This blog is an adjunct to our Optimal Momentum investing website which can be found through the Website tab. It contains news and other information that may be of interest to momentum investors.

Monday, November 10, 2014

Individual Stock Momentum - That Dog Won't Hunt

Dead or dying academic ideas latched on to by unwary institutional investors litter the investment graveyard landscape. My new book, Dual Momentum Investing: An Innovative Strategy for Higher Returns with Lower Risk, describes some of these, such as the small cap premium, portfolio insurance, and portfolio diversification with passive commodities. Most of these occurred because of incomplete information or omitted variables.
Shortly after Rolf Banz published a paper based on his University of Chicago PhD dissertation that identified a small cap premium from 1936 through 1975, Dimensional Fund Advisors (DFA) and others quickly tried to exploit this "small cap anomaly." They learned later that this apparent anomaly was driven by a mistake in how researchers treated missing data for delisted stocks, many of which were small caps. As noted in my book, studies since then have shown that the small cap premium no longer exists and may never have existed.

Portfolio insurance was based on the elegant idea that you could synthesize protective options through a combination of stock buying and selling combined with short-term borrowing and lending. You could "insure" your portfolio using these synthetic options. However, what portfolio insurers failed to take into account was the short- term mean reverting nature of stocks. At that time, most academics thought stocks followed a random walk and had little or no auto-correlation, even though for many years stock exchange specialists made handsome mean reversion profits by trading against public order flow. Portfolio insurers quietly packed up their bags and disappeared not long after they first appeared.

In the mid-2000s, academics published studies showing that passive commodities could be a decent portfolio diversifier. Investors jumping on to that bandwagon failed to realize that very large inflows of speculative capital from institutional investors could eradicate the premium that had previously been flowing from hedgers to speculators. Front-running costs of over 3% annually from simultaneous rolling over index future contracts would also take its toll on speculative investor profits. After half a dozen years, there were new research papers showing that adding commodities to a stock/bond portfolio was no longer beneficial.

It may very well be that relative strength momentum applied to individual stocks is the latest academic concept doomed to failure because of investors blindly following academics without seeing the bigger picture. Many academic studies of momentum ignore transaction costs, which can be significant. Not only is there high turnover in rebalancing momentum portfolios made up of individual stocks, but Lesmond et al. (2004) show that the stocks generating the largest momentum returns are the smallest, less liquid ones having higher trading costs.  

A trading costs study by Frazzini et al. (2012) of AQR, covering 13 years of data in 19 developed markets, states that "...the main anomalies to standard asset pricing models are robust, implementable, and sizeable." However, Lesmond et al. conclude that "… the magnitude of the abnormal returns associated with these trading strategies [stock momentum] creates an illusion of profit opportunity when, in fact, none exists." As pointed out in our recent post, "Value and Momentum Revisited," Fischer et al (2014), using lower transaction cost estimates than Lesmond et al., also found that transaction costs negate much of the momentum profits from portfolios of individual stocks.

Transaction costs, however, are only half the story. Academic researchers validate cross-sectional relative strength momentum by looking at winners versus losers and segmenting the stock market into deciles, quintiles, quartiles, or terciles. According to Siganos (2007), beyond the first few extreme winners and losers, there is a continuous decline of momentum gains from larger momentum portfolios. Siganos found maximum momentum returns using a portfolio limited to the 40 top and bottom performing stocks.

Yet all publicly available stock momentum funds use more than 40 stocks, and some use ten times more than that! The iShares MSCI USA Momentum Factor ETF holds 125 stocks, and the PowerShares DWA Momentum Portfolio has 100 holdings.The AQR Momentum Fund, AQR Small Cap Momentum Fund, and AQR International Momentum Fund hold 479, 953, and 440 stocks, respectively. These represent nearly 50% of the underlying indexes from which these momentum funds draw their holdings. The annual expense ratios of AQR's momentum funds range from 0.50 to 0.90%. In contrast to this, you can invest in the underlying indexes from which AQR draws their dilute momentum holdings for a cost of only 0.05% per year. When you add in another 0.7% per year that AQR estimates as transaction costs for their quarterly rebalanced large/midcap momentum index, in my mind it raises serious questions about how investors can capture momentum profits from individual stocks.

