Book Review of Quantitative Momentum
I have been looking forward to Wes Gray and Jack Vogel's new book,
Quantitative Momentum
.
It is the only book besides my own
Dual Momentum
that relies on academic research to develop systematic momentum strategies. My book uses a macro approach of applying momentum to indices and asset classes. Wes and Jack (W&J) take a more common approach and apply momentum to individual stocks.
W&J begin their book with an excellent question. Since there is ample research showing momentum to be a superior investment approach over the past 200 years, why isn’t everyone using it?
W&J do good job explaining the behavioral biases that keep many investors away from momentum. W&J also discuss marketplace constraints like advisor career risk when momentum underperforms its benchmark.
But these biases and constraints are not undesirable if one becomes a momentum investor. They keep momentum from being over exploited.
In Chapter 1 W&J give a short history of trend based versus fundamental analysis based investing. They show that both approaches can work.
In Chapter 2 W&J discuss irrational-noise traders who can dislocate prices from their fundamental values and keep them dislocated for some time. In the case of value, investors overreact in the short-run to bad news. In the case of momentum, investors under react to good news.
Investment managers are hired to exploit long-run profit opportunities, but their performance is judged by investors looking at short-term results. Advisors who continue to focus on longer-term opportunities, like value or momentum, may then get fired. So anomalies like momentum do not get arbitraged away. Mispricing can persist, sometimes for long periods.
In one of the key points of the book, W&J discuss the importance of sustainable investors as well as sustainable alpha. Gregg Fisher once said, “We don’t have people with investment problems. We have investments with people problems.” Investors often lack the requisite patience to stay with their chosen strategies during periods of benchmark underperformance.
To prepare investors for those difficult times, W&J highlight the risks associated with value and momentum investing. They point to Julian Robertson’s Tiger Funds. These funds lost almost all their clients by sticking to their value model in the late 1990s. Value underperformed the market in 5 out of 6 years then, sometimes by double digits. W&J made this surprising statement, “True value investing is almost impossible.”
What can investors do about this? W&J point out that momentum is largely uncorrelated with value. This means an investment in momentum can make value investing more tolerable. Investors should keep in mind though that momentum and value are largely uncorrelated only when their market risks are hedged. As long-only strategies, momentum and value are correlated to the market and to each other. All can simultaneously experience large bear market losses.
There is another reason why non-correlation may not be so important. As I show in my recent blog post, “ Factor Investing: Buyer Beware ,” value investing in actual practice has not shown any significant advantage over the market. If investors have no reason to hold value stocks, momentum loses some of its attractiveness as a diversification strategy.
In Chapter 3 W&J give a brief history of stock market momentum and the important psychological challenges of momentum investing. W&J make the point that value and momentum are similar since both are driven by short-term investor pessimism. With value, pessimism is because of poor fundamentals. With momentum, pessimism is about performance continuation.
W&J reveal that momentum, like value, can underperform over long periods. They point out a 5-year stretch when momentum underperformed the broad market by 15%. This could be challenging to any investor.
In Chapter 4 W&J show that a 50/50 allocation to value and momentum can reduce the tracking error of separate value and momentum portfolios during extended periods of relative poor performance. What is also worth noting and may be of some concern is the decline over time of both value and momentum premia.
In Chapter 5 W&J show momentum as an intermediate term anomaly. Stocks exhibit a strong reversal pattern in returns when performance is measured over a short period of 1 month or less. There is also mean reversion of returns on a long-term basis of 3 to 5-years.
Stock momentum works best using an intermediate term 3 to 12-month look back period. W&J use 12-months for quantitative momentum and skip the most recent month because of mean reversion.
W&J show in Table 5.5 that frequently rebalanced, concentrated momentum portfolios perform best. Ideal portfolios hold only 50 stocks and get rebalanced monthly.
W&J point out that concentrated portfolio/higher rebalance frequency is not a good approach for large asset managers with billions to invest because of scalability issues.
Stock momentum is a high turnover strategy, and many momentum stocks are volatile with wide bid-ask spreads. There is bound to be some price impact from trading momentum stocks. This is especially true with frequently balanced, concentrated momentum portfolios.
