Aqr Delta Strategy

In the summer of 2011, the principals at AQR Capital Management met in their Greenwich, CT, office to resolve how finest to market their new DELTA technique. After launching in the late summer of 2008, the DELTA strategy had compiled a wonderful observe document, but David Kabiller, a Founding Principal and the Head of Client Strategies at AQR, was frustrated that the fund had not grown faster in light of its exceptional performance. In Kabiller’s experience, the mixture of a solid monitor record plus an revolutionary product often led to explosive growth in belongings under management (AUM), but that had not been the case up to now with DELTA.

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The DELTA strategy was a product that offered investors publicity to a basket of 9 major hedge fund strategies.

The DELTA technique was innovative in two ways. First, in terms of its structure, AQR carried out the underlying strategies utilizing a well-defined investment course of, with the aim of delivering exposure to a well-diversified portfolio of hedge fund methods. Second, when it comes to its fees, the brand new DELTA strategy charged relatively decrease fees: 1 percent management fees plus 10 % of efficiency over a cash hurdle (or, alternatively, a management charge of 2 p.c only). This charge structure was low relative to the industry, the place 2 percent administration fees plus 20 % of efficiency, usually with no hurdle, was normal. These options, whereas distinct relative to other related “hedge fund replication” merchandise, had yet to completely resonate with investors, and Kabiller wanted to resolve on a more effective advertising approach given the large variety of rivals coming into this space.


AQR was established in 1998 and headquartered in Greenwich, CT. The founding Principals of the agency included Clifford Asness, David Kabiller, Robert Krail, and John Liew, who had all worked together at Goldman Sachs Asset Management before leaving to start AQR. Asness, Krail, and Liew had all met within the Finance PhD program on the University of Chicago, the place Asness’ dissertation had targeted on momentum investing. AQR’s over 200 workers managed $24.0 Billion in property. A large amount of these assets have been invested in hedge fund methods.

Professors Daniel Bergstresser (HBS), Lauren Cohen (HBS), Randolph Cohen (MIT), and Christopher Malloy (HBS) ready this case. HBS instances are developed solely as the premise for class dialogue. Cases are not supposed to function endorsements, sources of primary information, or illustrations of effective or ineffective management. Copyright © 2011, 2012 President and Fellows of Harvard College. To order copies or request permission to breed materials, name 1-800-5457685, write Harvard Business School Publishing, Boston, MA 02163, or go to This publication may not be digitized, photocopied, or otherwise reproduced, posted, or transmitted, with out the permission of Harvard Business School.

Voor- en nadelen Hedge Fund:

While open-end mutual funds needed to register with the SEC, calculate and publish daily net asset values (NAVs), and provide traders with every day liquidity, hedge funds weren’t automatically regulated by the SEC and enjoyed as a lot flexibility as they could negotiate with their shoppers with respect to liquidity. In trade for this light-touch regulation, hedge funds have been restricted in their advertising: only excessive internet value and institutional investors might immediately put money into these funds. Nevertheless, academic work had by the late Nineteen Nineties established that hedge funds provided a danger publicity that was much less correlated with broad market indexes than most mutual funds, and probably offered excessive risk-adjusted returns.

The performance of the hedge fund business during the 2001-2002 recession was particularly good; Exhibit 1 reveals that whereas inventory market indices (S&P and NASDAQ) fell dramatically during this era, broad hedge fund indices (e.g., DJCS_Hedge and HFRI_FW, which have been designed to trace the overall performance of the hedge fund industry) rose. In response to the perception that hedge funds really supplied outperformance, institutional money flowed into hedge funds during the late Nineties and 2000s, and the size of the industry grew rapidly. Exhibit 2 charts the expansion in the variety of funds and whole AUM (assets beneath management) within the hedge fund trade since 1997. With this development in property and managers, questions began to surface concerning the position of hedge funds in a portfolio and whether or not there have been different ways to capture those returns with out being exposed to a few of the negatives of hedge fund investing.

