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 frequently if you check for signals too frequently.
It usually 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 over time.
There are also other reasons why momentum investing has not yet caught on. 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 to those who think more complex approaches have more merit. This is a common misconception. Some investors also have prejudices against newer styles of investing or investing in indices rather than in stocks. Interestingly, 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. Dual momentum investing also triggers familiarity bias and home country bias that keep some from using it.
One risk is that history is unreliable, and the future may not be like the past. However, there are several hundred years of out-of-sample performance supporting both relative and absolute momentum. There are also behavioral reasons why 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 the stock indices we use are much more scalable than individual stocks. They are also less popular as momentum investments.
There is risk associated with the trend-following component of dual momentum being slow-moving in order to reduce whipsaws. This means much of the short term volatility of the stock market still exists with dual momentum. Additionally, there are re-entry lags when a new bull market begins after being in bonds during bear markets.
Our Global Equities Momentum (GEM) model underperformed its benchmarks in 1979-80 and 2009-11. No strategy outperforms all the time. Investors should understand that. Future drawdowns may be larger than those during the past. Please see our Disclaimer page for additional risk factors.
Many other models use many parameters and overfit a limited amount of data. These may not hold up going forward. GEM is simple, logical, and based on momentum that has been tested back to at least the early 1800s. GEM has also done well out-of-sample. See here.
The number of sectors depends on one’s attitude toward reward and risk. Fewer sectors mean higher expected returns and higher volatility. You can search for parameters to create a sector rotation model suited to your individual risk preferences. Be aware though that data-mined parameters may not hold up well out-of-sample.
I show here the performance of DMSR using additional data since my book was published. DMSR no longer looks as attractive as broader-based dual momentum models like GEM. 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 we use. They make up 17% of that index based on market capitalization. Investors are more prone to panic to sell more volatile assets like EMs during times of crisis. Those who want to add an extra allocation to EMs should proceed cautiously.
The negative correlation you see now between stocks and bonds has not always been there. So long-term bonds may not always be the best core asset when stocks are weak.
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 generally do better with shorter lookback periods. My enhanced GBM model, therefore, uses different parameters than GEM. Enhanced GBM is one of the proprietary models I license to investment professionals. 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 not difficult to put together something that looks good in hindsight. The unemployment rate may have been useful as a stock market timing indicator back to 1970. But it gives worse results than the trend alone before that time.
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 multiple lookback periods and several trend-following variations to make the models more adaptive. Our proprietary models also apply dual momentum to bonds and additional assets where it has worked well. In addition to enhanced GEM, we also have balanced and conservative proprietary models to accommodate different investor risk preferences. Please see the Dual Momentum Proprietary Models page or contact us for more information on our proprietary models.
Those who want to reduce the short-term volatility and systematic noise of GEM might want a modest permanent allocation to short or intermediate-term bonds as suggested at the end of chapter 8 in my book. To reduce trend-following tracking error, one could have a modest permanent allocation to an S&P 500 or All-World equity index fund. Better still would be a modest allocation to a relative momentum strategy switching between U.S. and non-U.S. equity index funds. Another way to do this would be by allocating to other non-correlated investment strategies. We use a variety of assets and momentum approaches to diversify in 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. Your signals could still be derived from an ex-U.S. all-country world stock ETF as shown in my book.
Our research shows they do not improve GEM’s results. Even if they did, we would be cautious. Factor-based funds are often subject to data mining and selection biases in their construction. Real-time results from factor-based funds have not been encouraging. This may get worse in the days ahead as the amount of capital in factor-based funds continues to grow. See our blog posts here and here.
There are a number of them mentioned in the reviews of my book and 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 Index ex-US together with the S&P 500 in order to be all-inclusive and avoid selection bias. Selection bias is where you select a subset of the data in order to make your results look better or worse. EAFE omits Canada and emerging markets which represent a significant 24% of the world’s equity market. 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 in late 1988. I see no valid reason to invest with MSCI EAFE that has had considerably lower returns than MSCI ACWI ex-U.S. Using EAFE instead of ACWI ex-U.S misrepresents our models and tries to make them look worse than other models that incorporate emerging markets.
A major 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. Even if they were not, to get accurate relative strength signals you would need to deduct 30% of the dividends from U.S. indices or 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 impose their own ideas often 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 or ETF Screen portfolio to determine the GEM signals.
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. Different variations of dual momentum or trend following show similar results.
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 exactly. To reduce feelings of regret no matter what happens, you may want to use this approach. Another possibility is to wait a few days 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 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 from Treasury bills without any downside risk.
Accelerating Dual Momentum is an example of what not to do when working with models. It is highly data mined using a limited amount of data. It also lacks good theoretical justifications for much of what it does. You can read more specifics in my blog post, “Perils of Data Mining.”
Dual momentum has a trend following component that lags behind when a new bull market begins. That is the cost of 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 need to understand how 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 profits. Second, this bull market has been one of the longest in history. This means there has also been no 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. You could say that GEM has lost its effectiveness if you believe U.S. stocks will always outperform non-U.S. stocks or there will never be another bear market.
