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Momentum and Turnover: Evidence from the German Stock Market

Author

Listed:
  • Glaser, Markus

    (Sonderforschungsbereich 504)

  • Weber, Martin

    (Lehrstuhl für ABWL, Finanzwirtschaft, insb. Bankbetriebslehre)

Abstract

This paper analyzes the relation between momentum strategies (strategies that buy stocks with high returns over the previous three to 12 months and sell stocks with low returns over the same period) and turnover (number of shares traded divided by the number of shares outstanding) for the German stock market. Our main finding is that momentum strategies are more profitable among high-turnover stocks. In contrast to US evidence, this result is mainly driven by winners: high-turnover winners have higher returns than low-turnover winners. We present various robustness checks, long-horizon results, evidence on seasonality, and control for size-, book-to-market-, and industry-effects. We argue that our results are useful to empirically evaluate competing explanations for the momentum effect.

Suggested Citation

  • Glaser, Markus & Weber, Martin, 2002. "Momentum and Turnover: Evidence from the German Stock Market," Sonderforschungsbereich 504 Publications 02-43, Sonderforschungsbereich 504, Universität Mannheim;Sonderforschungsbereich 504, University of Mannheim.
  • Handle: RePEc:xrs:sfbmaa:02-43
    Note: Financial support from the Deutsche Forschungsgemeinschaft (DFG) is gratefully acknowledged.
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    Cited by:

    1. Tim Herberger & Daniel Kohlert & Andreas Oehler, 2011. "Momentum and industry-dependence: An analysis of the Swiss stock market," Journal of Asset Management, Palgrave Macmillan, vol. 11(6), pages 391-400, February.
    2. Philipp Dirkx & Franziska J. Peter, 2020. "The Fama-French Five-Factor Model Plus Momentum: Evidence for the German Market," Schmalenbach Business Review, Springer;Schmalenbach-Gesellschaft, vol. 72(4), pages 661-684, October.
    3. Luis Muga & Rafael Santamaría, 2009. "Momentum, market states and investor behavior," Empirical Economics, Springer, vol. 37(1), pages 105-130, September.
    4. Glaser, Markus & Nöth, Markus & Weber, Martin, 2003. "Behavioral Finance," Sonderforschungsbereich 504 Publications 03-14, Sonderforschungsbereich 504, Universität Mannheim;Sonderforschungsbereich 504, University of Mannheim.
    5. Hofmann, Daniel & Keiber, Karl Ludwig & Luczak, Adalbert, 2022. "Up and down together? On the linkage of momentum and reversal," Global Finance Journal, Elsevier, vol. 54(C).
    6. Amir Amel†Zadeh, 2011. "The Return of the Size Anomaly: Evidence from the German Stock Market," European Financial Management, European Financial Management Association, vol. 17(1), pages 145-182, January.
    7. Swanson, Peggy E. & Lin, Anchor Y., 2005. "Trading behavior and investment performance of U.S. investors in global equity markets," Journal of Multinational Financial Management, Elsevier, vol. 15(2), pages 99-115, April.
    8. Markus Glaser & Thomas Langer & Martin Weber, 2007. "On the Trend Recognition and Forecasting Ability of Professional Traders," Decision Analysis, INFORMS, vol. 4(4), pages 176-193, December.
    9. Tina Kalayil & Somya Tyagi & Mahfuza Khatun & Sikandar Siddiqui, 2019. "A Risk-Sensitive Momentum Approach To Stock Selection," Economic Annals, Faculty of Economics and Business, University of Belgrade, vol. 64(220), pages 61-84, January –.
    10. Tim A. Herberger & Matthias Horn & Andreas Oehler, 2020. "Are intraday reversal and momentum trading strategies feasible? An analysis for German blue chip stocks," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 34(2), pages 179-197, June.
    11. Marie-Hélène Broihanne & Maxime Merli & Patrick Roger, 2008. "A Behavioural Approach To Financial Puzzles," Working Papers of LaRGE Research Center 2008-01, Laboratoire de Recherche en Gestion et Economie (LaRGE), Université de Strasbourg.
    12. Alexander Franck & Andreas Walter & Johannes Witt, 2013. "Momentum strategies of German mutual funds," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 27(3), pages 307-332, September.
    13. Han-Ching Huang & Bo-Sheng Wu, 2020. "The Performance of Trading Strategies based on the Ratio of Option and Stock Volume," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 10(4), pages 1-9.
    14. Martin H. Schmidt, 2017. "Trading strategies based on past returns: evidence from Germany," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 31(2), pages 201-256, May.
    15. Supriya Maheshwari & Raj S. Dhankar, 2017. "Profitability of Volume-based Momentum and Contrarian Strategies in the Indian Stock Market," Global Business Review, International Management Institute, vol. 18(4), pages 974-992, August.
    16. Yu-Nan Tai, 2014. "Investor Overreaction in Asian and US Stock Markets: Evidence from the 2008 Financial Crisis," The International Journal of Business and Finance Research, The Institute for Business and Finance Research, vol. 8(3), pages 71-93.
    17. Till, Gábor, 2021. "Az árfolyam-nyereség arány szerepe a német tőzsdei kereskedésben [The role of the P/E ratio in trading on the German stock exchange]," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(7), pages 815-846.
    18. Christian Fieberg & Armin Varmaz & Thorsten Poddig, 2016. "Covariances vs. characteristics: what does explain the cross section of the German stock market returns?," Business Research, Springer;German Academic Association for Business Research, vol. 9(1), pages 27-50, April.

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    More about this item

    JEL classification:

    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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