There is a great deal of confusion about how to measure the success of hedge fund replication – in a sense, to answer the question, “Has hedge fund replication worked?”  In this note, we provide a candid assessment of the successes and failures of the space and introduce a framework of five criteria – a “scorecard” – as a guide for potential investors.

On the one hand, replication products overall have fulfilled the original promise of delivering “hedge fund returns” but with much lower all-in fees and daily liquidity.  Specifically, over the past five plus years an array of replication products has delivered returns comparable to funds of hedge funds and, more importantly, outperformed managed account platforms, UCITS funds and investable hedge fund indices.

On the other hand, potential investors often are put off by the complexity and opacity of many such products – especially those offered by investment banks.  We attribute this frustration to unrealistic expectations, set by the banks themselves, that the strategy should be as simple and predictable as “investing in the S&P 500 index” – that is, a default allocation that requires minimal due diligence with de minimus tracking error and no idiosyncratic (manager) risk.  As discussed in detail below, this was misguided and has hindered more widespread adoption.

In the chart below, we offer a scorecard on standard hedge fund replication products along five criteria: performance, liquidity, transparency, fee reduction and “index-like” alternative:

Chart 1

 “Replication” Defined

Note:  For compliance reasons, we do not include the performance of Beachhead products since this would limit the distribution of this paper to a small subset of investors for whom it might be valuable.  Furthermore, at Beachhead we have migrated away from the “standard” approach described herein in an effort to capture both hedge fund alpha and beta through fee disintermediation and other more sophisticated strategies.

Replication is a broad term.  For our purposes, hedge fund replication is defined as a factor-based approach to delivering the returns of a pool of hedge funds.   The pool might be an index or an actual portfolio.[1]  It’s based on the (now proven) concept that hedge funds derive the majority of returns from market forces, that exposures to different markets change over time, but that these shifts are slow enough that a “backward looking” model can keep up.  Therefore, a dynamically–adjusted portfolio of market betas (equities, bonds, currencies, etc.) can do a very good job of delivering returns that look a lot like those of the pool of actual funds.

Chart 2

When discussing the replication “universe” below, we focus only on funds and indices with live performance; pro forma index returns are subject to backfill bias.  As noted, it is often challenging to try to make “fee equivalent” comparisons across strategies.  Consequently, we specify when likely fee adjustments would impact the conclusions.

Importantly, we differentiate hedge fund replication from rules-based trading strategies, which seek to capture “alternative betas” like momentum, currency carry, merger arbitrage, etc.   These strategies can be an effective way to get exposure to a particular strategy at a lower cost and with greater transparency.  However, alternative betas represent a small portion of overall hedge fund returns.  Therefore, while the rules-based approach can provide additional liquidity or reduce fees at the margin, factor-based replication is necessary to approximate the returns of a diversified portfolio or index.

Evaluating the Five Criteria of Hedge Fund Replication

Performance:  Good Relative, Low Absolute, Returns

The principle criticism of replication products is that returns over the past five years have been “mediocre.” As shown below, the primary cause was the decline in hedge fund returns, not the failure of replication per se.

Remember that most replication products were designed to match the performance of funds of hedge funds, net of fees, at a time when trailing hedge fund returns had been exceptionally high on a risk-adjusted basis.  As of mid 2008 funds of funds had returned 8% per annum over the preceding five years – equal to equities and much higher than bonds.  It was taken as a given that performance would remain strong.  Therefore, the products were designed to offer comparable net returns but with superior liquidity and transparency – which were scarce at the time.  In the subsequent five years, however, hedge funds significantly underperformed expectations, especially relative to stocks and bonds.  As shown below, this explains virtually all of the “mediocrity.”

Chart 3

Interestingly, replication products had much lower drawdowns during the financial crisis than hedge funds and funds of funds.  As with funds of funds, the replication strategies modestly underperformed most direct portfolios since the crisis, as represented below by the HFRI Fund Weighted Composite.

Chart 4

Given the superior liquidity of replication, a fairer comparison is to judge the performance of replication strategies against liquid “alternatives” to hedge funds.[2]  Replication had a similar drawdown during the crisis, but has outperformed recently.

Chart 5

The results above should provide comfort to investors that, as hedge fund returns improve over time, so too should replication results.

Liquidity:  Daily, No Gating Risk

All replication products provide daily liquidity and have no gating or suspension risk.  In a market dislocation, investors should be able to efficiently cut exposure to replication products – a valuable benefit that is not captured in historical returns.

Arguably, though, the “value” of liquidity has declined since the crisis.  Many hedge funds now provide investors with shorter redemption cycles and there has been a marked expansion of more liquid alternatives, like UCITS funds and managed account platforms.  However, overall there is little doubt that replication products can provide far more reliable liquidity than direct hedge funds and most other liquid hedge fund alternatives.

Transparency:  Available, But Often Difficult to Interpret

Position level transparency enables investors to monitor current holdings and provides a window into exposures as a risk management tool.  Unfortunately, while many replication products technically offer transparency, the information value is limited.

For example, the top holdings on Bloomberg for the Goldman Sachs Absolute Return Tracker are Treasurys and repurchase agreements; market exposure instead is held through derivatives that are “off balance sheet.”  As an investor, this raises a series of questions, such as who are the counterparties, what are the actual underlying costs vs. investing in straightforward market instruments, and whether there are conflict of interest (self-dealing) issues.  In a similar vein, while the IndexIQ ETF invests mostly in other ETFs, its holdings include a variety of overlapping funds, presumably to meet mutual fund diversification and position limit requirements. Many of those fixed income ETFs in turn invest through derivatives and have the same issues related to underlying counterparty risks, all-in costs and potential drag on performance.

These portfolios are typical in the space:  they place an unnecessarily high due diligence burden on investors, complicate portfolio level analyses and make it more difficult to monitor results over time.

Fees:  Lower (Headline) Fees, But Not Better Performance

The fees for replication mutual funds are in the range of 100 bps to 200 bps – a significant reduction relative to hedge funds – and vary considerably between the retail and institutional markets.  In general, replication fees are 50% or less than hedge fund fees, and lower relative to indirect investors (through funds of funds, platforms, etc.).  Lower fees, however, have not translated into a commensurate increase in performance.  Here’s why:

As noted above, almost every established hedge fund replication product is designed to target the net of fee performance of the relevant index or portfolio of funds.  Before the crisis, hedge fund fees were roughly 30-40% of gross returns; post-crisis this figure was much higher.  Consequently, as industry returns have declined, this assumption has been called into question.

