Right up until last fall, practically every alternative investment conference this side of the date line had at least one panel of experts discussing and debating the elusive search for alpha, and how to capture and augment a traditional or even non-traditional portfolio by finding managers that were truly capable of generating non-beta returns.

And then the black swan-poop hit the fan.

Nowadays talk of alpha generation and alpha-beta separation still permeates, though the search for it – and expectations of finding it – has greatly diminished. It’s more about earning a return – period – than earning a return above and beyond what the rest of the market is looking for.

Along these new lines has emerged a very quiet yet growing subset of individuals who believe that alpha still exists, but that getting it isn’t, dare they say, legal.

From market-timing and late-trading to illiquid valuation techniques and 20:1 levered bets to discrepancies in share pricings between markets and indices to the growing popularity of super low-latency flash trading, these pundits, who wish to remain both nameless and faceless for fear of being drawn and quartered by their bretheren, argue that alpha can’t be obtained legally.

Of course, for every one individual who might dare argue that alpha can’t truly be obtained, there are hundreds who will vehemently argue that it can: that alpha in of itself can be created simply by allocating to a non-traditional portfolio or basket, which in turns makes it a non-beta play.

Dig more deeply, though, and true alpha generation begins to look a little more difficult to come by: now-defunct hedge fund Galleon promised alpha, as did a host of alternatives shops before it, Lancer Group, Beacon Hill and many other notorious shops who claimed by definition to produce alpha through their various methodologies and abilities, most of which weren’t, at the end of the day, on the up and up.

From an academic perspective, the question of whether alpha exists and can be obtained is actually nothing new. Roger Urwin and Gerard Roelofs of Watson Wyatt produced this presentation back in early 2006 that questioned whether pure alpha or even pure beta exists.

And from this report published by Dr. Lars Jaeger, a partner with Swiss-based asset manager Partners Group, alpha, if it can be obtained at all, is steadily diminishing.

Which begs the philosophical question: What exactly is alpha? Is it a tangible and quantifiable concept, a true risk-adjusted measure of the so-called active return on an investment in excess of the compensation for the risk borne? Is it an ideal that many lay claim to but that can’t actually be obtained? Or is it simply the first letter in the Greek alphabet?

Alpha is a risk-adjusted measure of the so-called active return on an investment. It is the return in excess of the compensation for the risk borne, and thus commonly used to assess active managers’ performances. Often, the return of a benchmark is subtracted in order to consider relative performance, which yields Jensen’s alpha.

According to Montreal-based Castle Hall Alternatives, which maintains a comprehensive database of frauds, blowups and other hedge fund misnomers, some 300-plus hedge fund frauds and / or implosions have taken place over the past decade or so. While difficult to figure out which of those frauds and blowups claimed to run an “alpha” strategy, complex, illiquid, levered or some combination does permeate as a theme.

So is alpha simply an alternative to beta, in which case by definition anything not part of the mean of generating non-correlated returns? Or is alpha in fact plain-vanilla alternative beta? Or is alpha something that is indeed non-correlated and above and beyond what the rest of us mere mortals can produce, but not in a legal or perhaps ethical fashion?

As our name suggests, we believe in the ability to generate alpha, and we believe there are many bright minds and quantifiable alternative strategies that can and so produce it in a perfectly legal and compliant way.

However, there likely does lurk a group of managers and traders who aren’t following the rules when it comes to generating it. From a due diligence perspective, the key is trying to figure out – and stay ahead of – those who might be taking the low road to getting it.

Some food for thought for the US Thanksgiving weekend.

Special to AllAboutAlpha.com by: Dr. Lars Jaeger, Partner, Partners Group…

For a long time, many investors have regarded hedge funds as an investment class that generates absolute returns by means of managers’ sophistication in extracting inefficiencies from the complexity of the global capital markets.  However, the current financial crisis has forced investors to reconsider this belief.  Even before 2008, the hedge fund battlefield had been littered with the bodies of secretive funds such as LTCM, Quantum, Tiger, Niederhoffer, and Beacon Hill, all of which failed spectacularly in comparably much less severe market environments.

The crisis year 2008 saw countless new casualties.  Hedge funds have proven to be part of “the system” and even if they enjoy greater flexibility and certain advantages, they were not able to fight against the type of market distress we have recently seen.  The average hedge fund has lost around 20-25% in 2008. The industry has subsequently experienced several “worst months in history” only to be topped by one of the next months.  October and November 2008 were just the latest “menses horribilis” for hedge funds, months in which even some high flying stars of the scene experienced losses in the range of -25% to -50%.

Finally December brought another major blow of pain to hedge fund investors when the alleged Ponzi scheme of Wall Street icon Bernard Madoff fell apart pulling 50 billion USD out of the hedge fund industry (including high profile funds of hedge funds) and causing a big stain on the industry’s public reputation.

Figure 1 provides an overview of the industry’s returns in the various strategies.  (ed: HFRX is an investable index that generally underperforms traditional indexes such as its non-investable sister, the HFRI.)

These losses occurred just as hedge funds had expanded to a broader institutional investor base intrigued by their promise of “absolute returns”.  Watching their investments fall short of these promises, these investors are growing increasingly skeptical about what the “traditional hedge fund model” is able to deliver.

As a result, the institutional investors that drove recent industry growth have become less willing to drop billions into a black box and hope for the best.  In fact, they have started to pull out their money in unprecedented amounts – leading to another devastating blow: a liquidity trap (which ultimately led to the demise of Madoff’s fund).  In their search for returns, hedge funds had recently begun to invest in less liquid investments and apply private equity techniques to public targets (activist investing), thus extending the liquidity features of their underlying investments.

