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Detecting Crowded Trades in Currency Funds

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  • Momtchil Pojarliev
  • Richard M. Levich

Abstract

The financial crisis of 2008 highlights the importance of detecting crowded trades due to the risks they pose to the stability of the financial system and to the global economy. However, there is a perception that crowded trades are difficult to identify. To date, no single measure to capture the crowdedness of a trade or a trading style has developed. We propose a methodology to measure crowded trades and apply it to professional currency managers. Our results suggest that carry became a crowded trading strategy towards the end of Q1 2008, shortly before a massive liquidation of carry trades. The timing suggests a possible adverse relationship between our measure of style crowdedness and the future performance of the trading style. Crowdedness in the trend following and value strategies confirm this hypothesis. We apply our approach to currencies but the methodology is general and could be used to measure the popularity or crowdedness of any trade with an identifiable time series return. Our methodology may offer useful insights regarding the popularity of certain trades - in currencies, gold, or other assets - among hedge funds. Further research in this area might be very relevant for investors, managers and regulators.

Suggested Citation

  • Momtchil Pojarliev & Richard M. Levich, 2010. "Detecting Crowded Trades in Currency Funds," NBER Working Papers 15698, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:15698
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    Cited by:

    1. Marc van Kralingen & Diego Garlaschelli & Karolina Scholtus & Iman van Lelyveld, 2020. "Crowded trades, market clustering, and price instability," Tinbergen Institute Discussion Papers 20-007/II, Tinbergen Institute.
    2. Seok, Sang Ik & Cho, Hoon & Ryu, Doojin, 2019. "Firm-specific investor sentiment and daily stock returns," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
    3. Bruno, Salvatore & Chincarini, Ludwig B. & Ohara, Frank, 2018. "Portfolio construction and crowding," Journal of Empirical Finance, Elsevier, vol. 47(C), pages 190-206.
    4. Osler, Carol & Savaser, Tanseli, 2011. "Extreme returns: The case of currencies," Journal of Banking & Finance, Elsevier, vol. 35(11), pages 2868-2880, November.
    5. Spronk, Richard & Verschoor, Willem F.C. & Zwinkels, Remco C.J., 2013. "Carry trade and foreign exchange rate puzzles," European Economic Review, Elsevier, vol. 60(C), pages 17-31.
    6. Bussière, Matthieu & Hoerova, Marie & Klaus, Benjamin, 2015. "Commonality in hedge fund returns: Driving factors and implications," Journal of Banking & Finance, Elsevier, vol. 54(C), pages 266-280.
    7. Sam Nasypbek & Scheherazade S Rehman, 2011. "Explaining the returns of active currency managers," BIS Papers chapters, in: Bank for International Settlements (ed.), Portfolio and risk management for central banks and sovereign wealth funds, volume 58, pages 211-256, Bank for International Settlements.
    8. Olessia CAILLÉ & Louis RAFFESTIN, 2018. "Cross-asset holdings and the resiliency of wholesale funding," LEO Working Papers / DR LEO 2628, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.
    9. Chowdhury, Biplob & Dungey, Mardi & Kangogo, Moses & Sayeed, Mohammad Abu & Volkov, Vladimir, 2019. "The changing network of financial market linkages: The Asian experience," International Review of Financial Analysis, Elsevier, vol. 64(C), pages 71-92.
    10. Liyun Zhou & Chunpeng Yang, 2019. "Differences in the effects of seller-initiated versus buyer-initiated crowded trades in stock markets," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 14(4), pages 859-890, December.
    11. Gueorgui Konstantinov, 2016. "Capturing short-term and long-term alpha of global bond portfolios: evidence from EUR-investors’ perspective," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 30(3), pages 337-365, August.
    12. Seok, Sang Ik & Cho, Hoon & Ryu, Doojin, 2019. "Firm-specific investor sentiment and the stock market response to earnings news," The North American Journal of Economics and Finance, Elsevier, vol. 48(C), pages 221-240.
    13. Reed, Adam V., 2015. "Connecting supply, short-sellers and stock returns: Research challenges," Journal of Accounting and Economics, Elsevier, vol. 60(2), pages 97-103.
    14. Qian Zhang & Kuo-Jui Wu & Ming-Lang Tseng, 2019. "Exploring Carry Trade and Exchange Rate toward Sustainable Financial Resources: An application of the Artificial Intelligence UKF Method," Sustainability, MDPI, vol. 11(12), pages 1-26, June.
    15. Zhou, Liyun & Yang, Chunpeng, 2019. "Stochastic investor sentiment, crowdedness and deviation of asset prices from fundamentals," Economic Modelling, Elsevier, vol. 79(C), pages 130-140.
    16. Willem F.C. Verschoor & Remco C.J. Zwinkels, 2013. "Do foreign exchange fund managers behave like heterogeneous agents?," Quantitative Finance, Taylor & Francis Journals, vol. 13(7), pages 1125-1134, February.
    17. Stepan Gorban & Anna A. Obizhaeva & Yajun Wang, 2020. "Trading in Crowded Markets," Working Papers w0275, New Economic School (NES).

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    JEL classification:

    • F31 - International Economics - - International Finance - - - Foreign Exchange
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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