Going forward, a better approach may be to target the pre-fee, or gross, returns of the hedge fund portfolio.  Part of the problem is that investors often unnecessarily pay away a substantial portion of alpha by overpaying for beta.  Replication strategies, if properly designed and implemented, should be able to recapture a portion of these lost fees and help investors to better evaluate whether a fee structure is fair and reasonable.

“Index-like” Alternative:  Cut Some, But Added Other, Idiosyncratic Risk

The final value proposition of replication was to provide an “index-like” alternative to investing in individual hedge funds.  “Index-like” implies several attributes:  investable, liquid, relatively low cost and a significant reduction in idiosyncratic risk.  Investing should be relatively simple and efficient and hence require substantially less due diligence.  In 2007-08, the analogy most often used was that of the S&P 500 – how investors could use replication as their “default” allocation and concentrate due diligence and monitoring resources on individual managers.

As noted, this comparison was misguided for a few reasons.  At a basic level, there was not and is not a widely accepted definition of the “hedge fund industry”; consequently, different products track different populations of funds.  Some track indices with well-established data biases; others are constructed opaquely from internal databases (e.g. prime brokerage clients) and raise conflict of interest questions.  Some view index returns as, by definition, mediocre and hence unattractive in an industry where allocators constantly seek to identify outperformers.

Second, given the “approximation” approach of replication models, performance by product will vary depending on choice of factors, window length, investment vehicles, fees and a variety of other constraints.  What this should translate to in practice is that while replication models can successfully reduce hedge fund manager risk (e.g., Madoff/fraud and/or headline risk), investors still need to carefully evaluate any replication product – in a sense, the idiosyncratic risk of one replication product/provider versus another.

In reality, potential investors should consider replication to be a low cost investment strategy and not an index.[3]  As with any strategy that relies on a quantitative model, there is a great deal of human judgment that goes into building the model and interpreting the results, and this should not deter investors from seeking the other valuable benefits that the strategy can offer.

Conclusions:  What to Expect Going Forward?

The most important thing about hedge fund replication is that it adds another (and very powerful) tool to the arsenal of investors.  Hedge fund replication proves that the primary drivers of hedge fund returns can be identified and that these exposures are stable enough to foster a reliable investment strategy.  The ability to deconstruct hedge fund returns enables investors to make more informed decisions about the merits of different strategies and to better identify where true alpha resides – and, hence, isolate when it’s worthwhile to sacrifice liquidity and pay high fees for portfolio diversification.

The hedge fund industry overall has undergone a wrenching change over the past six or seven years.  The composition of the investor base is far more institutional today.  The entire fund of funds industry effectively has restructured, with perhaps 80% of pre-crisis funds now closed, and many of its traditional investors now invest directly.  More widespread and comprehensive due diligence practices have reduced the risk of individual manager fraud or blow-up risk.  Investors are much more sensitive to gating and suspension issues, and this shows up in better redemption terms and much more liquid underlying portfolios.  In addition, many more liquid investment vehicles – whether UCITS funds, managed account platforms or now alternative mutual funds – are available today.  Disappointing returns have sharpened the focus on hedge fund fees.

In this context, several leading investors now predict that replication-based products are the “next wave” for pension plans and other fee-sensitive investors. Many highly sophisticated investors already incorporate replication strategies into their investment portfolios and 2012-13 saw a marked increase in interest among leading consultants and institutional investors.

In conclusion, though, we assert that “standard” replication products offer an effective yet only partial solution.  Much of the real promise, we believe, lies in a “customized” approach where replication methodologies are adapted to the specific, stringent and changing demands of investors.  One promising approach is to target pre-fee returns and hence improve performance through a form of “fee disintermediation.”  For some portfolios, this can improve performance by 200 bps or more annually.  Another solution is to replicate the return profile of actual “high alpha” portfolios – those with a higher returns, concentration and turnover.  There is strong evidence that even 300-400 bps of persistent outperformance can be “captured” by a carefully designed and implemented replication strategy.  These and other enhancements lay the groundwork for the next generation of replication products and should help sophisticated investors to achieve their long-term goals of maximizing net of fee performance while minimizing risk.

[1] This is true as well for alternative beta strategies, which essentially are single strategy funds.  See Merger Arbitrage Replication:  Does it Work?

[2] The composite consists of investable hedge fund indices, UCITS products and managed account platforms sponsored by Lyxor, RBC, HFR, Alix Capital, and Dow Jones/Credit Suisse (discontinued in May 2013). Note that we only use live data and that there may be differences in reported numbers and actual net of fee returns realized by investors.

[3] Replication generally does not work for individual funds because the exposures of individual funds are generally less stable, and hence less predictable, than those of a portfolio.



Alternative betas, or risk premia, are established investment strategies that are simple enough to automate with a computer but too complicated for most investors to implement directly. For instance, you can program a computer to buy “value” stocks and short “growth” stocks, but few investors choose to do this on their own. The same argument can be made for merger arbitrage, currency carry trades, momentum, trend following, commodity roll trades and other common trading strategies employed by hedge funds.

The advertised appeal of alternative beta products is that they have a low correlation to traditional assets and have a high-expected return – the practical definition of a valuable diversifier. With widespread pressure to bring down the cost of investing, many investors are considering whether to invest directly in alternative betas to avoid high hedge fund fees and improve liquidity. Having examined a broad range of these products, we conclude that there are two (big) unanswered questions. Each arguably undercuts the diversification thesis.

1. What are expected returns?

There is a paradox in the alternative beta diversification thesis. Expected returns for alternative risk premia are supposed to be high since most investors do not or cannot invest in them directly. However, the proliferation of products should lead to capital inflows and hence drive down returns over time.

This is not a small issue. Take benchmark equity strategies, where we have two decades of data since they were “discovered.”  In 1993, Fama observed that buying value and shorting growth delivered substantial excess returns over 1963-1990. During that period, the Sharpe ratio was 0.57, somewhat higher than the long term Sharpe ratio of the equity markets. Similarly, Carhart showed in 1997 that momentum over the same period offered similarly compelling returns – an even higher Sharpe ratio of 0.85.

These strategies did not remain undiscovered for long. Numerous firms soon offered products and funds specifically to provide access to these strategies. The results were entirely predictable. As capital flowed in, returns declined. In the past ten years, the Sharpe ratios of value and momentum have been 0.15 and 0.02, respectively.