Many, including Partners Group, were concerned about this development since private equity funds had a much more stable and long term capital base.  In addition, we were concerned about hedge fund “black boxes”, as readers of our research will surely recall (see previous AllAboutAlpha.com posts).  Unfortunately, these concerns proved to be justified much faster than we could have ever anticipated.  In 2008, an asset-liability mismatch forces a number of hedge funds to withhold redemptions, and the revelation of the alleged Madoff Ponzi scheme caught many investors off guard (especially fund of funds that put insufficient emphasis on solid due diligence, transparency and active risk management).

2009 and Beyond

In light of the excruciating pain that hedge funds have suffered and a growing consensus – even among hedge fund advocates – that the industry is going to suffer short and mid-term redemptions, many investment professionals are asking themselves about the long term effects on the industry.

In light of these developments, we anticipate the following effects on the global hedge fund industry:

1. With the shrunken balance sheets of the banks, hedge funds will have less access to leverage financing.  This will obviously affect those strategies that have been employing significant leverage, i.e. the “Relative Value” strategies such as Fixed Income Arbitrage, Convertible Arbitrage, and Statistical Arbitrage.
2. Regulatory constraints such as the banning on short-selling coupled with increased regulatory oversight are going to rob hedge funds of the flexibility necessary to exploit their return sources. This will affect most equity related strategies such as Long/Short Equity, Event Driven, and Equity Market Neutral.
3. The decline of alpha has been documented on countless occasions even before all the recent trouble started.  The majority of today’s hedge fund returns stem from risk premia rather than market inefficiencies, in others words, from “beta” instead of “alpha”.  Risk premia have risen across all markets in the ongoing flight to quality.  Consequently, declining and negative (alternative) betas have had a detrimental effect on hedge fund returns.  However, short to mid-term expected alternative beta returns will likely be significantly above historical averages.
4. Significant losses, the introduction of redemption gates, and the largest alleged fraud in the history of Wall Street means that opacity and illiquidity – once considered a source of strength for the hedge fund machine – has turned into a formidable liability.  The industry will finally have to give up its black box approach, and the major fund of hedge funds will have to revisit their investment and business model.
5. The prototypical 2/20 fee model and possibly higher trading and financing fees from their prime brokers will mean that the fee burden faced by hedge fund investors will have to come down in order for net returns to become attractive again.  Indeed, we can observe that this has already begun.

Hedge funds are here to stay, but not here to stay the same.  While the first three points above are structural rather than cyclical, alternative beta will remain a promising source of investment returns.  In other words, there is a tailwind for hedge funds.  Market dislocation and investors’ fears will provide for ample return opportunities in form of high “standstill returns” from alternative beta.

This means that 2009 will likely be a strong year for the surviving hedge funds.  Those investors and investment managers with cash to invest now are surely going to be richly rewarded.

Whither “Absolute Returns”?

But how about the original hedge fund promise of “absolute returns”?  Hedge funds have been marketing their “alpha” while many have actually delivered “diversified beta” (what a few years back we started calling the “alternative beta” game, i.e. diversify across a large spectrum of return drivers that balance the investment risk of each individual underlying risk).

The market distress this year has given a final vindication to this hypothesis.  In a painful way hedge fund investors had to learn what some academics and very few hedge fund product providers have told them all these years – that hedge funds delivered mostly (alternative) beta returns.

As a consequence of the recent financial crisis, the motto of hedge funds should now be, “Chase alpha where available, diversify across betas where necessary”.  As a result of declining alpha at home, many of the top hedge funds had already moved to where the fields were still green, namely the private capital markets.

Hybrid Hedge Fund Strategies and Liquidity

But there is an important prerequisite for hedge funds “going private” – having a stable and well-secured capital base. In other words, the hedge fund needs to persuade investors to forgo liquidity.  In other words, the hedge fund manager needs to know what he is doing with respect to asset/liability management.

That does not mean that the new “absolute return” portfolio will have to mimic a conventional private equity portfolio (requiring, for example, an investment commitment of eight to ten years).   Many investors already have that part of their portfolios managed by (pure) private equity players and will expect a different kind of exposure and liquidity from their absolute return investments.

This being said, the short duration end of private market investments such as mezzanine loans and late stage (purely financial) secondary investments offer a wide spectrum of opportunities that the investor with higher liquidity demands can benefit from in his absolute return bucket.  Mezzanine and senior bank loans for examples have payback periods of 36 months rather than ten years, and a late stage secondary can return the capital equally fast.

These are areas in which hedge funds have started to become very active in the recent years.  While the focus on generating absolute returns through alpha naturally drives investors to private market investments, in practice many investors have liquidity needs.  So institutional investors need to find the right balance between maximizing (risk adjusted) return and providing sufficient liquidity.  Too much liquidity means foregoing returns; too little liquidity can quickly turn off investors.

A New Approach to Portfolio Construction

Once the right balance between return objectives and liquidity profile is established, investors must turn to these asset allocation decisions.  With the traditional (mean variance based) optimization model and related statistical optimization techniques failing to deliver reliable results, we suggest a different macroeconomic scenario based approach for the portfolio construction.  (Other investment managers such as Bridgewater Associates have expressed similar ideas.)

Asset class pricing and investment returns are generally a function of expectations of changes in  macroeconomic variables such as growth and inflation.  However, exact forecasts of these parameters are extremely difficult, if not impossible.  For that reason the investor should balance an absolute return portfolio across an entire range of optimal portfolios in each respective scenario.  Concretely, this means averaging across the different “scenario portfolios” in order to obtain the final balanced asset allocation.  By balancing risk across the different environments, the investor is able to earn various asset class returns while minimizing the portfolio’s susceptibility to any one environment.

