Research has shown that stock prices are reactive rather than trending over short periods of time. Stocks are more likely to rebound from short-term fluctuations than to continue in the same direction. You will get whipsawed if you check for signals too frequently.
It takes a while for research to work its way into the investment marketplace. We saw that with indexing. Public awareness should grow as information about momentum becomes more widely accepted.
There are other reasons momentum investing has not yet caught on in a big way. First, it is not as psychologically appealing to buy what has gone up in price as it is to buy things that appear to be cheap. Momentum may also seem too simple for those who mistakenly think more complex approaches have more merit. Some investors have prejudices against other styles of investing or investing in indices rather than in stocks. Interestingly, some of the same behavioral factors that explain why momentum works also explain why momentum has not caught on yet: anchoring, herding, conservatism, and the slow diffusion of information. There is also a strong and universal home country bias that keeps many from investing heavily outside of their home country using dual momentum.
Finally, limits to arbitrage keep institutional investors from investing in new ideas because of career risk. If they are wrong but doing what everyone else is doing, they have a better chance of keeping their clients. But they are likely to lose clients or their jobs if they lose money when others are making money. Dual momentum, like all strategies, will have periods of underperformance.
One risk is that history is unreliable. The future may not be as good as the past. But there are several hundred years of out-of-sample performance supporting both relative and absolute momentum. There are also behavioral reasons momentum has a good chance to continue working since behavioral biases are hard to change.
There is some risk that momentum will attract substantial capital and not work as well in the future because of too many participants. But stock indices that we often use are much more scalable than individual stocks. Behavioral biases also keep investors away from dual momentum.
Much of the short-term volatility of the stock market still exists with dual momentum. There are re-entry lags when a new bull market begins after being in bonds during bear markets. You should expect this, especially from our public dual momentum models. I designed our proprietary models to reduce transitional lags.
If you invest with dual momentum after the stock market has gone up a lot, your risk is higher of a market pullback.
There is also the risk of tracking errors. No strategy outperforms its benchmarks all the time.
Future drawdowns may also be larger than those in the past. Please see our Disclaimer page for additional risk factors.
The number of sectors depends on one’s attitude toward reward and risk. Fewer sectors mean higher expected returns and higher volatility. You can find parameters to create a sector rotation model suited to your individual risk preferences. Be aware though that data-mined parameter may not hold up well out-of-sample.
I show here the performance of DMSR using additional data since my I published my book. DMSR no longer looks as attractive as broader-based dual momentum models like GEM or our proprietary models.
Using data back to 1801, Geczy and Samonov (2015) show that momentum with geographically diversified stock indices outperforms momentum with sectors, as well as individual stocks, currencies, bonds, and commodities. This may be because home country bias keeps investors from investing much in more attractive geographic areas, thus creating abnormal profits for those who do.
EMs are already included in the MSCI ACWI ex-U.S. index that GEM uses. They make up 17% of that index based on market capitalization. Investors are more prone to panic and sell more volatile assets like EMs during times of crisis. Those who want to add an extra allocation to EMs should proceed cautiously. We use EMs as a separate asset in our proprietary models since we have better risk control and more diversification there. md
Modest positions in non-correlated assets often work well as diversifiers. We have lower correlation proprietary models that act as good diversifiers to our other proprietary models. Contact us for more information.
There may be some advantages in using multiple lookback periods if done intelligently and not indiscriminately. There are tradeoffs that need to be considered when you add complexity to a model. See here for more on this. We find it better to add other assets and more trend determinants rather than to have many lookback periods.
The negative correlation you have seen between stocks and bonds has not always existed. There have been long periods of positive correlation between stocks and bonds.
Source: Graham Capital Management Research Note, September 2017
Long-term bonds also have considerable duration risk. During times of crisis, investors usually prefer safe harbor assets with little risk of any kind. See here for more on why long-term bonds may not be the best safe harbor asset.
Bonds behave differently than stocks. They usually do better using shorter lookback periods. An enhanced version of GBM is one of the proprietary models I license to investment professionals and family offices. To achieve a similar risk profile, you can use the suggestion at the end of Chapter 8 of my book and allocate a permanent percentage of your portfolio to short or intermediate-term bonds.
