You can lead an investor to liquid alternative beta, but you can’t force him or her to drink it. That’s the tongue-in-cheek sort-of message behind a white paper academic study released by Credit Suisse Asset Management this week on liquid alternative beta (LAB, for short), better known as hedge fund replication.

The report (click here to download in PDF form; click here for Credit Suisse’s LAB Web page) argues that just as index-linked investments in the long-only world have slowly but surely gained traction and acceptance, so too will LAB gain acceptance as an effective diversification and portfolio management tool – eventually.

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Hedge fund detractors often argue that hedge fund returns are driven by systematic risk factors (beta) not manager skill (alpha) as is often assumed.  During the hedge fund industry’s 2-decade-run of positive returns, this argument took the sheen off of hedge fund returns and suggested they could replicated using much cheaper passive investments.

But 2008 threw a bit of a wrench into the works.  If beta (or it’s exotic cousin alternative beta) was responsible for the positive returns, then were they also responsible for the negative returns?  And if so, was hedge fund alpha actually positive during the dark days of 2008?

A new study says yes, hedge funds produced alpha in 2008, just as they had in previous years.  In 2010’s “The ABCs of Hedge Funds: Alphas, Betas, & Costs“, Roger Ibbotson, Peng Chen, and Kevin Zhu update their widely-read 2006 paper of the same name.

The trio of researchers are clearly impressed with what they discover…

“The positive alpha [of hedge funds] is quite remarkable, since the mutual fund industry in aggregate does not produce alpha net of fees. The year by year results also show that alphas from hedge funds were positive during every year of the last decade, even through the recent financial crisis of 2008 and 2009.”

What’s even more notable is that this conclusion is reached after adjusting for common complaints such as “backfill bias” and “survivorship bias.”

As in the 2006 edition of their analysis, Ibbotson, Chen and Zhu decompose hedge fund strategy indices into alpha, beta and “costs” (backing out a “1.5 and 20″ fee level).   In contrast to other studies that attempt to identify hedge fund alpha, they use only stocks, bonds and cash as regressors.  While many might question this approach, the trio says there is method in the madness…

“We agree that a portion of the hedge fund returns can be explained by non-traditional betas (or hedge fund betas). However, these non-traditional beta exposures are not well specified or agreed upon, and are not readily available to individual or institutional investors. A substantial portion of alpha can always be thought of as betas waiting to be discovered or implemented. Nevertheless, since hedge funds are the primary way to gain exposure to these non-traditional betas, these non-traditional betas should be viewed as part of the value-added that hedge funds provide compared to traditional long-only managers.”

For the more graphically-inclined, here’s what they found (Jan. ‘95 to Dec. ‘09)…

Alphas, Betas, Costs & Deltas

If you’re like us, you might be wondering how this year’s results differ from the 2006 results (which included data from Jan. ‘95 to Apr. ‘06).  In other words, how does the introduction of 2008 data change things?

So we measured the difference between the 2006 strategy-specific alphas and the 2010 strategy specific alphas.  As you can see from the chart below, the alphas produced by many hedge fund strategies fell as a result of adding recent data to the analysis – although the alpha of an equal weighted index of hedge funds remained about the same.  Emerging markets managers must have had a humdinger of a year in 2008 in order to increase their average annual alpha by 3%.  Given the out-performance of emerging markets equities over the S&P 500, this comes as no surprise.

Backfill

The paper also contains an interesting table showing the percentage of return data for each strategy that represents “backfill” (returns from months prior to the point at which the fund began listing itself.  One might assume that a high percentage of backfill means that managers in that category tend to wait a little longer before reporting their returns to the hedge fund database.

Could it be that Managed Futures Managers and Short Managers tend to begin reporting data only after a longer track record has been established?  Are they less sure of themselves during the start-up phase?  Or is this just a statistical anomaly?

Does Size Matter?

