Quantitative Momentum. Vogel Jack R.

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Originally referred to as relative strength, before academics developed a more jargon-like term, cross-sectional momentum is a measure of a stock's performance, relative to other stocks.15

      A simple example will illustrate the difference. Consider a hypothetical scenario where we have two stocks in our universe: Apple and Google. Twelve months ago, Apple was $25 per share and Google was also $25 per share. Today, Apple is $100 per share and Google is $50 per share.

      Next, we examine a simple time-series momentum rule and a simple cross-sectional momentum rule.

      The time-series rule will buy a stock that has positive performance over the past 12 months, and will sell a stock if the stock has negative performance. Here is how our time-series momentum-trading rule would treat this scenario:

      • Time-series momentum: Long Apple and long Google because both stocks have strong absolute momentum.

      Our cross-sectional rule will buy a stock if the stock's past performance over the past 12 months is relatively stronger than the past performance of other stocks in the universe (and will sell a stock if it has poor relative performance to other stocks). Here is how our cross-sectional momentum-trading rule would treat this scenario:

      • Cross-sectional momentum: Long Apple and short Google because Apple is relatively stronger performing than Google.

      Note that even though both stocks have increased in price (we are long both from a time-series momentum perspective), Apple's price has gone up much more than Google's price; thus, Apple has stronger momentum in the cross-section (suggesting long Apple and short Google from a cross-sectional momentum perspective).

      One could use elements of both types of momentum to develop a momentum strategy. For example, we could consider both momentum elements and invest based on both the time series rule and the cross-sectional rules. Using our example above, we would go long Apple, because the time-series rule says buy and the cross-sectional rule also says buy, but we might take no position in Google because one of the rules (i.e., cross-sectional momentum) says to sell.16

      As outlined above, the various forms of momentum can be used to develop a stock selection methodology. We want to highlight that time-series and cross-sectional momentum are often used in a market-timing or asset-class selection context. Let us be clear: This book is not focused on market-timing or asset class selection – we are trying to understand how different elements of momentum might be useful in the context of individual stock selection. This book is a stock picking book, not an asset allocation book.

SUMMARY

      In this chapter, we outline the long-running debate between technical and fundamental investors. Many readers are certainly familiar with both faiths, and there are certainly zealots to be found in each camp. In many circumstances the debate between technical and fundamental investing tactics isn't a debate – it is a yelling match. We want to stop the yelling and start the research. To circumvent the yelling match, in the next chapter we will describe the sustainable active investing framework. This framework will help us better understand why certain strategies work and why others do not, independent of the dogma. Through this lens we can form testable hypotheses and have a constructive discussion. Our framework is decidedly not perfect, but we do our best to contextualize the debate. Because, let's be honest, the mission of active investing is not to argue about which investment philosophy is better – who cares – we just want to beat the market over the long term! Also, to reiterate, if you are an advanced practitioner looking to learn about the details of our proposed stock-selection momentum strategy, feel free to skip to Chapter 5.

CHAPTER 2

      Why Can Active Investment Strategies Work?

      “The worst thing I can be is the same as everybody else.”

– Attributed to Arnold Schwarzenegger

      The debate over active investing versus passive investing is akin to other classic conflicts, such as Philadelphia Eagles versus Dallas Cowboys or Coke versus Pepsi. In short, once our preference for one style over the other is established, it often becomes a proven fact or incontrovertible reality in our minds. Psychology research describes the notion of “confirmation bias,” in which people prefer evidence that supports their earlier conclusions, and ignore disconfirming evidence.

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      1

      Teresa Corzo, Margarita Prat, and Esther Vaquero, “Behavioral Finance In Joseph de la Vega's Confusion de Confusiones,” The Journal of Behavioral Finance 15 (2014): 341–350.

      2

      Joseph de la Vega, Confusion de Confusiones. An English translation of Confusion de Confusiones, 1688, is available via babel.hathitrust.org/cgi/pt?id=uc

1

Teresa Corzo, Margarita Prat, and Esther Vaquero, “Behavioral Finance In Joseph de la Vega's Confusion de Confusiones,” The Journal of Behavioral Finance 15 (2014): 341–350.

2

Joseph de la Vega, Confusion de Confusiones. An English translation of Confusion de Confusiones, 1688, is available via babel.hathitrust.org/cgi/pt?id=uc1.32106019504239, accessed 2/15/2015.

3

Attributed to Jared Hullick.

4

De la Vega.

5

www.ndl.go.jp/scenery/kansai/e/column/markets_in_osaka.html, accessed February 15, 2015.

6

Jasmina Hasanhodzic, “Technical Analysis: Neural network based pattern recognition of technical trading indicators, statistical evaluation of their predictive value and a historical overview of the field,” MIT Master's Thesis (1979). Accessible at hdl.handle.net/1721.1/28725.

7

Steve Nison, Japanese Candlestick Charting Techniques (New York: Prentice Hall Press, 2001).

8

Edwin Lefevre and Roger Lowenstein, Reminiscences of a Stock Operator (Hoboken, NJ: John Wiley & Sons, 2006).

9

Benjamin Graham, The Intelligent Investor (New York: Harper, 1949).

10

Burt Malkiel, A Random Walk Down Wall Street (New York: W.

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<p>15</p>

See Andreas Clenow, “Stocks on the Move: Beating the Market with Hedge Fund Momentum Strategies,” self-published, 2015, for a practitioner perspective, and see Narasimhan Jegadeesh and Sheridan Titman, “Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency,” The Journal of Finance 48 (1993): 65–91, for an academic discussion.

<p>16</p>

See Antonacci's Dual Momentum book for a discussion of dual momentum in an asset allocation context, which is different than our context of individual stock selection. It conveys the idea of using both types of momentum in an investment system.