January 24, 2016

Why Is Momentum Neglected?

In the words of Asness et al (2014), “No other factor…has nearly as long a track record, as much out-of-sample evidence (including across time, geography and even security type), or as strong and reliable a return premium as momentum.” They were speaking only of relative strength momentum. When you add in absolute momentum, which has shown the ability to further boost returns as well as decrease bear market risk exposure, you have to wonder why many more investors are not enthusiastic about momentum. This is especially surprising since the stock market has twice experienced 50% losses during the past 15 years and is back in a precarious position again.

One reason for a lack of interest may be common misconceptions about momentum. This prompted Asness and his posse in 2014 to publish a paper called “Fact, Fiction, and Momentum Investing.”

We have seen others characterize momentum as a shorter-term moving average approach or something based on daily price changes. But momentum is a well-documented intermediate term anomaly effective over a 3 to 12 month look back period. For stocks, longer (3 to 5 years) and shorter periods (1 month or less) are mean reverting, which means they perform the opposite of momentum. Daily price changes are just noise with little or no serial correlation.

We think there is more to the lack of interest in momentum than just incorrect information. Some investors diligently search for reasons, real or imagined, to reject, criticize, ignore, or misrepresent  momentum. Why is this?

Here are some possible explanations gleaned from my discussions with others, online reviews of my book, and some internet articles about momentum.

Reason #1: I have done a lousy job explaining momentum.

This reason was also given by Cliff Asness who did his PhD dissertation on momentum. I wrote an entire book about it, but there is so much more to momentum than one can cover in any one book, article, or research study. To appreciate the efficacy of momentum you need to spend some time exploring the small mountain of momentum research done over the past 20 years. There have been hundreds of research studies by academics on relative strength (cross-sectional) and absolute (time-series) momentum. Momentum has shown consistent in- sample and out-of-sample profits and strong robustness with many different markets all the way back to the year 1801.  Results have been impressive enough to turn the academic world on its head and sway them away from their prior efficient market view of the world. Even Fama and French, two of the bastions of efficient market theory, called momentum the “premier anomaly.”

In my book and blog posts you will find references to many momentum research studies you can download for free. Wading through these may seem like a daunting task and, to quote Yogi Berra, “If people won’t come to the ballpark, how are you going to stop them?” But you can gain considerable insight from reading just the papers’ abstracts, conclusions, and exhibits. Momentum is not as complicated as you might think. In fact, one of the main attractions of momentum is its simplicity.

Reason #2: Momentum is too simple.

Some people wonder how an approach this simple can be so good. Momentum has even been called a trivial strategy, but its results are hardly trivial.

Simple is good, since it means less chance of overfitting the data. Synergy happens when you combine simple absolute momentum with simple relative momentum. Over the long run, relative momentum offsets the underperformance of absolute momentum in bull markets. Absolute momentum, unlike relative momentum, can side step severe bear market drawdowns. This complementary combination can boost profits while also reducing bear market risk exposure. Our last blog post, “Why Does Dual Momentum Outperform”, shows how relative and absolute momentum work together synergistically to create the whole of dual momentum that is greater than the sum of its parts.

We also opt for simplicity by using a simple stock and bond portfolio. Because of the drawdown reducing benefit of absolute momentum, dual momentum does not need to diversify into a large number of assets to reduce portfolio risk.

The post receiving the most views on my blog is the one about our dual momentum sector rotation model. People seem attracted to approaches with more “moving parts,” even though, as in this case, complex models are often no better than simpler ones with fewer parameters. Frederic Chopin called simplicity “the final achievement.”

I recently gave a presentation in Florida where the sponsoring chairperson said he initially dismissed my book because the approach in it looked too simple. After he back tested the strategy himself and saw how strong and robust it was, he became an enthusiastic supporter of dual momentum.

Simplicity is a great virtue, but it requires hard work to achieve it and education to appreciate it. And to make matters worse, complexity sells better.   - Edsger Dijkstra, 1972 Turing Award winner              

Reason #3: Momentum is hard to get your head around.

We all love a good story, and momentum is not a good “once upon a time” concept. Most of us understand the principle behind value investing. We buy what is “cheap”. The concept of value is widely accepted throughout the investment industry. Yet Israel and Moskowitz (2012), using book-to-market and other common value criteria, show that “the value premium is largely concentrated among only small stocks (microcaps) and is insignificant among the two largest quintiles.” Because of liquidity and cost issues, hardly anyone invests in microcaps. Other studies show that value works with large stocks but only during January. The following table from Das and Rao (2012) illustrates this point.