Alternatives to hedge funds

Although many buyers have been interested in the potential for acquiring excessive returns and/or low covariance with other investments in their portfolio, many nonetheless found hedge funds themselves to be unappealing. Among the explanations for his or her distaste were: a) illiquidity, b) minimum investment necessities, c) excessive charges, d) the issue of choosing the right hedge fund manager, e) the shortcoming to gain entry to prime quality funds, and f) the shortage of established benchmarks in the trade. Most hedge funds solely allowed redemptions on sure dates – usually on the finish of each quarter. Additionally many funds had an initial lockup – that is, traders could not redeem from the fund for a set period after investing; the period was usually one year although some funds had no lockup and others had locked up investors for as lengthy as 5 years.

Most funds additionally had a minimal funding measurement of a minimal of $1 million. In addition, many buyers found the charges charged by hedge funds, which often amounted to 2% of assets under administration (some funds even charged the complete value of their operations to their funds, amounting to more than 2% administration fees) plus an additional 20% of earnings generated by the fund, to be extreme and hoped to acquire related benefits at a lower price. Some investors also found the concept of selecting a portfolio from the various hundreds of accessible hedge funds to be an intimidating task, particularly given the lack of transparency (both as to investment course of and holdings) that was frequent amongst hedge fund managers. And in fact even if an investor might determine a set of funds that made up an attractive portfolio, the managers of those funds may not accept an investment at that time or from that investor. Finally, in distinction to the mutual fund trade, there was a lack of established benchmarks for hedge funds, making it tough to assess ability versus luck and idiosyncratic versus systematic returns. While hedge fund indices existed, these have been simply peer groups, not true benchmarks, and had been biased by a number of issues, together with style drift and survivorship bias. In response to those criticisms, different products were soon introduced into the marketplace.

Funds of Hedge Funds (FOFs)

One popular different to direct hedge fund investing was the funds of hedge funds (FOFs) structure. FOFs aimed to take investors’ money and allocate it among a select group of hedge funds – sometimes amongst a small quantity (even in the single digits in some cases), and sometimes among hundreds of funds.

onerous= burdensome/ heavy

This strategy solved a quantity of the problems dealing with hedge fund buyers, particularly those with modest capital. FOFs had less onerous liquidity rules than individual hedge funds, and FOFs have been less more probably to encounter liquidity issues than particular person funds since they could get hold of liquidity from numerous underlying funds. Still, FOFs were ultimately subject to the underlying liquidity (both with respect to liquidity phrases and underlying holdings) of the funds they had been investing in. In addition, a single minimum investment purchased a portfolio of many funds, and an experienced and hopefully professional financial skilled, or group of such professionals, chosen the funds, and selected allocations amongst them that (presumably) produced a well-optimized portfolio. Finally, FOF managers claimed that their expertise and connections offered access to hard-to-enter funds. Thus FOFs introduced an interesting package, and indeed near half of all cash invested in hedge funds came through FOFs. However, many buyers have been put off by FOF charges, which historically included an additional layer of fees often as high as half the level of hedge fund charges themselves (thus making whole charges paid about 1.5 instances higher than for direct investing).

Multi-strategy Funds

Another strategy to obtaining an alternative-investment portfolio whereas avoiding some of the challenges of one-strategy-at-a-time creation was to spend money on multi-strategy hedge funds. Such choices have been typically made by massive hedge fund companies that provided a variety of particular person strategies. Investors might have the choice to put cash into a multi-strategy fund that allocated assets across the different silos within the agency. One major benefit of multi-strategy funds over FOFs was fees: multi-strategy funds typically didn’t cost an additional charge layer over and above the hedge fund fee (as FOFs did). Further, multi-strategy funds only charged efficiency charges when the total investment was within the cash; whereas, in the case of FOFs and direct single technique investments, an investor might be topic to efficiency charges even when the web, aggregate performance wasn’t optimistic.

