Assessing spillover effects in currency markets

We measure the spillover effect that big moves in one currency pair can have on a group of currencies from a purely statistical point of view.

We measure the spillover effect that big moves in one currency pair can have on a group of currencies from a purely statistical point of view.

We have two objectives in mind. The first one is understanding the importance of a shock from one currency to a group of currencies and how it propagates over time. The second one is to compare the importance of a shock now to a specified period.

Main results:

  • In Asia, the spillover effect from CNY is high, with CNY explaining 18% of the variance of IDR and around 16% of the variability of KRW. The variations in TWD are also to a large extent explained by KRW moves. INR shocks do not seem to have any significant contagion effects on other Asian currencies.

  • The spillover effect from CNY to KRW has grown significantly since 2008 Global Financial Crisis (GFC). The increased trade and financial exposure of Korea to China provides a likely explanation.

  • There is an increase in the explanatory power of the variance of the EEM currencies since the pandemic by EUR, due to an increase in the explanatory power for HUF.

  • Since the GFC, the contribution of the TRY to other European emerging currencies has fallen, while the TRY remains the European currency that is less impacted by the variance in other currencies. The contagion impact from PLN to the variance of other EEM currencies is high. In addition, the regional currency that is the most impacted by other regional currencies is HUF. With Central European economies competing on the same export markets, it makes sense that the explanatory power of each currency for the other is strong.

  • The explanatory power from BRL and CLP for the variance of other Latin American currencies has grown since the GFC.