A related issue is that few products actually have live track records. Those that do were often launched in the past several years. Most products are marketed as indices, for which reporting standards are very low:  simply labeling a pro forma track record an “index” sidesteps most of the onerous disclosures that apply to investment products. As an investor, you often have to dig to learn when the index was formally launched; anything prior to this should be discounted for back-fill bias. Consequently, the pro forma returns, or a portfolio of them, will generally be overstated.

The obvious risk of these strategies is that inflows into a capacity constrained strategy will drive down returns to the point where they are no longer an effective source of diversification. By analogy, as discussed previously in a note, CTA returns have been low for almost a decade, and the most likely culprit is the influx of capital.

2. Do They Reduce Idiosyncratic Risk?

“Beta” strategies generally reduce idiosyncratic risk. When you invest in the S&P 500, you don’t need to worry about whether a manager bets wrong and goes off the rails. The term “beta” also implies something that can be clearly defined. In this context, the moniker “alternative beta” is something of a misnomer.

Modeling Risk:

Alternative beta products substitute “manager” risk with “model” risk. Due to the complexity of setting numerous parameters, one firm’s alternative beta will look very different from another’s. We addressed this in the merger arbitrage space and found very different results among providers. The implication for investors is that alternative beta products are more akin to low cost, systematic single strategy funds rather than a beta product per se.

Whereas some firms offer products that have been optimized, others are offered piecemeal. Barclays reportedly offers close to one thousand discrete products. For the former, investors need to evaluate the quality of a complicated optimization; in the latter, the range of products is overwhelmingly broad. In either case, the products fail to provide the clarity and simplicity that most investors associate with the term “beta.”

Implementation Risk:

Due to their complexity, alternative beta products typically are offered in swap form. There are several material issues with this. Liquidity for OTC products can be contingent upon stable markets: a standard ISDA agreement has sixteen pages covering market dislocations. The ability to execute is dependent upon getting the counterparty to repurchase the contract which, as many discovered during the crisis, may be difficult during a chaotic market. Buyers bear the credit risk of the counterparty that may or may not be priced into the product. All in pricing can be opaque at best, especially when it is dependent upon execution. Trading and transactions costs can be very high, such as for the execution of roll trades outside of specified windows.


Based on our review, there is a fundamental disconnect in how the products are positioned and the reality of investing in them. While the headline cost of investing may be low, overall pricing is much more opaque. As noted, liquidity is more constrained than advertised.

However, the biggest issue – and the most difficult to answer – is whether alternative betas are subject to arbitrage over time. No one knows where the tipping point is, and it’s nearly impossible to gauge contemporaneously. Because of this, product providers focus on historical returns, which are easy to calculate but unlikely to reflect returns going forward. As Kahneman observed in Thinking Fast and Slow, when asked a difficult question, human beings have a tendency to pose themselves an easier question and answer it instead. Well said.

By Andrew D. Beer, Chief Executive Officer of Beachhead Capital and Michael O. Weinberg, Adjunct Professor at Columbia University 

Well-documented advantages of alternative mutual funds include daily liquidity, lower all-in fees, greater regulatory oversight, lower minimum investment requirements and the absence of partnership K1s. These features make alternative mutual funds a viable investment for defined contribution plans and retail investors, an untapped multi-trillion dollar market for hedge fund managers.

The opportunity for fund of funds managers is clear. Post-crisis, funds of hedge funds faced a sharp decline in profitability due to a combination of disintermediation, declining fees and rising costs (e.g. customization). Gone are the days of managing a highly profitable co-mingled fund of hedge funds where each incremental dollar of revenue drops to the bottom line. Defined benefit pension plans – long-time investors in funds of funds – are in steady decline; by contrast, defined contribution plans are growing rapidly and current exposure to alternatives is de minimus. Alternative multi-manager mutual funds (AMMFs) could represent a new dawn for funds of funds:  co-mingled, highly scalable vehicles with strong potential investor demand.

However, mutual funds are far less flexible than hedge funds: all registered funds have structural limitations on leverage, shorting, illiquid assets, concentration and other criteria. This contradicts a core tenet of the hedge fund industry:  that talented managers perform better with fewer constraints. In fact, many early hedge fund managers were former mutual fund managers in search of a less constrained investment vehicle. By definition, structural constraints almost certainly will result in a performance differential over time:  the question is, by how much?  This paper looks at the evidence to date, some of the underlying causes, and raises some pertinent due diligence questions for potential investors.

1. Performance Drag: Evidence to Date

There is a limited amount of live data on AMMF performance. Of the thirteen funds that we currently track, only three have track records that extend back more than a year or two. Only five of thirteen have full year track records for 2012, while eight have full year track records for 2013. Any conclusions below should be taken in this context.

With that caveat, the chart below shows the full year performance of those five and eight funds, respectively. The magnitude of the performance drag is noteworthy:  the average AMMF underperformed the HFRI Fund of Hedge Funds index by 311 bps in 2012 and 420 bps in 2013, net of fees (the return figures are for institutional share classes only). The average AMMF also underperformed an index of liquid hedge funds (HFRX Global Investable Index) by approximately 200 bps in each year.

Full Year Performance Comparison 2012-13 

This is particularly surprising given that all-in fees in AMMFs are 150-250 bps lower than those in fund of fund funds; all things being equal, this should lead to higher performance. While the average AMMF charges slightly more than 200 bps per annum with no incentive fee,[1] the typical fund of hedge funds has all-in fees of 3.5% to 4.5% (75-150 bps per annum on top of underlying hedge fees of 1.6% and 20%, on average). On a fee equivalent basis, the performance differential rises to 448 bps in 2012 and 681 bps in 2013.

Estimated Fee Equivalent Performance Drag 2012-13

2. What Explains the Performance Drag?

When the HFRX GlobalInvestable Index was launched over a decade ago, performance drag initially was over 400 bps per annum, primarily due to adverse selection bias. That differential has come down over time, but still is persistently 100-200 bps per annum. Other liquid hedge fund strategies – investable hedge fund indices, managed account platforms, 130/30 funds, and UCITS products – have each underperformed hedge fund counterparts by around 200 bps per annum. This supports the general rule that liquid alternative strategies have a persistent long term performance drag relative to actual hedge funds.  (See The Performance Drag of Liquid Hedge Fund Strategies at

In the AMMF space, performance drag is likely to arise in two forms. First, following the HFRX example, hedge fund managers most eager to manage sub-accounts at reduced fees may be of a lesser quality. This may explain in part why the Hatteras Alpha Hedged Strategies Fund, the only fund with a ten year track record, underperformed the HFRIFOF since inception by 134 bps on an annualized basis since inception (including negative alpha of 1.8% given somewhat higher beta) and suffered much more pronounced drawdowns during the crisis (down 31.6% in 2008).[2]  On the surface, the current pool of subadvisors appears to be much more credible than the early participants in the investable hedge fund indices.