Yet as they say, the proof is in the pudding. In Chapter 6 of my new book, I show readers a simple way to find style-based alternatives to so-called smart beta funds. In many cases, style-based ETFs with lower expense ratios and lower transaction costs offer similar or better performance than their "smart beta" counterparts.  I thought it would be interesting to use the same technique to look at lower cost style-based alternatives to the largest and longest running publicly available funds that use momentum applied to individual stocks. The following comparative charts using momentum funds that can be accurately matched up with stylistic index funds begin at each momentum fund's inception date using the lowest cost class of momentum shares.

The stylistic equivalent fund to the AQR Momentum Fund (AMOMX), with an annual expense ratio of 0.50%, is the Vanguard U.S. Large Cap Growth ETF (VUG), with an expense ratio of .09%.

 

The stylistic equivalent fund to the AQR PowerShares DWA Momentum Portfolio (PDP), with an annual expense ratio of 0.65%, is the Vanguard U.S. Mid Cap Growth ETF (VOT), with an expense ratio of .09%
.
 
The stylistic equivalent fund to the AQR Small Cap Momentum Fund (ASMOX), with an annual expense ratio of 0.65%, is the Vanguard U.S. Small Cap Growth ETF (VBK), with an expense ratio of .09%.


The stylistic equivalent fund to the AQR International Momentum Fund (AIMOX), with an annual expense ratio of 0.65%, is the iShares MSCI EAFE Growth ETF (EFG), with an expense ratio of .40%.


The above charts give some evidence of why I am not a fan of using momentum with individual stocks. It should also be mentioned that relative strength stock momentum does little or nothing to reduce portfolio drawdown. To accomplish that, you need absolute momentum and/or cross asset diversification. In terms of both risk and return, momentum is more effective when used with asset classes or broad indexes, and when it incorporates trend-following absolute momentum, as described in my book.

Friday, October 31, 2014

Dual Momentum Investing Is Now Released

Today is the official release day of  Dual Momentum Investing: An Innovative Strategy for Higher Returns with Lower Risk. I wrote the book to help as many people as possible earn attractive returns and minimize bear market drawdowns.
book by Gary Antonacci

 Here is an excerpt from a thoughtful review by Reading the Markets:

Antonacci's extensive research and his clear-headed thinking have led to a book that every investor should read. The academically oriented reader will be grateful for his occasional excursions into the weeds, his carefully laid-out data, and his lengthy bibliography. The practically oriented investor will find a road map for moving ahead and staying out of really big trouble ...This one's a keeper!

Scott's Investments wrote:

Dual Momentum Investing: An Innovative Strategy for Higher Returns with Lower Risk is a must-read for individual investors and financial professionals…Antonacci has done the heavy lifting for his readers by thoroughly researching the history and data behind momentum investing. The result is a well-researched and overwhelming argument for momentum investing. Readers are rewarded with a simple, robust strategy that anyone can implement.

And from Alpha Architect...:

Antonacci demonstrates returns to Dual Momentum and the empirical evidence through extensive backtesting across multiple decades; the analysis includes various risk metrics (returns, standard deviations, Sharpe, drawdowns, etc.), and robustness studies, the interpretation of which he explains in detail, so that the reader can have an informed view of the data.

The evidence culminates in a simple but powerful applied momentum model: Antonacci’s Global Equities Momentum (GEM) strategy, which uses these dual momentum ideas to tactically allocate across and among domestic and international equity and bonds. And the results are nothing short of spectacular: superior returns, with low volatility.


The Kindle version of the book was released on October 9, so there are also a dozen reader reviews on Amazon, as well as endorsements from prominent industry professionals. Click here to read these, find out more about the book, or order it now.

