Abstract
This paper proposes a clustering-based factor analysis method to analyze the relationship between countries based on their Nominal Effective Exchange Rates (NEER). As an exchange rate is a relative value of a currency in terms of another currency, exchange rates can show the relationship between two countries where the relevant currencies are used. Based on this insight, this paper identifies currency clusters based on the movement of the exchange rates between countries over time. In the experiment, 60 countries’ NEER data from 2002-07-01 to 2022-06-30 were analyzed using the proposed clustering-based factor analysis method. In the proposed method, the clustering was performed on both country and time axes simultaneously. The results show that there are 11 meaningful clusters on both country and time axes. The country clusters are characterized by continents or currency-related properties. The separation between time clusters are related to the large-scale financial events, such as the Global Financial Crisis and the COVID-19 pandemic.
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