April 13, 2015

Understanding Dual, Relative, and Absolute Momentum

Years ago when I first started studying momentum, two things stood out in my mind. The first was most momentum research focused on cross-sectional stock studies looking at the future performance of stocks that had been strong versus stocks that had been weak. This was what interested academics most, since abnormal profit from strong versus weak stocks was relevant to whether or not the stock market was efficient. Researchers have done extensive out-of-sample validation testing of  momentum.[1] As a further check on the robustness of cross-sectional stock momentum, researchers looked at relative strength momentum applied to other assets and asset classes. The found that momentum worked well on almost everything. Past winners consistently outperformed going forward. This prompted Fama and French, two of the founders of efficient market theory, to call momentum the premier anomaly and to say that it is pervasive.

My first momentum research paper in 2011 applied relative momentum to stock market style, industry, and geographic sectors. I wanted to focus on equities because that is where risk premium and investment returns have been the highest over the long-run. I also reasoned it would be easier to apply momentum to market indexes or sectors rather than individual stocks, and that this would have lower transaction costs than momentum applied to individual stocks.

I also noticed that while relative momentum could lead to higher returns than buy-and-hold, it did little or nothing to reduce left tail risk during bear markets. In fact, bear market drawdown could be higher with relative momentum rather than without it. My first momentum paper dealt with this problem by including short and intermediate term bonds as additional asset classes. When the relative strength of stocks became less than the relative strength of short or intermediate term bonds, my model would switch into bonds. This reduced left tail risk considerably.

My next research paper in 2012, “Risk Premium Harvesting through Dual Momentum,” (winner of the 2012 NAAIM Wagner Award for Advances in Active Investment Management) expanded on what I had done earlier by clearly identifying two types of momentum: relative and absolute.[2] 

Researchers had found that both types of momentum were robust across sub-sample periods, look-back periods, and holding periods. Both types of momentum gave higher risk-adjusted returns than buy-and-hold, and both held up well in extensive out-of-sample back testing. Besides comparing and utilizing relative and absolute momentum, my 2012 paper also introduced the concept of dual momentum, a synergistic approach that benefited from the enhanced returns achieved from both forms of momentum, as well as the reduced left tail risk and lower drawdown that come from including absolute momentum.
 
There has been a massive amount of research on relative momentum over the past 20 years. In fact, relative strength/cross-sectional momentum has been one of the most heavily researched areas in modern finance. However, until recently there has been relatively little research done on absolute momentum. My 2013 paper “Absolute Momentum: A Simple Rule-Based Strategy and Universal Trend-Following Overlay” was an attempt to help balance that mismatch. Two of my more recent blog posts have also focused on absolute momentum.

The post  “And the Winner is…” described an 800 year back test of a variation of absolute momentum in Greyserman and Kaminski’s new book, Trend Following with Managed Futures: The Search for Crisis Alpha. The authors looked at 84 equities, fixed income, commodities, and currencies markets as they became available during the years 1200 through 2013. They established long or short equal risk sized positions based on whether prices were above or below their rolling 12-month past returns. The average annual return of this trend following strategy was 13%, with an annual volatility of 11% and a Sharpe ratio of 1.16. In contrast to this, buy-and-hold had a return of only 4.8%, volatility of 10.3%, and a Sharpe ratio of 0.47.  Maximum drawdown for trend following was also significantly lower than for buy-and-hold.

The “Absolute Momentum Revisited” post was my own out-of-sample research of absolute momentum on U.S. stocks back to the year 1927. Absolute momentum continued to show a higher Sharpe ratio, as well as substantially reduced volatility and maximum drawdown compared to a buy-and-hold approach. I concluded the post by saying, “Dual momentum, which uses both relative and absolute momentum, is still the premier momentum strategy for most investors, but absolute momentum may be a useful tool for some others.”

Before returning to dual momentum, I would like to mention a new study by Zakamulin (2015) called “Market Timing with Moving Averages: Anatomy and Performance of Trading Rules.” The author looked at absolute momentum (which he called the "momentum rule") and 5 different moving average rules, including the 10-month (200 day) simple moving average often written about and used as a trend following filter.  The author applied these rules to the S&P Composite stock market index from 1870 to 2010. Estimated transaction costs were accounted for, and all models were invested in U.S. Treasury bills when not in stocks. This 140 year study is now one of the longest back tests of trend following methods, including absolute momentum.