Saturday, October 25, 2014

Value Investing Redux

Believe it or not, I was once a value investor. From an early age I was impressed with the long-run success of such value luminaries as John Neff, Bill Ruane, Walter Schloss, and Max Heine. Being of a contrary temperament, I also liked the idea of buying stocks that were out-of-favor and ignored. Supporting this approach, DeBondt and Thaler (1985) presented evidence that stocks overreact to bad news, and that poor performers over the past 3 to 5 years tend to outperform when moving forward. Value investing also seemed to have representative bias going for it, whereby investors overreact to poor performance and project it far into the future while failing to account for long-run mean reversion.

In 1992, Fama and French presented their groundbreaking paper indicating that value and small cap stocks offered up a risk premium to investors. I, along with the rest of the civilized world, readily accepted this idea. In 1995, Kothari et al. discovered that the the Fama and French results may have been due to sample selection bias. Using a different data source, Kothari et al. found no significant evidence of a positive relationship between value and average returns. However, since Kothari et al. were challenging the work of the highly respected Fama and French, their discovery got very little attention.

What got me away from value wasn't anything about value itself, but rather was my discovery after reading a plethora of research papers on momentum of just how strong momentum is compared with anything else. Looking at relative strength momentum applied to individual stocks showed a much higher premium than from anything else. What I also found is that you can easily apply momentum to different asset classes in order to gain the benefits of diversification, while applying value to asset classes other than equities can be speculative and uncertain.

What really got me excited about momentum though was my own research showing that momentum can be applied not just across different investment opportunities, but to single investments themselves in the form of trend-following absolute momentum.  Absolute momentum not only enhances returns like relative momentum, but it can also dramatically reduce drawdown. As far as I could tell, no other anomaly could do this.

With all these advantages accruing to momentum, I saw no reason to consider any other investment approach. Reinforcing this view in my mind were the surprising results with respect to value in the research report last year by Israel and Moskowitz (See my post "Momentum…the Only Practical Anomaly?"). Working with U.S. equities data back to 1926, the authors said:

The value premium… is largely concentrated only among small stocks and is insignificant among the largest two quintiles of stocks (largest 40% of NYSE stocks). Our smallest size groupings of stocks contain mostly micro-cap stocks that may be difficult to trade and implement in a real-world portfolio.

So value, as popularly derived, was of no practical benefit to investors. On another front, Chen et al. (2011) proposed an asset pricing model in which investment and profitability are the main explanatory variables, rather than value and size. Fama and French (2014) then expanded their established three-factor model to include investment (expected future changes in book equity) and profitability (expected future net income relative to book assets). When doing so, they concluded that value was redundant.

VALUE METRICS

So did all this put a nail in the coffin with respect to value investing? Not necessarily. Israel and Moskowitz looked at value using the popular book-to-market (or price-to-book) ratio. They found similar results using other value measures, such as dividend yield and long-term reversals that had data going back to at least the 1930s. However, these were only singular measures of value.

Dhatt et al. (2001) found that composite measures of value were superior to any individual metric. Moreover, in their book Quantitative Value: A Practitioner's Guide to Automating Intelligent Investment and Eliminating Behavioral Errors, Gray and Carlisle identified a superior valuation metric based on enterprise multiple, defined as total enterprise value (TEV) divided by earnings before interest, taxes, depreciation, and amortization (EBITDA). Here is a table of valuation metric comparisons by Gray using equal weight portfolios sorted into quintiles. Data is from 1971 through 2010 and excludes micro caps. Perhaps use of the enterprise multiple instead of price-to-book (P/B) could restore confidence in the value premium?

comparative valuation metrics

VALUE AND QUALITY

Researchers have also found that adding a financial strength or quality metric can substantially improve the risk-adjusted results of value portfolios. Paying attention to these additional factors can help overcome the problem of the "value trap," which happens when stocks remain depressed (and may go bankrupt) because their poor fundamentals warrant it.

Using global data from 1988 through 2012 and U.S. data from 1963 through 2012, Kozlov and Petajisto (2013) found that going long stocks with high quality earnings (based on high return on equity, high cash flow, and low leverage) and short stocks with low quality earnings gave higher Sharpe ratios than a similar value strategy. They also found earnings quality to be negatively correlated with value. The best Sharpe ratio came from combining high quality with value, since there were significant diversification benefits.

