As we wrote in August, hedge funds seemed to be repositioning themselves for a down market.  According to the Hennessee Group, average net (dollar) exposure had fallen from a high of around 55% in mid 2007 (the market peak) to 35% by mid 2008.  Regardless of whether this means hedge funds can tel the future or not, shifting net exposure like that is obviously a useful skill.  The mere fact that funds kept pushing down their net exposure does suggest some ability to read the tea leaves.

Now a new study seems to add credence to the argument that hedge funds have a statistically significant ability to time markets.    Researchers from Citigroup and Athens University of Economics & Business found that there was a significant correlation between hedge fund market beta and market performance itself.  In other words, hedge funds (specifically, “equity hedge” and “equity market neutral” hedge funds in the HFR database) became slightly more correlated with the market right before the market actually rose.

The authors set out to examine the behavior of three factors on hedge fund returns: value, momentum and “market”.  But the market factor was the only one to show a significant relationship to future hedge fund returns.

As the table below shows, the correlation between the average market beta of hedge funds and the market’s returns is insignificant using the last month’s (”t-1″) market returns, is slightly higher using this month’s market returns and is relatively large (0.17) with next month’s returns.  In other words, equity hedge funds seem to modestly ratchet up their market beta concurrent with rises in the market, but clearly ratchet up their beta in anticipation of a good month to come for the markets.  Equity market neutral funds - although market neutral” also seem able to anticipate coming market “up months” (red circles below).

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Melvyn Teo’s paper on the relative merits of locally-based Asian hedge funds vs.  those with no local presence (see yesterday’s posting) amounts to a significant indictment the Efficient Market’s Hypothesis.  After all, why would one group of managers (i.e., those without a local office) be willing to forgo higher returns?  And why wouldn’t investors just stop investing in sub-optimizing, apparently irrational funds?  It’s as if these two groups were totally different species or something.

And indeed, they may be different species - in a sense.  Back in 2004, MIT’s Andrew Lo, the author of a huge library of refreshingly easy-to-read papers and articles, proposed a successor to the EMH that actually defined different groups of investors (pensions, individuals, traders etc.) as different “species” of investors and expanding on the biological analogy.  His resulting Adaptive Markets Hypothesis (AMH) explains the apparent irrationality of markets as a rational reaction to a change in environmental conditions.   His Journal of Portfolio Management paper can be downloaded here (academic version available here).

Drawing from behavioural finance, Lo says that investors make decisions using heuristics drawn from trial and error, not from concrete analytical models.  Drawing a page from Darwin, he says that without adequate trials and errors, there is no adaptation. 

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Despite the fact that hedge funds have often been described as being synonymous with alpha, they certainly don’t have a monopoly on it.  Naturally, mutual funds have been in the alpha game since the dawn of the fund management industry.  In many ways, the debate over “luck” and ”skill” in mutual funds mirror the tug-of-war between ”hedge fund beta” and “alpha” in Hedgistan.  And, like some studies of hedge fund alpha, new research suggests that mutual fund “skill” is dwindling.  The following review of a recent academic paper on this topic was written by Bob Huebscher, the founder and editor of Advisor Perspectives, an excellent newsletter dedicated to raising these and other issues in the financial advisor community. 

Luck versus Skill in Active Mutual Funds 

Guest Contribution By: Robert Huebscher, CEO, Advisor Perspectives

A recurring question in the topic of active versus passive management is the degree to which active mutual fund managers who outperform their benchmark can be considered to have done so through skill versus luck.  An academic study, described in an article by Mark Hulbert in the New York Times several weeks ago, answers this question through a new statistical technique.

The study’s authors are Russ Wermers, a professor of finance at the University of Maryland, Laurent Barras of the Swiss Finance Institute, and Oliver Scaillet of the University of Geneva.  We spoke with Professor Wermers on July 25, 2008.

The False Discovery Rate

If all active fund managers were to choose stocks by throwing darts, inevitably some small percentage would deliver alpha, even over some large period of time.  However, they would do so through random luck.  Fund managers are not dart throwers, yet some percentage of them will nonetheless deliver alpha through luck.  Wermers’ tool, known as the False Discovery Rate (FDR), identifies the size of the group delivering alpha through skill, and well as the size of the group failing to deliver alpha through lack of skill.

