Earlier in the week, we told you about a great 100 page “mini-book” on alpha/beta separation.  The authors (Analytic Investors’ Roger Clarke & Harindra de Silva and Brigham Young University’s Steven Thorley) provide a clear and cogent argument for why you’d want to separate and re-proportion the active and passive components embedded in any actively-managed investment mandate.

While the generic case outlined in the document involves a traditional long-only active fund, the authors also explore the potential role of hedge funds in alpha/beta separation.  They point out that despite the popular assumption that hedge fund returns are nearly all alpha, this is “only partially true” in aggregate.

Hedge Funds not all about alpha – Just mostly about alpha

The following table shows the average proportion of risk derived from alpha and beta across  arbitrarily-selected hedge fund strategies.

As you can see from the 5th line in the table, beta (vs. 3 equity and 2 fixed income factors) was responsible for only about 25% of returns, but 60% of risk.

That’s certainly a lot of “beta at alpha prices.”  But it’s not so bad compared to mutual funds:

The proportion of returns across four large and well known mutual funds (names in the paper at the bottom of page 28) averages around 85% (94% of risk).

Purists may take issue with the plain vanilla factors used by the authors to isolate alpha (i.e. nothing non-linear), but the conclusion is clear: the average hedge fund contains a higher proportion of alpha than the average mutual fund.  This reduced the amount of beta-reducing short exposure (ETFs futures, swaps etc.) required to isolate alpha.

Of course, these betas are based on a time series analysis of return streams.  But what if the fund’s exposures vary over time?  One solution is to use the current betas of the funds’ holdings to calculate a weighted average beta for the fund.  But whatever method method is used, the authors point out that unlike a lot of beta-estimating, this kind must be prescriptive (i.e. ex ante), not descriptive (ie. ex poste).

A more “economically justified way to compare fees”

Against this backdrop of the higher alpha-proportion of hedge funds, Clarke, de Silva and Thorley question the tendency for investors to compare hedge fund apples with mutual fund oranges:

“…seemingly small fees associated with traditionally managed funds can be quite high per unit of alpha…A more economically justified way to compare fees is to calculate the ratio of the dollar fee paid to the dollar amount of realized alpha, a framework more or less consistent with the current “performance fee” structure of the hedge fund industry.”

While performance fees would be a step in the right direction, they also point out two flies in the ointment:  hedge fund performance fees are asymmetrical, and they often use a hurdle that does not adequately capture exotic beta exposures.

“Alpha and Beta Reunion”

While it can work for liquid strategies such as hedge funds, calculating a reliable and actionable beta for many alternative investments is next to impossible.  You can’t strip out private equity beta, for example, since there is no reliable and liquid private equity index (you can, however, now short infrastructure beta through this recently announced product).

Sometimes, physically separating alpha and beta in order to recombine them in different proportions is possible, but inefficient since beta and alpha components would contain off-setting positions.  One solution to this, of course, is a short-extension (130/30) strategy.  In essence, a 1×0/x0 strategy aims to achieve the same thing as any alpha/beta separation strategy: re-proportioning the amounts of alpha and beta risk in an active fund.

The table from the report below shows that the proportion of alpha and beta risk changes with the gross and net exposures:

“Alpha/Beta Separation Likely to Accelerate”

In conclusion Clarke, de Silva and Thorley write that alpha/beta separation (in all of its forms) is a secular trend for several reasons:

“The practice of alpha–beta separation is likely to accelerate important institutional trends already in motion. These trends include, but are not limited to, the polarization between low-cost beta and high-fee alpha-only product providers, changes in the balance of active versus passive management in the more liquid capital markets, the inclusion of alternative asset classes in institutional portfolios, and the use of risk budgeting in portfolio construction.”

Traditional funds produce both alpha and beta.  By knowing how much of each is being delivered, investors can affect a more optimal outcome.  As the trio points out “…alpha–beta separation reminds the investor that in the complex world of active fund management, the sum of the parts is often greater than the whole.”

The cast and crew of AllAboutAlpha.com were in Los Angeles this week meeting with some of our favorite alpha centric asset managers and investment management consultants.  One of those companies was quant manager Analytic Investors.  Regular readers will remember the names Roger Clarke, Harindra de Silva, Steven Thorley and Steve Sapra for their work on extending the “law of active management” and penning a seminal work on short extension (a.k.a. 130/30) strategies.

Clarke, de Silva and Thorley were at it again this year with the release of a very interesting “monograph” (translation: “100 page mini-book”) on alpha/beta separation.  This paper is required reading for anyone with an opinion (either positive or negative) on the somewhat controversial strategy.  With so-called “alpha” allocations producing decidedly beta-like returns the past couple of years, many have discounted the value of delineating alpha from beta in the first place.