Using a different approach, Piotroski and So (2012) came up with a multi-factor scoring method (F-Score) to measure a firm's financial strength. This method was positively correlated with profitability and earnings growth. Piotroski and So found that strategies formed jointly on F-Score and value dramatically outperformed traditional value strategies.

Novy-Marx (2012) found he could simplify the quality factor to just gross profitability, defined as revenues minus cost of goods sold, scaled by assets. Novy-Marx (2013) found on U.S. stock data from 1963 through 2012 that profitable firms generated significantly higher returns (0.31% per month) than unprofitable firms, despite having higher price-to-book ratios. Novy-Marx (2012) also found that joint strategies combining value with Piotroski/So's F-Score, Greenblatt's magic formula, or gross profitability outperformed traditional value, with profitability with value being the strongest combination:

growth of value plus quality

What was particularly impressive here was the reduction in maximum drawdown that came from the joint use of value and profitability due to their large negative correlation. As we can see from the above table, maximum drawdown for large cap strategies dropped from -43% with value alone to -18.9% for value combined with profitability.

The key here is that combining quality with value could help us find stocks that are both reasonably priced and expected to grow. As Warren Buffett said, "Whether we're talking about socks or stocks, I like buying quality merchandise when it is marked down."

WHAT TO DO

Despite the above enhancements to value investing, given the advantages of dual momentum investing, if I were ever to get the urge to do value investing, I would just lie down until the urge goes away. However, if  I were actually going to add value to my portfolio, it would need to be calculated on a more sophisticated basis than price-to-book, and it would need to be be combined with profitability/quality to mitigate the potential value trap problem. More specifically, here is what I would look for in a value fund:

1)    It should combine value with quality and/or profitability screens.
2)    It should determine value based on multiple value metrics and/or a value metric that incorporates the enterprise multiple.
3)    It should re-balance at least quarterly to reduce possible style drift and to increase expected profits.
4)    It should not dilute returns by having an overly broad portfolio. In Chapter 6 of my new book, Dual Momentum Investing: An Innovative Strategy for Higher Returns with Lower Risk, I show that many so-called smart beta funds are like closet index funds with modest stylistic tilts. Unfortunately, most value funds are the same. Even though the value effect is more pronounced in the top 10-20% of value rated stocks, most funds dilute this effect by using the top third or top half of value stocks instead of the more profitable top 10-20%.
5)    The expense ratio should be reasonable. (This is true of all the funds I use.)
6)    For taxable accounts, ETFs are preferred over mutual funds and hedge funds. Tax liabilities usually only occur when you sell your ETF holdings, whereas mutual funds have yearly taxable distributions of dividends and capital gains.

CANDIDATES

Since value and quality do well together, it is natural to think of actively managed mutual funds when considering investment candidates based on these factors. This is because most active managers use fundamental analysis, which takes into account profitability in the form of financial strength, managerial acumen, competitiveness, quality of earnings, and other judgmental factors, in addition to valuation.

However, most active managers lack transparency so as to give the appearance of possessing proprietary knowledge that is worth paying a premium to access. This means it is usually very difficult to tell if they meet the first two criteria listed above. In addition, active mangers usually charge high fees. The Morningstar average large cap value fund annual expense ratio is 1.16%. Mutual funds also have a drag on their performance  because of reserves held for redemption, and, as mentioned above, these funds are generally not tax efficient.

There is one mutual fund, however, that may be worth looking at more closely. It is the AQR Core Equity Fund (QCELX).[1]  This fund meets our first three requirements, since it rebalances monthly and uses three indicators of profitability along with five indicators of value. For good measure, it adds three momentum indicators. QCELX also has a reasonable annual expense ratio of 58 basis points. However, it is not tax efficient, although AQR has plans for a more tax efficient version of the fund. But on the negative side, QCELX currently holds 413 stocks, which is more than 40% of the stocks in its 1000 mid/large cap stock selection universe.

