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The Trend Is Your Friend: Momentum Investing

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Abstract

Momentum is defined as the tendency of securities with good (poor) past performance to overperform (underperform) in the future. It is one of the most pervasive anomalies ever discovered and evidenced across numerous asset classes. In this chapter, the authors reviewed diverse momentum techniques and their variations, presenting potential improvements: volatility scaling, timing the momentum crashes, time-series and intermediate versions of momentum, a trend range, and the 52-week high strategies. They provided theoretical explanations and surveyed rich empirical evidence of momentum profitability, testing three momentum-based strategies across 24 international equity markets.

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Notes

  1. 1.

    Antonacci (2015) provides an interesting survey on the early evidence on momentum.

  2. 2.

    Other popular books depicting famous momentum traders include Chestnutt (1961), Haller (1965), Soros (2003), Covel (2007, 2009), O’Neil (2009), and the “Market wizards” series (Schwager 1994, 2003, 2012a, b).

  3. 3.

    Later, in 1968, Levy expanded his thoughts to a full book on investing.

  4. 4.

    See, for industry portfolio, Pan et al. (2004), Moskowitz and Grinblatt (1999), Faber (2010), Chen et al. (2012), Andreu et al. (2013), Szakmary and Zhou (2015), Plessis and Hallerbach (2016); for equity indices, Balvers and Wu (2006), Bhojraj and Swaminathan (2006), Muller and Ward (2010), Asness et al. (1997), Chan et al. (2000), Vu (2012), Andreu et al. (2013), Evans and Schmitz (2015), Grobys (2015), Zaremba (2016d), Zaremba and Andreu Sánchez (2017), Zaremba and Umutlu (2018a, b), Guilmin (2015), or Zaremba and Shemer (2017).

  5. 5.

    See, for government bonds, Luu and Yu (2012), Asness et al. (2013), Duyvesteyn and Martens (2014), Hambusch et al. (2015), Zaremba and Czapkiewicz (2017a, b), and Zaremba and Schabek (2017); for corporate bonds: Gebhardt et al. (2005), Pospisil and Zhang (2010), Kim et al. (2012), Jostova et al. (2013), de Carvalho et al. (2014), Israel et al. (2016), Barth et al. (2017), van Zundert (2017), Lin et al. (2017), and Houweling and van Zundert (2017); for interest rates, Durham (2013); for currencies, Okunev and White (2000), Bianchi et al. (2005), Menkoff et al. (2011), Burnside et al. (2011), Pojarliev and Levich (2013), Kroencke et al. (2013), Amen (2013), Accominotti and Chambers (2014), Olszewski and Zhou (2014), Orlov (2015), Bae and Elkamhi (2015), Filippou et al. (2015), and Grobys et al. (2016); for commodities, Pirrong (2005), Miffre and Rallis (2007), Fuertes et al. (2010), Gorton et al. (2013), de Groot et al. (2014), Szymanowska et al. (2014), Fuertes et al. (2015), and Zaremba (2016); and for real estate and REITs, Hung and Glascock (2010), Beracha and Skiba (2011), Goebel et al. (2012), Ro and Gallimore (2013), Feng et al. (2014)., and Moss et al. (2015).

  6. 6.

    See, for factor portfolios, Zaremba and Shemer (2016a, c, e, and Ehsani (2017); for style indices, Chen and De Bondt (2004), Tibbs et al. (2008), Clare et al. (2010), and Chen et al. (2012).

  7. 7.

    See, for example, Wang and Kochard (2011), Kim (2012), Asness et al. (2013), Bhansali et al. (2015), Baz et al. (2015), and Cooper et al. (2017).

  8. 8.

    See, for example, Fama and Blume (1966), van Horne and Parker (1967, 1968), or Jensen and Benington (1970).

  9. 9.

    The noisy rational expectations model in its most original form does not fully allow for technical analysis, because Grossman and Stiglitz (1976, 1980) assume that uninformed investors have rational expectations about future prices. Nonetheless, this gap has been filled by subsequent variations of this model, for example, Hellwig (1982), Brown and Jennings (1989), and Blume et al. (1994).

  10. 10.

    This example is inspired by Hurst et al. (2013).

  11. 11.

    For further discussion on the anchoring effect and its implications for underreaction, see also Slovic and Lichtenstein (1971), Watson and Buede (1987), Reidpath and Diamond (1995), and Barberis et al. (1998).

  12. 12.

    For further essential references for the disposition effect, see Shefrin and Statman (1985), Weber and Camerer (1998), Frazzini (2006), and Barberis and Xiong (2009). Moreover, an interesting survey of theory and evidence is provided by Kaustia (2010).

  13. 13.