A more serious issue, then, is that high quality managers simply may not be able to deliver comparable returns within the constraints of the ’40 Act structure.[3]  While it is impossible to make an apples-to-apples comparison,[4] one indirect method is to compare the performance of AMMFs to a portfolio of hedge funds managed by the same subadvisors. Here we find that AMMFs have on average underperformed an equally weighted basket of the “flagship” hedge funds of the subadvisors by over 200 basis points.[5]  On a pre-fee basis, the differential rises to over 500 basis points.[6]

Why is this?  In addition to investment constraints, hedge fund managers have a strong incentive to avoid cannibalizing their core businesses; therefore, given the general absence of incentive fees, the most attractive or capacity constrained trades are likely to wind up in higher fee vehicles.[7]  Irrespective, given the importance of the hedge fund managers’ reputations in marketing AMMFs, it is reasonable for investors to require AMMF managers to break down performance by subaccount relative to the most comparable hedge fund managed by the same subadvisors.

A final and important distinction is that AMMF managers directly pay the subadvisors:  unlike in a fund of hedge funds, each dollar of subadvisory fees comes directly out of the pocket of the AMMF manager. AMMF managers therefore have a strong incentive to select subadvisors who will work for 1% or less. A fair question for any AMMF sponsor is how many subadvisors/strategies were rejected due to high fee expectations, and why this does not lead to adverse selection.


In conclusion, while it’s still very early in the game, our analysis indicates that AMMFs are likely to be subject to a persistent performance drag over time. Based on the more robust data pool from other liquid alternatives, our expectation is that the performance drag should be around 200 bps per annum, net of fees. Fortunately, since return information is readily available on ’40 Act funds, it will be much easier to make ongoing comparisons, and we look forward to updating this analysis in the coming year or two.

This does not mean that AMMFs are necessarily inferior to hedge funds of funds. The structural advantages are very real, and will be worth more than 200 bps per annum for many investors. Further, investors who previously have been precluded from investing in hedge funds may find AMMFs to be a valuable diversifier.

As of early 2014, the evidence suggests that the performance drag will be higher than many investors realize and that the (real) advantages of greater liquidity, lower minimums and reporting simplicity are likely to come at the cost of diminished returns.


[1] Most funds currently include fee waivers and/or rebates to bring down all-in fees. The average rebate among 13 funds included in the study currently is 48 bps per annum. Note that fee rebates generally have a finite life, so a relevant due diligence question is the extent to which fee rebates will continue going forward.

[2] The institutional share class of the Hatteras fund was not introduced until late 2011, whereas the retail share class was introduced in 2002. The retail share class is referenced here.

[3] This is the principal reason the SEC does not permit prospectuses to show the hedge fund track records of the subadvisors. In fact, only one of the AMMFs (Balter) requires the subadvisors to run portfolios substantially identical to their hedge funds and therefore is permitted to disclose the track records of the subadvisors’ hedge funds in the offering documents.

[4] Due to a lack of transparency of manager weights in AMMFs and strategy overlap between AMMF sub-advised accounts and predecessor hedge funds, among other issues.

[5] More precisely, of the eight funds with full year performance for 2013, we have return data for the flagship hedge funds on at least 70% of the managers of four of them. Those AMMFs underperformed an equally weighted portfolio of the available hedge funds by an average of 314 bps, net of fees. Assuming that the AMMF managers are paid 100 bps of the management fee, the fee equivalent differential is 214 bps on average.

[6] At a conference in 2013, one prominent multi-strategy hedge fund firm analyzed the expected performance differential in their flagship fund and canceled plans to create a ’40 Act fund after determining that they would suffer an 800 bps drag.

[7] Note that one possible window into this may be which managers advise assets of wholly-owned offshore subsidiaries. In general, offshore subsidiaries can pay management and even incentive fees to managers without disclosure at the fund level. This is a relevant due diligence question for any funds with offshore subsidiaries.

By one estimate, the hedge fund industry managed $2.6 trillion in capital at year-end 2013.  Many expect growth to accelerate over the coming five years as institutional investors like US pension funds seek alternatives to investing in low yielding fixed income assets.  Deutsche Bank, for example, predicts that industry assets will grow by another $400 billion this year alone.

This growth comes in the face of widespread discontent about the cost of investing in hedge funds.  In the pre-crisis period, when hedge funds routinely outperformed traditional assets, the cost of investing was largely overlooked.  In recent years, though, as the average hedge fund delivered single digit returns, high fees increasingly have come under scrutiny.  To put the issue in context, investors paid approximately $95 billion in fees in 2013, or 44% of what their investors took home.  By our estimate, this figure is twice what it should be:  in other words, investors overpaid by a staggering $47 billion.  The same conclusion can be drawn for each year since the financial crisis.

Why is this?  In the post-crisis period, institutional investors and their consultants partially brought down the cost of investing by “dis-intermediating” funds of hedge funds – in essence, cutting out the middleman.  However, this represented only a small percentage of overall fees. Driven in part by risk aversion (you don’t get fired for hiring IBM), those same investors instead steered capital directly to the largest hedge funds – the $10 billion plus firms you read about in the press.  By some estimates, 100% of net capital inflows post-crisis went to the top 100 managers.  The big have gotten bigger and the small have struggled.

Why is this problematic?  Hedge funds charge two types of fees:  a management fee and a performance fee (typically 20% of profits).  When hedge funds were small, relatively high management fees (1.6% on average) were necessary to cover costs and to enable a manager to expand the research team, hire a head of operations, etc.  Performance fees were geared to better align the interests of investors and the manager, something that was sorely lacking in the mutual fund business.

As the industry matured, the fee structure didn’t.  A typical manager with $5 billion in assets under management earns $80 million in fees – most of it pure profit.  Incremental management fees don’t add to research coverage or a more robust investment process; they simply increase the manager’s take home pay.  Further, as funds grow, managers take less risk to preserve the value of the business.  Performance fees then no longer provide incentives for stellar returns, but rather become an annual tax on investors.  The absence of a hurdle rate on incentive fees meant that the 32% rise in the S&P 500 index last year resulted in 200bps of overpayment across the industry. When you overpay for beta, it is a dollar for dollar reduction in alpha: it’s why fee reduction is the purest form of alpha.[1]  Skill should be rewarded handsomely, not luck.