AQR has this same kind of broad participation in their momentum fund, where they hold 47% of the 1000 stocks in their selectable universe. Why they do not target factor profits more aggressively remains a mystery to me. Perhaps they expect so much capital to enter their funds that they anticipate liquidity issues. This may also explain why their portfolios are, for the most part, capitalization weighted instead of value or equal weighted.

In the ETF realm, until this past week there was only fund that qualified with the above criteria. It is the PowerShares Dynamic Large Cap Value ETF (PWV), based on Intellidex methodology. PWV uses a ranking selection method with four indicators of value and four indicators of growth. They subtract the value from the growth rankings and then select the largest negative scores. This process automatically gives PWV some profitability exposure, according to the research of Bridgeway Capital Management. Bridgeway found that a multi-indicator value approach (adding price/cash flow, price/earnings, and price/sales) provided greater exposure to gross profitability than a portfolio based only on price/book.

To help further with profitability exposure, after doing their basic screens, PWV adds weightings for price momentum, earnings momentum, quality, and management action. PWV selects the top 20% of the largest 250 stocks from a potential universe of 2000. This gives them a focused portfolio of just 50 stocks that PWV rebalances quarterly. However, I would  prefer that they derive their portfolio of 50 stocks by selecting the top 10% of the largest 500 stocks instead of the top 20% of the 250 largest stocks. They allocate half their capital equally to the top 15 ranked stocks, and the other half of their capital is divided equally among the remaining 35 stocks. Their annual expense ratio is a reasonable 58 basis points. PWV's performance since inception has been attractive compared to the iShares S&P 500 Value ETF.

Value plus quality versus value
                                                  Past performance is no assurance of future success.

This past week another ETF got to the short list of qualified candidates. The new kid on the block is Value Shares U.S. Quantitative Value ETF (QVAL) offered by Wes Gray's Alpha Architect. QVAL incorporates quality in a number of ways. First, it has forensic accounting screens to avoid firms at risk for financial distress or manipulation. Then it filters for financial strength using a modified Piotroski/So F-Score. Finally, QVAL checks for sound business fundamentals through what it calls an "economic moat." This is a screen for firms having sustainable competitive advantages, ala Warren Buffett.

Having written the book on valuation metrics, QVAL's management uses the enterprise multiple. They select just the top 10% of their large cap universe based on value, then drop the bottom half of these based on quality. The remaining 50 stock portfolio is equal weighted and rebalanced quarterly. QVAL's annual expense ratio of 79 basis points is higher than PVW and QCELX, but QVAL is the most focused fund among the three, selecting only the top 5% of quality/value stocks in their mid/large cap universe, compared to PVW's 20% and QCELX's 40%. QVAL represents true active management rather than the more usual "no guts, no glory" approach of most watered down, over diversified funds.

WHAT CAN GO WRONG

Value investing in general poses risks that all investors should be aware of. Chief among them is the high tracking error relative to the overall market. Value can go through sustained periods of under performance, such as during the 1990s. From 1994 through 1999, value underperformed growth by over 10% per year! With focused portfolios of just 50 stocks, PVW and QVAL can potentially have higher tracking error than other value funds. Value investors need to have a very long-term investment horizon and a high tolerance for long periods of under performance.

Value investing with focused portfolios, such as those of PWV and QVAL, is also subject to high volatility and high maximum drawdown, and investors should be prepared for this as well. Unfortunately though, investors can lose sight of this. They can panic and act counter to their best interests when confronted with severe drawdown. In a survey of its members since 1988, AAII found that the highest weight to cash and the lowest weight to equities was in March 2009, right at the bottom of the worst bear market since the 1930s.

There is a way, though, to mitigate this harmful behavior through the use of absolute momentum. (You didn't really think I would write a long post like this  without mentioning momentum, did you?) My research paper on absolute momentum and my new book show how to use trend following absolute momentum to reduce the expected drawdown of any investment opportunity. The chart below of absolute momentum applied to the S&P 500 illustrates this. Through absolute momentum, maybe value and momentum can coexist after all.
  Downside reduction through absolute momentum
[1] This material is for informational purposes only. It is not a recommendation to buy or an endorsement of any securities. Investments are subject to risk including loss of principal. You should do your own research before investing. Please see our Disclaimer page for additional information.

