by analysing more current data, centred around the most recent global financial crisis, with specific focus on the stock markets of Hong Kong and Tokyo.

Employing Pearson and Spearman correlation measures, the dynamic relationship of the two markets is determined over tranquil and crisis periods, as specified by an Markov-Switching Bayesian Vector AutoRegression (MSBVAR) model.

The authors find evidence in support of the existence of financial contagion (defined as an increase in correlation during a crisis period) for all frequencies of data analysed. This contagion is greatest when examining lower-frequency data. Additionally, there is also weaker evidence in some data sub-samples to support “herding” behaviour, whereby higher market correlations persist, following a crisis period.

The intention of this paper was not to analyse the cause or transmission mechanism of contagion between financial markets. Therefore future studies could extend the methodology used in this paper by including exogenous macroeconomic factors in the MSBVAR model.

The results of this paper serve to explain why the debate of the persistence and in fact existence of financial contagion remains alive. The authors have shown that the frequency of a time series dataset has a significant impact on the level of observed correlation and thus observation of financial contagion.