{"id":774,"date":"2017-10-03T21:14:53","date_gmt":"2017-10-03T21:14:53","guid":{"rendered":"http:\/\/quantpedia.com\/?p=774"},"modified":"2025-06-04T14:34:14","modified_gmt":"2025-06-04T12:34:14","slug":"a-suggestion-of-new-currency-factor-model","status":"publish","type":"post","link":"https:\/\/vvv.quantpedia.com\/es\/a-suggestion-of-new-currency-factor-model\/","title":{"rendered":"Suggestion of a New Currency Factor Model"},"content":{"rendered":"

\n\tA new research paper related to multiple currency strategies: <\/strong><\/p>\n

\n\tAutores:<\/strong> Aloosh, Bekaert<\/p>\n

\n\tT\u00edtulo: <\/strong>Currency Factors<\/p>\n

\n\tLink:<\/strong> https:\/\/papers.ssrn.com\/sol3\/papers.cfm?abstract_id=3022623<\/a><\/p>\n

\n\tAbstracto:<\/strong><\/p>\n

\n\tWe examine the ability of existing and new factor models to explain the comovements of G10-currency changes. Extant currency factors include the carry, volatility, value, and momentum factors. Using a new clustering technique, we find a clear two-block structure in currency comovements with the first block containing mostly the dollar currencies, and the other the European currencies. A factor model incorporating this “clustering” factor and two additional factors, a commodity currency factor and a “world” factor based on trading volumes, fits all bilateral exchange rates well, whatever the currency perspective. In particular, it explains on average about 60% of currency variation and generates a root mean squared error relative to sample correlations of only 0.11. The model also explains a considerable fraction of the variation in emerging market currencies.<\/p>\n

\n\tFragmentos destacados del art\u00edculo de investigaci\u00f3n acad\u00e9mica:<\/strong><\/p>\n

\n\t"In this paper, we set out to examine various factor models to explain currency comovements and document their fit with the data from a global perspective. That is, we attempt to identify a factor model that works well whatever the currency perspective is. To facilitate a global perspective on currency comovements, we introduce the concept of a “currency basket.” The currency basket simply averages all bilateral currency changes relative to one particular currency. As we show formally, by analyzing 10 currency baskets for the G10 currencies, we span all possible bilateral currency movements. We then contrast the explanatory power of the extant risk factors mentioned previously with the explanatory power of various new factors.<\/p>\n

\n\tMost importantly, we use a new clustering technique to introduce several new currency factors. When selecting two clusters, a very clear factor structure emerges, with the dollar currencies (Australian, Canadian, New Zealand and US) and the Japanese yen in one block and the European currencies in the other. When using three clusters, a commodity type currency factor also emerges. Combining these statistical factors with a “market” factor, based on currency trading volumes, and a commodity currency factor, we propose several parsimonious factor models and run a horse race versus models incorporating the existing factors.<\/p>\n

\n\tAmong the extant currency factors, the carry and value factors exhibit the highest explanatory power for currency variation. This is not surprising because both factors are relatively highly correlated with the first principal component in bilateral currency rates. However, a new parsimonious factor model incorporating the two-block clustering factor, a commodity factor and the market factor easily beats factor models created from extant risk factors, even models that feature double as many factors. The new factor model explains on average about 60% of the variation in changes in currency basket values. Moreover, the Root Mean Squared Error (RMSE) relative to sample correlations is only about 0.11, which is statistically significantly better than any model based on extant risk factors."
\n\t <\/p>\n\n

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\n\tA new research paper related to multiple currency strategies: <\/strong><\/p>\n

\n\tAutores:<\/strong> Aloosh, Bekaert<\/p>\n

\n\tT\u00edtulo: <\/strong>Currency Factors<\/p>\n

\n\tLink:<\/strong> https:\/\/papers.ssrn.com\/sol3\/papers.cfm?abstract_id=3022623<\/a><\/p>\n

\n\tAbstracto:<\/strong><\/p>\n

\n\tWe examine the ability of existing and new factor models to explain the comovements of G10-currency changes. Extant currency factors include the carry, volatility, value, and momentum factors. Using a new clustering technique, we find a clear two-block structure in currency comovements with the first block containing mostly the dollar currencies, and the other the European currencies. A factor model incorporating this “clustering” factor and two additional factors, a commodity currency factor and a “world” factor based on trading volumes, fits all bilateral exchange rates well, whatever the currency perspective. In particular, it explains on average about 60% of currency variation and generates a root mean squared error relative to sample correlations of only 0.11. The model also explains a considerable fraction of the variation in emerging market currencies.<\/p>\n

\n\tFragmentos destacados del art\u00edculo de investigaci\u00f3n acad\u00e9mica:<\/strong><\/p>\n

\n\t"In this paper, we set out to examine various factor models to explain currency comovements and document their fit with the data from a global perspective. That is, we attempt to identify a factor model that works well whatever the currency perspective is. To facilitate a global perspective on currency comovements, we introduce the concept of a “currency basket.” The currency basket simply averages all bilateral currency changes relative to one particular currency. As we show formally, by analyzing 10 currency baskets for the G10 currencies, we span all possible bilateral currency movements. We then contrast the explanatory power of the extant risk factors mentioned previously with the explanatory power of various new factors.<\/p>\n

\n\tMost importantly, we use a new clustering technique to introduce several new currency factors. When selecting two clusters, a very clear factor structure emerges, with the dollar currencies (Australian, Canadian, New Zealand and US) and the Japanese yen in one block and the European currencies in the other. When using three clusters, a commodity type currency factor also emerges. Combining these statistical factors with a “market” factor, based on currency trading volumes, and a commodity currency factor, we propose several parsimonious factor models and run a horse race versus models incorporating the existing factors.<\/p>\n

\n\tAmong the extant currency factors, the carry and value factors exhibit the highest explanatory power for currency variation. This is not surprising because both factors are relatively highly correlated with the first principal component in bilateral currency rates. However, a new parsimonious factor model incorporating the two-block clustering factor, a commodity factor and the market factor easily beats factor models created from extant risk factors, even models that feature double as many factors. The new factor model explains on average about 60% of the variation in changes in currency basket values. Moreover, the Root Mean Squared Error (RMSE) relative to sample correlations is only about 0.11, which is statistically significantly better than any model based on extant risk factors."
\n\t <\/p>\n

\n

\n\t
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