Everyone now knows the top-ranked momentum stocks. In fact, Alpha Architect shows the top 100 momentum stocks on their website each month to anyone who registers there. So all investors, not just multi-billion-dollar asset managers, may experience adverse price impact from trading the same momentum stocks that everyone else does.
Transaction costs can be a similar problem. W&J mention a paper called " The Illusionary Nature of Momentum Profits " by Lesmond, Schill, and Zhou (2002) published in the Journal of Financial Economics. Lesmond et al. conclude that after transaction costs, momentum profits are largely illusionary. W&J also mention research by Korajczyk and Sadka (2004) showing that stock momentum has a limited capacity of only about $5 billion.
Offsetting these arguments, W&J present the findings of Frazzini, Israel, and Moskowitz (2014) of AQR. Frazzini et al. argue that momentum trading costs are manageable based on AQR’s own proprietary transaction data from 1998 through 2011.
But the amount of capital in momentum strategies is higher now. In a more recent paper, Fisher, Shah, and Titman (2015) use observed bid-ask spreads from 2000 through 2013. They report, “Our estimates of trading costs are generally much larger than those reported in Frazzini, Israel and Moskowitz (2012), and somewhat smaller than those described in Lesmond, Schill and Zhou (2004) and Korajczyk and Sadka (2004).” Research by Jason Hsu PhD, co-founder of Research Affiliates, also supports the higher transaction cost conclusions of Fisher et al. and Lesmond et al.
Scalability and transaction costs are reasons why we prefer to use momentum with indices and asset classes rather than with individual stocks. Another reason is that according to
Geczy and Samonov
(2015), momentum applied to stock indices outperforms momentum applied to stocks even before transaction costs.
Chapter 6 is where W&J explain path dependency is and why it matters. They cite research by Da, Gurun, and Waracha (2014) showing that smooth and steady past performance is preferable to jumpy performance. The underlying logic is that investors underreact to continuous information. Investors should therefore prefer momentum accompanied by steady price appreciation rather than discreet price jumps.
To implement this idea, W&J advocate double sorting stocks on their 12-month momentum and their percentage of positive daily returns over the past 252 trading days. What they call “high-quality momentum" are top decile momentum stocks with the largest percentage of positive daily returns. Results are from 1927 through 2014, and transaction costs are not included.
The improvement in high-quality over generic momentum looks good. But a possible warning sign is W&J’s statement at the beginning of Chapter 6: “For over a year, we examined every respectable piece on momentum stock selection strategies we could find…”
Diligent data mining increases the odds that favorable results may be due to chance. Say you have different studies each showing no significance with a 95% confidence level of being correct. If you examine 20 or more of these studies, there is a good chance that one of them will be look significant even though the chance of that being correct is still only 5%. The classic green jelly bean example should make this clear.
Source: http://hvst.co/2ezBmqt
In Chapter 7 W&J attempt to further enhance momentum by adding seasonality. In the turn-of-the-year or January effect, investors engage in year-end tax loss selling. They hold on to their strongest stocks and may buy more of these as replacements for the stocks they sell.
Window dressing to make their quarter-end portfolios look more attractive may also cause investment professionals to sell their losers and buy more winners before the end of the quarter. To take advantage of these seasonal tendencies, W&J advocate rebalancing their momentum portfolios at the end of February, May, August and November. They say this may help capture higher momentum profits during the months following the end of each calendar quarter.
Here are the results from incorporating seasonality as “smart rebalancing.”
There is little risk-adjusted improvement over agnostic (generic) momentum as seen from the increase of only .01 in the Sharpe and Sortino ratios. But since portfolios are rebalanced quarterly anyway, there should be no harm in picking non-calendar ending quarters for doing so.
In Chapter 8 W&J suggest that readers address the trading cost issue by comparing the analysis presented in Lesmond et al. and Frazzini et al. They do not mention here the more recent studies by Fisher et al. and Hsu that I discuss above.