The study found that the majority of the trend following rules had better risk-adjusted out-of-sample performance than buy-and-hold. Absolute momentum was one of two trading rules that showed statistically significant outperformance. The other was a reverse exponential average. Among these rules, absolute momentum.produced the best results. Before getting too enamored with absolute momentum, we need to return to the overall theme of this blog and my book, which is dual momentum.

Here are the updated performance figures from 1974 through March 2015 for the absolute momentum part of dual momentum applied to the S&P 500 and MSCI All Country World Index ex-US (ACWX) indexes used in my Global Equities Momentum (GEM) model featured in my book and tracked on my website. The Barclays Capital U.S. Aggregate Bond Index is the safe harbor asset when absolute momentum exits equities. The GEM model is easy to implement, and its parameters have been validated in many academic papers.


 S&P500              AbsMom S&P500  ACWX              AbsMom ACWX
Annual Return    14.3   12.3   14.0  11.6
Annual Std Dev    12.2   15.4   12.2  17.2
Sharpe Ratio    0.66   0.41   0.64  0.32
Max Drawdown   -29.6  -51.0  -23.1 -57.4

We see that absolute momentum gave an impressive improvement in risk-adjusted performance compared to performance without the addition of absolute momentum.

Next, we compare the performance of absolute momentum to the performance of relative momentum that switched between the S&P 500 and ACWX indexes based only on their relative strength to each other. More importantly, we also see what happens when we combined both relative and absolute momentum, creating what I call dual momentum.


     Dual     Momentum   Relative Momentum S&P500     AbsMom   ACWX     AbsMom
Annual Return       17.7     14.7    14.3    14.0
Annual Std Dev       12.4     15.8    12.2    12.2
Sharpe Ratio       0.89      0.53    0.66    0.64
Max Drawdown      -17.8    -54.6   -29.6   -23.1

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 GEM Performance and Disclaimer pages for more information.


Relative momentum, like absolute momentum, gave higher returns than the indexes themselves. Relative momentum, however, unlike absolute momentum, did nothing to reduce volatility or tail risk/maximum drawdown. If I were forced to choose between using relative or absolute momentum, I would choose absolute momentum. However, as I clearly point out in my book, you do not have to pick one over the other. You can use both simultaneously, and that is where the magic happens - combining absolute and relative momentum to create dual momentum.

We see that dual momentum gave us a substantial increase in average and risk-adjusted returns compared not only to the underlying indexes, but also to relative and absolute momentum individually. In addition, dual momentum's maximum drawdown is the lowest of all.

With dual momentum, the whole is greater than the sum of its parts. Dual momentum is clearly the preferred momentum strategy here with respect to large cap U.S. and non-U.S. equity indexes.[3]  That is why I call this blog “Dual Momentum,” and my book Dual Momentum Investing: An Innovative Strategy for Higher Returns with Lower Risk.

[1] Geczy and Samonov (2012), for example, showed that momentum was highly effective on U.S. equities back to 1801.
[2] Some academics refer to absolute momentum as time series or trend following momentum. However, both relative and absolute momentum are based on economic time series (asset prices), and both are trend following. Relative strength momentum looks at the trend of one asset versus other assets, while absolute momentum looks at the trend of a single asset with respect to its own past.
[3] On the Performance page of my website, I show historical returns and track the real time performance of four other dual momentum models.
 

March 27, 2015

Sustainable Momentum Investing: Doing Well By Doing Good

Socially Responsible Investing (SRI), also known by the more recent name Sustainable Responsible Impact investing, is the major application of ethical and social criteria, as well as financial considerations, in making investment decisions. SRI recognizes and incorporates societal needs and benefits in the selection and management of investment portfolios.

SRI has a "feel good" aspect to it, but investors also want to know if they are sacrificing potential returns by adhering to their social ideals. We will look to see if SRI makes sense economically, as well as socially and ethically, and, if it does, then how investors can use SRI for momentum-based investing.

Early History of SRI

SRI first dates back to the Quakers who, in their 1758 yearly meeting, prohibited members from participating in the slave trade. Their Friends Fiduciary investment service has existed since 1892 and continues to manage Quaker assets following SRI guidelines.
 
