Seasonal Currency Patterns

Originally published in April 2019’s issue of Foreign Exchange Consensus Forecasts. The unabridged article and a recent sample issue are available to industry professionals. Simply send us an email at editors@consensuseconomics.com

Like many other economic variables, exchange rates are sometimes thought to be subject to seasonal influences. These could arise from a number of sources, including dependence on industries which are subject to seasonal swings in demand or supply (tourism and agriculture, for example) and financial effects such as the repatriation of overseas earnings ahead of a financial year end. In order to identify such patterns (or not), we have adopted a relatively widely used statistical approach, known as X12 ARIMA (developed by the US Census Bureau), to analyse underlying trends. Examining end month data from January 1999 to December 2018, we calculated X12 ARIMA seasonal factors for 36 of the major currencies we cover. These measure the average deviation of an exchange rate from its trend rate in each month over the past twenty years.

Our long-term historical analysis continues to suggest that seasonal influences on currencies are generally modest, particularly once adjustments are made to account for outlying observations. On average, of the 36 major currencies covered, almost all deviated from trend within a narrow range of plus or minus 1.0%. Estimates for the US dollar (based on NYBOT index weights) suggest that it has a slight tendency toward strength in the first half of the calendar year, except April, and weakness in July through September. In contrast, the euro (or its component currencies prior to 1999, which has a significant weight in the NYBOT index) showed the opposite pattern over the same period.

To illustrate the patterns of currencies where seasonal influences appear most significant, we show a selection of them as charts below, where the trend rate is set as 100. The solid blue line represents analyses of the long-term 20 year average (1999-2018). ARIMA outturns for the nine years 2010-2018 (black dotted line) period have also been added to charts in an attempt to take out the influence of the 2008 global financial crisis and its after-effects on the traditional patterns of seasonality.

 

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