W&J then do an in-depth analysis of “quantitative momentum” with respect to reward, risk, and robustness. They finish the chapter by making the point that momentum is sustainable because investors will continue to have behavioral biases. Investors are short-sighted performance chasers. This should also keep them from overexploiting the anomaly.
In the words of W&J, “… strategies like value and momentum presumably will continue to work because they sometimes fail spectacularly relative to passive benchmarks.” This may not be good news for those who at that time own momentum or value stocks. But W&J offer these words of encouragement. “ The ability to stay disciplined to a process is arguably the most important aspect of being a successful investor ” (emphasis added).
In Chapter 9 W&J show a combined 50/50 allocation to an equal weight, quarterly rebalanced momentum and value portfolio from 1974 through 2014.
The combined portfolio return is higher than that of momentum or value on their own. The combined portfolio also has less tracking error than either momentum or value vis-a-vis the broad market. Combining value and momentum shortens both the length and depth of benchmark underperformance.
As a final tweak to their approach, W&J show a trend following overlay applied to the combined portfolio. If a 12-month moving average of the S&P 500 index is greater than zero, they hold the combined portfolio. If the moving average is less than zero, they hold Treasury bills. Using this trend filter, the worst drawdown of the combined approach goes from -60.2% to -26.2%. But investors give up 1.5% in compound annual return, and there is an increase in tracking error.
My research shows that trend-following is more effective when applied to stock indices rather than to portfolios of individual value or momentum stocks. The reason for this has to do with volatility. The standard deviation of W&J’s quantitative momentum and combined portfolios are 25.6% and 21.4%. The standard deviation of the S&P 500 index is 15.5%. Higher volatility means you give up more profit before you can exit or re-enter stocks when using a trend following filter.
W&J finish the book by again referring to relative performance risk. One cannot stress enough that myopic investors give up potentially superior results when they become nervous or impatient and abandon their strategies.
In an Appendix, W&J examine some possible enhancements to momentum. These include earnings momentum, proximity to 52-week highs, stop losses, and absolute strength. Although W&J use the terms interchangeably here, you should not confuse absolute strength with absolute momentum. Otherwise, their analysis here is first rate. I would like to see W&J apply the same degree of analytic rigor to all the strategies featured on their Alpha Architect blog .
I remain skeptical about momentum applied to stock portfolios. Macro momentum applied to stock indices is a simpler approach that shows the same high potential returns as “quantitative momentum.” Macro momentum with broad-based indices has substantially lower transaction costs and no scalability issues. It also responds better to trend-following.
But I still recommend Quantitative Momentum to momentum investors for the following reasons:
1) Its emphasis on sustainable investors who can keep the big picture in mind and not be swayed by short-term performance
2) Its review of momentum principles and behavioral biases
3) Its rigorous research in the book’s Appendix
W&J begin their book with an excellent question. Since there is ample research showing momentum to be a superior investment approach over the past 200 years, why isn’t everyone using it?
W&J do good job explaining the behavioral biases that keep many investors away from momentum. W&J also discuss marketplace constraints like advisor career risk when momentum underperforms its benchmark.
But these biases and constraints are not undesirable if one becomes a momentum investor. They keep momentum from being over exploited.
In Chapter 1 W&J give a short history of trend based versus fundamental analysis based investing. They show that both approaches can work.
In Chapter 2 W&J discuss irrational-noise traders who can dislocate prices from their fundamental values and keep them dislocated for some time. In the case of value, investors overreact in the short-run to bad news. In the case of momentum, investors under react to good news.
Investment managers are hired to exploit long-run profit opportunities, but their performance is judged by investors looking at short-term results. Advisors who continue to focus on longer-term opportunities, like value or momentum, may then get fired. So anomalies like momentum do not get arbitraged away. Mispricing can persist, sometimes for long periods.
In one of the key points of the book, W&J discuss the importance of sustainable investors as well as sustainable alpha. Gregg Fisher once said, “We don’t have people with investment problems. We have investments with people problems.” Investors often lack the requisite patience to stay with their chosen strategies during periods of benchmark underperformance.