Another early adopter of SRI was John Wesley (1703-1791), one of the founders of the Methodist Church. Wesley’s sermon on “The Use of Money” outlined the basic tenets of social investing – do not harm others through your business practices and avoid industries which can harm the health of others. In the 1920s, the Methodist Church of Great Britain adopted this policy by investing in the UK stock market while avoiding companies involved with alcohol and gambling.

The first public offering of a socially-screened investment fund was in 1928 when an ecclesiastical group in Boston established the Pioneer Fund. In 1971, a Methodist group organized the PAX World Fund, which appealed to investors who wanted to be sure their profits were not coming from weapons production.  Two years later, SRI went mainstream when Dreyfus, a major mutual fund marketer, launched the Third Century Fund, which grouped together companies noted for their sensitivity to the environment and their local communities.

Social Change through SRI

In the 1980s, SRI became more widespread due to its negative screening of investments in South Africa. SRI practitioners were able to put pervasive pressure on the South African business community that eventually forced a group of businesses representing 75% of South African employers to draft a charter calling for the end of apartheid. Nelson Mandela himself remarked that the University of California's multi-billion dollar divestment was particularly significant in ending white minority rule in South Africa. .

SRI Performance

Although SRI has effectively used market forces to help bring about social change and has been emotionally rewarding to its participants, there has been a long-standing question of whether SRI performance has suffered due to the restricted opportunities available to SRI investors. Over the years, there have been many studies and meta-studies of SRI versus conventional investment performance. A number of studies from the 1990s and 2000s showed no statistical significance between the returns of socially responsible mutual funds and those of conventional funds. One objective survey and assessment of the subject that was the Royal Bank of Canada's 2012 report "Does Socially Responsible Investing Hurt Investment Returns?" The conclusion they reached, based on all the available evidence to date, was that investors had been no worse off with SRI investing than with conventional investing.

Evolution of SRI

In recent years, SRI evolved from exclusionary screening out of investments to include a more proactive approach toward Corporate Social Responsibility (CSR). CSR is a blend of both negative screening and positive selection in order to maximize financial return within a socially aligned investment strategy. Examples of negative screening factors are company involvements with gambling, alcohol, tobacco, weapons, under-age workers, animal testing, and damage to the environment. Examples of positive selection criteria are pollution control, community involvement, energy conservation, consumer protection, human rights, product safety, favorable employee working conditions, and renewable energy utilization. CSR oriented investment programs might also vote their proxies to advance ethical business practices, such as diversity, fair pay, and environmental protection.

CSR further evolved and expanded to include a broader set of Environmental, Social, and Governance (ESG) factors. Interestingly, ESG was soon seen to have practical benefits for the companies that employed these criteria, as well as for investors in those companies. Good citizenship has proven to be good for business.

Performance of ESG Companies

There are a number of reasons that can explain improvements in performance due to ESG. Corporate responsibility can create good relationships with governments and communities, as well as reduce the risks of onerous regulations and conflicts with advocacy groups. It can also influence how consumers perceive a brand and therefore serve a similar role to advertising. This can lead to higher sales and more loyal customers. In addition, corporate responsibility can have a positive influence on companies’ ability to attract and retain talented employees and maintain productive workforces.

According to DB Climate Change Advisors in their 2012 meta-analysis of more than 100 academic studies, “Sustainable Investing: Establishing Long-Term Values and Performance,” 100% of studies showed that companies with high ESG ratings exhibited financial outperformance and had a lower cost of capital, indicating they were less risky than companies with lower ESG ratings. Seeing all these benefits, the number of companies issuing sustainability reports has  skyrocketed. According to the 2013 KPMG Study of Corporate Responsibility Reporting, 93% of the world's 250 largest companies and 86% of the largest U.S. companies (by revenue) now publish annual sustainability reports.

However, what interests us most as investors is how investments in ESG oriented companies have performed relative to other companies. According to the DB Climate Change Advisors report, 89% of highly-rated ESG companies exhibited market-based outperformance and superior risk-adjusted stock returns.

A typical study by Eccles et al. (2011) compared the performance of 180 large U.S. firms by matching 90 high sustainability firms with 90 low sustainability firms. Beginning in 1993, $1 invested in the high sustainability portfolio would have grown to $22.60 by 2010, while the low sustainability portfolio grew to only $15.40.