The “Relative Value” Approach

Once the general scenario based portfolio is determined, allocations to different segments should be based on current relative value assessments (e.g. alpha opportunities in private equity markets are bigger than they are in public equity markets), fees (e.g. fee-efficient access to certain hedge fund strategies via alternative beta strategies) and liquidity.

In fact, while the overall asset mix across private markets, alternative beta, offshore hedge funds, and other asset classes and risk premia can be kept rather static, there is room to manoeuvre within each.  For example, it makes a difference whether one accesses leveraged buyout returns through a direct investment in a limited partnership or in the secondary market.  In addition, the relative attractiveness of hedge fund strategies fluctuates over time – demanding a tactical allocation process.

The final step in this asset allocation process is to conduct solid bottom up investment research (i.e. finding the best companies, the right structures, and the right types of instruments to extract the highest possible return from in a given market environment).

In summary, what is really needed for effective absolute return asset management is a holistic perspective on investing instead of one contained to particular asset classes and return drivers.  The key to absolute return investing is to combine all available asset classes and investment strategies.  Some of the smartest money managers in the world have already executed this successfully (and silently).

The new challenges and opportunities presented by the recent financial crisis require just such an integrated business model and investment approach.  Alternative asset managers with highly focused capabilities will struggle in 2009 and beyond.

- L. Jaeger, January 15, 2009

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

As 2008 enters the history books, we look back at the top ten most popular posts at AllAboutAlpha.com over the last 12 months.  As you can guess, most have a decidedly negative tone – redemption gates, shrinking AUM, warnings over quant models, securities lending problems, terrible monthly performances…

Thankfully the year is just about over.  If you are in the office today, here is a walk down memory lane that will make you especially happy to welcome in a new year.  (We have temporarily granted free access to all of these archived posts.)

1. Securities lending starting to dry up a little?: The hedge fund industry relies on short-selling. Short-selling relies on securities lending. And securities lending relies on the willingness of institutional investors to temporarily part with their stocks. So what happens if those lenders get nervous?
2. Hedge funds discovered not to be an “asset class” after all: When is an asset class not really an asset class?
3. Stigma of redemption gates fading fast: Back in the old days (like, in August), shutting a “redemption gate” used to be a form of punishment. Now it’s more like “tough love”.
4. Exactly how much of the hedge fund industry is about to get chopped anyway?: Recent estimates about the imminent shrinkage of the hedge fund industry have varied widely. So we asked one expert to help us cut through the confusion.
5. Replicating Hedge Funds: Traditional beta or alternative beta?: In this guest post, Partners Group’s Lars Jaeger says that although you could have replicated hedge funds using equity beta over the past 4 years, “alternative beta” is still where it’s at.
6. Exactly how bad was September for hedge funds?: If hedge funds beat equity markets in September, then what’s all the fuss about? For a visual answer to that question, just take a look at these charts.
7. Shadwick to Quants: “Financial models should come with health warnings!”: In this guest post, Dr. William Shadwick, developer of the Omega Function used in risk management, warns that “over-modeling” has “negative consequences”.
8. Asness: Quant funds not actually “HAL 9000? black boxes: In an article by Alpha magazine, AQR’s Clifford Asness says that quant funds can still profit from new opportunities and that they are actually far more transparent than most fundamentally-driven funds (or than the “HAL 9000″, for that matter).
9. Alternative Viewpoints: Commodities not about “buy and hold”: There is little doubt that commodities are hot. But as Keith Black, CAIA, argues in this guest post, investors must move well beyond simple “buy and hold” strategies.
10. Morningstar’s Deutsch: 130/30 “not monolithic” but does represent a “convergence” in money management: In this guest post, Morningstar’s Steve Deutsch has a bird’s-eye view of the burgeoning 1X0/X0 field. Today, he shares this perspective, concluding that money managers are stealing a page from the telecom playbook.

“One of the great things about hedge funds is that they have provided a field day for academic researchers to write scholarly articles on their risks and returns. Yet, for all of this scholarship, a practical roadmap to hedge funds has remained elusive. Until now.”

So begins a new 168 page treatise aimed at dispelling the “myths” surrounding hedge funds and educating investors.  The document, called “Road Map to Hedge Funds” was released this morning by the Alternative Investment Management Association (AIMA) and is squarely aimed at an institutional audience (the report is also bylined by The CAIA Association, UBS, and CalPERS).  Co-authors Alexander Ineichen of UBS (see related posts & interview) and Kurt Silberstein of CalPERS cover just about every question an institution might have about this poorly understood category of investments.  In his foreword to the document, alternative investment pioneer Mark Anson describes it as a:

“…pragmatic, user-friendly book that will go a long way to breaking down the myths of hedge funds while providing the user the ability to construct an intelligent hedge fund portfolio. Along the way, the psychobabble of the hedge fund world is eschewed to provide a commonsense guide in commonsense language that all can understand.”

Regular AllAboutAlpha.com readers will recognize a lot of the thought leaders quoted in the “book”: Larry Summers and Sandy Grossman from the recent “unnamed event” in Boston (see related posts), Peter Bernstein author of Capital Ideas Evolving (see AAA review), Nassim Taleb (see related posts), Lars Jaeger (see related posts), Andrew Lo (see related posts), Larry Siegel (see related post), and of course, Ineichen himself, who is also the author of Asymmetric Returns.

But beyond the usual alternative investment crowd, the document makes liberal reference to names more commonly associated with “traditional” thinking: Benjamin Graham, Winston Churchill, Mark Twain, Albert Einstein and Warren Buffett (yes, even the man who says hedge funds can’t even beat the S&P 500 over the next 10 years – see related post).

If you are really into the topics covered on this website, you may find the document to be a little basic (it’s designed for an “intermediate” audience).  After all, we eat Anson’s “psychobabble” for breakfast.  But the document does a great job of bringing together all of the salient topics in one easy-to-read form.