Thursday, October 9, 2014

Giving Investors a Chance

Researchers estimate that the worldwide cost of investment management is approximately $3 trillion per year. Some of this expense is unavoidable, such as the costs associated with custodial fees and for the periodic re-balancing of portfolios.

However, most of this high expense is in the form of compensation paid to the managers of actively managed mutual funds, hedge funds, and other managed programs. What do investors have to show for this large transfer of wealth from themselves to active money managers? The answer, unfortunately, is "not much." My book, Dual Momentum Investing: An Innovative Strategy for Higher Returns with Lower Risk, reveals an abundance of research that confirms the general lack of value-added from active investment management.

Lack of performance is due not just from the higher fees and transaction costs associated with active investment management.Institutional investors use disadvantageous periods for the evaluation and selection of their investments. Goyal and Wahal (2008) show that investment managers and their consultants tend to select investments based on performance over the prior three or so years. Yet momentum research papers show 3 to 5 years to be a relatively poor period for performance evaluation. Equity performance tends to be mean reverting over that time frame. A one-year relative evaluation period gives much better results. Vanguard issued a research note last July also documenting poor future performance based on a past 3- year evaluation period.

Making matters worse, yearly reports from Dalbar Inc., a market research firm, indicate poor timing decisions on the part of the investing public. For example, the average US equity investor achieved an annualized return of 5.0% over the past 20 years ending in 2013, which is 4.2% less than the 9.2% average annualized return of the S&P 500.

Investors are emotionally influenced by by market volatility when getting into and out of the markets. Equities have provided investors with the highest risk premium, but they also have been subject to high volatility and extreme drawdown, since few investors have been aware of the risk-reducing benefit of absolute momentum. When investors instead try to dampen volatility through diversification with fixed income or alternative investments with lower inherent risk premiums, they also dampen their long-run expected return.

Some try to boost returns by looking for more of an edge from their equity investments. Historically, investors have used value and small cap portfolio tilts in their attempts to achieve higher risk-adjusted returns.

Yet the latest research shows that small size and high value portfolios may not always provide the higher risk-adjusted returns that investors have been seeking (See our post "Momentum...the Only Practical Anomaly?") Momentum, on the other hand, does provide a proven edge, especially when dealing with indexes rather than individual stocks and when using both absolute and relative momentum together (dual momentum). Unfortunately though, the most popular momentum-based programs use only relative strength momentum, and they apply it to individual stocks, which necessitates higher transaction costs.

I know of one public program that uses dual momentum applied to asset classes. However, their fees are very high, and their portfolio choices leave much to be desired (My book also goes into considerable detail about asset selection, especially with respect to momentum-based portfolios.)

In the future, when the advantages of dual momentum become better known, there may be other dual momentum investment opportunities. However, they may still have fees that are too high, portfolios that are less than ideal, or models based on too little data. The biggest mistakes I see others make are using models that over fit the data and drawing conclusions based on limited amounts (typically around 15 years) of data.

To give investors a better chance to earn decent risk-adjusted returns, my new book fully discloses my simple Global Equity Momentum (GEM) model (see the Performance page of my website) and shows how to use it. GEM has performed well over 40 years of past data under different market conditions using the same approach validated in numerous academic research papers. It has also avoided most bear market equity erosion. For only the cost of a book, any investor can easily utilize GEM to benefit from dual momentum while using a sensible, minimal expense portfolio.

Thursday, September 11, 2014

Value and Momentum Revisited

Most academic research on momentum deals with individual stocks. Most applications of momentum are also oriented toward individual stocks. The three largest publically offered momentum programs (AQR momentum mutual funds, PowerShares DWA Momentum ETFs, and iShares MSCI USA Momentum Factor ETF) all use individual stock momentum. The only widely-available public program using momentum applied to asset classes was the ALPS Goldman Sachs Momentum Builder that recently went out of business due to lack of interest.