Rapidly Growing Investor Interest

Companies doing well by doing good have not gone unnoticed by investors. The outperformance in the stocks of high sustainability firms has been attracting considerable investor interest. According to a 2015 survey by the Morgan Stanley Institute for Sustainable Investing, over 70% of active individual investors describe themselves as interested in sustainable investing, and nearly 2 in 3 believe sustainable investing will become more prevalent over the next 5 years.

Looking at recent growth, the global sustainable market has risen from $13.1 trillion at the start of 2012 to $21.4 trillion at the start of 2014, and from 21.5% to 30.2% of all professionally managed assets. Europe has the highest percentage of sustainable assets at 63.7%. But the U.S. has been the fastest growing region over this period and now has 30.8% of all global sustainable assets. The amount of funds invested in the U.S. using social criteria grew from $40 billion in 1984 to $625 billion in 1991 and to $1.5 trillion in 1999.

According to the most recent biennial "Report on U.S. Sustainable, Responsible, and Impact Investing Trends" by the Forum for Sustainable and Responsible Investing (US SIF Foundation), the number of ESG mutual funds in the U.S. was 456 at the start of 2014, up from 333 two years earlier. Assets in U.S. sustainable funds were $6.57 trillion at the start of 2014, up from $3.74 trillion at the start of 2012. This is a growth of 76% in just two years. Assets held in some form of sustainable investment now account for more than $1 out of every $6 under professional management, which is up from $1 out of every $9 in 2012. Investors realizing that ESG oriented funds, which in the past showed no disadvantage to conventional funds, have evolved into ESG funds that now offer superior investment performance when compared with conventional funds.

Dual Momentum with ESG

In my book and on my website I show how dual momentum (a combination of relative strength momentum and trend-following absolute momentum) can enhance and improve the performance of different kinds of investment portfolios, such as global equities, balanced stocks and bonds, equity sectors, and fixed income. We will see now what happens when we apply dual momentum to the world of sustainable investing.

I usually prefer to use low cost index ETFs as investment vehicles. However, that may not be the best approach with ESG funds. There are two reasons for this. First, the difference between a conventional index ETF's annual expense ratio and the average equity mutual fund's annual expense ratio of 1.08 is not nearly as great for sustainable index funds. For example, the  annual expense ratios for the Vanguard and iShares S&P 500 conventional index fund ETFs are .05 and .07, respectively. The annual expense ratios of the two KLD 400 Social Index ETFs, on the other hand, are much higher at .50. Based on expense ratios, sustainability index ETFs are at a decided disadvantage to their conventional index counterparts.

The second reason that sustainability index funds can be problematic is because of their short performance records. The earliest U.S. based SRI index is the Domini 400 Social Index, now known as the MSCI KLD 400 Social Index. It did not begin until May 1990, and data for it is not readily available. The oldest SRI index fund (Vanguard FTSE Social Index) was established only 15 years ago in May 2000.[1]

For these reasons, as well as the reason that active management might add some value in an area such as sustainability, where more informed choices might be better than the mechanical rules, we will apply dual momentum to the oldest, actively managed, sustainable equities-based mutual funds.

Funds Used

The three sustainability equity funds that have track records longer than 25 years are Dreyfus Third Century (DRTHX) that began in April 1972, Parnassus (PARNX) that started in May 1985, and Amana Income (AMANX), that began in July 1986.[2] 

Looking at the details of these funds, Dreyfus Third Century's only explicit exclusionary screen is for tobacco products. However, Third Century has a strong ESG orientation by reason of their mandate to invest in companies that contribute to the enhancement of the quality of life in America, with special emphasis on the environment, product safety, employee safety, and equal opportunity employment. Third Century’s annual expense ratio is 1.01. Retail shares of the fund are closed now to new investors. However, the institutional shares (DRTCX), with an expense ratio of .91, can still be purchased ($1000 minimum) through financial professionals and brokerage firms. 

Parnassus Fund has an annual expense ratio of .86. This fund screens out companies involved with alcohol, tobacco, gambling, nuclear power, weapons, and Sudan. Parnassus engages in shareholder activism and community investment. The fund has a strong ESG orientation with its mandate to invest in companies having sustainable competitive advantages and ethical business practices. Parnassus also prefers to buy out-of-favor stocks.