It’s not all hedge fund cheer leading either.  For example, page 14 makes reference to the fact that hedge fund returns have been lower this decade than they were in the 80’s and 90’s and page 16 shows how wildly disparate industry size estimates have become.

But the most interesting part of the document is its myth-busting.  For example, for those out there who think hedge funds are taking over the world, check out this chart from the report…

See the two tiny bars on the right?  The entire hedge fund industry is smaller than the assets under management of a single firm (likely UBS we’re guessing).  This, despite what some have described as tsunami of institutional assets flowing into hedge funds over recent years.   According to data cited in the report (below), the tsunami wouldn’t even show up on the chart above.

As relatively active investors, hedge funds may indeed have a disproportionate influence in smaller, less liquid corners of the capital markets.  But this report clearly dispels the notion that they dominate capital markets in general.

Other myths addressed in the report include:

“Myth: Hedge funds gamble”

“…We do not think that there is an award for the most hilarious remark about hedge funds. If there were such an award, a strong contender for first prize would be the institutional investor who was quoted saying: “No, we don’t [currently invest in hedge funds]! It is completely obvious that hedge funds don’t work. We are not a casino.” The irony, of course, is that it is the long-only investor who depends most on luck and not the diversified hedge fund investor…”

“Myth: Hedge funds always hedge”

“…Returns are a function of taking risk. Hedge funds do not hedge all risk. If all risks were
hedged, there would be no return. The difference between hedge funds and long-only
managers is that hedge funds hedge certain risk while consciously being exposed to risk where
they expect a reward from bearing the risk…”

“Myth: Hedge funds are risky”

“Hedge funds, examined in isolation, are risky…To most investors, it is regarded as unwise not to diversify idiosyncratic risk. It should be similarly unwise not to diversify risk to a single hedge fund. Note that many critics of hedge funds do not distinguish between systematic and nonsystematic risk when demonising hedge funds…”

“Myth: Hedge funds are speculative”

“The misunderstanding of hedge funds being speculative comes from the myopic conclusion that an investor using speculative instruments must automatically be running speculative portfolios.”

“Myth: Hedge funds charge high fees”

“The attractive incentives in the hedge fund industry are regarded as one of the main drivers of high returns of hedge funds since it attracts managers who have – or are supposed to have – superior investment skill…

“…a higher proportion of the hedge fund manager’s capital is invested in positions about which the manager holds conviction (so) the management fee paid by the investor is based on a portfolio that consists of positions that are 100% managed actively.”

“Myth: Hedge fund generate strong returns in all market conditions”

“…hedge fund strategies are sometimes correlated with equities in a down market and sometimes not. If hedge funds are correlated with the stock market on the way up, that is actually fine with most people…”

“Myth: the lesson of LTCM is not to invest in hedge funds”

A picture says a thousand words…

And the list of myths goes on…

“Myth: hedge funds increase systemic risk of financial markets”

“Myth: selling short is the opposite of going long”

“Myth: there is no absolute return revolution”

The section on hedge fund myths ends with the following observation:

“There is still a lot of mythology with respect to hedge funds. Much of it is built on anecdotal evidence, oversimplification, myopia or simply a misrepresentation of facts. Although hedge funds are often branded as a separate asset class, a point can be made that hedge fund managers are simply asset managers utilising other strategies than those used by relative return long-only managers. The major difference between the two is the definition of their return objective; hedge funds aim for absolute returns by balancing investment opportunities and risk of financial loss. Long-only managers, by contrast, define their return objective in relative terms. They aim to win what Charles Ellis calls the loser’s game – that is, to beat the market.”

Despite the media sensationalism surrounding hedge funds, this is probably a good example of the “common sense” to which Mark Anson refers in his foreword.  So we highly recommend that you download the document (here), load up your printer with 200 sheets of fresh paper, hit print and grab a coffee.  At the very least, you’ll have something to read on the commute home this week.  Just don’t read it while you’re driving.

Title: Alternative Beta Strategies and Hedge Fund Replication
Author: Lars Jaeger
Published: October 2008

From Publisher: Serving as a handbook for replicating the returns of hedge funds at considerably lower cost, Alternative Beta Strategies and Hedge Fund Replication provides a unique focus on replication, explaining along the way the return sources of hedge funds, and their systematic risks, that make replication possible. It explains the background to the new discussion on hedge fund replication and how to derive the returns of many hedge fund strategies at much lower cost, it differentiates the various underlying approaches and explains how hedge fund replication can improve your own investment process into hedge funds.

Lars Jaeger

Partner and Head of the alternative beta strategies, Partners Group, Switzerland.  Author of several leading hedge funds publications.

Bio (Partners Group)
Research (SSRN)
Relevant Postings (AllAboutAlpha.com) 

Angelo Calvello has been around the alpha-centric investing world longer than almost anyone.  In fact according to our research, he actually coined the term “alpha-centric” investing.  In a guest posting today, he applies this thinking to hedge fund fees.  And what he concludes will surely surprise many.  

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

I recently attended a conference on 130/30 strategies.  The discussion eventually and inevitably drifted to the well worn but poorly understood topic of hedge fund fees and more specifically the inevitable compression of those charges. 

It is a debate founded on the belief that hedge fund fees are simply too high, although it is not clear what yardstick is being used to support this conclusions. Hedge fund fees could be compared to those charged by traditional long-only managers, but this would assume that fees charged for ‘active’ long only management fairly represent the value added by these strategies.  This, of course, is questionable. 

More…

Here is a sample of the news stories we didn’t get a chance to explore in detail this week.  As usual, all of them can be found on the Alpha-ticker above or in the news items section of AllAboutAlpha.com (free registration may be required for a few of these).