There are 16 major leading economic indicators. With so many to choose from, it is easy to put together something that looks good in hindsight. The unemployment rate was a useful stock market timing indicator back to1970. But it gives worse results than the trend alone before then.
The stock market itself is a leading economic indicator. There are potential data snooping and selection bias issues when you add additional indicators or parameters.
Theproprietary models we license to advisors and family offices use more assets than our public models. They also use multiple lookback periods and variations on trend-following. Besides an advanced version of GEM (A-GEM), we have balanced and fixed-income proprietary dual momentum models (E-GBM and DMFI) to accommodate different risk preferences. Our newest proprietary model (QBAT) uses daily rather than monthly data and breadth, trend, and mean reversion. It is our most advanced and most adaptable model. See the Proprietary Models page or contact us for more information on our proprietary models.
Most 401K plans include a fund for non-U.S. stocks. You could use that. If your 401k has an emerging market fund, you could create a synthetic ex-U.S. all country world fund by allocating 15-20% to the emerging market fund and 80-85% to a non-U.S. developed markets fund. You could still derive signals from an ex-U.S. all-country world stock ETF as shown in my book.
Our research shows that these do not improve GEM’s results. Factor-based funds are often subject to data mining and selection biases. Real-time results from factor-based funds have not been encouraging. See our blog posts here and here.
Bear markets usually don’t last as long as bull markets. There are lags with dual momentum getting into and out of stocks.
Bear markets are subject to sharp rallies that fade quickly and create whipsaw losses for those who try to trade them. We have gotten better results being in intermediate or short-term bonds rather than going short when stocks are trending down. The one exception to this is our QBAT model. It is nimble enough to trade intermediate-term rallies even in bear markets.
There are several of them mentioned in the reviews of my book on Amazon and elsewhere on the internet. Two of them are here and here. If you are still skeptical, you can do your own backtestingwith ETFs or mutual funds using Portfolio Visualizer.You should use an S&P 500 fund to determine “single absolute momentum.” Mutual funds have a longer history than ETFs. You could use VFINX, VWIGX, and VBMFX to get results back to 1987. These results are approximate and somewhat different from what you would get using ETFs or indices.
I use the All Country World ex-US Index along with the S&P 500 to be all-inclusive and to avoid selection bias. Selection bias is where you select a subset of the data in order to make your results look better or, in this case, worse. EAFE omits Canada and emerging markets, which represent a meaningful 24% of the world’s equity market.
ACWI ex-US and EAFE performance may appear similar. But ACWI ex-US gains more in up markets and loses more in down markets than EAFE. We designed dual momentum to capture the upside while avoiding much of the downside. So there is a big difference in performance here when using dual momentum.
EAFE is also slower than ACWI ex-U.S. in switching to non-U.S. stocks when they become stronger than U.S. stocks. So using EAFE can give different switching times.
We think it is misleading to say there is little difference in the performance of EAFE and ACWI ex-U.S. by looking back to 1970 or earlier since MSCI didn’t track emerging markets before 1988. There was no difference in performance before 1988 since ACWI ex-U.S. did not exist before then, Dual momentum captures much of the outperformance of ACWI ex-U.S. since then while reducing much of the downside.
Holding all else constant, GEM earned 130 basis points more in annual return using MSCI ACWI ex-U.S. rather than MSCI EAFE from when the ACWI ex-U.S. index was created by MSCI. I see no reason to invest with MSCI EAFE which produces considerably lower returns than MSCI ACWI ex-U.S. in GEM.
One reason is that there is a lot more index data history. Another is that non-U.S. stock ETFs and mutual funds (as well as index data using net instead of gross returns) withhold 30% of their dividend income for foreign taxes. (These are often recoverable by investors as a tax credit.) To get accurate relative strength signals, you would need to deduct 30% of the dividends from U.S. ETFs.
Expense ratios can also distort the relative performance between assets. Momentum decisions should be based only on asset performance. The markets do not care about taxes or other expenses.
Some do, but they can impose their own ideas without good reasons for their changes. You can easily determine the signals yourself with the information in Chapter 8 of my book. Alternatively, you can use a free Morningstar, Portfolio Visualizer, or ETF Screen portfolio to determine the GEM signals.
I show dual momentum both ways in my book. It may be better to apply relative momentum first if you are using a variety of assets. If you are only using the S&P 500 and non-U.S. stocks, then it is usually better to apply absolute momentum first.On page 98 of my book, I first determine absolute momentum using the S&P 500 index since the often U.S. leads world equity markets.