The FDR technique begins by segregating fund returns into three groups: negative alpha, zero alpha, and positive alpha.  The zero alpha group consists of those funds that earn returns just sufficient to match their benchmark, net of expenses.  They deliver zero alpha to their investors.  Based on the number of funds that exhibit an alpha close to zero, which are almost all funds without skills, the FDR technique estimates the number of funds without skills that end up with positive (or negative) alphas simply by luck (good of bad). Then, it is simply a matter of subtracting the actual size of the positive alpha group from the expected size (based on luck alone) to determine the size of the group of funds that delivered alpha through skill. A similar procedure is used to determine the size of the group that deliver negative alpha (net of expenses) through lack of skills.

The study used the Center for Research in Securities Prices (CRSP) data, and matched it with Thomson’s CDA data for fund investment-objective information.  The data is free of survivorship bias and only funds with at least 60 months of returns were included.  Share classes were consolidated (dollar weighted) into a single fund.  Sales loads were not modeled (if they were, it is likely an even smaller percentage of funds would have delivered alpha).

Key Findings

Over the 32 year period studied by Wermers and his co-authors, from 1975 to 2006, only 0.6% of funds delivered positive alpha through skill, as opposed to luck alone.  The FDR cannot determine which funds delivered alpha through skill; it can only estimate the size of this group.  Those select few funds (approximately 12 out of the 2,076 studied) will remain anonymous.

Of the remaining funds, 24.0% are unskilled and 75.4% are zero alpha (delivering excess returns sufficient to only cover fees and expenses).

A very interesting finding is that the proportion of skilled managers decreases over time, specifically from 1990 to 2006.  In 1990, 14.4% of funds fell into the skilled category, while 9.2% were in the unskilled category.   These numbers were 24.0% and 0.6%, respectively, in 2006.  As the study notes, although the number of actively managed funds has dramatically increased, skilled managers (those capable of picking stocks well enough to overcome their trading costs and expenses) have become increasingly rare.  The decay in alpha is shown in the graph below [click to enlarge]:

Funds were categorized into three investment objectives:  Growth, Growth & Income, and Aggressive Growth.  Wermers noted that this categorization was the only one consistently available for the 32 year time period he and his coauthors studied.  The funds in the Aggressive Growth category exhibited the greatest degree of skill.  These funds tilt toward small cap, low book-to-market, and momentum stocks.  The Growth & Income category, which includes traditional value and core funds, had no funds that exhibited skill, along with a substantial portion that were unskilled, a finding that the study terms remarkable.

Another curious finding concerns the relationship between skill and fund size.  In general, larger funds were more prevalent in the high alpha right tail of the data. We asked Wermers about this, since intuition would suggest that smaller boutique funds would exhibit greater skill, and that skill would erode as fund size grows and managers are forced to invest in a smaller universe of stocks.  Wermers believes that these findings are inconclusive, though, since the vast majority of right-tail funds are there by luck alone—a more detailed examination of the funds within the right and left tails is underway.

Implications for Advisors

Mark Hulbert posed the question of why skill declined over the 32 year period, and offered three possibilities:  high fees and expenses, increased market efficiency, and the movement of skilled mutual fund managers to the hedge fund industry. 

The study showed that over their entire histories, 9.6% of funds produced truly positive alphas before expenses, while almost none produced significantly positive alphas after expenses.  This indicated to the authors that, even though expenses for actively managed funds declined over the period studied, expenses eliminated the good performance of a lot of managers who appeared to have true stock picking skills.   Given that only 0.6% of funds produced alpha over this period, skills are dropping faster than expenses.   Wermers said that expenses are too high, relative to the ability of fund managers to generate alphas.   He added that a prescription is to pay close attention to the expenses charged by funds, as higher expenses do not seem to be associated with higher skills.  We concur, as does the overwhelming body of academic studies on mutual fund expenses.

Regarding the possibility that the market has become more efficient over this period, Wermers noted that several recent studies have shown this to be true.  The FDR test has not yet been applied to hedge fund or separately managed account databases.  If it did, and it revealed a similar decay in skill, that would support the hypothesis that the market has become more efficient.

We believe the fundamental reason for the decline in skill is the movement of skilled managers to the hedge funds, and this factor overwhelms any other possible explanation.  The hedge fund industry is the most profitable industry ever conceived, and its performance-based fees insure that skilled managers will be handsomely compensated.  By contrast, very few mutual funds utilize performance-based fees.  The asset-based fees in the mutual fund industry will naturally select for those managers who cannot succeed in the hedge fund industry.