In the rest of the asset management industry, large investors get fee concessions; it’s why retail investors have the odds stacked against them.  However, when institutional investors fall over themselves to invest in a name brand fund, the manager has little incentive to cut fees.  Counterintuitively, institutionalization has failed to result in real cost savings for most large investors.  And as we know, the cost of investing is one of the most important factors in long-term investment performance.

There are four potential solutions.  As noted recently by the head of hedge fund allocations for a large pension fund manager, sophisticated investors will migrate to a combination of hedge funds and comparable, but far less expensive, strategies like dynamic and alternative betas, in which investors break down the drivers of hedge fund returns and invest in them directly.[2]  What you don’t get in manager talent, you save in lower fees.

The second option is for investors to band together to demand a material reduction in fees.  A group of investors that constitute half the assets of a $5 billion fund has a much better chance to bring down fees than if each $50 million investor negotiates separately.  The two areas of focus should be to bring down management fees (as a percentage of assets under management) as assets increase and to insist that managers only earn performance fees above a specified benchmark.

A third possibility is to steer capital to smaller hedge funds.  Interestingly, the have and have-not bifurcation of the industry may be a catalyst for reform.  Many smaller hedge funds, facing years of difficulty in raising capital, are much more willing to drop fees today.  An institutional investor who can invest $50 million with a $200 million manager can pretty much set its own terms.  Importantly, since smaller managers generally outperform larger ones over time[3], investors could see a dual benefit of a pick up in performance and lower fees.

A fourth area garnering attention recently is the alternative mutual fund space, where hedge fund strategies are managed in registered investment funds.  These products are in their infancy with short track records and an unproven business model.  While some products are offered at roughly half the cost of investing in hedge funds, the fee structure still is double or more that of traditional mutual funds.  The elephant in the room is whether the performance of these products will match those of the hedge funds they emulate.  Most are marketed off track records of hedge funds, not mutual funds, and the mutual fund structure, by design, has many more constraints.  It’s a bit like asking a champion boxer to fight with his shoelaces tied.  The irony is that the appeal of hedge funds twenty years ago was to take talented investors and free them of the (many) constraints of managing assets in a mutual fund structure; we now appear to have come full circle.[4]

Pension funds, other institutional investors and their advisors need to take a hard look at this issue. As one pension fund trustee reportedly observed, at some point you stop looking at fees as a percentage of assets and focus on the dollars involved.  A pension fund with $4 billion invested in hedge funds that overpays by 2% per annum throws away $80 million a year.  Over a decade that’s $800 million.  To paraphrase the famous quote, a million here and a million there and soon you’re talking about real money.


[1] See Fee Reduction and Alpha Generation

[2] See Hedge Fund Replication: A Practitioner’s Scorecard and Two Unanswered Questions About Alternative Betas

[3] See Performance of Emerging Equity Long/Short Hedge Fund Managers

[4] See Performance Drag of Alternative Multi-Manager Mutual Funds

A vexing issue with hedge funds is the lack of persistence of returns.  Last year’s winners generally are no more likely to be this year’s. Consequently, while quantitative screening tools help investors to identify strong historical performance, they are of little use in determining which funds will perform better going forward.

Beachhead’s proprietary research demonstrates that, while alpha overall does not persist, “tactical” alpha does.  Broadly speaking, hedge fund alpha can be broken down into two sources:  position alpha and tactical alpha.  Position alpha represents outperformance due to security selection, illiquidity and other factors, such as optionality.  Tactical alpha represents medium-term relative value trades across asset classes – such as investing in credit post-crisis or shifting back to developed markets equities in 2012-13.[1]  Both position alpha and tactical alpha have a low correlation to equities over time, and hence are valuable diversifiers.

In order to study the persistence of tactical alpha, we examined the performance of 679 funds over the seven year period from 2007 to 2013.  The key conclusions are as follows:

  • Managers that generated high tactical alpha (top quintile) in a given year outperformed the overall pool by 246 bps per annum on average in the following year.
  • Outperformance was driven by greater alpha, not higher leverage:  alpha to the overall pool was 275 bps per annum with comparable beta.
  • High tactical alpha funds had a much higher Sharpe ratio (0.84 vs. 0.59) over the full time period.
  • As expected, high tactical alpha funds performed materially better during the crisis, with aggregate outperformance over 2008-09 of almost 17%.
  • Relative value funds show the most consistent outperformance due to tactical alpha: although representing only 18% of all funds, they accounted for 30% of top quintile funds.

These results lead to several important conclusions about hedge funds.  First, unlike position alpha, tactical alpha tends to persist.  This makes sense:  high tactical alpha suggests the manager has a good understanding of the current market and, since tactical alpha positions tend to shift relatively slowly, this understanding provides a valuable edge in the near future.

Second, hedge fund managers can add material value through asset allocation.  One potential implication is that hedge funds with broader mandates may have greater flexibility to capitalize on alpha opportunities among markets.  It is noteworthy that equity long/short funds added less value through tactical alpha, although it is unclear if this is due to a narrower mandate or lack of skill.[2]

Consequently, in order to maximize returns, allocators to hedge funds may be better served by focusing on tactical alpha than position alpha.  First, for many hedge funds, position alpha is rarely greater than all in fees; therefore, most alpha generation after fees tends to be tactical alpha.  Second, since tactical alpha persists, a portfolio of high tactical alpha managers is more likely to outperform going forward.  Finally, tactical alpha exposures can provide important, and highly valuable, insights into how managers collectively view the relative attractiveness of markets.

Please contact Andrew Beer or Mathias Mamou-Mani at Beachhead Capital for additional information.


[1] Tactical alpha is distinguished from near term net exposure management, which generally does not produce consistent alpha.

[2] Interestingly, macro funds tended to add little value through tactical alpha, although this may be due to a difference in investment time horizon.

Institutional hedge fund investing is entering a new era.  Generation one entailed investing through funds of hedge funds, which offered manager selection, access, diversification and better liquidity in an era when hedge funds were more opaque and less well understood.  The crisis, however, revealed that many funds of funds were running a dangerous asset-liability mismatch as over 80% of redemptions in early 2009 came from funds of funds.  Madoff and other frauds highlighted the risk of failures to adequately diligence certain strategies, which further heightened risk aversion in the coming years.

