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.

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 Less 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. Momentum applied to broad-based indexes or sectors, on the other hand, 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 Less 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
Annual Std Dev
Annual Sharpe
Max Drawdown

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
 Annual Std Dev
 Annual Sharpe
 Max Drawdown

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 w/Value
Annual Return
Annual Std Dev
Annual Sharpe
Max Drawdown

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:///
[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.

Wednesday, June 4, 2014

"Fact, Fiction, and Momentum Investing"

The AQR posse (Asness, Frazzini, Israel, and Moskowitz) recently issued a working paper that disproves many often-repeated myths about momentum investing, particularly as it applies to individual stocks. The authors back up their reasoning with results from academic papers and publicly available data. Here are the myths they address: 
  •   The momentum anomaly is small and sporadic 
  • ·It works mostly on the short side
  •   It works well only among small stocks
  •   It does not survive trading costs
  •   It does not work for a taxable investor
  •   It is best used as a screen rather than as a regular investment factor
  •   Its returns may not persist
  •   It is too volatile to rely on
  •   Different measures of momentum may give different results
  •   There is no theory or reasonable explanation to support it
 Below is a quick summary of the authors' evidence-based counter arguments:

1)  There is overwhelming evidence from scores of studies showing that momentum returns are remarkably stable and robust.

2)  There is little difference in performance between the long and short sides of momentum based on factor model regressions. Based on average returns versus the market, the long side has contributed more to momentum profits.

3)  As for working only among small caps, this is true only if you replace the word "momentum" with the word "value". Two of the authors, Israel & Moskowitz, wrote an important paper last year called "The Role of Shorting, Firm Size, and Time on Market Anomalies" that clearly showed this. That paper was the subject of my post, "Momentum...the Only Practical Anomaly?" Momentum actually works well across all size stocks.

4)  A study last year by three of these authors called "Trading Costs of Asset Pricing Anomalies" looked at large institutional trades across nineteen developed markets from 1998-2013. They found the trading costs of momentum to be low, despite a higher turnover than from other factors.

5) Several studies show that even though momentum with individual stocks has 5-6 times the annual turnover of value strategies, momentum actually has a similar tax burden. This is because momentum holds on to winners and sells losers, which avoids short-term gains in favor of long-term ones. Momentum also has a much lower dividend exposure than value.

6)   The authors point to papers showing that momentum works better as a factor-based approach than as a screen-based one.

7)  As for momentum's returns disappearing, one can say the same of any anomaly. Abnormal momentum returns have survived, however, for the past 212 years. Momentum has held up to considerable out-of-sample validation across time, geography, and asset type. The authors point out, "There is no evidence that momentum has weakened since it has become well-known and once many institutional investors embraced it and trading costs declined."

       8) Relative strength momentum is volatile, but the Sharpe ratio (which includes volatility) of momentum still comes up on top. The authors say, "Who are you calling small and sporadic?" (The authors ignore absolute momentum, which significantly reduces expected volatility and drawdown.)

9)  The authors agree that different measures of momentum can give different results, but they point out that this is true of any strategy. Different measures of momentum giving good results is a sign of robustness and not a cause for concern.

10) Momentum can be explained by either risk based or behavioral factors. As long as risks, risk preferences, biases, and/or behaviors do not change, momentum profits should continue unabated as they have for the past 200+ years. (My forthcoming book shows how behavioral biases are part of our DNA and are unlikely to change.)

The authors point out that most of the above myths can be shattered by a quick visit to Kenneth French's data library website. It is refreshing to see the authors, brought up in the Chicago efficient markets tradition, take on the challenge of those who say momentum profits cannot persist (despite plenty of evidence to the contrary) because that would contradict the theory of efficient markets. The authors point out that rejecting data because of a theory (or a one-sided view of the world) can be dangerous. They point to Columbus, Galileo, and the Salem witch trials as examples. Bravo!

The only problem I have with their paper is that the authors, perhaps keenly aware that risk-adjusted  momentum profits from individual stocks have been uninspiring over the past thirty years, repeatedly point out  that momentum works best when it is combined with value. Yet we can see in the aforementioned Israel & Moskowitz study that commonly used measures of value hold up only among the smallest stocks that represent only 10% of total market capitalization, and these are impractical for most investors to hold. Maybe the AQR crew needs to take a closer look at the true value of the emperor's new clothes.

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