One aspect of the fund’s methodology troubled us.  We believe a more meaningful question to ask is whether fund managers possess skill, not whether the fund possesses skill.  This could be answered by applying the FDR test at the manager level, not the fund level.  Wermers noted that the referees from the Journal of Finance who reviewed the study raised the same issue, and he plans to add these findings once he completes the analysis.

The final question is whether the study proves that it is almost hopeless to find skilled active managers, as Mark Hulbert notes in his article.  Wermers thinks not.  He said there is a role for smart sophisticated advisors to make a difference, because it is so hard to find a skilled active manager.  He added that advisors should also be prepared to say when it is appropriate for clients to go passive.  Advisors add value by looking at management, strategies, track records, expenses, and all other factors to determine whether skilled managers really work hard to find good active alpha, he said.

(c) Advisor Perspectives.  This article originally appeared in the August 5th edition of the Advisor Perspectives newsletter.

The opinions expressed in this guest posting are those of the author and not necessarily those of AllAboutAlpha.com.  

We are pleased to present another commentary from the man who first coined the term “alpha-centric”, Angelo Calvello.  Today, Calvello uses examples such as Man Investments and BGI to argue that there is more than one way for asset managers to become truly alpha-centric.

Special to AllAboutAlpha.com by: Angelo Calvello, Ph.D.

Investors, faced with funding shortfalls and stricter accounting regulations, are demanding innovative ways of achieving absolute returns.  In the process, they are challenging the asset management industry to break down artificial barriers and constraints and consider solutions to problems we did not know existed a year or two ago. 

In many cases, these investors are offering those of us who can provide demonstrable value the opportunity to transform ourselves from vendors into partners who share their vision. The common denominator is the concerted focus on finding and generating alpha. The defining challenge for the asset management industry is to create and adopt business models and mindsets that will allow us to succeed in this new alpha-centric world.

Multiple Sources

Institutional investors are already seeking investment solutions beyond narrow, single-source portable alpha strategies.  They are exploring and implementing multi-alpha solutions that provide exposure to multiple asset classes at the portfolio level.

Because alpha is scarce, transitory and capacity-constrained, these solutions need to be structured flexibly so that alpha sources can be changed as they reach capacity or lose their edge. These solutions must also be structured to provide not just the desired return and volatility targets, but consistent positive returns while avoiding large losses.

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In a follow-up to a presentation we told you about in early June by Professor Richard Taffler (see posting - “Leading academics on Freud, finance and quacks“), we stumbled upon this useful example of how the investment management community is channelling old Sigmund.

In this article, Investment News reports that “Wealth management, family office and other advisory firms increasingly are using psychology — and psychologists — to work both with wealthy clients and the advisers who serve them.”

While the story covers a more practical instance of the emerging field of emotional finance, you can see that it shares the same common theme as Taffler’s work (and also Denise Shull’s recent guest posting on AllAboutAlpha.com).

While Taffler and Shull both argue that emotion affects trading decisions, the Investment News piece shows that emotion (quite naturally) also affects the wealth management relationship.  Ergo, by getting into the heads of their clients, wealth managers can better address the sub-optimal decisions they make.  As one expert cited in the article suggested, within 10 years most financial management firms will offer psychological counselling.

Note to laid-off Wall Street professionals: consider becoming a shrink.

The commoditization of alpha has been a recurring theme on these pages (see, for example, “Alpha - once beatified, now beta-fied“).  We came across the graphic below in a recent presentation given by Andrew Lo to the Society for Financial Econometrics in June.  The presentation was called “What will happen to the quants in August 2017?”.  But this particular slide sums up the inextricable evolution from alpha to beta. 

It seems to have become a financial axiom that actively managed mutual funds fail to justify their fees.  Ergo, index funds are often proposed as the best way to lose the least amount of money.

But what if the underperformance of actively managed funds has been driven by their underlying strategy, not their stock-picking buffoonery?

Beneath the complexity of their recent paper on benchmark indices, that’s the question posed by Martijn Cremers and Antti Petajisto of Yale and Eric Zitzewitz of Dartmouth. (You may recall the names Cremers and Petajisto from their paper on active share – a new metric to measure active management.  See related posting.)

The researchers found that academic models aimed at isolating manager skill by adding new variables to the CAPM (such as the Fama/French and Carhart models) are a substantial weakness.  Instead, they propose using actual indices as variables in an equation to reveal manager skill.

