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Currency Factors

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  • 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.

Suggested Citation

  • Arash Aloosh & Geert Bekaert, 2019. "Currency Factors," NBER Working Papers 25449, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:25449
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    2. Andrew Lilley & Matteo Maggiori & Brent Neiman & Jesse Schreger, 2019. "Exchange Rate Reconnect," NBER Working Papers 26046, National Bureau of Economic Research, Inc.
    3. Adam Zaremba & George Kambouris, 2019. "The sources of momentum in international government bond returns," Applied Economics, Taylor & Francis Journals, vol. 51(8), pages 848-857, February.
    4. Charles W. Calomiris & Harry Mamaysky, 2019. "Monetary Policy and Exchange Rate Returns: Time-Varying Risk Regimes," NBER Working Papers 25714, National Bureau of Economic Research, Inc.
    5. Bettendorf, Timo & Heinlein, Reinhold, 2019. "Connectedness between G10 currencies: Searching for the causal structure," Discussion Papers 06/2019, Deutsche Bundesbank.
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    7. Fredy Gamboa-Estrada & José Vicente Romero, 2022. "Common and idiosyncratic movements in Latin-American exchange rates," International Economics, CEPII research center, issue 171, pages 174-190.
    8. Morten Risstad & Airin Thodesen & Kristian August Thune & Sjur Westgaard, 2023. "On the Exchange Rate Dynamics of the Norwegian Krone," JRFM, MDPI, vol. 16(7), pages 1-18, June.
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    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

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