To prepare investors for those difficult times, W&J highlight the risks associated with value and momentum investing. They point to Julian Robertson’s Tiger Funds. These funds lost almost all their clients by sticking to their value model in the late 1990s. Value underperformed the market in 5 out of 6 years then, sometimes by double digits. W&J made this surprising statement, “True value investing is almost impossible.”
What can investors do about this? W&J point out that momentum is largely uncorrelated with value. This means an investment in momentum can make value investing more tolerable. Investors should keep in mind though that momentum and value are largely uncorrelated only when their market risks are hedged. As long-only strategies, momentum and value are correlated to the market and to each other. All can simultaneously experience large bear market losses.
There is another reason why non-correlation may not be so important. As I show in my recent blog post, “ Factor Investing: Buyer Beware ,” value investing in actual practice has not shown any significant advantage over the market. If investors have no reason to hold value stocks, momentum loses some of its attractiveness as a diversification strategy.
In Chapter 3 W&J give a brief history of stock market momentum and the important psychological challenges of momentum investing. W&J make the point that value and momentum are similar since both are driven by short-term investor pessimism. With value, pessimism is because of poor fundamentals. With momentum, pessimism is about performance continuation.
W&J reveal that momentum, like value, can underperform over long periods. They point out a 5-year stretch when momentum underperformed the broad market by 15%. This could be challenging to any investor.
In Chapter 4 W&J show that a 50/50 allocation to value and momentum can reduce the tracking error of separate value and momentum portfolios during extended periods of relative poor performance. What is also worth noting and may be of some concern is the decline over time of both value and momentum premia.
Stock momentum works best using an intermediate term 3 to 12-month look back period. W&J use 12-months for quantitative momentum and skip the most recent month because of mean reversion.
W&J show in Table 5.5 that frequently rebalanced, concentrated momentum portfolios perform best. Ideal portfolios hold only 50 stocks and get rebalanced monthly.
Stock momentum is a high turnover strategy, and many momentum stocks are volatile with wide bid-ask spreads. There is bound to be some price impact from trading momentum stocks. This is especially true with frequently balanced, concentrated momentum portfolios.
Everyone now knows the top-ranked momentum stocks. In fact, Alpha Architect shows the top 100 momentum stocks on their website each month to anyone who registers there. So all investors, not just multi-billion-dollar asset managers, may experience adverse price impact from trading the same momentum stocks that everyone else does.
Transaction costs can be a similar problem. W&J mention a paper called " The Illusionary Nature of Momentum Profits " by Lesmond, Schill, and Zhou (2002) published in the Journal of Financial Economics. Lesmond et al. conclude that after transaction costs, momentum profits are largely illusionary. W&J also mention research by Korajczyk and Sadka (2004) showing that stock momentum has a limited capacity of only about $5 billion.
Offsetting these arguments, W&J present the findings of Frazzini, Israel, and Moskowitz (2014) of AQR. Frazzini et al. argue that momentum trading costs are manageable based on AQR’s own proprietary transaction data from 1998 through 2011.
But the amount of capital in momentum strategies is higher now. In a more recent paper, Fisher, Shah, and Titman (2015) use observed bid-ask spreads from 2000 through 2013. They report, “Our estimates of trading costs are generally much larger than those reported in Frazzini, Israel and Moskowitz (2012), and somewhat smaller than those described in Lesmond, Schill and Zhou (2004) and Korajczyk and Sadka (2004).” Research by Jason Hsu PhD, co-founder of Research Affiliates, also supports the higher transaction cost conclusions of Fisher et al. and Lesmond et al.
Chapter 6 is where W&J explain path dependency is and why it matters. They cite research by Da, Gurun, and Waracha (2014) showing that smooth and steady past performance is preferable to jumpy performance. The underlying logic is that investors underreact to continuous information. Investors should therefore prefer momentum accompanied by steady price appreciation rather than discreet price jumps.
To implement this idea, W&J advocate double sorting stocks on their 12-month momentum and their percentage of positive daily returns over the past 252 trading days. What they call “high-quality momentum" are top decile momentum stocks with the largest percentage of positive daily returns. Results are from 1927 through 2014, and transaction costs are not included.
