Working Paper: NBER ID: w25449
Authors: Arash Aloosh; Geert Bekaert
Abstract: We examine the ability of existing and new factor models to explain the comovements of G10- currency changes, measured using the novel concept of “currency baskets”, representing the overall movement of a particular currency. Using a 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 currency basket correlations much better than extant factors, such as value and carry, do. 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 fits comovements in emerging market currencies well. Economically, the correlations between currency baskets underlying the factor structure are inversely related to the physical distances between countries. The factor structure is also related to the exposure of the corresponding pricing kernels with respect to the global pricing kernel and is apparent in cross-country retail sales growth data.
Keywords: Currency Comovements; Factor Models; G10 Currencies
JEL Codes: C23; C53; G11
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| clustering factor (C38) | currency variation (F31) |
| commodity currency factor (F16) | currency variation (F31) |
| market factor (P23) | currency variation (F31) |
| physical distances between countries (F29) | correlations between currency baskets (F31) |
| factor structure (L10) | exposure of pricing kernels (G19) |
| factor structure (L10) | cross-country retail sales growth data (L81) |