As the trio writes:

“The separation of alpha and beta sources of return in institutional portfolios has arrived and is having a profound influence on the way investors view risk and return. Some observers believe that the impact of alpha–beta separation will be as transformative as modern portfolio theory was in the 1960s, while others consider it merely a passing fad. As usual, the truth is probably somewhere in the middle, but the need for a better understanding of alpha–beta principles and terminology among investment professionals is clear.”

Clarke, de Silva and Thorley present a methodical and cogent argument for why alpha and beta should be separated in the first place.  Much of the material on this topic is either too high level (marketing bumpf) or too technical (a lesson on how to execute a swap for beta exposure).  This monograph is a “Goldilocks” description of alpha/beta separation in our opinion.  Those of you who read “Portable Alpha: Theory and Practice” edited by PIMCO’s Sabrina Callin (who was also on our itinerary this week in LA), will find this to be a useful complement to that book.

One of the questions posed to proponents of alpha/beta separation is “Why?”  Why would you even want to separate the alpha and beta that is embedded in every active fund or investment mandate?  This monograph answers this question in a concise, yet sufficiently-detailed manner.

The problem with active management, say the trio is that the ratio of active and passive risk arises organically out of the myriad of separate investment decisions made by the manager.  The resulting ratio may not yield the highest possible Sharpe ratio, however.  In other words, it may be sub-optimal.

For example, assume you owned an actively managed fund with a 0.62 Sharpe ratio.  If you decide to allocate, say, 10% (or even 50%) to cash, you’d have a fund with a lower volatility, a lower return and, of course, the same Sharpe ratio.

But that (unlevered) 50% portfolio – like any actively managed portfolio – is made up of active and passive risk.  It’s essentially made up of a market beta portfolio and a “pure alpha” portfolio.  If you create an efficient-frontier-like line tying together all possible combinations of these two separate funds, you can see that the unlevered fund you began with is really just one arbitrary point on this line.

Unfortunately, it’s not necessarily the point with the highest Sharpe ratio.  Recall that our fund has a Sharpe of 0.62.  But by reallocating between the embedded “alpha fund” and the embedded “beta fund”, you can increase the Sharpe ratio to 0.73 (see chart below from the monograph).

So what?  Well, if you wanted to allocate 90% to the active fund, you could have a 0.62 Shape (“90/10 Mix” above) or a 0.73 Sharpe by allocating 90% to active fund and shorting the market.  The table below corresponds to the chart above:

Like the apparent free lunch served up in an article we covered recently by the rocket scientists at First Quadrant (another stop on our tour of LA this week), Clarke, de Silva and Thorley seem to have pulled a rabbit out of a hat here.  But as they point out, this is simply a logical explanation for the “active risk puzzle” identified by Goldman’s Robert Litterman earlier this decade.  The problem is essentially that active/passive combinations found in active mandates (whether they are of the mutual or hedge variety) leave part of lunch sitting on the table.

There’s plenty more in this paper worth highlighting.  We’ll get to some of it in an upcoming post.

It’s often said that hedge funds – and by extension active management in general – thrive on market volatility.  Without volatility, they say, stock pickers have little opportunity to ply their trade.

Great theory.  But with the volatility of the average stock now well into in the stratosphere; shouldn’t today be a golden age for active managers?

Yes and no, according to one expert.  Steve Sapra of Analytic Investors (see related posts) told a conference audience in New York this week that volatility alone isn’t enough to give active managers their moment in the sun.  Instead, active management requires two things: high volatility and a high “cross sectional dispersion” between stock returns.  While Sapra’s remarks were targeted to a group of 130/30 managers and investors (at Terrapinn’s annual 130/30 conference), his lessons can easily be applied to active management in general (”120/20″, “110/10″ or just plain “100/0″).

As Sapra explained, cross sectional dispersion measures the extent to which stocks move in different directions at a point in time.  Active managers rely on these disparate movements as fuel for their market beating returns (a.k.a. “tracking error”).  As a result, said Sapra, cross-sectional dispersion is usually a more important predictor of active management opportunities than volatility in general.

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Roger Clarke

Chairman, Analytic Investors.   Served as a member of the editorial boards of the Journal of Portfolio Management and the Financial Analysts Journal. He also served on the faculty of Brigham Young University for eight years.

Analytic Investors
Relevant Postings (AllAboutAlpha.com)

Harindra de Silva

President, Analytic Investors.  Author of several articles and studies on finance-related topics including stock market anomalies, market volatility and asset valuation.