Morgan Stanley says Alpha/Beta Separation “the way of the future”. The AllAboutAlpha site partner lays out its alpha-centric philosophy telling IPE that the pension industry is about to experience a “second wave” of LDI strategies based on the separation of alpha and beta.

Dutch Insurer Aegon splits portfolio into alpha and beta segments are farms each one out to a different manager. According to the firm’s press release, “By managing the parts separately from one another, better risk-return ratios are possible. This way, more sources of value added will be available and a greater focus can be created in the portfolio. Separating the US share portfolio has created an increase of a yearly average of the total return of 2.5% without any risk increase.”

More…

Earlier today, a conference wrapped up in London featuring some of the big names in the hedge fund replication industry (Bill Fung & David Hsieh – see related news item from today, Lars Jaeger – see related posting, and William Shadwick – see related posting, and others).  In case you couldn’t make it to this powwow, you’re in luck.  We trained an uncommonly intelligent house fly (he prefers the name “Musca Domestica”) to take notes over the past two days and send them to us by a miniature fly-sized Blackberry.  What follows are the Blackberry ruminations of our ‘fly on the wall’ at the world’s leading alternative beta gabfest.

9:00 AM Monday, March 10: “Got in yesterday despite the bad weather back home and a 300 mph jet stream (which also cramped up my wings a little – had to get a wing massage – but don’t worry, I won’t expense that).  Nice Sunday afternoon in London though.  Saw a Goose and a Black Swan cavorting yesterday in the park across from Buckingham Palace.  Bad omen?  Daffodils are blooming here, but storm coming in to London today.  Miserable this morning.  Hopefully send something more interesting about replication shortly.”

10:23 AM: “Peter Norman from AP7 discussed their separation of alpha and beta (see related posting). They get beta for free given its low-cost. Then they pursue alpha through risk budgeting to managers and not through capital allocations.  Long positions are funded by short positions.  AP7 covers any temporary losses and allows managers to use their credit.  Risk allocation is done using a tracking error methodology carried over from their old long-only active management approach.  Going forward, contemplating moving to a VaR approach.”

More…

Regular readers may remember the name William Shadwick (see related posting).  Widely known as the developer of the Omega Function and Omega Metrics®, Shadwick won the 2007 Journalism Award of the Investment Management Consultants Association ,jointly with Ana Cascon, for a paper in which they lifted the veil on some of their powerful new statistics for finance.  A prominent mathematician, he was responsible for establishing the Fields Institute for Research in Mathematical Sciences before entering the finance industry in 1998.  He is the founder of Omega Analysis, a quantitative research firm in London.

Shadwick, who believes in using sophisticated tools and avoiding unnecessary complexity, issues a general warning about the hidden assumptions in quantitative models below. He has also been watching the ongoing debate between Harry Kat and Lars Jaeger and tells AllAboutAlpha, I’m afraid it doesn’t offer much comfort to either the Jaeger or the Kat schoolI think that over-modeling has had some severely negative consequences and it’s about time people started to pay more attention to the gap between theory and reality.

That’s all very well in practice, but it will never work in theory!
(Financial models should come with health warnings)

Special to AllAboutAlpha.com by: Dr. William Shadwick, Omega Analysis

The title of this piece comes from a joke about a highly qualified financial engineer’s reaction to a well-proven trading strategy. It illustrates the tension between theory and practice that we have all seen as quantitative methods become ever more common at trading desks and in investment management.

In general, the rise of quantitative tools in finance has been highly beneficial but the widespread use of models has been a decidedly mixed blessing. In science, the constant development of theories expressed as mathematical models to be tested, rejected, confirmed or refined through observation and experiment is the main source of progress in our understanding of the physical world.  This process is also crucial for engineering and technology where it is the key to predicting future events and controlling them to our advantage.

It was inevitable that this paradigm would eventually be adopted in economics and finance too.  In the half century since Markowitz put portfolio construction on a quantitative footing there has been a steady growth in the use of increasingly sophisticated and complex models and statistical techniques in investment management.

The nature of the financial markets is such that this growth in models has not been accompanied by the sort of testing that the field science demands.  Finance academics simply cannot perform experiments like those upon which the sciences rely, and they are also severely constrained in the type of observations they can make.  Data and information about what goes on in reality (as opposed to theory) is, and is likely to remain, in very short supply in comparison to the sciences.
The end users of the models in finance are not intent on understanding how markets may be explained.  That is the goal of academic research.  Instead, they want to employ theory and models to produce profits.  Like physical engineering, which has had its share of collapsing bridges, financial engineering has therefore led to many accidents.

For example, the current mess in the credit markets would not have been possible without the extensive and inappropriate rise of sophisticated models.  The results of mis-priced risk have now been cascading through the financial system for several months and show no sign of abating.

Assumptions = Hidden Models

A mathematical model can be thought of as a process that states:

If assumption A is satisfied, then input of B is guaranteed to be followed by output of C.

A robust model is one in which:

If A is close enough to being satisfied and the input is close enough to B then a result close to C is guaranteed.

The most basic requirement for the use of mathematical models – in any context – is that they are appropriate for the job.  The model tells you nothing about what happens if assumption A is not even close to being satisfied.  In this case, no matter how diligently one applies the model with the expectation of getting from B to C, the process cannot be trusted.  If the model is not robust, the difference in output may even be very dangerous.

Hidden Model: Return distributions are independent and identically distributed

The increased use of quantitative methods means that models are now almost ubiquitous and are often present but hidden.  For example, almost every hedge fund investor or manager has used the square root of 12 rule to produce an annualized volatility figure from a sample of monthly returns.  But how many people remember to check the assumption upon which the rule is based? The returns must be independent draws from the same distribution (i.i.d., or independent and identically distributed) for this rule to be justified.