Value investing is also subject to sustained tracking error (six straight years of under performance in the 1990s), larger drawdowns than the broad market, and value traps where cheap companies can become much cheaper. The energy and mining stocks are showing us that now. They appeared inexpensive over the past few years, but no one accounted for the dramatic drop in the future value of their assets.

Value investing is still quite popular because investors like the idea of buying what may be cheap. But investors forget (or never realized in the first place) that stocks may be cheap because their risks may be high.

With momentum investing, instead of buying what is cheap, we buy what has appreciated. Buying strength goes against human psychology. In fact, the disposition effect makes us want to sell recent winners rather than buy them. It goes against the maxim first uttered in the early 1800s, “cut short your losses and let your profits run on.” The behavioral heuristics of anchoring and conservatism can also create inertia keeping us from buying momentum winners.

Reason #4: You cannot trust back tested results.
Like the Wizard of Oz witches, there can be good back tests and bad back tests. Practitioners often prefer complicated models. They may search for the best ex-ante assets, parameters, or filters without considering if their logic makes sense, how consistent their results are over time, and what the impact is of transaction costs. They tend to use limited amounts of data, over optimize their model parameters, and overfit the data.

This kind of back testing usually does not hold up well ex-post, and it is good to be skeptical of it.
Academic trained researchers, however, prefer simple (parsimonious) models, and they apply them to as much data as possible. They then look to verify promising models on out-of-sample data whenever it becomes available.

Trained researchers also give importance to robustness. They prefer models that hold up over a range of parameter values and when applied to other non-correlated markets.

Momentum has held up well based on these more stringent criteria. It has worked over a wide range of look back periods and across almost all asset classes. Here is a table from Geczy and Samanov (2015b) showing decade-by-decade long-only (the winner’s column) momentum performance of U.S. stocks from 1801 through 2010:

Only 2 out of the last 21 decades showed momentum underperformance versus buy-and-hold, and those performance differences were small. Here is a similar table from Geczy and Samonov (2015a) with long winners and short losers using different asset classes over the same 210 year period:
We see impressive consistency over the past 21 decades across all asset classes. The authors also confirm the efficacy of absolute momentum over the 210 year period. But momentum is not just a good fit to the data. There are some deep seated behaviorally-based reasons that can explain why momentum has performed well and has a good chance of continuing to perform well.

Reason #5: Momentum is not diversified.

Relative strength momentum could not exist without diversification. Relative strength requires multiple assets to compare and choose from. You can think of momentum as vertical rather than horizontal diversification. It diversifies across time rather than across assets to better exploit market strength and avoid the performance drag that comes from always holding lower risk premium assets.

The U.S. stock market has the highest long-run risk premium, and that is why we use it as our core dual momentum asset. This gives us a logical reason rather than one based on data mining. We look for the highest risk premium, then manage that risk. We hold short term bonds when stocks are weak and it makes the most sense to be in fixed income.
Source: Jeremy Siegel, Stocks for the Long Run. McGraw-Hill

Why do we diversify in the first place? It is usually to reduce portfolio volatility, uncertainty, and downside risk exposure. Dual momentum does this automatically. By keeping that in mind, we may be able to better tolerate the higher short-term volatility that comes from holding a single asset portfolio. As Charlie Munger said at the 2004 Berkshire Hathaway annual meeting, “The idea of excessive diversification is madness… almost all good investments will involve relatively little diversification.”

Reason #6: Momentum conflicts with strongly-held prior beliefs.

Beliefs can have a powerful influence on how we perceive new information. This may have created confirmation bias that now causes them to reject momentum investing if they perceive momentum as being the opposite of value investing. Then there is the buy-and-hold Borg (“resistance is futile; you will be absorbed”) that rejects any approach trying to beat the market.
Dual momentum may experience extra prejudice since it includes trend-following absolute momentum that may seem like voodoo to those taught that you cannot successfully adapt to changing market conditions. Andrew Lo and other academics have now demonstrated that this is not always true.  Trend following has been shown to be effective all the way back to the 1700s. According to Greyserman and Kaminski (2014), equities with trend following showed a higher Sharpe ratio, reduced downside exposure, and gave nearly a 3% greater annual return than buy-and-hold from 1695 through 2013.