Studies here, here, and here show that stocks perform best early in the month. This is when institutional investors make changes to their portfolios. Prices then are most representative of their true value. Rebalancing during that time frame has shown the best results with our models. Here are the Sharpe and Sortino ratios for GEM based on the trading day of the month.
Our published results are based on month-end closing prices. I have tested using a 50/50 allocation to stocks and bonds when the signal is close. Results are about the same as following the signal precisely. To reduce feelings of regret no matter what happens, you may want to use this approach. Another possibility is to wait a day or two and see which way the signal goes.
The idea behind absolute momentum is to look at the return of the S&P 500 above the risk-free return. If the risk-free return is greater, you can stay in bonds until stocks show a positive excess return. There is no reason to bear the risk of stocks when you could earn a better return without so much downside risk.
Dual momentum has a trend-following component that lags when a new bull market begins. That is the cost for avoiding the carnage of the preceding bear market. It is unfair to look only at a new bull market without also considering the preceding bear market. You need to consider at least a full market cycle to make a proper evaluation of performance. GEM has outperformed its benchmark portfolio since 2008, which includes a full market cycle.
You also should understand why GEM has outperformed over the long run. First, there are the profits from switching between U.S. and non-U.S. stocks. Since 2009, U.S. stocks have continuously outperformed non-U.S. stocks. So there has been little opportunity for relative strength profit. Second, this secular bull market has been one of the longest in history. This means there has little opportunity for absolute momentum profits. It is difficult for any trend-following approach to keep up with the stock market when it is so strong.
Our proprietary models use variations of dual momentum and are more adaptive to changing market conditions. We designed them to perform well under all market conditions.
Since 1971, 73% of GEM’s gains have been long term, while nearly 100% of its losses have been short term. Long-term capital gains are taxed now at a historically low rate but might be higher when ETF investors realize their profit. Many investors don’t know that over 40% of the long-run return of the S&P 500 comes from dividends. These are taxed each year even if earned in an ETF. ETFs also have to pass along taxable gains from futures, options, short positions, and stocks that settle in cash, Those who want to defer all income, including interest and dividends, can do so by applying dual momentum to a retirement account or by using a low-cost Nationwide or Fidelity variable annuity.
They use net rather than gross returns for non-U.S. index data. Net returns have a 30% reduction in dividends to account for foreign tax withholding. This puts GEM at a disadvantage to models that are not invested in foreign ETFs. If you are going to account for taxes, you should apply the same adjustment to all indices and ETFs instead of penalizing only models that invest globally.
The main reason for the difference though is their use of MSCI EAFE rather than MSCI ACWI ex-U.S which includes Canada and emerging markets. They say there is not much difference in performance between the two indices. That is true only if you look at both bull and bear markets. But dual momentum tries to bypass bear markets while participating fully in bull markets. GEM also switches into non-U.S. stocks quicker using ACWI ex-U.S. rather than EAFE.
Using MSCI EAFE instead of MSCI ACWI ex-U.S. decreases GEM’s diversification and has lowered its return by 130 bps annually since MSCI ACWI ex-U.S. became usable in 1989. This site does not penalize other models accordingly. They can use ETFs that capture emerging market profits.
Because you can use ensemble methods to look at and use many things does not mean you should always do so. Tobias Moskowitz, a top momentum researcher, said, ”Momentum is a phenomenon that exists at 6 to 12-month horizons. Beyond 12 months, momentum wanes…” Most academic papers on momentum use lookback periods of 6 or 12 months. The ensemble paper you mentioned shows a fall-off in results with lookback periods under 3 months and over 12 months.
There is some benefit in using a modest number of lookback periods. We use different lookback periods in our own proprietary models. But we select them based on their appropriateness reasons, not randomly. Reducing specification risk by incorporating other factors or diverse trading approaches makes more sense than using an array of highly correlated lookback periods.
You cannot correctly judge the probability of something happening after it has already happened. You need to look at results out-of-sample. A 12-month lookback has more out-of-sample validation than any other lookback period. It was first introduced by Cowles & Jones in 1937 and validated by Jegadeesh & Titman in their seminal 1993 study. Other examples are in this blog post, including validation back to the year 1223.
