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Momentum strategies of German mutual funds

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Abstract

The existence of the momentum effect in stock returns has been documented for the US (e.g., Jegadeesh and Titman in J. Finance 48(1), 65–91, 1993) and many other national equity markets worldwide (e.g., Griffin et al. in J. Finance 58(6), 2515–2547, 2003). However, little is known about the active employment of momentum strategies among institutional investors outside the US. This paper provides first evidence of momentum behavior among German mutual funds. We find the fund trades to follow stock returns on an aggregated institutional level. Moreover, we detect significant momentum behavior among funds with a European and global equity focus, as well as among funds predominantly investing in Asia. In contrast, German funds do not seem to engage in momentum strategies when trading domestic stocks. While only half the funds in our sample trade in accordance with past returns, 66 % of the funds within the largest size quintile follow momentum strategies. Finally, we do not find momentum trading funds to outperform the other funds.

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Notes

  1. For a comprehensive list of momentum trading studies using US data, see Sias (2007).

  2. Only two other studies focus on momentum behavior by investors outside the US: Grinblatt and Keloharju (2000) analyze the momentum behavior of various investor types within the Finnish stock market and De Haan and Kakes (2011) examine the investment strategies of Dutch pension funds, life insurers, and non-life insurers. Other papers focusing on the existence of the momentum effect within national stock markets include, e.g., Rey and Schmid (2007).

  3. The disposition effect describes the tendency of investors to sell past winner stocks while keeping stocks that have lost in value.

  4. We do not use this methodology to analyze specific subgroups of funds as the approach is rather limited in its informative value.

  5. Chen et al. (2004) argue that larger funds need to find more stocks to invest in as they cannot just scale up their current holdings due to liquidity problems that would result in a negative influence on the securities’ prices.

  6. See § 44 I and II InvG (Investmentgesetz).

  7. Stotz (2007) finds that the annualized return difference between surviving and closing funds in the German mutual fund industry is substantial, making the absence of survivorship bias an important attribute of this empirical study.

  8. Because momentum trading is measured relative to the historical performance of the stocks held in the individual portfolios, it is not necessary to synchronize the reporting dates as described, for example, by Wermers (1999).

  9. Note that Eq. (1) differs from Sias (2007) in that the denominator is the number of shares held by the institutions rather than the number of all shares outstanding. This is to better reflect the fact that the sample contains international stocks, in which the covered funds’ ownership represents only a small fraction of all shares outstanding.

  10. Sias (2007) uses a similar modification.

  11. A dyad is defined as a period for which holding information is available at the beginning and at the end of the period.

  12. Note that a “buy” (“sell”) adjustment does not require a purchase (sale) of shares of the actual security, but rather an increase (decrease) in the relative equity position due to portfolio trades in general.

  13. Therefore, a fund with partially missing portfolio information in a given period is omitted from the analysis for the dyads that are affected. This results in slightly fewer observations for the TAL0M measure.

  14. According to § 59 InvG, German mutual funds are prohibited from short selling.

  15. Walter and Weber (2006) support this assumption by suggesting that the lack of superior performance in their sample of German mutual funds indicates momentum trading rather than stock picking talent.

  16. Due to the wide geographic scope of the holdings in our fund universe, the security returns were adjusted using the returns of the MSCI World index.

  17. This value was adjusted as the unadjusted value was heavily skewed due to a few outliers. The reported value for the fifth quintile was restricted to observations smaller than the value of the third quartile plus 1.5 times the interquartile range (Q3–Q1) of the fifth quintile. This procedure follows an approach described by Hoaglin et al. (2000). The adjustment did not change the general trend presented.

  18. However, since the fund sample used by Grinblatt et al. (1995) is not free of survivorship bias, it is possible that liquidated funds that may have employed contrarian strategies were not included in their sample.

  19. We assess market conditions by the sign of the return of the MSCI World index over the respective periods.

  20. In unreported results, we find that the subgroup of funds investing solely in German equities also exhibits significant lag-1 contrarian strategies.

  21. In line with the results from Sect. 3.2 and the findings that contemporaneous period returns are more important determinants of portfolio choice than lagged returns (Grinblatt et al. 1995), we focus on the GTW lag-0 momentum measures in the following.

  22. Barber and Odean (2008) document that in an environment with many stocks to choose from, individual investors are more likely to buy stocks that have recently caught their attention, for example, stocks that exhibited high prior returns.

  23. Certainly, other common stock trading strategies, such as high versus low beta stocks, large versus small market capitalization stocks, and value versus growth stocks (see, e.g., Carhart 1997), can also be realized with limited research dedication. Indeed, Asness et al. (2012) find that a combination of value and momentum strategies across different asset classes can be especially beneficial for investors.

  24. As a robustness check, we differentiate fund size in terms of number of different securities held and find similar results of momentum trading for the respective size quintiles.

  25. More precisely, Grinblatt et al. (1995) show that, on average, well performing funds tend to herd by buying past winning stocks.

  26. Eling and Schuhmacher (2007) show that the choice of performance measure does not affect performance rankings of hedge funds and that the Sharpe ratio is adequate for evaluating hedge funds. Although under normal circumstances, mutual funds and hedge funds cannot be easily compared due to structural differences, the composition of the L0M measure, which removes the short-sale restriction from mutual funds, allows us to conclude that the results of Eling and Schuhmacher (2007) should also be valid in this case.

  27. The low Sharpe ratio of 0.00 for the extreme momentum quintile Q5 indicates that the high L0M\(f,t\) measure is not the result of successful stock-picking at the beginning of the period. As this trading behavior would by definition have led to a higher fund performance, the high L0M\(f,t\) level must be the result of active momentum behavior.

  28. We calculate portfolio turnover in accordance with the methodology of the Center for Research in Security Prices (CRSP): The minimum of a fund’s total value of stock purchases and sales in \(t\), divided by the total net assets of the fund in \(t\).

  29. We use dummy variables for the funds’ respective geographic investment focus (Germany, Europe-wide, Asia, other regions, other countries, worldwide, and industry) that equal 1 if a fund exhibits the specific investment focus; 0 otherwise.

  30. Please note that the high adjusted \(R^{2}\) of the regressions are mainly due to the high dependence of the Sharpe ratios on market conditions.

  31. Note that this is a hypothetical return owed to the construction of the L0M measure and not an actual return achieved by the funds.

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Acknowledgments

We thank Alexander G. Kerl, Markus M. Schmid (the editor), an anonymous referee, participants at the 2013 Campus for Finance Research Conference, and participants at the FMI Seminar at the Justus-Liebig-University Giessen for valuable comments and suggestions.

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Authors and Affiliations

  1. Department of Financial Services, Justus-Liebig-University Giessen, Licher Str. 74, 35394 , Giessen, Germany

    Alexander Franck & Andreas Walter

  2. Ernst & Young GmbH, Eschborn, Germany

    Johannes F. Witt

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  1. Alexander Franck
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  2. Andreas Walter
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Correspondence to Alexander Franck.

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The authors are exclusively responsible for any errors and inaccuracies. The views expressed in this paper are those of the authors and do not necessarily reflect those of the University of Giessen or Ernst & Young GmbH.

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Franck, A., Walter, A. & Witt, J.F. Momentum strategies of German mutual funds. Financ Mark Portf Manag 27, 307–332 (2013). https://doi.org/10.1007/s11408-013-0211-z

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