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 at a historically low rate now but might be higher when ETF investors realize their profit. Many investors also don’t know that over 40% of the long-run return of the S&P 500 comes from dividends. These are taxed whether or not they are earned in an ETF. Those who want to defer all income, including interest and dividends, can do so by using dual momentum in a retirement plan or through 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 do so with 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. They say there is not much difference in performance between the two indices. That is close to being 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. So dual momentum has done much better with the ACWI ex-U.S. which is more volatile than the EAFE. Using MSCI EAFE instead of MSCI ACWI ex-U.S. decreases GEM’s diversification and lowers its return by 130 bps annually since MSCI ACWI ex-U.S. became usable in 1989. This site does not penalize other models accordingly. Those models are able to benefit from emerging market ETFs and indices. They are also able to use ETFs and indices with considerably less popularity and trading volume than the MSCI ACWI ex-U.S.
Because you can use ensemble methods to look at many things at once does not mean you should. 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 stock momentum use lookback periods of 6 or 12 months. The ensemble method you mention shows a fall-off in results with lookbacks under 3 months and over 12 months.
There is some benefit in using a modest number of lookback periods. We use different ones in our proprietary models. But they are selected based on logical reasons, not randomly. Reducing specification risk by incorporating exogenous factors or different trading approaches makes more sense than using a wide array of lookback periods that tend to be highly correlated.
Also, you cannot correctly judge the probability of something happening after it has already happened. You have 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 other momentum stock funds. This due to its having a focused portfolio (around 125 stocks), relatively low fees (15 bps), lower selling than buying thresholds to reduce turnover, and two lookback periods. But the main contributing factor to the fund’s good performance has been its heavy weighting toward 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 when large-cap growth stocks get back to normal.
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 can create 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 much 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 this way. 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 is generally 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 a lookback period of 3 to 12 months. Longer lookback periods minimize 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.
A 3-month look back has worked well with GEM back to 1979. But over a longer period, a 12-month look back performed better. 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 and 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. For more on stock momentum, see our review of the book Quantitative Momentum.
We were constrained by the lack of non-U.S. stock index data when I wrote my book. Additional data we acquired since then has validated the outperformance of GEM. In addition, both relative strength and absolute momentum were found to outperform buy and hold when tested back to 1801 by Geczy & Samonov (2015). Absolute momentum showed superior returns and less downside risk going back 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 returns. So we want to be in them as long as their trend is positive. We use absolute momentum to tell us that. Once we decide to be in stocks, we use relative momentum to tell us whether to be in U.S. or non-U.S. stocks.
Moving averages and other forms of trend following 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 the market 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.
Stop-losses were once thought to reduce return whenever they reduce risk exposure. But more recent research shows that stops can actually enhance return if they are used with care. I have a blog post that discusses this. We found dual momentum more effective than stop losses in reducing risk exposure and enhancing expected return. Stops do not add much value when using dual momentum.
Dual momentum works best when volatility is not too high. Individual countries can have very high volatility. This can make it difficult to get in and out using trend-following momentum without giving up considerable profit. This is also one of the reasons we do not use small-cap indices or stock sectors. Additionally, country index funds can have less liquidity and higher bid-ask spreads than broad-based index funds. This can create the same potential price impact and scalability issues as momentum applied to individual stocks.
Most leveraged ETFs use daily resets which make them best suited for day trading. Daily resets are also not tax-efficient since leveraged ETFs give mostly short-term capital gains and losses.
Our models are designed to be in tune with major market movements. There is still considerable short-term volatility with dual momentum. Intra-month drawdowns close to 20% have occasionally occurred, and larger ones may happen in the future. Investors should consider that before using 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 to serve 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 our models are slow-moving, there is often 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.
There is a tendency for international stocks to 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, GEM is usually out of international stocks. There is thus little reason to use hedged ETFs. GEM automatically deals with and can profit from exchange rate exposure.
Low correlation across global stocks is not the main source of relative momentum profits. The benefits come more on a global macro level from performance differences between the U.S. economy (reflected in the strength or weakness of the U.S. dollar) 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 can instead profit by going against it.
If stocks have been up a lot recently, it might make sense to wait a little to 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’s open, you can set up a chart on SharpCharts that updates real-time during trading hours. You can then get your signals 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 GEM signals. Newer printings of my book suggest using SharpCharts instead of PerfCharts, which lag a day behind the 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 likely to give a return no higher than what you easily earn yourself with GEM. This ETF is supposed to offer more consistency than simple dual momentum. But diversifying with non-correlated assets or different strategies should be more effective than their strategy of using correlated lookback periods for diversification. My proprietary models diversify with additional assets and different dual momentum trading approaches. Contact us for more information.
Dual momentum has done well when used with bonds. We apply dual momentum to bonds in our proprietary models. The lookback periods are different, and there are more sectors to evaluate. This requires some due diligence. That is why we designed GEM to simply use aggregate bonds instead.
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. Over 60% of their holdings are government debt. The remaining bonds are investment-grade 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.
Absolute momentum exits equities and enters bonds when it identifies a bear market in stocks. This often happens early in a recession. That usually leads to falling aggregate demand falls and the FED lowering interest rates. When stocks are weak, there is also a tendency for investors to move their capital from stocks to bonds. This also increases the demand for bonds.
GEM aims to be totally in bonds when stocks are in a bear market. You can see below 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 a modest reduction in expected return.