Besides incorporating ESG factors and exclusions for alcohol, tobacco, gambling, and pornography, Amana Income (AMANX) avoids companies with high debt-to-equity ratios and large receivables compared to total assets. Their emphasis on companies with stable earnings, high quality operations, and strong balance sheets free of excessive debt gives Amana a tilt toward quality, which is now recognized in academic circles as a beneficial risk premium factor.[3]

In addition, Amana prefers to hold shares in companies where management has a sizable stake, and the fund will sell shares in companies where insiders are selling. There is a large body of academic literature confirming that insiders are better informed and earn abnormal profits from their trades.[4]  Amana Income has an expense ratio of 1.14, plus .25 in 12b-1 marketing fees. However, institutional shares (AMINX) requiring a minimum investment of $100,000 are available with an expense ratio of .90 and no 12b-1 fees.

Here are performance figures through February 2015 for these three sustainability funds starting from July 1986, when performance data first became available for Amana Income. We also include the Vanguard 500 Index fund (VFINX), based on the S&P 500 index, as a benchmark. Vanguard 500 Index has an expense ratio of .17 [5]


DRTHX PARNX AMANX VFINX
Ann Rtn 9.80 12.63 9.71 11.35
Std Dev 15.79 21.71 12.02 15.32
Sharpe 0.37 0.39 0.48 0.47
Max DD -59.98 -47.98 -34.70 -50.97

We see that Parnassus has a higher return than the S&P 500 with around the same maximum drawdown, while Amana Income has about the same Sharpe ratio as the market with a lower maximum drawdown. The lack of performance homogeneity among these funds is a good thing for relative strength momentum investing. More diversity in performance creates more opportunities for profit. So let us see what happens now when we apply dual momentum to these funds.

First though, I should mention a potential problem of using higher cost actively managed funds. The performance of actively managed funds may revert toward the mean of all funds and be overtaken by the performance of lower-cost index funds. However, this may not be such a problem here for two reasons.

First, we are not selecting actively managed funds based on superior past performance that might subsequently mean revert. We are simply using the three sustainability funds that have the longest track records. Second, we can easily include a low-cost stock index fund in our dual momentum portfolio. Dual momentum is adaptable. If there is a falloff in performance of our actively managed funds, the relative strength component of dual momentum can automatically move us to our lower-cost index fund. This is why we can confidently use actively managed funds within a dual momentum portfolio framework.[6]

Performance Results

Below is the same performance we saw above but with the addition of a dual momentum portfolio made up of all three sustainability funds, the Vanguard 500 index fund for the reason given above, and the Vanguard Total Bond fund (VBMFX) as a refuge for when absolute momentum takes us out of equities. The operating logic behind this model that we call ESG Momentum (ESGM) is the same as for our Global Equities Momentum (GEM) model and is fully disclosed in my book, Dual Momentum Investing: An Innovative Strategy for Higher Returns with Lower Risk


   DRTHX   PARNX  AMANX    VFINX   VBMFX    ESGM
Ann Rtn 9.80 12.63 9.71 11.35 6.48 16.91
Std Dev 15.79 21.71 12.02 15.32 3.90 13.96
Sharpe 0.37 0.39 0.48 0.47 0.69 0.87
Max DD -59.98 -47.98 -34.7 -50.97 -5.86 -22.73
% Used 12 35 13 17 23 100

Results are hypothetical, are NOT an indicator of future results and do NOT represent returns that any investor actually attained. This is not a recommendation to buy or sell any security. Please see our Disclaimer page for more information.

We see that the Sharpe ratio of our ESGM model portfolio was more than twice as high as the average Sharpe ratio of the four equity funds, and the ESGM maximum drawdown was less than half as large.[7] By being in bonds at the right time, ESGM was able to bypass the full severity of bear market drawdowns.

ESGM was in our three sustainability funds 78% of the time that it was in equities. So our mission was accomplished of being mostly in investments that contribute to advancements in social, environmental, and governance practices, while simultaneously giving us exceptional risk-adjusted returns by using dual momentum.

