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Good Carry, Bad Carry

Published online by Cambridge University Press:  21 October 2019

Geert Bekaert  and
George Panayotov Open the ORCID record for George Panayotov [Opens in a new window]
Geert Bekaert
Affiliation:
Bekaert, gb241@columbia.edu, Columbia University Business School
George Panayotov*
Affiliation:
Panayotov, panayotov@ust.hk, Hong Kong University of Science and Technology School of Business
*
Panayotov (corresponding author), panayotov@ust.hk
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Abstract

We distinguish between “good” and “bad” carry trades constructed from Group of Ten (G-10) currencies. The good trades exhibit higher Sharpe ratios and sometimes positive return skewness, in contrast to the bad trades, which have both substantially lower Sharpe ratios and highly negative return skewness. Surprisingly, good trades do not involve the most typical carry currencies like the Australian dollar and Japanese yen. The distinction between good and bad carry trades significantly alters our understanding of currency carry trade returns, and invalidates, for example, explanations invoking return skewness and crash risk.

Type
Research Article
Information
Journal of Financial and Quantitative Analysis , Volume 55 , Issue 4 , June 2020 , pp. 1063 - 1094
Copyright
Copyright © Michael G. Foster School of Business, University of Washington 2019

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Footnotes

We acknowledge many fruitful suggestions by Raymond Kan and discussions with Gurdip Bakshi, Utpal Bhattacharya, Steve Riddiough, Giorgio Valente, and Jialin Yu. Participants at the 2016 Annual Conference in International Finance at City University of Hong Kong; the 2016 Bank of England, Banca d’Italia, and 6th European Central Bank Workshop on Financial Determinants of Foreign Exchange Rates; the 2018 Vienna Symposium on Foreign Exchange Markets; and seminars at Nanyang Technology University, the Sabanci Center in Istanbul, the Shanghai Advanced Institute of Finance, the University of New South Wales, and Xiamen University provided helpful insights. Any remaining errors are our responsibility alone. Panayotov acknowledges support from the Hong Kong Research Grants Council (grant no. 16505715).

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