Interview (Pensions & Investments)
Analytic Investors
Research (SSRN)
Relevant Postings (AllAboutAlpha.com)

Earlier this month, Pensions & Investments held a tri-city 130/30 dog-and-pony show in San Francisco, Chicago and New York.  And this week, they released several presentations given at the event.  So if you happened to have missed the show when it came through town, you might be interested in seeing the slideware available here at P&I.  Below we give you our take.

John Power of Pyramis gave a succinct overview of the rationale, costs and benefits of 130/30 that also included what has probably become the most popular slide in any 130/30 presentation:

The key message, of course, is that you simply can’t bet against most names in the index in a significant manner.  In our view, the difference between underweighting a 0.5% position by 0.5% and underweighting it by, say, 0.6% isn’t significant from an investment standpoint (some might argue the requisite introduction of short-selling brings with it some new operational issues).

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Faced with a lack of track record for active extension funds, researchers are forced to re-create how these funds would have performed if they had existed for some time.  The idea is to select an “alpha model” (an unfortunate term since alpha cannot technically be “modeled”) and run it back in time using real market data to see how it would have performed.  The model is run once as a long-only portfolio and then again using any number of 1X0/X0 strategies.  Comparing the performance of the models can yield some insight into whether the short extension itself adds value to a given alpha model.

The latest to conduct this analysis are Carl Armfelt and Daniel Somos, graduate students at the Stockholm School of Economics.  Armfelt & Somos selected a set of basic Fama/French factors to create their alpha model and ran it all the way back to 1927.  Here’s what they found:

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Although it’s usually obfuscated by complex mathematics and applied only to world of investment management, “alpha” is a remarkably ubiquitous concept with applications that go well beyond the Capital Asset Pricing Model.   Steven Sapra, co-author of a recent paper on 130/30 (see related posting) provides us with proof of this.  Regular readers may recall his article about “NFL Alphas” posted on the Analytic Investors website last winter (see related posting).  Sapra has continued to research this topic and his latest conclusions are contained in an article to be published in the upcoming edition of the Journal of Sports Economics (a very cool-looking publication that AllAboutAlpha readers may find interesting).  The study is also available here.

The article goes by the unwieldy title “Evidence of Betting Market Intra-Season Efficiency and Inter-Season Over-reaction to Unexpected NFL Team Performance”, but can probably be summarized as simply “Don’t Fall for the Darlings”. Sapra compares the expected results of over 4,000 regular season NFL games (based on the point spread) with the actual results of each match-up.  If the NFL wager market is perfectly efficient, the actual results should be randomly distributed around the predicted results.  In other words, a “fair” point spread means that the marginal bettor is ambivalent between taking either side of a bet – in the same way that the marginal investor should be ambivalent about paying the “fair” price for a security.

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With 1X0/X0 strategies pegged to draw in trillions over the next decade, the sticky question of the potential market impact was top of mind today in New York at a conference focused on portable alpha and 130/30 strategies.  Participants ruminated on portable alpha yesterday.  Today was all 130/30.

With the short selling required for 130/30, the 800 pound gorilla in the room was the finite supply of stock actually available to borrow.  In a posting last fall, we discussed a report by Goldman Sachs on this topic (see related posting).  Speakers here seem to share our skepticism about whether this posed an immediate problem.

However, many weren’t so sanguine about the longer term.  I asked Deutsche Bank’s Brian Bausano, Co-head of Global Prime Finance for the firm, whether there would someday be a “shortage of shorts”.  He replied that, notwithstanding today’s huge excess borrow capacity, potential shortages would be “non-linear” and would likely occur in certain parts of the market first.  For example, he suggested that borrow shortages would likely show up in small-cap names first since small cap names are more likely to be shorted by 130/30 managers and since there is simply less stock available in these names.

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As you probably know if you are a regular reader, The Institute for Quantitative Research in Finance” (or Q-Group for short) is one of the world’s foremost communities of quant rock-stars from the academic and practitioner communities.  In his video interview for the American Finance Association’s “History of Finance” project, William Sharpe tells of how he was actually at a Q-Group annual seminar when he learned of his Nobel Prize.

Well, no one won a Nobel Prize at last spring’s meeting.  But the 17 pages of session summaries, now available here, are well worth a read.  Here is a selection of what you’ll find:

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Readers of yesterday’s posting on Gordon Johnson’s 130/30 paper will remember that he took inspiration from the earlier work of Roger Clarke, Harindra de Silva and Steven Sapra.  Well it turns out this prolific trio (plus fourth bandmember Steven Thorley) have just published a new paper of their own on 1X0/X0.