A link to the ESGM model's monthly and annual results is now on the Performance page of our website. It will be updated monthly along with the rest of our dual momentum models. Those wanting news and additional information on sustainability can visit GreenBiz, Social Funds, and US SIF.

     Past performance is no assurance of future success.

[1] The two social responsibility ETFs, KLD and DSI, began in 2005 and 2006 respectively.
[2] PAX World Balanced began in August 1971 and CSIF Balanced Portfolio began in October 1982, but both funds have large bond allocations. 
[3] See Asness et al. (2013), "Quality Minus Junk.".
[4] For example, see Jeng et al. (2003) "Estimating the Returns to Insider Trading: A Performance Evaluation Perspective" or  Cohen, Malloy, and Pomorski (2012), "Decoding Insider Information".
[5] We could have used Vanguard's Admiral shares with an expense ratio of .05 or a low-cost S&P 500  ETF, but we wanted to be consistent with the retail shares we used for our socially responsible funds.
[6] There are many more ESG oriented funds, both index and actively managed, that one can choose.  The three used here were selected based on their longevity.
[7] If one uses the oldest no-load SRI bond fund, Parnassus Fixed Income (PRFIX), in place of Vanguard Total Bond from the inception of PRFIX in October 1992, the metrics improve to 17.31% for annual return, 13.97 for standard deviation, and 0.89 for Sharpe ratio. Maximum drawdown remains at -22.73%.  

February 24, 2015

Do the Right Thing: Consider Persistence and Reversion

I used to always cut fruits and veggies in the wrong directions. I finally got around this problem by  turning them in the opposite direction to the way I initially wanted to cut them. Similarly, many investors and investment managers are making investment decisions the wrong way and need to reverse how they are going about this.

This problem began with the random walk hypothesis (RWH). That idea, popular in the 1960s and 1970s, said that stocks fluctuate randomly (in statistical terms, are independent and identically distributed). RWH is synonymous with the concept of efficient markets. As such, it eliminated serious interest in tactical asset allocation, trend following, or momentum investing among both academics and most institutional investors.

Some practitioners, however, were creating a substantial body of anecdotal evidence that stock fluctuations were not random, but instead showed short and long-term mean reversion, as well as intermediate- term serial correlation. 

Stock exchange specialists and brokerage firm trading desks made large profits going against short-term customer order flow, which gave them high short-term mean reversion profits. The success of momentum traders like Jack Dreyfus and Richard Driehaus showed that stocks could also exhibit price continuation (momentum). Successful long-term value investors, buying depressed stocks that would eventually recover and outperform the market, indicated that one can also earn long-term mean reversion profits from stocks.

In the mid to late 1980, academics began to catch up with practitioners in discovering the flows of RWH. Ironically, Fama and French (1988), two of the pioneers of efficient market theory, were among the first to show that stocks mean revert based on a 3 to 5-year time horizon. Around the same time, Lo and MacKinlay (1988) and Poterba and Summers (1987) came up with compelling evidence to reject RWH. In the early 1990s, Jegadeesh and Titman (1993) in their seminal papers demonstrated convincingly that price continuation momentum exists on a 3 to 12-month basis. Furthermore, they and others showed that stocks are mean-reverting when looking at one-month returns. They therefore skipped those returns when looking at intermediate-term stock momentum.

Showing just how far academics have come in accepting  12-month momentum (indicating positive serial correlation) , one-month mean reversion, and 3 to 5-year mean reversion, all three of these factors are now in the online Ken French data library for researchers to use in their studies.

So how does all this relate to how investors and investment managers are making poor investment decisions? First, there is still a cultural affinity to RWH despite all the evidence to the contrary. This leads many investors to ignore the profit opportunities inherent in momentum investing.

Next, investors and investment professionals often focus on the wrong time frames in judging investments. Goyal and Wahal (2008) report  that plan sponsors and institutional asset managers choose investment managers based greatly on performance over the past 3 years. Yet we know now that 3-year performance is mean reverting, and strong performance over that time frame is not indicative of similarly strong future results.

As another example, the Morningstar rating methodology weights 3-year performance more heavily than 5 or 10-year performance. If longer term performance is unavailable, ratings are based entirely on 3 year performance. The Vanguard Research report "Mutual Fund Ratings and Future Performance" (2010) found that from February 1992 through August 2009, there was no systematic outperformance by funds rated 4 or 5 stars by Morningstar or underperformance by funds rated 1 or 2 stars. The median 5-star fund's excess return was not consistently higher than the median 1-star fund's excess return.  