Generation two has been a disintermediation of funds of hedge funds through direct allocations to a diversified portfolio of single managers.  Driven by institutionalization and dissemination of knowledge about manager selection and due diligence, three quarters of investors today allocate directly.  This has helped to reduce the all in cost of investing by 100 bps or more.

Generation three involves a shift to a core satellite model, where the core allocation to a given strategy or sub-strategy is implemented through low cost, liquid alternatives, including dynamic or alternative beta programs.  A good analogy is long equity investing, where two decades ago an institution might have selected two dozen active managers – each at relatively high fees – but now utilize low cost index funds/ETFs to obtain core exposures and concentrate resources on identifying higher value added, more idiosyncratic “alpha” satellite funds.  Generation three promises to materially drive down all in fees by 200 bps or more, improve liquidity and risk management, and enable investors to concentrate resources on higher alpha opportunities.

Why is this happening today?  There are four principal drivers:

  • Numerous liquid alternative products have established track records of delivering comparable returns to higher cost, illiquid hedge fund portfolios.  This contrasts with investable hedge fund indices, which have materially underperformed due to adverse selection and investment constraints.
  • With lower returns, institutions face increasing pressure to reduce all in fees.  The flow of capital to only the largest firms has prevented a material reduction in fees, even among larger investors.  Whereas the focus of the past five years was on disintermediating fund of funds level fees, attention has shifted to the 2/20 structure.
  • A better understanding of the underlying drivers of performance, such as more sophisticated factor/risk premia models, has demystified the drivers of returns and demonstrated that many funds are overpaid for providing beta-like performance.
  • Capacity issues for larger investors (e.g. CalPERS).

There is little question that the hedge fund industry will continue to grow. Citibank estimates that traditional hedge fund assets will rise to almost $5 trillion by the end of 2018, or roughly five times the total just a decade ago, as institutions diversify away from low yielding fixed income investment and seek to meet high long term return targets.  The rise of liquid alternatives could bring another $1 trillion into the industry as retail investors make meaningful allocations for the first time.

With growth comes the need to evolve.  The traditional investment business has shifted to a model of “pay less for beta, pay up for alpha.”  With more innovative tools at their disposal, institutional investors can better manage their portfolios to enhance net of fee returns, lower costs, improve liquidity and reduce risks.

As of mid-month October, the S&P 500 was down over 5% and the MSCI World was down 6%.  In this context, drawdowns among hedge funds have been unexpectedly large.  Before fees, the HFRX Global Investable index was down over 4%, while the Equity Long/Short and Event-Driven sectors were down 5% and over 7%, respectively (note that the reported losses are lessened by the reversal of accrued performance fees).  The average alternative multi-manager mutual fund (generally with 0.2 to 0.3 equity beta targets) was down 3% net of fees.

What explains the underperformance?  A significant portion likely is due to position crowding, which occurs when many hedge funds hold similar positions.  In good times, additional buying can support stock prices and contribute to excess returns.  For instance, the GS VIP index, which tracks positions in which hedge fund managers have a significant stake, outperformed the S&P 500 index by around 400 bps (per annum) from 2009 to September 2014.  Performance like this is used to support the thesis that hedge fund managers add value over time through stock selection.

In periods of market stress, however, those same positions can underperform significantly as hedge funds cut positions simultaneously.  The table below shows the GS VIP performance during the market drawdowns of 2008, 2011 and the current year:

In each of these drawdowns, widely-held positions declined by 30-50% more than the market as a whole.  While gross underperformance in September through mid-October has not been nearly as pronounced as earlier periods, the data suggests that these positions will further underperform if the markets decline further.

Another form of position crowding occurs when hedge funds invest in a common theme.  This year, many event-driven managers have owned stocks that are takeover candidates due to tax inversion arbitrage; a recent shift in the regulatory environment led to price declines in numerous such positions (most recently Shire, which purportedly caused over $1 billion in losses for hedge funds last week alone).  Anecdotally, many hedge funds also have outsized exposure to oil and gas producers, an implicit bet on high oil prices; it remains to be seen if the recent decline in oil prices has caused outsized losses here as well.  Likewise, the sudden drop in 10 year Treasury yields last week has also been blamed on hedge funds scrambling to cover short positions.

It is quite possible that the concentration of capital among the largest hedge funds will exacerbate this going forward.  Further, numerous investment products now clone long positions of prominent hedge funds (from recent 13F filings) and investors regularly piggyback on positions held by their hedge funds. This additional capital may amplify both upside and downside performance in the quarters and years ahead.

Position crowding is analogous to (or maybe a form of) illiquidity risk.  Alpha can quickly turn negative in periods of market stress, as we saw with illiquid hedge funds during 2008.  Looked at another way, low beta funds became high beta when markets declined.  The same is true for position crowding.  Hedge fund investors who are seeking to protect against downside moves may need to factor this into overall portfolio construction.

We’re surrounded by investment products that track indices. S&P index funds seek to replicate the performance of the S&P 500 index – easily accomplished by simply buying the constituent stocks in designated weights. Other indices are more difficult to track – for example when the product invests in futures to approximate spot market returns (GSCI) or acquires only a subsample of index constituents (Barclays Ag).

A new generation of indices promises to emulate more complicated investment strategies, such as currency carry, volatility and roll trades. Investment banks now offer institutional investors an array of derivative products tied to such indices, and asset managers are packaging them into ETFs and other fund products.

One problem, however, is that newly created indices tend to overstate historical, hypothetical performance. From a commercial perspective, there’s little point in launching a new index if the pro forma returns are unattractive; consequently, there’s a strong incentive to adjust the calculation methodology until the results look favorable.

Further, unlike mutual funds, indices can be created and published with minimal disclosure of key information, such as when the index went “live” and what assumptions are made about trading and other costs. The combination can mislead investors who may expect actual net of fee fund returns to match hypothetical gross of fee index returns.

A case study is the PowerShares Multi-Strategy Alternative Portfolio fund (LALT), an active ETF launched at the end of May 2014. This Fund seeks to match or outperform the Morgan Stanley Multi-Strategy Alternative Index (Bloomberg ticker MSUSLALT), comprised of a combination of risk premia strategies designed to deliver absolute returns.

Unrealistic historical index returns

On Bloomberg, the Index data begins on 1/1/2003.  Given the start date, it is possible that the Index was launched sometime in 2013 with roughly ten years of backfilled data.  Unfortunately, there is no requirement to differentiate between backfilled and live results, and neither the LALT prospectus nor Bloomberg sheds any light on when the Index went “live.”

