McKinley Capital Price Momentum: Incorporating Under-Appreciated Information

May 16, 2017

Robert A. Gillam, CFA Chief Investment Officer McKinley Capital Management, LLC
Gregory S. Samorajski, CFA Director of Investments McKinley Capital Management, LLC

Executive Summary

Momentum, as used in investment management, is the observed phenomenon that the prices of financial instruments appear to follow trends. Momentum is used to compute investment signals. Two practitioner-oriented articles have been recently distributed. Jim McKee (“McKee”), with the Callan Institute, published a short article explaining when and why momentum investing works and how to manage the risk of large losses1.  Christopher Geczy and Mikhail Samonov wrote an article regarding the returns to momentum investing in the U.S. equity markets from 1801 to 20122.  Among other findings, the article reports the empirical duration of positive momentum signals in the U.S. equity markets, over a period of approximately five months, and quantifies the risk of momentum investing around major market inflection points. McKinley Capital Management, LLC (“McKinley Capital” or “the firm”), is a prominent registered investment advisory firm that uses price momentum and earnings acceleration signals to manage global equity investments. The firm is one of the concept leaders in the application of momentum signals in global investing. In this paper, the firm summarizes recent articles, adds its own research insights, and analyzes the effectiveness and risks of momentum investing in the global developed equity markets for the past 20 years.

Momentum Investing: What is it, Why Might it Work, and What are the Risks?

Momentum investors seek to exploit the possibility that, for a period of time, security prices seem to follow trends. The idea is that investors buy or hold equities that have been the best performers during the prior six to twelve months, and short-sell or avoid equities that have underperformed in the same time period. In his article, McKee explains his opinion of the theory3.  As a behavioral finance phenomenon, when new information arrives into the market, investors initially underreact. Thus, good (bad) news results in somewhat higher (lower) prices; which, never-the-less, remain below (above) those implied by the news. This effect creates the possibility for continued price change as the new information becomes more widely understood and incorporated. At some point, other behavioral shortcomings, such as confirmation bias, support the continuation of the trend until the market price represents over-reaction to the news. The final phase occurs when overreaction results in trend reversal. The Geczy and Samonov analysis indicates that in the U.S. equity markets, positive performance, based on momentum signals, has persisted for between five and eight months before systematically reversing4.

McKee explains that when the trend reverses, the correction can be sudden and large. This leads to the risk that momentum investing can be profitable in the long run, but is subject to occasional large losses, even when employing a long-short equity momentum strategy. These reversals often occur at major market inflection points5; the time period March to May 2009 comes to mind. McKee recommends diversification across markets, and the use of multiple factors and strategies to reduce risk6.  Indeed, commodity trading advisors and other global macro strategists often diversify their trend-following positions across many markets – stock indexes, bonds, currencies, metals, agriculture, energy, etc. The hope is that not all markets inflect at the same time. Similarly, within the equity sector, institutional investors often employ managers when taken together incorporate diverse investment styles and factors.

Are there additional tactics available to managers who specialize in equity momentum investing, and to investors who seek the best managers in each style? Geczy and Samonov explain the challenge with market reversals7.  Momentum calculations can be decomposed into stock specific and systematic market-based effects. Because of the market effect, it is not surprising to learn that following a prolonged up market, on average, the best raw momentum scores are calculated for high risk, high beta stocks. Similarly, low risk, low beta stocks, on average, are assigned the best scores following a prolonged down market. This “market-effect” is what makes inflection points treacherous. For example, the authors show that in the U.S., the beta of an unadjusted market neutral momentum portfolio has varied between .2 and .8 following an “up” market duration of between two to three years. Following similar duration “down” markets, unadjusted  market neutral long-short portfolio betas have varied between -.4 and -1.08.  When a down equity market reverses sharply, a low risk, negative beta portfolio is likely to underperform. The authors demonstrate that the time of highest risk for U.S. equity momentum investing is following a down market of two to two and one-half years9.

The McKinley Capital Approach to Momentum Investing

McKinley Capital specializes in global growth equity investing utilizing its expertise and understanding of the benefits of price momentum and earnings acceleration. The firm has used momentum as a component of its long-only investment process since its founding in 1990. However, the firm’s specialized expertise in price momentum might be best expressed through momentum exposure implicit in its long/short alternative investment strategies. This exposure is derived from holding long positive momentum global equities and short selling low momentum equities. McKinley Capital does not currently manage a stand-alone, long/short global momentum strategy. Although, the firm believes it could create such a product. If unleveraged, McKinley Capital believes such a strategy could generate high single digit returns, below 8% volatility and low correlation with traditional asset classes10. In researching and managing its dynamic momentum component, McKinley Capital has had the opportunity to confirm and extend many of the U.S. results reported by Geczy and Samonov, into the global equity space.