MTUM has outperformed some of other momentum funds. This is due to its focused portfolio (around 125 stocks), relatively low fees (15 bps), lower selling-than-buying thresholds, and its use of two lookback periods.
But the main contributing factor to MTUM’s performance has been its heavy weighting on large-cap growth stocks. Large-cap growth ETFs like VONG, SCHG, IWF, and MGK have all outperformed MTUM. QQQ has done better than all of these. It remains to be seen how well MTUM will perform over time and when large-cap growth stocks get back to normal performance.
High stock valuation levels can mean lower expected stock returns, and low bond yields usually point to lower future bond returns. But stocks and bonds still fluctuate and create trading opportunities. In 2000, there were also high stock market valuations and low bond yields. But our GEM model had a compound annual return of 11.6% over the next 10 years, whereas a 60/40 stock/bond portfolio returned only 2.5%.
Any anomaly can lose profitability if it becomes too widely followed. However, the behavioral basis behind momentum is strong and persistent. Human nature does not readily change.
The same biases that make dual momentum work also keep investors away from it. This is especially true of institutional investors who often have an aversion to tactical approaches.
Shleifer and Vishny (1997) show that asset managers are afraid of strategies that deviate from popular benchmarks because investors may leave following periods of underperformance. This can create career risk. Home country bias is also a strong disincentive to invest outside one’s own country. It keeps investors from having as much with non-U.S. stocks when they are stronger than U.S. stocks.
The performance of actively managed funds has, in the aggregate, been inferior to passively managed funds. People have known about that since the 1960s. Yet over 70% of all domestic equity funds are still actively managed. Dual momentum investing may very well show the same disconnect.
Academic research shows that over the long run, momentum for stocks works best with lookback periods of 3 to 12 months. Longer lookbacks reduce transaction costs and increase the likelihood of long-term capital gains.
A 12-month look back was found to work well by Cowles & Jones in 1937. It has held up well ever since. Staying with this look-back period reduces concerns about data mining and seasonality bias. See our blog post “Perils of Data Mining” for more on this.
It makes sense to skip the last month when you are applying momentum to individual stocks because they can overreact to news then mean revert. If you use stock indices or other asset classes like we do, you do not need to skip the last month.
See here for why we prefer to use momentum with indices instead of stocks. According to this study, stock momentum profits have been insignificant since 1999. According to another study, momentum profits disappeared in the early 1990s. There is also the matter of transaction costs. See here for the most recent research on that. For more on stock momentum, see our review of the book Quantitative Momentum.
The lack of non-U.S. stock index data constrained us when I wrote my book. Additional data we received since then validated the outperformance of GEM. In addition, Geczy & Samonov (2015) found that both relative strength and absolute momentum outperformed buy and hold back to 1801. Absolute momentum showed superior returns and less downside risk to the beginning of stock trading in the 1600s and to 1223 with other assets in Greyserman & Kaminski’s book.
Over the long run, dual momentum performs better. Historically, stocks provide the best return. So we want to be in them as long as their trend is positive. GEM uses absolute momentum to tell us that. Once we decide to be in stocks, GEM uses relative momentum to tell us whether to be in U.S. or non-U.S. stocks.
Moving averages and other forms of trend following can also work. But Zakamulin showed that absolute momentum outperformed 3 different types of moving averages on 155 years of stock market index data. Absolute momentum and reverse exponential moving averages were the only two methods that outperformed buy-and-hold with statistical significance.
On page 98 of my book, I first determine absolute momentum using the S&P 500 index since the U.S. leads world equity markets. I also cite a supporting reference. By doing so, you may occasionally be in aggregate bonds when the trend in U.S. stocks is down, even when non-U.S. stocks are the strongest asset. On page 101 of my book, there is a flowchart that applies relative momentum before absolute momentum for those who prefer doing momentum that way. That may be what you were using.
Investors once thought stop-losses reduce return as they reduce risk exposure. But more recent research shows that stops can enhance return if they are used with care. I have a blog post that discusses this. We found dual momentum more effective than stops in reducing risk exposure and enhancing expected return. Stops add little or no value to dual momentum.
Dual momentum works best when volatility is not too high. Individual countries can have extreme volatility. This can make it difficult to get in and out quickly enough with trend-following momentum without giving up considerable profit. This is also one reason why we do not use stock sectors with our longer-term models.