Vanguard also reported that investment committees typically use a 3-year window to evaluate the performance of their portfolio managers.  Yet we know that investors and asset managers should focus more on performance outside the 3 to 5-year performance window due to mean reversion using that time frame.

The other problem in performance evaluation is often found among individual investors who overreact to short-term results. When I managed investment partnerships in the 1970s and 1980s, my investors would invariably want to add funds after a single month of strong performance, and, conversely, they would almost never add to their accounts following a significant down month. Short-term mean reversion implies that they should have been doing just the opposite. Dalbar's annual "Quantitative Analysis of Investor Behavior" supports the idea that investors overreact to short-term performance by buying highs and selling lows instead of keeping the big picture in mind, which seriously harms their long term returns. [1]

Doing what may be the wrong thing has even been adopted as an investment strategy by the Global X JP Morgan Sector Rotation ETF (SCTO). This fund buys the strongest U.S. stock market sectors based on  the prior one month’s performance. 

So there you have it. Investment committees, institutional asset managers, Morningstar, and others emphasize 3-year past performance as an indicator of future success, when the just opposite is likely to be true. Adding to this confusion, individual investors and others chase after strong 1-month performance by buying these short-term rallies when they would be better off buying dips.  

Investors and investment managers take heed. Do the right thing. Read the literature. And, if you need to, don’t forget to turn your fruits and veggies in the right direction.

[1] One of the advantages of using a trend following filter like absolute momentum (which is half of dual momentum) to identify regime change and reduce drawdown is that can also reduce investors' loss aversion, ambiguity aversion, and the flight-to-safety heuristic. It may therefore give investors more confidence to stay with the trend and even buy dips.

January 21, 2015

And the Winner Is...

Until recently, the longest back test using stock market data was Geczy and Samonov’s 2012 study of relative strength momentum called “212Years of Price Momentum: The World’s Longest Backtest: 1801-2012”. The length of that study has now been exceeded by an 800 year back test of trend following in Greyserman and Kaminski’s new book, Trend Following with Managed Futures: The Search for Crisis Alpha. The authors looked at 84 equities, fixed income, commodities, and currencies markets as they became available from the years 1200 through 2013. They established long or short equal risk sized positions based on whether prices were above or below their rolling 12-month past returns.

The average annual return of this strategy was 13% with an annual volatility of 11% and a Sharpe ratio of 1.16. In contrast to this, buy-and-hold had a return of 4.8%, volatility of 10.3%, and a Sharpe ratio of 0.47.  Maximum drawdown for trend following was also substantially lower than for buy-and-hold. Equities alone with trend following showed a substantially higher Sharpe ratio and nearly a 3% greater annual return than with buy-and-hold from 1695 through 2013.


However, let’s not just look at trend following on its own.  Let’s also compare it to other possible risk reducing or return enhancing approaches and see what then looks best. We will base our comparisons on the performance of U.S. equities because that is where long-run risk premium and total return have been the highest. We also have U.S. stock market data available from the Kenneth French data library all the way back to July 1926.

We will first compare trend following in the form of absolute momentum to seasonality and then to the style and factor-based approaches of value, growth, large cap, and small cap.[1] We will also see if it makes sense to combine these with trend following.

For seasonality, we look at the Halloween effect, sometimes called “Sell in May and go away…” This has been known to practitioners for many years. There have also been a handful of academic papers documenting the positive results of holding U.S. stocks only from November through April. The following table shows the results of this strategy compared with absolute momentum applied to the broad U.S. stock market from May 1927 through December 2014. With 10-month absolute momentum, we are long stocks when the excess return (total return less the Treasury bill rate) over the past 10 months has been positive.[2] Otherwise, we hold Treasury bills. We also hold Treasury bills when we are out of U.S. stocks according to the Halloween effect (in stocks Nov-Apr, out of stocks May-Oct). 



                                                             Seasonality




US Mkt
Nov-Apr
AbsMom
Nov-Apr+AM
Annual Return
11.8
9.6
11.5
7.4
Annual Std Dev
18.7
12.1
12.9
9.4
Annual Sharpe
0.42
0.48
0.58
0.39
Maximum DD
-83.7
-56.7
-41.4
-43.8







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 Disclaimer page for more information.