Following are summary findings. Momentum as a risk factor has been rewarded in the global developed universe over the past 20 years. With regard to the momentum signal, there have been gains to diversification across multiple global developed markets. McKinley Capital concurs with McKee’s and Geczy and Samonov’s risk analysis. For the same reasons as in the U.S., global momentum investing is likely to be volatile at major market inflection points. As justified in the following chart, the firm seeks to limit any long-short risk mismatch of its portfolio regardless of the duration of the up or down market state. It does this by adjusting the long/short investment ratio as the unadjusted risk of each side changes. Finally, McKinley Capital incorporates a process to ensure that long and short exposure is reduced prior to the possibility of a major inflection point. Research results follow.

The firm is often asked why, in its early years as a U.S. based equity manager, it chose momentum as one of its primary investment factors. The answer is based on the observation that, long-term, momentum has been the factor most indicative of excess returns in the U.S. markets. Table 1 shows the Fama  and French returns to momentum, value, and small size tilted portfolios in the U.S. from 1927 to 2017. Of the three main Fama and French factors, momentum has been the best on an absolute and risk adjusted basis. There is no comparable long-term non-U.S. data. The Fama and French database begins in 1990. However, the  limited Fama and French data available seems roughly consistent.

Table 1: Fama and French U.S. Factor Returns
January 1927 – March 2017

Annualized Return
(Winners Minus Losers)
Annualized Standard Deviation
(Winners Minus Losers)
Return / Risk
Momentum 6.53% 16.38% 0.40
Value 3.55% 14.00% 0.25
Size 3.04% 17.26% 0.18

Source: Kenneth R. French website, Data retreved May 2017. Factor winners minus losers (WML) returns are as follows: 1) Momentum – Top 30% ranked by momentum minus bottom 30% ranked by momentum segmented by market capitalization, 2) Value – Top 30% ranked by book to market minus bottom 30% ranked book to market, and 3) Size – Top 30% ranked by market capitalization minus bottom 30% ranked by market capitalization.

Figure 1: Simple Momentum Results: Equally Weighted Average Return and Volatility (Simulation) Jan 1997 - Nov 2016

20 Years of Global Momentum Results

To test the effectiveness of momentum based global investing, the firm collected almost 20 years (12/31/97 – 11/30/2016) of monthly stock returns in USD across eight global developed regions – U.S., Canada, U.K, Euro Europe, Non-Euro Europe, Asia Ex-Japan (developed only), Japan, and Australia/New Zealand. Every month, the firm grouped each stock in each region into quintiles based on a simple momentum score, and measured the equally weighted average return difference between the top and bottom quintile stocks (W-L) for the subsequent month11. The results are portrayed in Figure 1. In seven out of eight regions, the W-L simulated portfolio (the “portfolio”) generated positive annualized returns. The returns ranged from a high of 14.60% in Non-Euro Europe to a low of -0.1% in Asia ex-Japan (developed only). These results provide evidence that momentum, as a compensated risk factor, is not limited to the U.S. In fact, with an annualized return of 4.20%, the U.S. ranked only 6th out of the 8 global regions12. These results are of the same order of magnitude as the long term U.S. results reported by Geczy and Samonov, and Fama and French. From 1801 to 2012, the Geczy and Samonov U.S. W-L U.S. momentum portfolios showed an annualized return of 3.8%. As indicated in Table 1, from January 1927 to March 2017, the Fama and French U.S. W-L U.S. momentum portfolios showed an annualized return of 6.5%.

This research indicates that stand-alone dollar neutral investing can be risky. The standard deviation of W-L returns varied from a low of 20.47% annualized in Australia/New Zealand to a high of 31.90% annualized in Asia Ex-Japan (developed only). In the center were Euro Europe at 23.80% annualized and the U.K. at 24.73% annualized. McKee’s recommendation to diversify helped manage the risk. The monthly standard deviation of a combined equal region weighted W-L portfolio was 19.02% annualized. The equal region weighted portfolio annualized return was 10.40%. The reason diversification across regions works is that momentum based returns have been lowly correlated across global developed countries. Table 2 reports data collected by McKinley Capital in an earlier study. The research suggests other ways in addition to diversification that may reduce risk. As discussed earlier, dollar neutral W-L momentum portfolios can have unequal long and short side risk – whether measured by total risk or by beta. This is due to the “market–effect.” Following periods of strong up (down) markets, the higher (lower) total risk, higher (lower) beta securities will be measured with the higher (lower) momentum scores, all other things being equal. It is not clear this market direction based momentum risk is compensated.

