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To follow or not to follow – An empirical analysis of the returns of actors on social trading platforms

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  • Dorfleitner, Gregor
  • Fischer, Lukas
  • Lung, Carina
  • Willmertinger, Philipp
  • Stang, Nico
  • Dietrich, Natalie

Abstract

We analyze the returns of traders, i.e. signal providers, on social trading platforms and of investors following these traders by utilizing differently sophisticated investment strategies. It becomes evident that simply investing in those traders with the highest accumulated returns leads to high losses, while taking the Sharpe ratio into account improves the achieved returns. Positive returns, however, are only possible for sophisticated strategies that consider information on the risk of the signal providers’ portfolios. Moreover, no strategy reveals a positive abnormal return after transaction costs in the sense of a Carhart four-factor model. Further, we analyze predictors of the weekly returns of the signal providers in a panel set-up. We find that highly active trading behavior is negatively related with the returns, while there is no wisdom-of-the-crowd effect, in the sense of a positive relationship of the number of followers or invested capital with the returns.

Suggested Citation

  • Dorfleitner, Gregor & Fischer, Lukas & Lung, Carina & Willmertinger, Philipp & Stang, Nico & Dietrich, Natalie, 2018. "To follow or not to follow – An empirical analysis of the returns of actors on social trading platforms," The Quarterly Review of Economics and Finance, Elsevier, vol. 70(C), pages 160-171.
  • Handle: RePEc:eee:quaeco:v:70:y:2018:i:c:p:160-171
    DOI: 10.1016/j.qref.2018.04.009
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    Cited by:

    1. Scheckenbach, Isabel & Wimmer, Maximilian & Dorfleitner, Gregor, 2021. "The higher you fly, the harder you try not to fall: An analysis of the risk taking behavior in social trading," The Quarterly Review of Economics and Finance, Elsevier, vol. 82(C), pages 239-259.
    2. Schneider, Julian & Oehler, Andreas, 2021. "Competition for visibility: When do (FX) signal providers employ lotteries?," International Review of Financial Analysis, Elsevier, vol. 78(C).
    3. Steiger, Sören & Pelster, Matthias, 2020. "Social interactions and asset pricing bubbles," Journal of Economic Behavior & Organization, Elsevier, vol. 179(C), pages 503-522.
    4. Erdős, Sándor & Papp, Tamás & Vörös, Zsófia, 2022. "The effects of community-based signals on investment decisions in copy trading," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 97(C).
    5. Gregor Dorfleitner & Lars Hornuf & Lena Wannenmacher, 2020. "The German FinTech Market in 2020," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 73(08), pages 33-40, August.

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    More about this item

    Keywords

    Social trading; Performance analysis; Panel regression; Signal providers; Mirror trading; Investment strategies;
    All these keywords.

    JEL classification:

    • G20 - Financial Economics - - Financial Institutions and Services - - - General
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill

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