No investment approach is perfect, and dual momentum will at times underperform its benchmark when looking at incomplete market cycles [1].  Its absolute momentum component can be subject to whipsaws, especially during bull markets [2]. Career risk can be a significant factor among investment professionals who fear tracking error and deviations from investing norms.

Reason #7: Momentum outperformance may not last.

Stocks and bonds may return less in the days ahead. But then most other investment portfolios would also show lower returns. Momentum has outperformed from at least the 1800s.

Anything can happen in the investment world, and momentum could lose some of its luster. But if you want to play stump the critic, ask them why they think momentum outperformance is unlikely to continue. You may guess the sun will stop rising in the East some day, but past evidence is against it. I have not yet heard a credible reason on what would cause the sun or dual momentum to suddenly change direction.

Reason #8: Momentum may attract too much interest, and this will ruin it.

Anomalies can lose their effectiveness if too many people get on board. This may be particularly true for an approach like dual momentum that offers both higher expected returns and lower risk exposure.

But investors have known about the momentum anomaly for more than 20 years, and there has been no degradation in its out-of-sample performance, despite blog posts saying otherwise. Over the past 15 years, the Sharpe ratio of the top one-third value-weighted momentum deciles of U.S. stocks was 0.41, compared to 0.15 for the bottom one-third deciles [3].
Research has shown that stock momentum has earned twice the annualized return premium as value since 1927. Despite this, momentum investing has not attracted anywhere near the amount of interest that value investing has. Value is used more than momentum in multi-factor funds. The word “value” is found over 130 times more often than the word “momentum” in the names of all U.S. mutual funds and ETFs.

Since most momentum research covers individual stocks, momentum is most commonly used with portfolios of individual stocks. But we use broad market indices with dual momentum, and these are much more scalable than individual stocks.

There is much less interest in absolute or dual momentum than in relative momentum because many still refuse to accept trend following. This gives our dual momentum approach even more scalability.
For abnormal profits to be arbitraged away, investors need to behave rationally, and momentum profits are most likely due to investor irrationality.

Reason #9: If momentum is so good, why hasn’t it attracted more interest, especially from institutional investors?

There are innumerable value, buy-and-hold, and other investors whose biases keep them from being receptive to momentum. This is especially true of institutional investors. Institutional constraints keep most institutional investors away from momentum in general. Career risk associated with tracking error, long-standing aversion to trend following, and confirmation bias are disincentives that keep institutional investors away from dual momentum. Without their participation, it is unlikely momentum will be over exploited. The reasons that keep investors from accepting and using dual momentum are the same reasons that should keep it from ever becoming too popular [4].


There are risk factors and challenges associated with momentum investing. These include the possibilities of whipsaw, lags in stock market re-entries, and other forms of tracking error. Risk premiums may also change over time, but this is not a potential issue limited to just momentum. Momentum can also be challenging to use, since its signals may run counter to our emotional inclinations.

But the aversion some have to momentum has little to do with these risk factors. The behavioral biases that keep investors away from momentum investing are the same ones that cause momentum to work in the first place. These include conservatism, confirmation bias, and anchoring that prevent us from accepting something new or unfamiliar. Other influencing biases are herding and overconfidence by those who are  committed to other investment approaches [5].

It should come as no surprise that the same irrationality causing momentum to work in the first place also keeps investors from accepting and using it. Behavioral economists have long shown that people are irrational. And that’s all people, not just my ex-wife. For those who can overcome their behavioral biases and prejudices, may the momentum force be with you.

[1] Dual momentum underperformed its benchmark in 1979-80 and 2009-11.
[2] Since 1971, our Global Equities Momentum model exited and reentered stocks 9 times within 3 months. During this same period, the popular 10-month moving average exited and reentered stocks 20 times.
[3] See Israel and Moskowitz (2012) for more evidence of continuing momentum outperformance.
[4] See Sheifer and Vishny (1997) for more on the limits of arbitrage.
[5] For an introduction to behavioral biases, see "Are You Trying Too Hard: The Case for Systematic Decision Making" by Alpha Architect.

December 17, 2015

Why Does Dual Momentum Outperform?

Those who have read my momentum research papers, book, and this blog should know that simple dual momentum has handily outperformed buy-and-hold. The following chart shows the 10- year rolling excess return of our popular Global Equities Momentum (GEM) dual momentum model compared to a 70/30 S&P 500/U.S. bond benchmark [1]

Results are hypothetical, are NOT an indicator of future results, and do NOT represent returns that any investor actually attained. Indexes are unmanaged, do not reflect management or trading fees, and one cannot invest directly in an index. Please see our Performance and Disclaimer pages for more information.