The backfill thesis is supported by historical performance.  The following chart shows the Index returns for the ten years preceding the launch of LALT against the S&P 500 and HFRIFOF index.

The Danger of Indices - 1

Over the decade, the Index “returned” 6.83% per annum with an annualized standard deviation of 2.93% and a Sharpe ratio of 1.64.  The maximum drawdown – during a period that covers the Great Financial Crisis – was only 2.33%.  The Index “delivered” almost 90% of the return of the S&P 500 with one fifth the volatility.  Annual performance was almost 350 bps higher than that of the HFRI Fund of Funds index, which has limited data bias and generally represents live performance. The following table provides some summary statistics:

The Danger of Indices - 2

If the Index represented actual performance, it would rank among the best performing hedge funds over the past decade.  In fact, the risk adjusted return (Sharpe ratio) was better than 97% of all hedge funds in the HFR database over the same period.  Only three live hedge funds had smaller drawdowns. Plus, unlike investing in illiquid and expensive hedge funds, the performance in theory was achievable at low cost and with daily liquidity.

Disconnect between hypothetical and live returns

Prior to May 2014, the Index would have outperformed 97% of hedge funds. Since then it has lagged hedge funds by 600bps.

Since launch, however, both the Index and Fund have failed to meet these high expectations – to say the least.  Each is down approximately 8% since May 2014 – underperformance of 600 bps versus the HFRXGL (daily investable hedge fund) index, which itself tends to underperform the HFRIFOF index by 100-200 bps per annum due to adverse selection bias.  The drawdown over the first seven and a half months is more than triple the hypothetical drawdown over the ten preceding years – during a time when the S&P has risen 8%.

The Danger of Indices - 3

Looking at the live returns, it appears that the Fund and Index were hurt when the Swiss Franc decoupled from the Euro on January 15, 2015.  This underscores the backfill issue:  while the Index “sidestepped” any major adverse market events over the past decade, both the Index and Fund walked into a proverbial propeller seven months after launch.

This issue is particularly timely given the plethora of complicated risk premia products introduced by investment banks over the past two years.  Most indices created recently will be subject to the same backfill bias highlighted above.  A live index, the Merrill Lynch Foreign Exchange Arbitrage Index, is down over 6% in January – but will currency carry indices launched in the future show better pro forma results?  And will investors appreciate this distinction?

Most investment bank indices are subject to the same backfill bias.

 In order to better align investor expectations with likely performance, indices should be subject to the same rigorous disclosure requirements as funds:  investors should know when the index went “live,” which performance is hypothetical, and what assumptions are made about costs and expenses.  Otherwise, the tendency to publish only successful indices will persist.

Investors and managers find themselves at an interesting inflection point in the evolution of the hedge fund industry.  The growth of liquid alternatives has focused attention on what happens when talented hedge fund managers are asked to manage money within the constraints of a mutual fund structure. The results so far are disappointing:  alternative multi-manager mutual funds underperformed the HFRI Fund of Funds index by close to 200 bps in 2014, despite a 200-300 bps fee advantage (and, as noted in a previous paper[1], underperformed by 400 bps on average in 2013 and 2012). This underperformance mirrors the issues with investable indices, which lagged by an even wider margin in the early years.

Constraints are the Achilles heel of talented investors. Despite deep levels of talent and resources, the vast majority of traditional managers underperform lower cost indices over time. The original concept of the hedge fund industry was that with fewer constraints, talented managers could deliver exceptional returns.  Not surprisingly, many of the original distressed debt investors in the early 1990s were merger arbitrage specialists – when the junk bond market collapsed, they moved to capitalize on it.

The institutionalization of the hedge fund industry has introduced a new set of constraints.  Institutional fear of strategy shift relegates most managers to narrow mandates:  a talented equity long/short manager with health care expertise faces an uphill battle explaining to current investors why half the portfolio should be in credit, another sector, or even cash if the opportunity set within healthcare is not compelling. Effectively, most managers are given a hammer and instructed to look for one particular kind of nail.

This paper looks at two less well known examples:  strategy bias in hedge fund indices, which have been overweight underperforming sectors post-crisis, and funds of funds, whose own constraints have led to meaningful underperformance relative to less constrained multi-strategy portfolios.

Strategy Bias in Hedge Fund Indices

The pre-crisis years were relatively easy sledding for hedge fund allocators, such as funds of funds.  In 2003-07, all major hedge fund strategies generated high risk adjusted returns.  Equity Hedge, Relative Value, Event Driven and Macro all had Sharpe ratios of between 1.29 and 2.17 – exceptionally high relative to traditional assets, where long-term Sharpe ratios typically are 0.2-0.3.

Sharpe Ratio of HFRI Strategies

In this environment, an allocator throwing darts at a wall of hedge fund names would have meaningfully outperformed traditional assets.  This led to the development of a “fully diversified” hedge fund portfolio – relatively static allocations across strategies and, sometimes, dozens of managers.  Diversification would minimize manager risk and, in theory, protect against market drawdowns.  Consequently, the portfolios tended to reflect the composition of the overall industry which, in terms of number of funds, has always been heavily biased to Equity Hedge and Macro.   Today, 70% of the HFR Fund Weighted Index consists of Equity Hedge and Macro funds.

HFRI Fund Weighted Index

Why is this?  Because the barriers to entry are lowest – it’s much easier to launch Equity Hedge and Macro funds, so most funds at any given point in time will consist of those strategies.  Further, because reporting to indices is elective and is viewed as a de facto form of marketing, the composition of the database similarly will reflect the composition of the number of funds across the overall industry.

The post-crisis years have been a rude awakening, with a wide divergence in the risk adjusted returns of the same strategies.  The Sharpe ratio of Macro strategies, for instance, dropped by two-thirds from the pre-crisis to post-crisis period, and was less than a quarter that of Relative Value.  The Sharpe ratio of Equity Hedge strategies dropped by half over the same period.

Sharpe Ratio of HFRI Strategies 2010-2014

Opportunity sets change, but many allocators can only capitalize at the margin.

Viewed in this light, the indices have been overweight underperforming strategies for years.  This explains in part why many of the actively managed hedge fund portfolios have been able to persistently outperform the indices.  As the opportunity sets change, they adapt accordingly.

Funds of Funds vs. Multi-Strategy Hedge Funds

Take the performance of the HFRI Fund of Funds index versus the largest multi-strategy funds[2]. The latter, by definition, have open mandates to pursue opportunities wherever and whenever they arise.  Managers with billions of dollars of capital at stake have the right incentives and resources to maximize risk adjusted returns over time.

