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Trade momentum for alpha

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  • Hong, Weiting

Abstract

I provide new evidence on the value-relevance of international trade development, the heterogeneous distribution of foreign economic benefits among market participants, and the value-add of additional geographic information disclosure by designing the Trade Momentum Index with publicly available citation share, export volume, and trade barrier data. Using a sample of 13,016 firm-year combinations of goods-exporting U.S. firms between 2008 and 2020, I find that a Trade Momentum Index-based, equal-weight hedge portfolio generates a statistically significant annualized alpha of 17.42% at a Sharpe ratio of 0.8255. This result exhibits robustness as the abnormal returns persist under different factor models.

Suggested Citation

  • Hong, Weiting, 2022. "Trade momentum for alpha," Finance Research Letters, Elsevier, vol. 50(C).
  • Handle: RePEc:eee:finlet:v:50:y:2022:i:c:s1544612322004834
    DOI: 10.1016/j.frl.2022.103300
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    References listed on IDEAS

    as
    1. Fama, Eugene F. & French, Kenneth R., 2015. "A five-factor asset pricing model," Journal of Financial Economics, Elsevier, vol. 116(1), pages 1-22.
    2. Fama, Eugene F. & French, Kenneth R., 1993. "Common risk factors in the returns on stocks and bonds," Journal of Financial Economics, Elsevier, vol. 33(1), pages 3-56, February.
    3. Ole‐Kristian Hope & Tony Kang & Wayne B. Thomas & Florin Vasvari, 2008. "Pricing and Mispricing Effects of SFAS 131," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 35(3‐4), pages 281-306, April.
    4. Justin R. Pierce & Peter K. Schott, 2009. "A Concordance Between Ten-Digit U.S. Harmonized System Codes and SIC/NAICS Product Classes and Industries," NBER Working Papers 15548, National Bureau of Economic Research, Inc.
    5. Ole-Kristian Hope & Tony Kang & Wayne B. Thomas & Florin Vasvari, 2008. "Pricing and Mispricing Effects of SFAS 131," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 35(3-4), pages 281-306.
    6. Carhart, Mark M, 1997. "On Persistence in Mutual Fund Performance," Journal of Finance, American Finance Association, vol. 52(1), pages 57-82, March.
    7. Li, Ningzhong & Richardson, Scott & Tuna, İrem, 2014. "Macro to micro: Country exposures, firm fundamentals and stock returns," Journal of Accounting and Economics, Elsevier, vol. 58(1), pages 1-20.
    8. Fontagné, Lionel & Guillin, Amélie & Mitaritonna, Cristina, 2010. "Estimations of Tariff Equivalents for the Services Sectors," Conference papers 331941, Purdue University, Center for Global Trade Analysis, Global Trade Analysis Project.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Asset pricing; Forecasting returns; International trade; Investment decisions; Market inefficiency; Portfolio choice;
    All these keywords.

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • F14 - International Economics - - Trade - - - Empirical Studies of Trade

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