GEM has always outperformed its benchmark and continues to do so now, although the amount of outperformance has varied over time. In 1984 and 1997-2000, those who might have guessed that dual momentum had lost its mojo saw its dominance come roaring right back.

In Chapter 4 of my book, I give some explanations why momentum has worked so well and been called the “premier anomaly” by Fama and French. The reasons for the outperformance of momentum fall into two general categories: rational and behavioral. In the rational camp are those who believe that momentum earns higher returns because its risks are greater. That argument is harder to justify now that absolute momentum has shown the ability to provide higher returns and reduced risk exposure.

The behavioral explanation for momentum centers on initial investor underreaction of prices to new information. This is followed later by overreaction. Underreaction likely comes from anchoring, conservatism, and the slow diffusion of information. Overreaction is due to herding (the bandwagon effect), representativeness (assuming continuation of the present), and overconfidence. Price gains attract more buying, which leads to further price gains. The same is true with losses and continued selling.

The herding instinct is one of the strongest forces in nature. It is what allows animals in nature to better survive predator attacks. It is a powerful primordial instinct built in to our brain chemistry and DNA. It is therefore unlikely to disappear. Representativeness and overconfidence are also evident when there are strong momentum-based trends.

Furthermore, investors' loss aversion may decrease as they see prices rise and they become overconfident. Their loss aversion may similarly increase as prices fall and they become more fearful. Studies have shown that investors are 1.5 to 2 times more likely to avoid losses than they are willing to seek gains. These natural psychological responses are also unlikely to change in the future.

One can make a sound logical argument for the investor overreaction explanation of the momentum effect with individual stocks. Stocks can have high idiosyncratic volatility and be influenced by news events, such as earnings surprises, management changes, plant shutdowns, employee strikes, product recalls, supply chain disruptions, regulatory constraints, and litigation.

A recent study by Heidari (2015) called “Over or Under? Momentum, Idiosyncratic Volatility and Overreaction” looked into investor under or overreaction with stocks and found evidence that supported the overreaction explanation as the source of momentum profits, especially when idiosyncratic volatility was high.

Many economic trends, not just stock prices, get overextended and then mean revert. The business cycle itself trends and mean reverts. Since the late 1980s, researchers have known that stock prices are long-term mean reverting [2]. Mean reversion supports the premise that stocks overreact and become overextended, which leads to their mean reversion. We will make a case that overreaction in both bull and bear market environments provides a good explanation for why dual momentum has worked so well compared to buy-and-hold. 

Dual Momentum Performance

Earlier we posted "Dual, Relative, & Absolute Momentum" that highlighted the differences between dual, relative, and absolute momentum. Here is a chart of our GEM model and its relative and absolute momentum components referenced in that post. GEM uses relative momentum to switch between U.S. and non-U.S. stocks and absolute momentum to switch between stocks and bonds. Instructions on how to use GEM are in my book, Dual Momentum Investing: An Innovative Strategy for Higher Returns with Lower Risk.

Results are hypothetical, are NOT an indicator of future results, and do NOT represent returns that any investor actually attained. Indexes are unmanaged, do not reflect management or trading fees, and one cannot invest directly in an index. Please see our Performance and Disclaimer pages for more information.

Relative momentum provided almost 300 basis points more annual average return than the underlying S&P 500 and MSCI ACWI ex-US indices. It did this by capturing profits from both indices rather than from just from a single one. We can tell from the above chart that some of these profits came from price overreaction, since both indices pulled back sharply following their strong run ups.

Even though relative momentum can give us substantially increased profits, it does nothing to alleviate downside risk. Relative momentum volatility and maximum drawdown are comparable to the underlying indices themselves.

We see in the above chart that absolute momentum applied to the S&P 500 created almost the same terminal wealth as relative momentum, and it did so with much less drawdown.  Absolute momentum accomplished this by side stepping the severe downside bear market overreactions in stocks. As with relative momentum, there is ample evidence of price overreaction, since there were sharp rebounds from oversold levels following most bear market lows.

We see that overreaction comes into play twice with dual momentum. First, is when we exploit positive overreaction to earn higher profits from the strongest market selected by relative momentum. Trend following absolute momentum can help lock in these overreaction profits before the markets can mean revert.