This is an example of a hidden model.  It is not the returns of a hedge fund that we are talking about but the model of returns of a hedge fund.  Does anybody really believe that hedge fund returns have no auto correlation?   Does anybody really believe that there is an unchanging distribution from which the returns are drawn?

Returns on hedge fund investments or stock market prices are not random variables.  However the extent of apparent randomness in their behavior means that statistical tools are most appropriate for describing them and for making predictions of the future.  In the case of the square root of 12 rule, the prediction is the annual volatility expected over many years.  While nobody would feel that a sample of 3 annual returns would merit the calculation of an annual volatility, we’re happy to use a sample of 36 monthly returns and the model of returns as i.i.d. random variables to make the prediction.

The danger in such an assumption is that it can easily underestimate the true annual volatility of returns. This may produce serious strains on an investment program because the path by which the NAV goes from its initial value to its value 5 or 10 years later often matters a great deal.  It matters to a manager who may spend significant time without receiving a performance fee after a large loss or a series of smaller ones.  It matters to the investor who requires some of the proceeds of his investment for income during the period.  This is, of course, the reason for wanting an estimate of annual volatility in the first place.  (It is difficult to find an example of an investor who only needs to know that his investment NAV will rise in the long term while being unable to count on using the proceeds at any intervening time before the long term -   when, as Keynes said, we’re all dead.)

Hidden Model: Return are normally distributed

There are more dangerous assumptions than returns being independent and identically distributed.  One might also assume that they were normally distributed.   Probably everyone has heard the black swans argument about the importance of extreme events in markets and Mandelbrot and Taleb’s attacks on the reliance on normal distributions in finance theory.

I think they have greatly overestimated the number of academics who haven’t yet noticed that market returns aren’t normal. However there is no doubt that the persistence of press and industry descriptions of large market losses in terms of standard deviations (and ascribing an extremely low probability to such an event in consequence) indicates a widespread hidden assumption of normality.

This is dangerous for the obvious reason that it call lead to a feeling of safety where none exists. If you know that there is a 1 in 10 chance of a catastrophic loss instead of believing the chance to be 1 in 1000, the expected return you require for taking such a risk will be very different. There is no doubt that many of the estimates of loss responsible for the sub-prime debacle required exactly this sort of mis-pricing.

Hidden Model: Standard deviation is a proxy for risk

In great part, these dangers are a consequence of another hidden model, namely the use of standard deviation of returns as a proxy for risk. The realization that this model of risk is especially dangerous when applied to hedge funds has led both academics and finance practitioners to make use of skewness and kurtosis in an attempt at more sophisticated modeling of risk.

Skewness is intended to model asymmetry – the mismatch of upside and downside risk. Kurtosis is intended to model the likelihood of extreme events or fat tails.  Of course, certain assumptions must be satisfied for these models to perform as intended.   Dangers introduced by relying on these metrics are compounded by the great sensitivity of skewness and kurtosis to (even moderate) outliers.  These are not statistics meant for small samples.

Hidden assumptions in hedge fund replication

The extent to which distributional replicators will succeed in reproducing hedge fund returns will depend on the extent to which the noisiness of skewness and kurtosis can be managed.  An even more critical assumption (underpinning distributional replication) is that distributions with the same mean, variance, skewness and kurtosis must be very similar.  This is not true in general.  So replicators must depend on this assumption being satisfied – at least approximately – for the distributions that matter to them.

The use of standard deviation to describe risk is also an essential part of the risk-factor approach to hedge fund replication.  In fact, the term risk-factor itself equates risk with standard deviation of returns.  In this case, the (linear regression) model could be said to be hidden in plain sight, but it is no more easily remembered for that.

Does everyone who uses the term alpha really mean it to be interchangeable with an artifact of a particular model of returns?   For that matter, does everyone accept the hidden model in the statistician’s use of the word explain when he says that certain risk-factors explain some percentage of hedge fund returns?

It sounds rather different if he instead says that he has a model which (while nothing can be known about its actual similarity to a particular investment strategy or indeed how likely its assumptions are to be satisfied), manages to approximately reproduce the strategy’s mean, standard deviation, and correlation with a number of financial indices.

Bottom Line: Hidden assumptions should give rise to health warnings on quantitative models

Models are everywhere in quantitative finance but it is almost impossible to find any attendant statements regarding the assumptions upon which they are based.  Their purveyors should issue health warnings that tell the user that hidden assumptions are present and that failing to check that the assumptions are valid may be dangerous to investment health.
It is essential that we recognize the difference between finance and science.  In science, increasingly sophisticated mathematical techniques always produce better results over time.  But this need not be the case in finance.  Nevertheless finance can and should aspire to the status of an engineering discipline.

While you are unlikely to find health warnings on financial models any time soon, there are a few simple principles which can reduce the danger they present:

• It is far more important to look to simplicity (and common sense) than it is to look to increasing complexity as a means to better control investment outcome.
• A model whose robustness is unknown or unknowable should never be employed.
• Sophisticated tools should only be used if it is possible to verify that all required assumptions are satisfied (at least to a good approximation).  When this condition can be met, a simple application of a sophisticated technique is preferable to a complicated one.

Keeping these in mind will reduce the risk that financial models may pose to your investment health!

- William F. Shadwick, February 2008

Note: Shadwick is speaking tomorrow at Terrapinn’s Hedge Fund Replication and Alternative Beta Conference in London.