Many regard these four as being the originators of the craze we now know as 130/30.  In an article last spring on the website of UK-based consultancy bfinance, AllAboutAlpha.com Hall of Famer Tris Lett observed that, like so many mega-trends, 130/30 was originally cooked up on the sunny shores of Southern California:

“While some may say that they were running strategies in the short enabled structure before Analytic Investors, I can find no one who precedes them.  Harindra de Silva, Roger Clarke and Steve Sapra of Analytic Investors earn the credit for naming the process and operating the first real time portfolio. On July 1, 2002, Analytic [of Los Angeles] launched its Core Plus Equity Composite (120/20) strategy.”

Clarke, de Silva, Thorley and Sapra have since achieved stardom by producing several papers on the topic of 130/30.  Their newest production, “Long/Short Extensions: How Much is Enough?” has now been revised after a limited release over the summer at a screen near you.

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Rob Arnott isn’t afraid to go against the grain.  His “fundamental indexing” methodology ignores price and value-weighted indices and instead uses fundamental business metrics such as sales and revenue to construct investment benchmarks.  He says this avoids the propensity for indices to overweight temporarily overvalued stocks and underweight temporarily undervalued stocks.

But the idea has always had its skeptics – many of whom argue that fundamental indexing amounts to value investing in disguise.  After all, they say, it simply amounts to overweighting high book-to-price stocks and underweighting low book-to-price stocks.  Arnott is well aware of such criticisms and apparently plans to launch a counter-offensive soon.  According to P&I, that counter-offensive will involve none other than Harry Max Markowitz, father of modern portfolio theory.

P&I reports on a paper in the works by Harvard professor Andre Perold called “Fundamentally Flawed Indexing”.  Apparently, those who have seen it say it makes a lot of sense.  Eric Sorensen, president and CEO of PanAgora (see posting: “King of Quants“) tells P&I that fundamental indexation assumes “large-cap stocks are overvalued, and you don’t know that”.

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With the major league baseball season getting under way in the US, Alpha Male’s 5 year old son has quickly become enamored with the daily league standings. Well here’s a league table that he won’t find in our local paper. Pensions & Investments reports today that institutional money managers now manage, you guessed it, $30 billion in 130/30 “or similar equity strategies” ($29.9 billion to be precise). And for those scoring the game at home, P&I also has a great listing of who exactly is offering what in the burgeoning world of “1X0/X0″.

P&I’s Jay Cooper reports that State Street, BGI, and Jacobs Levy have the early lead, but that “no firm has established itself as king of the mountain yet”. Other analysts polled for the story pegged the number at up to $60 billion when you include capital “allocated but not yet invested”.

Apparently, it hasn’t been too tough convincing asset managers to offer “short extension” strategies – the fees are higher. According to P&I, fees for 130/30 range between 60 and 100 bps vs. 50-80 for a typical US active large cap strategy. (Manager database provider eVestment Alliance also keeps a list of institutional manager fees across a whole whack of strategies for easy comparison).

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“130/30″ seems to have successfully supplanted “portable alpha” as the term most likely to roll off the tongues of institutional investors and asset management marketers.  But how did such a term arise from nowhere so quickly to capture our collective imagination? This article on the website of UK-based consultancy bfinance written by 130/30 advocate (and amateur historian), Tris Lett, says the term is really only about 5 years old and it hails from California. Says Lett:

“Harindra de Silva, Roger Clarke and Steve Sapra of Analytic Investors earn the credit for naming the process and operating the first real time portfolio. On July 1, 2002, Analytic launched its Core Plus Equity Composite (120/20) strategy.”

“This makes perfect sense given the line of portfolio research they published based on Grinold/Kahn’s “Law of Active Management” to whose logic they introduced the important notion of the transfer coefficient. They pointed out that short sales increase the alpha generating opportunity set.”

For those new to 130/30 (”1X0/X0″), this article is a great introduction to the concept (and not just because it references “the widely read blog AllAboutAlpha.com“.)

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“NFL Alphas” 

Admittedly, alpha is a bit of an obsession for us at AllAboutAlpha.com.  We view alpha as the “magical”, un-replicatable, skill-based, value-add produced by human creativity.  In a world where nearly everything can be explained by systems, just about the only thing we can’t synthetically and cheaply replicate is human ingenuity.  In other words, what we can’t explain using known variables we chalk up to “alpha”.  This applies to financial markets, business, education, the arts, and even - as this article points out – to American football. 

Analytic Investors (see previous posting) calculates an “alpha” for NFL teams at the end of each season of American football.  They define this alpha as “the extent to which each team exceeded or underperformed its expectations”.  Essentially, they attempt to identify how well a team performed given the raw materials available to it.  While a comprehensive list of these raw materials isn’t listed anywhere, the “market” (i.e. bettors) collectively defines them via predicted margins of victory.  We might refer to this alpha - this unexplainable quality – as “heart” or perhaps “skill” displayed by the head coach in making the most with what he was given.

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