Yet momentum applied to individual stocks is not the ideal way to use momentum. Transaction costs due to high turnover of stock portfolios can negate much of the benefit of momentum investing, and most stock momentum programs dilute the momentum effect by selecting hundreds of stocks instead of just the ones showing highest relative strength. Momentum applied to indexes or sectors, rather than individual stocks, can capture high momentum profits with much lower transaction costs.

Here is a table from my new book Dual Momentum Investing: An Innovative Approach to Higher Returns with Lower Risk. (The book can be ordered now from Amazon.) This table shows the performance of the AQR Momentum Index composed of the top one-third of the 1000 highest capitalization U.S. stocks based on 12-month relative strength momentum with a one-month lag. AQR weights their index positions based on market capitalization and adjusts the positions quarterly. For comparison, we show the performance of applying absolute momentum to the Russell 1000 by moving into aggregate bonds whenever 12-month absolute momentum is negative.

Table 9.2 AQR Momentum, Russell 1000, and Russell 1000 w/Absolute Momentum 1980-2013


AQR Momentum Index [1]
Russell 1000 Index
Russell 1000 w/Abs Momentum
Annual Return
15.14
13.09
15.92
Annual Std Dev
18.27
15.51
12.57
Annual Sharpe
 0.51
 0.49
 0.80
Max Drawdown
              -51.02
            -51.13
             -23.41

These figures do not account for the 0.7% per year in additional transaction costs for the AQR Momentum Index, would have put it at a disadvantage to even the Russell 1000 index on a risk-adjusted basis. 

Table 9.3 shows the AQR Momentum Index, the Russell 1000 Value Index, and a 50/50 combination of value and momentum, which was advocated in the Asness et al. (2013) paper "Value and Momentum Everywhere." This combination is supposed to be desirable due to the negative correlation between value and momentum. We see that value combined with momentum (rebalanced monthly) does give a slightly higher Sharpe ratio than either value or momentum alone. However, there is little or no advantage with respect to maximum drawdown, and the results still pale in comparison to simple absolute momentum used with the Russell 1000 Index [2].

Table 9.3 AQR Momentum, Russell 1000 Value, 50/50 AQR Momentum with Value 1980-2013


AQR Mom Index
Russell 1000 Value Index
50/50 AQR Mom with Value
Russell 1000 w/Abs Mom
 Annual Return
15.14
13.52
14.33
15.92
 Annual Std Dev
18.27
14.87
15.71
12.57
 Annual Sharpe
 0.49
 0.53
 0.55
 0.80
 Max Drawdown
          -51.02
       -55.56
          -51.47
             -23.41

As a further check on the possible worthiness of combining value with momentum, I used the Global Equity Momentum (GEM) model described and tracked on the Performance page of our website. Full disclosure of GEM and instructions on how to use it are in my book. Using relative momentum, GEM switches between the S&P 500 and the MSCI EAFE when absolute stock momentum is positive. When absolute momentum turns negative, GEM moves into aggregate bonds. 

The table below shows GEM results from January 1974 through August 2014, as well as the results from adding the MSCI USA Value (large and mid-cap) index to GEM as an additional switching option and rebalanced monthly. We see that the inclusion of value into the momentum model adds nothing to the performance of GEM.


GEM
GEM w/Value
Annual Return
17.43
17.24
Annual Std Dev
12.64
12.52
Annual Sharpe
  0.86
0.86
Max Drawdown
            -22.72
               -22.94

Furthermore, as I pointed out in a blog post last year called "Momentum…the Only Practical Anomaly?", Israel and Moskowitz of AQR show in their 2013 paper that value, as it is commonly used, only offers a long-term premium when applied to very small stocks. These stocks are generally unusable by institutional investors. How one can mix individual stock momentum (which may offer nothing special after transaction costs) with value (which may also not be all that it was once thought to be) and create something extraordinary, may be a challenging endeavor. This is especially in true in light of an earlier paper by Daniel and Titman (1999) showing that value strategies are strongest among low momentum rather than high momentum stocks, and momentum strategies are strongest among growth rather than value stocks.