Table 2: Traditional Long/Short Momentum (Winners Minus Losers: WML) Monthly Return Correlation Matrix (Simulation),
Mar 1991 – Dec 2014

U.S. Canada U.K. Germany France Japan Hong Kong Australia
U.S. 0.58 0.67 0.46 0.32 0.44 0.28 0.42
Canada 0.58 0.44 0.31 0.30 0.28 0.26 0.37
U.K. 0.67 0.44 0.55 0.47 0.38 0.26 0.50
Germany 0.46 0.31 0.55 0.37 0.26 0.29 0.37
France 0.32 0.30 0.47 0.37 0.19 0.16 0.29
Japan 0.44 0.28 0.38 0.26 0.19 0.14 0.17
Hong Kong 0.28 0.26 0.26 0.29 0.16 0.14 0.29
Australia 0.42 0.37 0.50 0.37 0.29 0.17 0.29

Source: FactSet, 12/23/16. Analysis by McKinley Capital Management, LLC, 12/28/16. Data is simulated not actual. Past performance is not indicative of future returns. Information is believed to be reliable but accuracy cannot be guaranteed.

To address this question, McKinley Capital measured the modeled13  total risk and beta for each long and short side portfolio for each region and the equal weighted combination14, and computed the ratio. For example, in the U.S., the ratio of long to short modeled total risk averaged .97, but varied from a high of 1.84 to a low of .52. The comparable ratio numbers for U.S. W-L modeled beta were .99 average, 2.44 high, and .49 low. Other regions showed similar dispersion. The firm formed equal risk portfolios by using a long side of 100%, but adjusting the percentage weight of the short portfolio by the inverse of the risk ratio. For example, if the risk ratio was .9 (shorts riskier than longs) the short side weight would be 90%. The results are shown in Table 3. For each region, the standard deviation was reduced using equal risk weighting within each region. At the aggregate level, the monthly standard deviation of the eight region W-L portfolio was reduced from 5.49% to 4.45% using total risk weighting, and to 4.52% using beta weighting15. The average monthly return results varied by region. At the aggregate level, the average monthly return for the eight region total risk weighted portfolio was .93%, and .94% for the beta weighted portfolio. Due to the miniscule reduction in return, the firm concludes that market direction based momentum risk has not been significantly compensated in the global developed equity markets. McKinley Capital offers equal risk weighted W-L portfolio construction for its dynamic momentum strategy.

Table 3: Simple Momentum Results – Equally Risk Weighted Return and Volatility (Simulation)
Jan 1997 – Nov 2016

Mean Monthly
Monthly Return St.
Mean Monthly
Return(Beta Risk
Monthly Return
St. Dev. (Beta Risk
Mean Monthly
Return (Total
Return Risk
Monthly Return St.
Dev. (Total Return
Risk Weighted)
U.S. 0.66 7.75 0.61 6.51 0.62 6.35
U.K. 1.13 7.14 0.97 6.18 0.98 6.12
Canada 1.47 8.06 1.30 6.87 1.25 6.90
Euro – Europe 1.22 6.87 1.17 5.34 1.16 5.17
Japan 1.32 5.96 1.24 4.96 1.14 4.66
Asia Ex-Japan 0.24 6.60 0.29 6.09 0.14 6.13
Australia/New Zealand 0.49 9.21 0.57 8.38 0.76 8.69
Equal Weighted Global 0.99 5.49 0.94 4.52 0.93 4.45

Source: FactSet, 12/23/16. Analysis by McKinley Capital Management, LLC, 12/28/16. Data is simulated not actual. Past performance is not indicative of future returns. Information is believed to be reliable but accuracy cannot be guaranteed.

While risk adjusted long/short positioning is expected to mitigate risk, the firm notes that major market inflection points represent additional risk to momentum strategies. As suggested by Geczy and Samonov, the risk is highest when the market experiences a V-shaped recovery from a sustained bear market. Table 4 lists some of the worst months for momentum in the U.S., most having occurred following recoveries from sustained bear markets.

Table 4: Worst Momentum Months Driven by Outperformance of Prior Loser Stocks During Junk Rallies (Simulation)
Worst Months for Momentum, U.S. 1927-2014