The second way overreaction comes into play is when we avoid it by standing aside from stocks when absolute momentum identifies the trend of the market as being down. Based on this synergistic capturing of overreaction profits while avoiding overreaction losses, dual momentum produced twice the incremental return of relative momentum alone. And it did this while maintaining the same stability as absolute momentum. We should keep in mind that stock market overreaction, as the driving force behind dual momentum, is not likely to disappear.

Distribution of Returns

Looking at things a little differently, the following histogram shows the distribution of  12-month returns of GEM versus the S&P 500. We see that GEM has participated well in bull market upside gains while truncating left tail risk representing bear market losses. Dual momentum, in effect, converted market overreaction losses into profits.

Market Environments

We can also gain some insight by looking at the comparative performance of GEM and the S&P 500 during separate bull and bear market periods.



S&P 500
S&P 500
Jan 71-Dec 72
Oct 74-Nov 80
Jan 73-Sep 74
Aug 82-Aug 87
Dec 80-Jul 82
Dec 87-Aug 00
Sep 87-Nov 87
Oct 02-Oct 07
Sep 00-Sep 02
Mar 09-Nov15
Nov 07-Feb 09
Average Return
Average Return

Results are hypothetical, are NOT an indicator of future results, and do NOT represent returns that any investor actually attained. Indexes are unmanaged, do not reflect management or trading fees, and one cannot invest directly in an index. Please see our Performance and Disclaimer pages for more information.

During bull markets, GEM produced an average return somewhat higher than the S&P 500. This meant that relative momentum earned more than absolute momentum gave up on those occasions when absolute momentum exited stocks and had to reenter stocks a month or several months later [3].  Relative momentum also overcame lost profits when trend-following absolute momentum kept GEM out of stocks as new bull markets were just getting started. With only absolute momentum, the bull market average return would have been 214.9% instead of the 289.9% return that came from using both relative and absolute momentum.

What really stand out though are the average profits that GEM earned in bear market environments when stocks lost an average of 37%. Without only relative momentum, the bear market average return would have been -33.1% instead of the 3.6% positive return that came form using both relative and absolute momentum. Absolute momentum, by side stepping bear market losses, is what accounted for much of GEM’s outperformance.

Large losses need much larger gains to recover from those losses. For example, a 50% loss requires a 100% gain to get back to breakeven. By avoiding large losses in the first place, GEM has not been saddled with this kind of loss recovery burden. Warren Buffett was right when he said that the first (and second) rule of investing is to avoid losses.   

But increased profits through relative strength and loss avoidance through absolute momentum are only half the story. Avoiding losses also contributes to our peace of mind. It helps prevent us from becoming irrationally exuberant or uncomfortably depressed, which can lead to poor timing decisions. Not only does dual momentum help capture overreaction bull market profits and reduce overreaction bear market losses, but it gives us a disciplined framework to keep us from overreacting to the wild vagaries of the market.

[1] GEM has been in stocks 70% of the time and in aggregate or government/credit bonds around 30% of the time since January 1971. See the Performance page of our website for more information.
[2] See Poterba and Summers (1988) or Fama and French (1988).

[3] Since January 1971, there have been 9 instances of absolute momentum causing GEM to exit stocks and reenter them within the next 3 months, foregoing an average 3.1% difference in return. 

November 21, 2015

Bring More Data

Several months ago we posted an article called “Bring Data” where we showed the importance of having abundant data for system development and validation. This was further reinforced to us recently when someone actually brought us additional U.S. stock sector data. Previously, we only had Morningstar sector data that went back to 1992, which we used to construct our Dual Momentum Sector Rotation (DMSR) model. (S&P sector data also goes back to only the early 1990s.) DMSR was shown in my book as one example of other ways you might use dual momentum.

When we were given equivalent Thompson Reuters U.S. stock sector data back to 1973, we immediately extended our DMSR back test to include this additional data. After incorporating the new data, DMSR still looked considerably more attractive than buying and holding the S&P 500 index. But one could argue that the performance of our dual momentum models using broad-based equity indexes, such as Global Equities Momentum (GEM), now look better than DMSR. Here are the comparative performance figures from January 1974 through October 2015:

S&P 500
Average Annual Return
Standard Deviation
Sharpe Ratio
Maximum Drawdown

Results are hypothetical, are NOT an indicator of future results, and do NOT represent returns that any investor actually attained. Indexes are unmanaged, do not reflect management or trading fees, and one cannot invest directly in an index. 