Another interesting observation contained in the paper is that larger funds (or, we surmise, funds managed by larger managers) tend to produce higher raw returns…

But wait!  The study also found that larger funds tended to have a higher volatility.  So the smaller funds actually had the better reward-to-risk ratio (specifically, those in the 20-50% decile)…

Interesting observations aside, the main conclusion of this paper is that hedge funds do seem to produce alpha – at least, at the moment.  The 2006 edition of the paper concluded with this ominous forecast:

“A significant amount of money has flowed into hedge funds in the past several years. Therefore we cannot be assured that the high past alphas we measure are a good prediction of the future alpha in the hedge fund industry.”

By 2010, this forecast seems to have come partially true for some strategies as their alphas fell.  The trio makes the same forecast in the current edition of the study.  So the $1.5 trillion question remains: Wither hedge fund alpha?

Despite having its 15 minutes of fame a couple of years ago, so-called “hedge fund replication” still seems to capture the imagination of bargain-hunting institutional investors (see related post).  Regular readers and students of this labyrinthine field will recall that there are basically three ways to approximate hedge fund index returns using other means:  Factor-based (investing in trade-able versions of off-the-shelf passive exposures), rules-based (using trading algorithms to essentially mimic the trading strategy of various classes of hedge fund) and distributional (re-creating the end result of hedge fund indices – their return distributions – without regard to the timing of returns or correlation with the index being replicated).  Distributional replication models have so far been based on the dynamic trading of one particular asset – usually a futures contract – as opposed to the choice of underlying assets.

AllAboutAlpha.com contributor Professor Harry Kat and Helder Palaro formerly of the Cass Business School (at the City University of London) are widely credited with giving life to this approach (see original post – search “Kat” in sidebar for more).  Nicolas Papageorgiou, Bruno Remillard, and Alexandre Hocquard  from HEC Business School in Montreal proposed some modifications to this technique in 2007 (see related post). More…

By: Andrew Saunders, Member of the Editorial Board of AllAboutAlpha.com, & Director, EFX Prime Services

In January the Wall Street Journal reported that ETF assets had crested $1 trillion. No longer is it simply another way to capture S&P 500 beta. It seems that every day there is an innovative new investment idea that is packaged in an ETF form. Joining us this month to discuss how ETFs play a role in an alternative investment portfolio is Adam Patti, CEO and Founder of IndexIQ . A lifelong entrepreneur, Adam has founded and run a number of companies in a number of business areas including marketing, technology and supply chain management. He was an early pioneer in ETFs, having led an indexing/ETF initiative involving two products while at Fortune Magazine, including the Fortune 500, the first fundamentally derived Broad-based index. His new venture brings ETFs to the alternative realm via a distinct replication methodology seeking to offer exposure to the return profiles of a number of hedge fund indices. Is this the wave of the future? Adam is here to shed light on this growing segment of ETFs. More…

Hedge funds: you either love ‘em or hate ‘em, right?

Well, it appears that investors and commentators may actually love them and hate them at the same time.  As Wikipedia defines a “love-hate relationship:”

“…a personal relationship involving simultaneous or alternating emotions of love and enmity. This relationship does not have to be of a romantic nature, and may be instead of a sibling one. It may occur when people have completely lost the intimacy within a loving relationship, yet still retain some passion for, or perhaps some commitment to, each other.”

It seems that every January, there is a proliferation of media stories about how – despite their apparent disdain for hedge funds -  investors show a commitment to hedge funds by clamoring to mimic them through either a) hedge fund replication products or b) “hedged” mutual funds. More…

The infinite monkey theorem states that a monkey hitting keys at random on a typewriter keyboard for an infinite amount of time will eventually bang out some sort of recognizable text, such as the complete works of William Shakespeare.

Along the same lines, one might argue that Exchange-Traded Funds, or ETFs, are in alternatives’ form at least a version of the monkey-at-typewriter theorem, by virtue that a synthetic composition of securities combined into something that is purportedly a hedge fund can mimic, if not the best, but the same strategy and returns as a hedge fund manager — eventually.