Nevertheless, researchers are nothing if not persistent and imaginative. When it was found that Markowitz mean variance optimization (MVO) gave inconsistent results, researchers tried constraining the inputs, incorporating prior information to shrink the estimates, and even ignoring returns altogether to try to create portfolios that were more robust. In the end, they found that because of estimation error, equal weight portfolios were generally superior to MVO portfolios. The same overreach is true with respect to the Capital Asset Pricing Model (CAPM). This started out as a single factor model that expanded to 3 and then 4 factors. Factor fishing has now come up with more than 80 possible data-mined factors, yet the factor pricing model may still not effectively model the real world. 

Therefore, it didn't surprise me to see recent a paper by Fisher, Shaw, and Titman (2014) called "Combining Value and Momentum" that tries hard to find other ways to use value and momentum together. (Yes, this is the same Titman who co-authored the above paper that showed momentum working better with growth rather than value stocks, and who co-authored the seminal momentum papers of the 1990s with Jegadeesh.)

What is perhaps most interesting are the various findings the authors came up in the course of their research. As the saying goes, the devil is in the details. Here are some of those details.

The authors separate stocks into 2 size categories, large cap corresponding to the Russell 1000 index, and small cap corresponding to all other stocks in the CRSP database from 1975 through 2013. They base momentum on prior 12-month performance skipping the last month. With respect to value and momentum separately, the authors find:
  • Value, as measured by the price-to-book ratio, is beneficial only with small stocks and not with large stocks. This is the same conclusion reached by Israel and Moskowitz who used data back to 1926, and who also found it to be true of other valuation measures that had data back to at least the 1930's.
  • Despite high momentum portfolio Sharpe ratios before transaction costs, the high transaction costs associated with momentum portfolio turnover negates much of the difference in Sharpe ratios between large momentum and large value portfolios.
  •  Since small stocks have even higher transaction costs than large stocks, the authors incorporate higher transaction costs to conclude that none of the small momentum portfolio Sharpe ratios are higher than the Sharpe ratios of the small market portfolios.
  • In other words, based on high transaction costs, individual stock momentum may not be very good with either small or large stocks [3]. So all we are left with that provides above market risk-adjusted returns are small value stocks that most investors (and particularly institutional ones) find too expensive and difficult to trade.
The authors then look for ways to salvage momentum by combining it with value in two different ways. The first is to rank firms by momentum and value separately, and then compute an average rank. One signal can outweigh the other, and momentum still has high transaction costs with this approach. 

The authors' second approach is to use momentum as a filter for value-based portfolios. They buy stocks only when value and momentum are both favorable, and they sell stocks only when both factors are unfavorable. Momentum does not trigger trades, but instead influences the portfolios by delaying or avoiding trades. Data mining for the highest ex-post Sharpe ratios with this second approach, the authors find much greater exposure to the value factor. The optimal small cap portfolios, for example, have value allocations of 79% or more. The role of momentum with this approach is very small. 

The authors' first approach gives slightly higher Sharpe ratios when trading costs are low, and the opposite is true if trading costs are high. Of course, we do not know if these Sharpe ratios will continue out-of-sample into the future.

We can avoid the issues of high trading costs and less certain Sharpe ratios if we instead use momentum with indexes or sectors rather than with individual stocks. In our 2012 post called "Value and Momentum…Not Here" we asked if there should be just value and momentum everywhere. I didn't think so then, and I see even less reason to believe so now.


[1] http:///www.aqrindex.com
[2]  Results of momentum combined with value are better if a quality factor, such as profitability, is added, and if momentum, value, and profitability are applied simultaneously to the same portfolio.See "Quality Investing" by Novy-Marx.
[3] A study last year by Frazzini, Israel, and Moskowitz looked at large institutional trades across 19 developed markets from 1998-2013. They found the trading costs of momentum to be low, despite a higher turnover than from other factors. On the other hand, a study by Lesmond, Schill, and Zhou (2004) called "The Illusionary Nature of Momentum Profits" showed that transaction costs reduced momentum strategy returns to close to zero. Fisher et al. uses transaction cost estimates that are in between these two. 

The above are hypothetical results, 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. One cannot invest directly in an index.