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Can the intermediary capital risk predict foreign exchange rates?

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  • Yin, Libo

Abstract

The intermediary capital risk (ICR) is recently perceived as an important indicator of economic activities and risk premiums. In this paper, we provide individual time-series predictability of ICR for exchange rates of twelve major currencies against US dollar, in both in-sample and out-of-sample settings. This predictive pattern is robust when controlling for macroeconomic variables. Further analysis shows that a simple linear regression is sufficient to capture the predictive performance. Our results imply that the ICR factor is a useful predictor for exchange rates.

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  • Yin, Libo, 2020. "Can the intermediary capital risk predict foreign exchange rates?," Finance Research Letters, Elsevier, vol. 37(C).
  • Handle: RePEc:eee:finlet:v:37:y:2020:i:c:s1544612319305367
    DOI: 10.1016/j.frl.2019.101349
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    1. Markus K. Brunnermeier & Yuliy Sannikov, 2014. "A Macroeconomic Model with a Financial Sector," American Economic Review, American Economic Association, vol. 104(2), pages 379-421, February.
    2. Lucio Sarno & Giorgio Valente, 2009. "Exchange Rates and Fundamentals: Footloose or Evolving Relationship?," Journal of the European Economic Association, MIT Press, vol. 7(4), pages 786-830, June.
    3. Zhiguo He & Arvind Krishnamurthy, 2013. "Intermediary Asset Pricing," American Economic Review, American Economic Association, vol. 103(2), pages 732-770, April.
    4. Charles Engel & Kenneth D. West, 2005. "Exchange Rates and Fundamentals," Journal of Political Economy, University of Chicago Press, vol. 113(3), pages 485-517, June.
    5. Roubaud, David & Arouri, Mohamed, 2018. "Oil prices, exchange rates and stock markets under uncertainty and regime-switching," Finance Research Letters, Elsevier, vol. 27(C), pages 28-33.
    6. Barbara Rossi, 2013. "Exchange Rate Predictability," Journal of Economic Literature, American Economic Association, vol. 51(4), pages 1063-1119, December.
    7. Domenico Ferraro & Kenneth S. Rogoff & Barbara Rossi, 2011. "Can oil prices forecast exchange rates?," Working Papers 11-34, Federal Reserve Bank of Philadelphia.
    8. Kyle Jurado & Sydney C. Ludvigson & Serena Ng, 2015. "Measuring Uncertainty," American Economic Review, American Economic Association, vol. 105(3), pages 1177-1216, March.
    9. Gino Cenedese & Richard Payne & Lucio Sarno & Giorgio Valente, 2016. "What Do Stock Markets Tell Us about Exchange Rates?," Review of Finance, European Finance Association, vol. 20(3), pages 1045-1080.
    10. Rime, Dagfinn & Sarno, Lucio & Sojli, Elvira, 2010. "Exchange rate forecasting, order flow and macroeconomic information," Journal of International Economics, Elsevier, vol. 80(1), pages 72-88, January.
    11. Caporale, Guglielmo Maria & Spagnolo, Fabio & Spagnolo, Nicola, 2017. "Macro news and exchange rates in the BRICS," Finance Research Letters, Elsevier, vol. 21(C), pages 140-143.
    12. He, Zhiguo & Kelly, Bryan & Manela, Asaf, 2017. "Intermediary asset pricing: New evidence from many asset classes," Journal of Financial Economics, Elsevier, vol. 126(1), pages 1-35.
    13. Clark, Todd E. & West, Kenneth D., 2007. "Approximately normal tests for equal predictive accuracy in nested models," Journal of Econometrics, Elsevier, vol. 138(1), pages 291-311, May.
    14. Frijns, Bart & Huynh, Thanh D. & Tourani-Rad, Alireza & Westerholm, P. Joakim, 2018. "Institutional trading and asset pricing," Journal of Banking & Finance, Elsevier, vol. 89(C), pages 59-77.
    15. Tobias Adrian & Erkko Etula & Tyler Muir, 2014. "Financial Intermediaries and the Cross-Section of Asset Returns," Journal of Finance, American Finance Association, vol. 69(6), pages 2557-2596, December.
    16. Christopher J. Neely & David E. Rapach & Jun Tu & Guofu Zhou, 2014. "Forecasting the Equity Risk Premium: The Role of Technical Indicators," Management Science, INFORMS, vol. 60(7), pages 1772-1791, July.
    17. Meese, Richard A. & Rogoff, Kenneth, 1983. "Empirical exchange rate models of the seventies : Do they fit out of sample?," Journal of International Economics, Elsevier, vol. 14(1-2), pages 3-24, February.
    18. Christina Christou & Rangan Gupta & Christis Hassapis & Tahir Suleman, 2018. "The role of economic uncertainty in forecasting exchange rate returns and realized volatility: Evidence from quantile predictive regressions," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 37(7), pages 705-719, November.
    19. John Y. Campbell & Samuel B. Thompson, 2008. "Predicting Excess Stock Returns Out of Sample: Can Anything Beat the Historical Average?," Review of Financial Studies, Society for Financial Studies, vol. 21(4), pages 1509-1531, July.
    20. Pasquale Della Corte & Steven J. Riddiough & Lucio Sarno, 2016. "Currency Premia and Global Imbalances," Review of Financial Studies, Society for Financial Studies, vol. 29(8), pages 2161-2193.
    21. Husted, Lucas & Rogers, John & Sun, Bo, 2018. "Uncertainty, currency excess returns, and risk reversals," Journal of International Money and Finance, Elsevier, vol. 88(C), pages 228-241.
    22. Lucio Sarno & Maik Schmeling, 2014. "Which Fundamentals Drive Exchange Rates? A Cross‐Sectional Perspective," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 46(2-3), pages 267-292, March.
    23. Ferraro, Domenico & Rogoff, Kenneth & Rossi, Barbara, 2015. "Can oil prices forecast exchange rates? An empirical analysis of the relationship between commodity prices and exchange rates," Journal of International Money and Finance, Elsevier, vol. 54(C), pages 116-141.
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