All this monkey business theory stems from Rye Brook, New York-based IndexIQ’s release of the IQ ARB Merger Arbitrage ETF (ticker: MNA), which began trading this past Tuesday.

How it works: the ETF relies on a fixed rule book – the main requirement being that an acquirer must have offered a premium to a target company’s market price: More…

Ah, the good old days – when the hedge fund “secret sauce” was revealed and suppliers set about developing the products that would bring it to investors the world over under the moniker “hedge fund cloning”.  But as Swiss researchers Erik Wallerstein, Nils Tuchschmid and Sassan Zakerc note in a recent paper called “How do hedge fund clones manage the real world?”:

“Some years ago hedge fund replication was a much discussed topic on the hedge fund horizon. A credit crunch and some hedge fund Ponzi schemes later, the attention has turned elsewhere.  2008 performance of broad hedge fund indices where dismal at best. This did not bode well for selling pitches to persuade investors to turn to funds which replicate this performance.”

However, the trio goes on to argue that the $2 billion hedge fund replication business is far from dead.  Hedge fund replicas, they say, “…have several unique and interesting features, many which where attractive during the crises of 2008.”

They analyze the recent performance of 21 hedge fund clones from 17 companies covering the full spectrum of replication techniques from factor replication to distributional replication to mechanical replication.  (see the “Alternative Beta and Hedge Fund Replication” category at the right side of this page for extensive coverage of these topics).

Here’s how the 21 fund stack up from March 2008 to May 2009 (chart based on data in paper)… More…

With hedge fund performance starting to look up, a reader recently suggested we check up on the trials and tribulations of “hedge fund replicators” – those who aim to clone the returns of hedge funds via passive exposure to highly liquid and ubiquitous investments.  The most well understood method of doing is to use a factor model based on a trailing regression of hedge fund industry returns.  One of the most prominent players in this space is probably Merrill Lynch, purveyors of the “Merrill Lynch Factor Model” (factor model website).

The firm describes the index this way in its marketing sheet: More…

In just about every action movie and TV show these days there is at least one scene where the hero asks one of his or her techies to “sharpen” a satellite image.  Suddenly, what looked like a fuzzy bunch of pixelated squares takes on the form of someone’s face, a car, or some kind of mobile rocket launcher.   We’re not graphic imaging specialists.  But to us, it looks kind of outlandish that someone could take a very small amount of information (a few pixels) and divine the underlying image in fantastic detail.

But in a way, that’s exactly what Daniel Li & Michael Markov (of quantitative investment software vendor Markov Processes) and Russ Wermers of the University of Maryland have done in a paper released last month called “Monitoring Daily Hedge Fund Performance When Only Monthly Data is Available.”  Their trick is to leverage another kind of technology: hedge fund replication.

As we have reported extensively, “linear factor replication” aims to predict the performance of hedge funds based on a multiple regression of their historical returns on a number of variables such as equities, Fama/French factors, and several more “exotic” risk factors. More…

Passive investment in hedge funds has always been somewhat of an oxymoron.  Hedge funds, after all, aim to deliver active management (alpha).  And since alpha is a zero sum game, a passive investment in hedge funds should deliver a zero return.  Nonetheless, this axiom has always been challenged by proponents of various products designed to deliver aggregate “hedge fund returns”.

First there was the passive fund of funds; then came the investable hedge fund index; and finally there was hedge fund replication.  In essence, all of these products delivered similar value propositions: diversification, transparency, and liquidity.  (Despite the tendency for these providers to compete on returns, out-performance was never officially the goal of these “passive” products).

Hedge fund replication seemed to be the story of the year in 2008.  But in the post-Madoff environment, the pendulum may be swinging back in the other direction.  The investable hedge fund index – derided by proponents of hedge fund replication as being expensive and opaque since it invests in hedge funds themselves - is making a comeback. More…