Because the monthly correlation between GEM and DMSR is only 0.59, sector rotation can still have a useful but modest role to play in a diversified equities-oriented portfolio. But DMSR is not the best choice as a core portfolio holding. Sector rotation programs that use data no further back than the early 1990s to develop their models may be in for a rude awakening someday if future drawdowns are higher and returns are lower than they expect based on back testing with a limited amount of data.

Along the same lines, there are also momentum-based portfolios popping up on the internet all the time now, some even labeled as “dual momentum,” that are modeled on the basis of only 10 or 15 years of ETF data. Momentum may be robust enough that future results won’t suffer much because of this. But those who think they are constructing optimal models this way are just fooling themselves. Overfitting modest amounts of data is one of the most pernicious problems in the development of investment models. Those who do this may argue that the markets change over time, so the best model parameters from years ago may not be as relevant as today’s best parameters. This may be true. However, what is also true is that today’s parameter values are also likely to be sub-optimal when moving forward in time. The following chart from my book, Dual Momentum Investing, shows what I mean:

 Chart courtesy of Tony Cooper

The S&P 500 is highlighted in different colors for each 15 year period. You can see that the latest period, 1999-2013, looks different from the preceding period, 1984-1998. 1999-2013, in fact, looks more like the earlier 1969-1983 period. 1984-1998 is also different from its preceding period, 1969-1983 and similar to the earlier years 1954-1968. If you had used each 15-year period to develop your model, you would have had something unsuited for each of the next 15-year periods. You would have  been better off using all four periods to formulate a model rather than just the last 15-year period. The more data you use, the more likely you are to have a robust model that will hold up reasonably well in the future, even though it isn’t the best fit to any one particular period.

The 12-month look back parameter we use for our GEM and ESGM dual momentum models was found to work well in 1937 by Cowles & Jones. It has been used extensively in momentum research since then and has held up well out-of-sample. But there is a lot more history than that to help give us more confidence in momentum. Let's take a look at some of that now.

We focus on stocks as our core asset since they have historically offered the highest risk premium to investors. U.S. stocks, in particular, have given investors the best long-run returns. Other assets can create a drag on long-run portfolio performance. They also lose some importance as diversifiers once you use a trend following overlay like absolute momentum to help attenuate your downside risk exposure.

The longest back test on stock market momentum is by Geczy and Samonov (G&S). Their 2013 paper called “212 Years of Price Momentum: The World’s Longest Back Test 1801-2012” compared the top one-third to the bottom one-third of U.S. stocks sorted monthly by relative momentum. Over this entire sample period, the top equally weighted momentum stocks outperformed the bottom ones by 0.4% per month with a highly significant t-stat of 5.7. Prior to this study, momentum outperformance on U.S. stocks had been found significant back to 1926. G&S showed that stock momentum was also positive and statistically significant from 1801 to 1926.

G&S also found that stock market momentum was remarkably consistent. In only 2 of the 21 decades from 1801 through 2012 did long-only momentum under perform buy-and- hold, and these were by just -1.2% and -0.7% annually. In all the other 19 decades, momentum outperformed buy-and-hold by an average of 3.8% annually.

This year G&S came out with a new study called, “215 Years of Global Multi-Asset Momentum: 1800-2014: Equities, Sectors, Currencies, Bonds, Commodities, and Stocks.” Here G&S expanded their momentum study to cover six different asset classes, including bonds, stock sectors, and equity indices, which are the ones we use in our momentum models. [1] G&S demonstrated the outperformance of momentum inside and across all asset classes except commodities. Here is a chart from their paper showing the log cumulative equally weighted average of the 6 asset classes plus the cross asset momentum excess returns.
The strongest momentum effect is in equity indices, which had a long-only monthly excess return over buy-and-hold of 0.52% with a highly significant t-stat of 11.7, compared to 0.29% with a t-stat of 6.4 for individual U.S. stocks before transaction costs, which would be much higher for stocks. G&S also show that long-only absolute (time series) momentum outperformed buy-and-hold by 0.15% per month with a t-stat of 11.2.

For those who want to further their momentum education, I suggest you first read the seminal paper by Jegadeesh and Titman (1993) that started the modern momentum renaissance. Next, learn about absolute momentum from Moskowitz et al (2012) or Antonacci (2013). Then follow up with Geczy and Samonov (2015) to satisfy yourself as to the efficacy and robustness of momentum investing based on 215 years of empirical evidence.

[1] Equity indexes are equally as good as individual stocks (or better, according to G&S) in capturing the momentum effect. Indexes are much easier to use and avoid the enormously high transaction costs associated with rebalancing momentum-based stock portfolios.