Diligent data mining increases the odds that favorable results may be due to chance. Say you have different studies each showing no significance with a 95% confidence level of being correct. If you examine 20 or more of these studies, there is a good chance that one of them will be look significant even though the chance of that being correct is still only 5%. The classic green jelly bean example should make this clear.
In Chapter 7 W&J attempt to further enhance momentum by adding seasonality. In the turn-of-the-year or January effect, investors engage in year-end tax loss selling. They hold on to their strongest stocks and may buy more of these as replacements for the stocks they sell.
Window dressing to make their quarter-end portfolios look more attractive may also cause investment professionals to sell their losers and buy more winners before the end of the quarter. To take advantage of these seasonal tendencies, W&J advocate rebalancing their momentum portfolios at the end of February, May, August and November. They say this may help capture higher momentum profits during the months following the end of each calendar quarter.
Here are the results from incorporating seasonality as “smart rebalancing.”
In Chapter 8 W&J suggest that readers address the trading cost issue by comparing the analysis presented in Lesmond et al. and Frazzini et al. They do not mention here the more recent studies by Fisher et al. and Hsu that I discuss above.
W&J then do an in-depth analysis of “quantitative momentum” with respect to reward, risk, and robustness. They finish the chapter by making the point that momentum is sustainable because investors will continue to have behavioral biases. Investors are short-sighted performance chasers. This should also keep them from overexploiting the anomaly.
In the words of W&J, “… strategies like value and momentum presumably will continue to work because they sometimes fail spectacularly relative to passive benchmarks.” This may not be good news for those who at that time own momentum or value stocks. But W&J offer these words of encouragement. “ The ability to stay disciplined to a process is arguably the most important aspect of being a successful investor ” (emphasis added).
In Chapter 9 W&J show a combined 50/50 allocation to an equal weight, quarterly rebalanced momentum and value portfolio from 1974 through 2014.
The combined portfolio return is higher than that of momentum or value on their own. The combined portfolio also has less tracking error than either momentum or value vis-a-vis the broad market. Combining value and momentum shortens both the length and depth of benchmark underperformance.
As a final tweak to their approach, W&J show a trend following overlay applied to the combined portfolio. If a 12-month moving average of the S&P 500 index is greater than zero, they hold the combined portfolio. If the moving average is less than zero, they hold Treasury bills. Using this trend filter, the worst drawdown of the combined approach goes from -60.2% to -26.2%. But investors give up 1.5% in compound annual return, and there is an increase in tracking error.
My research shows that trend-following is more effective when applied to stock indices rather than to portfolios of individual value or momentum stocks. The reason for this has to do with volatility. The standard deviation of W&J’s quantitative momentum and combined portfolios are 25.6% and 21.4%. The standard deviation of the S&P 500 index is 15.5%. Higher volatility means you give up more profit before you can exit or re-enter stocks when using a trend following filter.
W&J finish the book by again referring to relative performance risk. One cannot stress enough that myopic investors give up potentially superior results when they become nervous or impatient and abandon their strategies.
In an Appendix, W&J examine some possible enhancements to momentum. These include earnings momentum, proximity to 52-week highs, stop losses, and absolute strength. Although W&J use the terms interchangeably here, you should not confuse absolute strength with absolute momentum. Otherwise, their analysis here is first rate. I would like to see W&J apply the same degree of analytic rigor to all the strategies featured on their Alpha Architect blog .
I remain skeptical about momentum applied to stock portfolios. Macro momentum applied to stock indices is a simpler approach that shows the same high potential returns as “quantitative momentum.” Macro momentum with broad-based indices has substantially lower transaction costs and no scalability issues. It also responds better to trend-following.
But I still recommend Quantitative Momentum to momentum investors for the following reasons:
1) Its emphasis on sustainable investors who can keep the big picture in mind and not be swayed by short-term performance
2) Its review of momentum principles and behavioral biases
3) Its rigorous research in the book’s Appendix
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