One of our primary objectives at AllAboutAlpha.com is to encourage debate and discussion on emerging topics in investment management.  That is why we cover new academic studies, surveys, counter-intuitive viewpoints and controversial opinions.  Today, we bring you the latest in an ongoing debate between two well-known and highly regarded figures in the hedge fund industry, Professor Harry Kat of the Cass Business School and Dr. Lars Jaeger of fund manager Partners Group (previous postings: Jaeger…Kat…Jaeger…).  Although Kat and Jaeger differ on many issues, they share a common interest in furthering the field of finance through frank, collegial and mutually-respectful debate.  And judging from our traffic, so do you the reader.

Today, Kat responds to Jaeger’s rebuttal…

Special to AllAboutAlpha.com by: Professor Harry M. Kat, Cass Business School, London

Before I respond to Lars Jaeger’s comments in more detail, it is probably good to backtrack a bit.  In my note of February 20, 2008, I made the following 3 points:

First, if you want to replicate a diversified hedge fund index, you don’t need alternative betas since such an index is almost fully driven by traditional risk factors.

Second, the (traditional) factor exposures of diversified hedge fund indices do not seem to change quickly enough over time to completely invalidate the factor model approach.  The performance (backtested or live) of the various factor model based replication products supports this.  I showed the evolution of the Goldman Sachs ART index because the Bloomberg data go back until 1996, but I could well have picked another comparable product.

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Lars Jaeger’s recent commentary on “alternative beta” (see posting) raised the ire of Professor Harry Kat (see posting).  Today, Dr. Jaeger responds to Kat’s protests by highlighting the “inconsistencies” in his arguments.

Special to AllAboutAlpha.com by: Lars Jaeger, Ph.D., CFA, FRM, Partner, Partners Group

In his reply to my recent contribution at AllAboutAlpha.com, Harry Kat says that he agrees with “several points” in my argument (I only made a few key points anyway).  Specifically, Kat seemed to agree that factor models capture mostly the “traditional beta” in hedge funds.  Further, he seemed to agree with my argument that “hedge fund replication isn’t really about replicating hedge funds. It is about replicating hedge fund indices.”  And he goes on to re-state many of my original points.

We seem to be in agreement on some very fundamental points. That is good news to me, as Harry has not always agreed with much what I have said in the past.  However, he then suggests that there is a need to “fill in the picture” as my comments were only “part of the hedge fund replication story.”

I surely never claimed to know the entire hedge fund replication “story”.  But what he actually provides us with – in order to “fill in the picture” – is merely a performance comparison between the ART Index (Goldman Sachs’ replication product) and the PG ABS Index (the Partners Group Alternative Beta Strategies). 

In doing so, Harry is inconsistent in at least three ways.  Firstly, he is inconsistent in the way he applies fees in his analysis.  While he compares the PG ABS net of fees, he chooses to report the performance of the ART index gross of fees, a rather important difference as hedge fund investors surely understand.

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Not one to shy away from a debate, Professor Harry Kat responds to last week’s column by Dr. Lars Jaeger on traditional and alternative betas in hedge fund replication.  While Kat agrees with several of Jaeger’s arguments, he wonders if the mechanical-trading approach to delivering alternative beta isn’t just too complex.

Some Comments on Lars Jaeger’s Hedge Fund Replication and Alternative Beta: Two different ways of looking at replicating hedge funds

Special to AllAboutAlpha.com by: Professor Harry Kat, Cass Business School, London

In a note last week on AllAboutAlpha.com, Lars Jaeger discussed the two most common approaches to hedge fund replication: factor models and mechanical trading rules designed to capture alternative betas.  Although I agree with several of the points that he makes, his comments are only part of the hedge fund replication story.  In this brief note, I will attempt to fill in the picture.  Most of my comments can also be found in some of my earlier writings on the subject.  But it doesn’t hurt to repeat them, however, as we need to be clear on the issue.

What is very important when trying to make sense of hedge fund replication products, is to keep an eye on what they actually aim to replicate.  Almost without exception they aim to replicate, either explicitly or implicitly, a diversified hedge fund index.  So hedge fund replication isn’t really about replicating hedge funds.  It is about replicating hedge fund indices.

Does that matter?  Isn’t a hedge fund index just a portfolio of hedge funds?  Yes, it is.  But therein lays the problem. When combining hedge funds into a portfolio, many typical hedge fund features diversify away.  As a result, diversified hedge fund indices have only a few hedge fund-like properties left and are mainly driven by equity and credit risk.  This is easily confirmed by calculating their correlation with the S&P 500 for example.  The important conclusion from this is that we do not need alternative betas to replicate a diversified hedge fund index.  As Jaeger also suggests, it is primarily driven by traditional betas. With precious little alternative beta actually present in a diversified hedge fund index, the main problem when replicating it is traditional beta.

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We are pleased to bring you a guest posting today from Dr. Lars Jaeger of Partners Group.  Regular readers and students of hedge fund replication will recall that Dr. Jaeger edited one of the first books covering the topic back in 2003.   Since then, he has written a number of papers on hedge fund replication (see related posting) and has spoken at many conferences.  He’s also one of the speakers on the programme for Terrapinn’s second Alternative Beta & Hedge Fund Replication conference in London (March 10-12).

Hedge Fund Replication and Alternative Beta: Two different ways of looking at replicating hedge funds

Special to AllAboutAlpha.com by: Lars Jaeger, Ph.D., CFA, FRM, Partner, Partners Group

The discussion on alpha versus beta in the breakdown of investment returns is as old as the capital asset pricing model which defined these terms some 40 years ago.  Today, it has finally reached the hedge fund industry – an area of investing traditionally associated with pure alpha or absolute return.

Investors and researchers alike realize that hedge fund returns are largely composed of betas. However, hedge fund beta is different from traditional beta.  While both are the result of exposures to systematic risks in the global capital markets, beta in hedge fund investing can be significantly more complex than traditional beta (and can be often be “hidden in the alpha smokescreen”).

