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  • Are Momentum Strategies Feasible in Intraday-Trading? Empirical Results from the German Stock Market

    Tim A. Herbergera*, Matthias Horna and Andreas Oehlerb

    Abstract Momentum trading strategies have been proved to be profitable in different asset classes and on various national capital markets in the past. However, there are some indications for eroding momentum profits. Based on the theory of gradual information distribution on capital markets and the technological progress of the last years, we suppose that the momentum effect transformed from a monthly basis to shorter time horizons. With regard to stocks that were listed in the German blue chip index DAX 30 between November 2013 and June 2014, this study is the first to examine, whether such strategies generate market adjusted excess returns on an intraday-trading basis. We analyze 16 momentum strategies, inspired by Jegadeesh/Titman´s (1993, 2001) original momentum strategy design (4x4), with ranking and holding periods of 15, 30, 45 or 60 minutes. For each stock, we analyze 15.131 price observations on a five minutes frequency. From the empirical results we conclude that the momentum strategy does not provide positive excess returns. However, we find indications for price reversals in intraday stock market returns for past loser stocks. Our results are robust on portfolio size (winning as well as loser portfolio) and the duration of a lag between the end of ranking period and beginning the holding period.

    JEL Classification: G10, G11, G14

    Key Words: Behavioral Finance, Intraday-Trading, Momentum Strategies

    a Department of Finance, Bamberg University, Bamberg, Germany. b Full Professor and Chair of Finance, Bamberg University, Bamberg, Germany. * Address correspondence to Tim A. Herberger, Bamberg University, Department of Finance, Kaerntenstrasse 7, D-96045 Bamberg, Germany, e-mail: tim-alexander.herberger@uni-bamberg.de.

  • Are Momentum Strategies Feasible in Intraday-Trading? Empirical Results from the German Stock Market

    Abstract Momentum trading strategies have been proved to be profitable in different asset classes and on various national capital markets in the past. However, there are some indications for eroding momentum profits. Based on the theory of gradual information distribution on capital markets and the technological progress of the last years, we suppose that the momentum effect transformed from a monthly basis to shorter time horizons. With regard to stocks that were listed in the German blue chip index DAX 30 between November 2013 and June 2014, this study is the first to examine, whether such strategies generate market adjusted excess returns on an intraday-trading basis. We analyze 16 momentum strategies, inspired by Jegadeesh/Titman´s (1993, 2001) original momentum strategy design (4x4), with ranking and holding periods of 15, 30, 45 or 60 minutes. For each stock, we analyze 15.131 price observations on a five minutes frequency. From the empirical results we conclude that the momentum strategy does not provide positive excess returns. However, we find indications for price reversals in intraday stock market returns for past loser stocks. Our results are robust on portfolio size (winning as well as loser portfolio) and the duration of a lag between the end of ranking period and beginning the holding period.

    JEL Classification: G10, G11, G14

    Key Words: Behavioral Finance, Intraday-Trading, Momentum Strategies

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    1 Introduction

    The momentum effect has been well documented and confirmed by numerous

    empirical studies that are based on various asset classes like different international

    equity markets1, bonds2, currencies3, commodities4 and real estate5 or use different

    indicators for the buying and selling signals6. In 1993 Jegadeesh/Titman show for the

    US stock market that significantly positive excess returns can be generated by applying

    momentum strategies (16 strategies with respective formation periods of 3, 6, 9 or 12

    months and with a subsequent holding period of 3, 6, 9, 12 months). Based on the

    ‘relative strength’-concept (Levy (1967)), those stocks are bought that generate the

    highest return during the ranking period (winner portfolio). At the same time, stocks

    showing the lowest return during the respective ranking period are sold short (loser

    portfolio). The total return of the strategy consists of the return of the winner portfolio

    plus the return of the looser portfolio (momentum portfolio). Consequently, a

    momentum strategy is a gross zero cost portfolio strategy. The authors conclude that

    stock prices are auto-correlated, contradicting to the neoclassic efficient market

    hypotheses (Fama/Fisher/Jensen/Roll (1969)), and that significant excess returns can

    be generated through exploitation of this existing auto-correlation.