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In March, we wrote about a yet to be published paper by Kenneth French called “The Cost of Active Management”. In this paper, French concludes that the total cost of the “futile search for superior returns” is 67 bps or about 10% of annual returns (resulting from management fees and trading costs).  At the time, all we had to go on was a New York Times article about the paper by well-known financial commentator Marc Hulbert.  A recent interview with French by the online newsletter Advisor Perspectives brought this paper back to our attention.  The full study is now available online and we felt was worthy of a second, more detailed, examination.

Immediate benefits of active management

Institutions have increased their allocation to passive investing significantly over the past 20 years, prompting Advisor Perspectives to wonder if institutions wising up to high active management fees.  Interestingly, French points to increasing institutional hedge fund allocations as evidence that they are not, in fact, becoming more passive after all:

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In our monthly column featuring the thoughts of a member of the Chartered Alternative Investment Analyst (CAIA) Association, we feature an active publisher in highly rated journals who has recently written an article on weather variables and their impact on financial markets. Wessel Marquering, Ph.D., CAIA, is quantitative researcher at the Talergroup.  Marquering and fellow researcher Ben Jacobson wrote an interesting paper on weather and financial markets for the Journal of Banking & Finance.  What follows are Marquering’s thoughts on the promise and peril of trying to extract alpha from the weather.

Alpha in the Weather: Alternative Viewpoints, powered by CAIA

Special to AllAboutAlpha.com by: Dr. Wessel Marquering, CAIA, Talergroup

As readers of this website are no doubt aware, weather derivatives trading is taking off - with trading volumes going through the roof and more hedge funds venturing into this space. Basically, a weather derivative is a financial product in which two parties agree to exchange cash flows determined by reference to a weather index. The reference indices include temperature, rainfall, wind speed, humidity, snowfall, to name a few, but the most heavily traded contracts are based on temperature indices.

On the one hand, weather derivatives can be used to manage risk, by insuring for example farmers against a bad crop, as an insurance against bad weather on holidays, by decreasing the exposure to temperature-related risk factors, etc. On the other hand, they have become a relatively new way to generate alpha.

These alpha opportunities arise because weather derivatives are difficult to price. And since weather patterns are not random, the Black-Scholes option model is not entirely appropriate. Some hedge funds actually hire meteorologists and run highly quantitative models to forecast the weather in an attempt to identify bargain contracts.  Since the weather is uncorrelated to, for example, sub-prime, Iraq war, etc., they are a great addition to investors’ portfolios.

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If you’re in the hedge fund industry, you know the name Pertrac.  These are the guys who make the ubiquitous software platform that many hedge funds use to analyse and report performance to their investors.  Last March, the firm compared the performance of large ($500 million+), medium ($100 million-$500 million) and small (under $100 million) hedge funds to see if size determined success in Hedgistan.  They also compared the performance of young (under 2 years old), middle aged (2-4 years old) and seasoned (4 years old +) hedge funds.

Earlier this week, the company announced the updated results of the same study.  It came as no surprise to researchers that last year’s findings were reinforced.  Young funds and small funds did better than their larger and older cousins.  The chart below appears in the firm’s press release:

You don’t need to be a finance Ph.D. to see the parallels between this research and the work of Eugene Fama and Kenneth French on the “small-cap bias”.  Apparently, small cap stocks aren’t the only small things that tend to outperform.

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Whether one is referring to a 1X0/X0 fund or to some other long/short variant like a market neutral fund, there is often an implicit assumption that the “net exposure” provides all the insight required into the return potential of the fund.  For example, many commonly assume that 130/30 funds are “beta neutral” and therefore that the “30/30″ portion will generate pure alpha.  But what if that short-extension was just offsetting?  To use an extreme example, if it was 30% long the S&P and 30% short the S&P, then there would be no alpha.

A research paper by Morgan Stanley (available here at AllAboutAlpha.com with free registration) reminds us that dollar-weighted exposure is not synonymous with beta-weighted net exposure.  But the paper, another in a series by Marty Leibowitz and Anthony Bova, also argues that the beta-weighted net exposure doesn’t really tell us a lot about the potential information ratio (alpha/tracking error) of the fund.  To gauge the potential IR of a fund, one should instead look at the ratio of “active” long positions to “active” short positions - or what Leibowitz and Bova call the “active ratio”.

The active ratio, they argue, is more descriptive of the risk/return dynamics of a fund than the more recognized dollar-weighted or beta-weighted net exposure.  They say the Active Ratio can reveal how long/short funds and 130/30 funds are really just first cousins:

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