We therefore refer to this beta as “alternative beta”, a term that now part of the hedge fund lexicon.  In fact, the increased academic and non-academic effort to model and understand hedge fund return sources has also reached Wall Street.  The new buzzword: “hedge fund replication”.

Most providers of “hedge fund replication” use a trading model application of a linear factor decomposition of hedge fund returns (as represented by particular return time series).  However, these models yield satisfactory results for only a few hedge fund strategies, namely directional ones such as Long/Short Equity or Event Driven (see Table 1 for the R-squared values for various strategy sectors).

When linear factor models work, traditional beta (i.e., equity market factors) are all that is required.  In other words, hedge fund replication of this kind works when investors need it least to work – in the directional equity space.

On the other hand, linear factor models are not satisfactorily successful when applied to most other hedge fund strategy sectors, specifically non-directional and Relative Value hedge funds or indices.  In order to cope with these strategies we have to employ more complex market factors and/or dynamically adjust factors to include non-linear profiles.  These factors are likely to represent dynamic trading strategies that capture alternative risk premia with their contingent and non-linear payout profiles.

In addition, linear models are backward looking only.  In contrast to hedge fund managers who base their decisions on current data, these models adjust exposures with a significant time lag.  This can be problematic in a fast changing environment!

Many hedge fund “replicators” use these backward looking regression models as the basis to estimate current and future hedge fund exposures.  They essentially ask “Why not give up on alternative beta and model hedge funds with traditional beta only?”

Actually, this approach would have proven reasonably successful in the last four years (which is exactly the period most providers choose to display when they show their back-tested performance to attract investors).   However, even in this benign environment for equity directional strategies, alternative betas can add value to investors’ portfolios.  Figure 1 shows a simple risk weighted average of the following generic alternative beta factors:

• Deutsche Bank Carry Index,
• CDX High Yield Index,
• CRB Commodity Index,
• value versus growth spread,
• small cap versus large cap spread,
• BXM covered call writing (BXM Index – 0.5*SPX Index),
• the Merger Arbitrage Fund (MERFX  Index), and,
• the spread between emerging market equity returns and developed equity markets (MSCI Emerging Markets – MSCI World).

The second chart represents the Merrill Lynch factor model which we believe is a very good proxy for the equity component in hedge fund returns.

Source: Bloomberg, PG calculation*

We see that alternative beta can yield similarly attractive results as equity beta in hedge funds during periods of equity bull markets. The result looks very different, however, when we include the bear market from March 2000 to March 2003, a period when hedge funds, in aggregate, made money despite heavy losses in the equity markets.  This is shown in the figure below, which is based on the same data - just extended further into the past.  Here we see the real attractiveness of alternative betas.

Source: Bloomberg, PG calculation

However, the large majority of alternative beta can only be extracted by conditional trading rules directly aimed at benefiting from particular risk premia in the global capital markets.  Instead of naively replicating past properties of doubtful (i.e., biased) time series with inappropriate (i.e., linear) models, it seems more appropriate to tackle the hedge fund risk premia/alternative betas one by one.  We believe that the hedge fund investor is well advised to stay with the alternative beta returns rather than chase the pseudo hedge fund returns of traditional beta.  Hedge funds may be simpler than what many investors have believed so far, but they are not that simple.

How recent market developments have impacted the field of “hedge fund replication”

In Roman mythology, Janus is the god of gates and doors as well as of beginnings and endings.  He is usually depicted with two faces looking in opposite directions.  The year 2007 will be remembered by investors as a Janus year.  The first half was sparked with euphoria and buoyant equity markets, only shortly interrupted by the turbulences in late February/early March.

Retrospectively, many consider this period now as the end of the four year period of low volatility and low investor risk aversion that began in 2003.  In contrast, the second half of 2007 proved one of the most difficult periods for investors in the last decade - comparable perhaps only to the summer of 1998.  The second half of 2007 have represented the beginning of a new phase in the global markets characterized by higher volatility, more uncertainty and hence higher risk premiums across asset classes.

A closer look reveals that the crisis triggered by the US sub-prime market, which sent shock waves around the world is mostly a non-equity crisis.  While the credit and the inter-bank lending market was sent into paralysis, the FX markets turned the carry trade sour, small cap and value underperformed large cap and growth, volatility soared, and merger deal spreads widened dramatically.  But the global equity markets themselves experienced limited losses (albeit showing much higher volatility).  The MSCI World index closed 2007 only about 5% below its all time high.

This caused hedge fund replication programs that focus on alternative (hedge fund) beta to underperform those based on traditional equity beta.  The first 20 days of trading in 2008 shows that this is about to change.

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

Apparently, the universe is big.  Really big.  We learned this week that it holds about 10^80 atoms (see previous posting).  But how big is the alpha universe?  How much alpha can possibly be generated by hedge funds (or any active manager)?  Neither universe is easy to get your head around and neither can be measured directly.

We tackled this question about a year ago in relation to a seminal white paper written by Lars Jaeger and Christian Wagner (see related posting).  But we thought it would be interesting to revisit this given the myriad of new estimates that have recently come out on the size of the hedge fund industry.

To get to the bottom of this, we went right to the expert on the topic, Hilary Till of Chicago-based Premia Capital Management.  Till wrote a paper back in 2004 for both the Journal of Alternative Investments and the AIMA Journal on the theoretical capacity of the hedge fund industry.  The AIMA Journal version of the piece was called “The Capacity Implications of the Search for Alpha” and Jaeger and Wagner actually cite it when establishing a conceptual framework on hedge-fund capacity.

In a summary of 2004 article (available here) Till says:

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