In the pre-crisis period, risk-adjusted returns between large multi-strategy funds and the HFRI Fund of Funds index (adjusted for the second layer of fees) were comparable.  However, in the past five years, the Sharpe ratio of multi-strategy funds was almost double that of the typical fund of hedge funds.


What has driven the outperformance by multi-strategy managers in recent years?   In large part, multi-strategy funds have been much better at adjusting their portfolios to capitalize on shifts in the opportunity set.  The following chart breaks down pre-fee performance according to equity beta, tactical alpha (shifts in asset allocation among key markets), and position alpha (primarily security selection and illiquidity premia).


The results are striking:  despite similar beta exposure, multi-strategy managers generated vastly more tactical alpha and position alpha.  We see this in greater exposure to credit and emerging markets post 2008, more illiquid assets in 2012, and more aggressive shifts to US equity exposure in 2012-13.  By contrast, under pressure from investors who fear a repeat of the gatings and suspensions from 2009, many funds of funds have shifted to more liquid strategies, which have underperformed on a risk adjusted basis.


The implications of this analysis are several-fold.  First, the most sophisticated allocators, including leading funds of funds, have become more adept at shifting exposures across strategies based on feedback from underlying managers.  In analyzing dozens of live portfolios, we’ve seen persistent outperformance of 300 bps or more relative to the indices:  the best allocators are becoming more like multi-strategy funds than index trackers.

Multi-strategy funds have been much better at adjusting their portfolios to capitalize on shifts in the opportunity set.

Second, the perception that hedge fund indices, with their relatively static weights, have generated disappointing performance is valid.  By analogy, it’s as if the S&P was significantly overweight industrials during a tech boom.  In the replication space, we’ve seen how successfully tracking (and in most cases, outperforming) the fund of funds and liquid indices has failed to produce absolute returns commensurate with expectations from the pre-crisis period.

Finally, there are serious questions about the degree to which newly-launched liquid alternative products – with a panoply of new constraints – will continue to underperform investor expectations.  In some strategies, such as equity long/short, the impact should be minimal.  However, in a diversified model – such as that employed by alternative multi-manager mutual funds – the impact of regulatory constraints on performance may be expected to be far more pronounced.

[1] See Performance Drag of Alternative Multi-Manager Mutual Funds

[2] Custom equal weighted index based on the 16 largest funds in the Credit Suisse Multi Strategy Index.

Of course it’s true until everyone knows it’s true.
Famous economist in response to publication of Stocks for the Long Run (1994)

Everyone likes bargains.  Perhaps this explains the irresistible appeal of the Value benchmark factor.  The original paper by Eugene Fama and Kenneth French in 1992 propagated the model that investors chase the latest highfliers, while boring “value” stocks are overlooked and underpriced.  The key conclusion was that “value” stocks, as defined by low price-to-book ratios, outperform high multiple stocks and that this outperformance tends to be more pronounced during market downturns – a highly valuable property for an investment portfolio. Historical Sharpe Ratio

But what if it’s all wrong?  Not that the original paper was wrong, but that the return “anomaly” has been priced away or fundamentally changed?  A simple review of risk adjusted returns highlights the issue.  In 1963-90, the period studied, the Value factor had a Sharpe ratio of 0.54 – around double that of traditional assets over time.  Since its “discovery,” the Sharpe ratio declined to 0.17 in 1995-2004 and dropped further to 0.03 in the past decade.[1]

What might this tell us?  Most likely, excess returns were arbitraged away as more investors flocked to the space.  Today, “value” investing is the norm rather than the anomaly, like when Warren Buffett ran a partnership in the 1960s and was buying “cigar butts” for less than net cash.  The growth stock mantra of Peter Lynch and the idea of chasing “ten baggers” seems like a distant memory.  Today, a quick screen on Bloomberg lists 942 value-focused equity mutual funds with assets under management of approximately $1.5 trillion.  Add institutional managed accounts and value-focused investors like hedge funds and the number is much, much higher.  Value isn’t overlooked anymore.

What seems obvious is that the process of identifying and buying stocks is very different today.  Imagine a typical investor in the 1970s.  He reads the Wall Street Journal, scans the stock pages and calls his broker.  The broker recommends an exciting growth stock with a great story, which maximizes his chance of getting paid a commission.  It’s hard to see the same broker trying to explain, say, how a failing consolidated steel company is a bargain because the market’s overestimating the cost of pension liabilities.  The oft touted growth bias of the typical investor, then, may be explained instead by agency issues with the advisor which are less relevant in a world with better dissemination of information, the shift to fee-based advisory and other tectonic shifts in the investing landscape.

Another question is whether the composition of “cheap” stocks has changed over time.  One possible hint comes from the correlation of the Value factor to the overall market.  Correlation was decidedly negative in the period studied and the subsequent decade, which bolstered the argument that cheap stocks were “safer”:  they fell less when markets declined, and vice versa.  Over past decade, however, the correlation has been clearly positive.  This is harder to explain and undercuts the argument for Value as a diversifier under Modern Portfolio Theory.[2]

What’s changed?  One possibility is industry or sector bias.  Unfortunately, it’s difficult to tell given the inaccuracy of simple classifications like SIC codes, especially given how much US industry has changed over the past decades (e.g. deconglomerization).  Another possibility is a change in accounting standards – for instance, the elimination of pooling of interests acquisitions under GAAP in 2001.  Did this fundamentally alter the concept of “book value”? Rolling Five Year Correlation

The danger of investing based on academic studies is that our own biases often rise to the surface.  We tend to overlook the fact that published studies invariably have “interesting” results – the pressure to data mine should not be underestimated.  What looks good on paper may have little relevance once translated into an investment strategy – a failure to screen for market capitalization, for example, can undercut the notion of “investability.”  Conclusions are emphasized over assumptions; yet, the latter are equally, if not more, important.  We often hope that such studies reveal an immutable truism about the market and investors – since relying on truisms is easier than messy realities.

When studies like the HML paper become canonical – what investing course doesn’t cover the Fama-French factors? – we cling to the original conclusions even as the world evolves.  The end result is that academic studies can steer investors to strategies that might have worked decades ago, but not today.  The performance of the Value factor “post-discovery” should be a cautionary tale for investors considering the panoply of smart beta and alternative risk premia today.

[1] Based on data available on Kenneth French’s data library:

[2] Market returns from Kenneth French’s data library were utilized.