Country index funds also have less liquidity and higher bid-ask spreads than broad-based index funds. This can create the same price impact and scalability issues as momentum used with individual stocks.
Most leveraged ETFs use daily resets which makes them best suited for day trading. Tracking errors can be considerable with highly leveraged (3X) ETFs held for longer periods. Leveraged ETFs are also not tax-efficient since they give mostly short-term capital gains and losses.
Our QBAT proprietary model is the only model we have that is adaptive enough to use a 2X leveraged ETF.
We designed our models to be in tune with major market movements. There is still considerable short-term volatility with dual momentum. Intra-month drawdowns over 20% have occasionally occurred, and larger ones may happen in the future. Investors should consider that before using any kind of leverage.
Equities are our core assets because they offer the highest long-run risk premium. Shorting stocks is, therefore, climbing an uphill battle. We want every advantage we can get by having the equity risk premium on our side as a tailwind for future performance.
There are also higher costs associated with inverse ETFs. You can own an S&P 500 ETF for an annual expense of 3 basis points, while the expense ratio of an S&P 500 inverse ETF can be 89 basis points or higher.
Because stocks have an upside bias and most of our models are slow-moving, there is not that much profit from short positions by the time you enter and exit. The average bull market since 1942 has lasted 32 months, while the average bear market has lasted only 12 months. Switching to bonds during stock market weakness identified by dual momentum has historically done better than being short the stock market.
International stocks usually outperform U.S. stocks when the U.S. dollar is weak and non-U.S. currencies are strong. This lets us profit from the strength in non-U.S. currencies. When non-U.S. currencies are weak, we are usually out of international stocks. There is thus little reason to use hedged ETFs. Our models automatically deal with and profit from exchange rate exposure.
Low correlation across global stocks is not the main source of relative momentum profits. Profits come more on a global macro level from performance differences between the U.S. economy versus the rest of the world. See the chart in the previous answer.Strong home country bias keeps investors from investing as much as they might otherwise invest in non-U.S. stocks.We do not have that bias and instead profit by going against it.
If stocks have been up a lot recently, it might make sense to wait some and avoid possible short-term mean reversion pullbacks. Because everyone has different risk preferences, when you act is an individual decision.
If you want to trade the same day as your signals instead of waiting until the next day, you can set up a chart on SharpCharts that updates in real-time during trading hours. You can then get your signals and act just before the markets close. SharpCharts is easy to use since it defaults to a one-year lookback. You can bookmark and use the same chart each month to get your signals. Newer printings of my book suggest SharpCharts instead of PerfCharts, which lag a day behind with their data.
Momentum crashes are caused by the short side of long/short momentum portfolios suffering large losses when stocks rebound sharply off V-shaped market bottoms. This happened in 1932 and 2009. Since we do not hold short positions, momentum crashes are irrelevant to us.
I would never pay 87 bps per year to invest in a fund that is unlikely to give a return higher than what you easily earn yourself with GEM. This ETF is supposed to offer more consistency than simple dual momentum. But diversifying with other assets or different strategies is more effective than their strategy of using multiple correlated lookback periods for diversification. My proprietary models diversify with additional assets and different trading approaches, as well as multiple lookback periods. Contact us for more information.
Dual momentum has done well with bonds. We apply dual momentum to bonds in our proprietary models. Lookback periods are different, and there are more bond sectors to evaluate requiring some due diligence. That is why we kept GEM simple by using aggregate bonds.
GEM has been in bonds less than 30% of the time. Bonds have been responsible for only 20% of GEM’s profits.
Aggregate bonds have an average duration of around 6 years. They are not as sensitive to interest rate changes as longer-duration bonds. More than 60% of their holdings are government debt. The remaining bonds are investment-grade and spread out over 6800 holdings. This means their credit risk is minimal. As the chart below shows, their returns have been relatively steady under varied market conditions.
GEM aims to be totally in bonds when stocks are in a bear market. You can see how intermediate bonds have performed during those times.
We think it is reasonable to accept a little duration risk during bear markets in stocks. If you disagree, you can substitute shorter-term government bonds or Treasury bills with only a modest reduction in expected return. We use a variety of bond sectors and cash equivalents in our proprietary models.