We see that the 6-month seasonal filter of U.S. stock market returns substantially reduces volatility and maximum drawdown but at the cost of reducing annual returns by over 200 basis points. Trend following absolute momentum, on the other hand, gives a greater reduction in maximum drawdown than seasonality with almost no reduction in return. There is little reason to consider seasonal filtering when absolute momentum gives a greater reduction in risk without diminished returns.   

The table below shows the U.S. market separated into the top and bottom 30% based on book-to-market (value/growth) and market capitalization (small/large). We see that value and small cap stocks have the highest returns but also the highest volatility and largest maximum drawdowns. 

                                                                 Style


US Mkt
Value
Growth
Large
 Small
Annual Return
11.8
16.2
11.3
11.5
 16.6
Annual Std Dev
18.7
25.1
18.7
18.1
 29.3
Annual Sharpe
0.42
0.46
0.39
0.42
 0.41
Maximum DD
-83.7
-88.2
-81.7
-82.9
-90.4

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 Disclaimer page for more information.

Most academic studies ignore tail risk/maximum drawdown, but these can be very important to investors. Not many of us would be comfortable with 90% drawdowns.[3] In addition, on a risk-adjusted basis (Sharpe ratio), neither small cap nor value stocks appear much better than growth or large cap stocks. This is consistent with recent academic research showing a lack of small size premium and a value premium that is associated mostly with hard-to-trade micro-cap stocks.[4] Let’s now see what happens now when we apply absolute momentum to these market style segments:

                                                       Style w/Absolute Momentum


MktAbsMom
ValAbsMom
GroAbsMom
LgAbsMom
SmAbsMom
Annual Return
11.5
13.3
10.3
11.5
13.9
Annual Std Dev
12.9
17.2
13.3
12.5
21.1
Annual Sharpe
0.58
0.53
0.48
0.60
0.46
Maximum DD
-41.4
-66.8
-42.3
-36.2
-76.9

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 Disclaimer page for more information.

In every case, adding absolute momentum reduces volatility, increases the Sharpe ratio, and substantially lowers maximum drawdown. The biggest impact of absolute momentum, however, is on large cap stocks, followed by the overall market index. The use of a trend following absolute momentum overlay further reduces the relative appeal of value or small cap stocks.   

One may wonder why large cap stocks respond better to trend following. The answer may lie in a study by Lo and MacKinlay (1990) showing that portfolio returns are strongly positively autocorrelated (trend following), and that the returns of large cap stocks usually lead the returns of small cap stocks. Since trend following lags behind turns in the market, investment results should be better if you can minimize that lag by being in the segment of the market that is most responsive to changes in trend. That segment is large cap stocks, notably the S&P 500 index, which leads the rest of the market.[5]

In my book, Dual Momentum Investing: An Innovative Strategy for Higher Returns with Lower Risk, I give readers an easy-to-use, powerful strategy incorporating both relative strength momentum to select between U.S. and non-U.S. stocks, and absolute momentum to determine market trend and choose between stocks or bonds. I call this dual momentum model Global Equities Momentum (GEM). And what index is the cornerstone of GEM? It is the S&P 500, the one most responsive to trend following absolute momentum and that gives the best long-run risk-adjusted results. 

Einstein said you should keep things as simple as possible, but no simpler. One can always create more complicated models or include more investable assets. But as we see here, trend following momentum is best when it is simply applied to large cap stocks.


[1] There is a study showing the effectiveness of absolute momentum back to 1903 by Hurst et al. (2012).
[2] We use 10-month absolute momentum instead of the more popular 10-month moving average because absolute momentum gives better results and 35% fewer trades, which means fewer false signals and whipsaw trades. See our last blog post, "Absolute Momentum Revisited". 
[3] The next largest maximum drawdown was 64.8 for value and 69.1 for small cap on a month-end basis, which were again the largest ones. Intra-month maximum drawdowns would have been even higher.
[4] See Israel and Moskowitz (2012).
[5] U.S. stock market returns have also led non-U.S. stock market returns. See Rapach, Strauss, and Zhou (2012).