    There are many theoretical models of feedback trading, developed by, for example, Shiller (1984), de Long et al. (1990a, b), Cutler et al. (1990), Hong and Stein (1999), and Shleifer (2000). Empirical evidence on this phenomenon could be found in Shiller (1988), de Long et al. (1990b), De Bondt (1993), Nosfinger and Sias (1999), and Bange (2000).

  14. 14.

    Key studies regarding the confirmation bias include Lord et al. (1979), Forsythe et al. (1992), Pouget and Villeneuve (2012), and Bowden (2015). Moreover, further references regarding this phenomenon are in Rabin and Schrag (1999) and Pouget and Villeneuve (2008).

  15. 15.

    The representativeness heuristic was initially discussed in a series of papers authored by Kahneman and Tversky (Kahneman and Tversky 1972; Tversky and Kahneman 1971, 1974, 1982). The impact on stock market investors, which eventually leads to overreaction, was documented in the papers of Kaestner (2006), Frieder (2008), Alwathainani (2012), and Boussaidi (2013).

  16. 16.

    Evidence of the long-run underperformance is documented by, among others, De Bondt and Thaler (1985), Moskowitz et al. (2012), and Asness et al. (2013). We will also discuss this effect more in detail in further sections of this book.

  17. 17.

    The link between the size premium and the January effect was discussed by, for example, Easterday et al. (2009), Haug and Hirschey (2006), or Zhang and Jacobsen (2012).

  18. 18.

    Some bond strategies also use simpler measures to cope with the impact of influence, like sorting the bonds on change in yields-to-maturity or on return difference with a duration-matched benchmark bonds. A discussion and examination of bond momentum strategies could be found in following studies: for government bonds, Luu and Yu (2012), Asness et al. (2013), Duyvesteyn and Martens (2014), Hambusch et al. (2015), Zaremba and Czapkiewicz (2017a, b), and Zaremba and Schabek (2017); and for corporate bonds, Gebhardt et al. (2005), Pospisil and Zhang (2010), Kim et al. (2012), Jostova et al. (2013), de Carvalho et al. (2014), Israel et al. (2016), Barth et al. (2017), van Zundert (2017), Lin et al. (2017), and Houweling and van Zundert (2017).

  19. 19.

    Key references include , for size, Jegadeesh and Titman (1993), Hong et al. (2000), Zhang (2006); for age, Zhang (2006); for book-to-market ratio, Asness (1997), Daniel and Titman (1999), Sagi and Seasholes (2007); for credit rating, Avramov et al. (2007); for analysts coverage , Hong et al. (2000); for idiosyncratic risk, Zhang (2006), Jiang et al. (2005), analyst forecast dispersion (Zhang 2006), R2 (Hou et al. 2006); for mutual fund ownership, Chen et al. (2002).

  20. 20.

    Da et al. (2014) argue that it is not only important how the information is processed by the market but also how it is feed thereto, as momentum tends to be stronger among the companies with information arriving in small amounts.

  21. 21.

    See Stockopedia (2012).

  22. 22.

    See also Grobys (2016).

  23. 23.

    For momentum in equity indices, see also Zaremba (2016, 2017c).

  24. 24.

    Some alternative return-based improvements of the momentum strategy may include focusing on firms showing more extreme returns in the formation period (Bandarchuk and Hilscher 2013) or more consistent returns in the formation period (Grinblatt and Moskowitz 2004). Further investigations of the interactions of the 52-week high effect and momentum could be found in, for example, Bhootra and Hur (2013), Hao et al. (2016), and Lee and Piqueira (2017).

  25. 25.

    The time-series momentum could be also improved by applying some ideas similar to the traditional momentum, like volatility scaling (Dudler et al. 2014; Kim et al. 2016).

  26. 26.

    For evidence , see, for example, Baltas and Kosowski (2012a, b), Cheema et al. (2017). Georgopoulou and Wang (2016), Goyal and Jegadeesh (2017), Hurst et al. (2017), Maymin et al. (2014), and Zhou and Zhu (2013).

  27. 27.

    See, also, Zakamulin (2015b, 2016b).

  28. 28.

    The concepts of acceleration and so-called gamma factor had been discussed also earlier in Andersen et al. (2000).

  29. 29.

    For details, see Hanauer (2014), Teplova and Mikova (2015), and Chang et al. (2018).

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  1. Poznan University of Economics and Business, Poznan, Poland

    Adam Zaremba

  2. AlphaBeta, Tel Aviv, Israel

    Jacob “Koby” Shemer

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Zaremba, A., Shemer, J.“. (2018). The Trend Is Your Friend: Momentum Investing. In: Price-Based Investment Strategies. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-319-91530-2_2

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