    Although the success of momentum trading strategies is well documented for the

    past, there are indications for eroding momentum profits at least for the US-stock

    market since the early 90s of the last century (Hwang/Rubesam (2013)). Based on a

    gradual distribution model for new information on the market (Hong/Stein (1999);

    Hong/Stein (2000); Chan/Jegadeesh/Lakonishok (1996)), we suppose that the

    technological progress, combined with a more efficient information distribution among

    market participants, led to a transformation of the momentum effect from a monthly

    basis to shorter time-horizons. In this sense, our paper contributes the extant literature

    with an adaption of the original 4x4 framework of Jegadeesh/Titman (1993) based on

    1 See Jegadeesh/Titman (1993) for the US stock market and Rouwenhorst (1998) for further national stock markets in Europe; Chan/Hameed/Tong (2000) for different national stock market indices; Andreu/Swinkels/Tjong-A-Tjoe (2013) for various country and industry exchange traded funds. 2 See Jostova/Nikolova/Philipov/Stahel (2013). 3 See Menkhoff/Sarno/Schmeling/Schrimpf (2012). 4 See Miffre/Rallis (2007). 5 See Ro/Gallimore (2014) for real estate mutual funds; Beracha/Skiba (2011) for residential real estate. 6 See Bootra/Hur (2013) for 52week-high and 52week-low.

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    monthly stock returns, to an intraday momentum strategy scheme based on 5-minute

    stock returns. We analyse 16 momentum strategies with ranking and holding periods

    of 15, 30, 45 or 60 minutes. We provide robustness checks by applying different

    portfolio sizes for winner and loser portfolios and various skipping periods between the

    ends of the ranking periods and the beginnings of the holding periods in order to

    rebalance the portfolios and to avoid bid-ask-biases.

    Based on 15.131 test runs, the empirical results show that the momentum strategy

    does not provide excess returns in intraday-trading. However, we find indications for

    reversals in intraday stock market returns for past loser stocks. Our results are robust

    on portfolio size and the duration of the lag between the ends of the formation periods

    and the beginnings of the holding periods.

    The remainder of the paper is structured as follows: Section 2 gives a literature

    review, a description of our contribution and the derivation of our hypotheses. Section

    3 explains the data and methodology of our analysis. The results of our analysis are

    presented and discussed in section 4. Section 5 provides a summary.

    2 Literature Review and Contribution

    The success of momentum strategies has hardly been questioned in recent years, but

    there are still controversial opinions on the cause of the excess returns that contradict

    neoclassic finance. Based on the neoclassic theory, Lesmond/Schill/Zhou (2004)

    argue that the momentum effect is a result of risk or liquidity premiums as well as

    market frictions. They state that no significant excess returns can be generated through

    momentum strategies after transaction costs have been taken into account. In contrast,

    Korajczyk/Sadka (2004) conclude that the profits realized in former studies result only

    partly on the negligence of transaction costs and thus, this does not constitute a

    complete explanation for the amount of the drawn excess returns. Conrad/Kaul (1993)

    explain the profitability of the momentum strategies by a cross-sectional variation of

    the mean returns. In contrast to that, Moskowitz/Grinblatt (1999) point out that the

    momentum effect can only be found in few industries. Thus, significant excess returns

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    can hardly be attested if the data is adjusted for industry effects. According to Wu

    (2002) as well as Wang (2003) the differences in expected returns over a specific

    period of time are the reason for the profitability of the momentum strategy. However,

    Grundy/Martin (2001) as well as Karolyi/Kho (2004) show that industrial influences and

    differences in time can only partly account for the success of momentum strategies

    with regard to expected returns. Chordia/Shivaumar (2002) conclude that

    macroeconomic variables can predict the momentum effect and the resulting excess

    returns.

    Based on a Behavioral Finance approach, the momentum effect is a consequence of

    investor biases. The investor-sentiment-mod