Month WML
Return (%)
Return (%)
Return (%)
Return (%)
Prior 6m
Return (%)
Prior 24m
Return (%)
Prior 12m
Volatility (%)
Aug 1932 -77.0 17.0 94.0 37.1 -18.3 -67.6 56.9
Jul 1932 -60.1 14.2 74.3 33.9 -39.8 -74.7 38.5
Apr 2009 -45.9 -0.1 45.8 10.2 -30.1 -40.6 26.4
Sep 1939 -45.2 7.9 53.1 16.9 -8.6 -21.6 23.3
Jan 2001 -42.0 -6.4 35.6 3.7 -10.6 10.6 18.8
Apr 1933 -41.9 28.9 70.8 39.0 -24.3 -58.9 63.9
Mar 2009 -39.3 4.8 44.1 9.0 -41.7 -44.9 23.0
Jun 1938 -33.2 10.5 43.7 23.9 -14.6 -27.9 35.6
Jun 1931 -29.3 8.1 37.4 14.0 -20.1 -47.5 29.4
May 1933 -26.9 19.3 46.2 21.5 21.1 -36.6 71.1
Aug 2009 -24.8 0.2 25.0 3.3 22.9 -27.3 30.6
Nov 2002 -20.4 2.2 22.6 6.1 -17.6 -36.2 20.5
Jan 1975 -19.7 11.4 31.2 14.2 -18.0 -41.7 23.9
Jan 1974 -19.3 -6.2 13.0 0.5 -4.3 -5.7 16.5
May 2009 -19.1 2.3 21.4 5.2 -7.0 -37.0 28.7
Worst 15 Avg -36.3 7.6 43.9 15.9 -14.1 -37.2 33.8
All Mths Avg 1.2 1.5 0.3 0.9 5.7 24.9 16.2

Source: Kenneth R. French Data Library, 2/26/15. Analysis by McKinley Capital Management, LLC, 2/26/15. Data is simulated not actual. Past performance is not indicative of future returns. Information is believed
to be reliable but accuracy cannot be guaranteed.

Figure 2: Risk Weighted Momentum Results with Market State Adjustments (Simulation)

While it is impossible to forecast the imminent arrival of a major turning point, it is possible to observe conditions which set the stage for a possible major reversal. For example, only after the market has declined significantly is it possible for a strong recovery to occur. To address this possibility, we test a simple market state rule based on the research of Geczy and Samonov. When the underlying regional market has declined over the prior 24 months, we define the market state as negative, and would exit all long and short positions in that region16.  The results are reported in Figure 2. For the eight region market state adjusted portfolio, the annualized return improves to 14.90% with a standard deviation of 15.20% annualized. The comparable numbers for the unadjusted portfolio were an annualized return of 10.40% and a standard deviation of 19.02% annualized. The total return risk weighted and market state adjusted portfolio had an annualized return of 13.30% and a standard deviation 13.40% annualized. This compares to an annualized return of 10.40% and a standard deviation of 15.30% annualized for the total return risk adjusted portfolio without the market state adjustment. Whichever version is selected, it appears that even a simple market state rule has the potential to increase return and reduce the risk of a global developed momentum strategy.


In this paper, the firm reviewed the research on the benefits and risks of momentum investing in the U.S. markets historically. The firm extended this research using 20 years of data covering all of the major global developed markets. McKinley Capital concluded that while there appears to be validity to the use of the momentum factor in global investing, there is also risk. In this paper, the firm reported the results of simple risk reduction techniques, and found efficacy to diversification across global regions, equal risk weighting and market state considerations. McKinley Capital would be pleased to provide you with the
information needed to understand the benefits and risks of the firm’s Dynamic Momentum approach.

1Jim McKee, “Momentum The Trend is Your Friend,” Callan Insitute Research, October, 2016.
2 Christopher C. Geczy and Mikhail Samonov, “Two Centuiries of Price-Return Momentum, Financial Analysts Journal, Vol 72, No. 5, September/October 2016. 32-56.
3 McKee, “Momentum,” 3.
4Geczy and Samonov, “Momentum,” 38-40.
5McKee, “Momentum,” 4.
6Ibid. 3, 5.
7Geczy and Samonov, “Momentum,” 43-50.
8Ibid, 47.
9Ibid, 49.
10Please contact your McKinley Capital account representative to receive detailed information and performance results for the firm’s alternative investment strategies.
11The momentum rank, PM71, is based on the rank of the unadjusted raw return of each security in a region over the past six months lagged by one month. For example, the rank on October 31st is based on the ranked raw returns of the region’s stocks from March 31st to September 30th. The one month lag accounts for the well-known short-term momentum reversal effect. See for example, Geczy and Samonov, “Momentum,” 35.
The offsetting effects of transactions costs and short stock rebates were ignored.
12Note that Geczy and Samonov’s grouping procedure was similar but not identical to the McKinley Capital method. Geczy and Samonov used a 12 lag 2 calculation. See, for example, Geczy and Samonov, “Momentum,” 35.
13Using the Axioma global fundamental model.
14For simplicity, the modeled beta and total risk of each portfolio was estimated as the average of modeled beta and total risk for each individual stock.
15McKinley Capital incorporates total risk weighting both within and across countries to manage risk in its Dynamic Momentum strategy.
16For other market state based strategies and detailed momentum investing references see “Global Momentum Engineering a Dynamic Exposure, McKinley Capital Management, LLC, January 2011.


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