A second potential benefit of multi-strategy funds was in portfolio development. Not solely was the allocation among methods carried out by professionals, those professionals likely had a high degree of insight and visibility into the opportunities obtainable to the person silo managers. Multi-strategy funds typically provided pretty much as good or higher liquidity than individual-strategy funds, and of course there was no bother gaining “access” to the underlying managers. Multi-strategy funds appeared to supply strong diversification, although in the famous case of the hedge fund Amaranth, buyers thought they had been investing in a diversified portfolio of strategies. However, excessive losses in one of many portfolio’s silos led to the lack of roughly 75% of complete portfolio worth. Consequently many investors felt they were not actually diversified if that they had a large allocation to a multi-strategy fund, but this could be potentially mitigated via the right quantity of transparency into the positions and dangers of the portfolio, or, after all, through diversification amongst several completely different multi-strategy funds, thereby minimizing single agency threat.

silos= opslagplaatsen

One potential concern with multi-strategy funds from the investor’s point of view was the query of portfolio supervisor quality. Although it was attainable that a single firm might collect underneath one roof the easiest managers in a wide range of specialties, some traders discovered this implausible.

Hedge Fund Replication

Starting in 2006, a variety of investment management companies also launched “hedge fund replication” products. These methods, carried out utilizing liquid instruments, purported to offer traders a ‘top-down’ exposure to the broad risk exposures of the hedge fund trade. These products could be viewed as an effort to provide ‘hedge fund beta,’ or the systematic a half of hedge fund efficiency. The rationale for these merchandise originated from research of hedge fund returns that highlighted the concept the road between ‘alpha’ and ‘beta,’ was probably fluid. The different systematic exposures of hedge funds could probably be viewed as a sort of “exotic beta.” If hedge fund returns could be approximated with dynamically traded portfolios of liquid assets, then traders attracted to hedge fund returns, but potentially on the lookout for a liquid or low-fee different to actual hedge funds may put money into a ‘hedge fund replication’ product that tried to mimic hedge fund returns using liquid belongings.

These top-down approaches aimed to make use of statistical strategies to create a portfolio of liquid property that had comparable performance to hedge funds as a category. One top-down strategy was to make use of linear regressions, or optimizations, to build a portfolio that had high correlations to historical hedge fund returns. An example of this approach consisted of three steps. First one would obtain a long-run time collection of returns on a diversified portfolio of hedge funds (e.g., the HFRI month-to-month hedge fund indices have been commonly used). Then one would acquire returns on a lot of liquid investments-these might be indexes of stocks (e.g., S&P 500, MSCI EAFE, MSCI Emerging, Russell 2000, and so on.), bonds (e.g., US 10-year authorities bonds), currencies (e.g., EUR-USD Spot Exchange Rate), and so forth. () Finally, one would use a normal statistical optimizer, or linear regression, to seek out the portfolio of liquid investments (either lengthy or quick and at weights implied by the statistical analysis) that most intently replicated the statistical traits of the hedge fund portfolio. Exhibit 3 presents the month-to-month returns from a set of indices that have been commonly used for hedge fund replication purposes.

1 Specifically, the goal was to create a portfolio that traditionally moved as close to a minimum of one for one with the hedge fund portfolio, so that it had high correlation with the hedge fund portfolio, and yet additionally matched other “statistical moments,” similar to volatility, skewness, and kurtosis. Historically, and ideally on a forward-looking basis as nicely, this portfolio would fulfill a job within the diversified portfolio much like the function that hedge funds would play. Exhibit 4 plots the latest return efficiency of some commonly used hedge fund indices (e.g., DJCS_Hedge, HFRI_FW, and HFRX_Global), which represent composite indices of individual hedge funds and had been designed to track the general return efficiency of the business; as well as a fund-ofhedge funds (FOF) index (HFRI_FOF) designed to track the overall return performance of funds of hedge funds. Exhibit 5 presents the return efficiency of four popular hedge fund replication index merchandise, produced by Merrill Lynch, Goldman Sachs, JP Morgan, and Credit Suisse. Exhibit 6 presents the return performance of the general hedge fund indices alongside the performance of these hedge fund replication products.

AQR’s approach

For years, the principals at AQR had been engaged on understanding the underlying nature of hedge fund returns and exploring the possibility of having the ability to seize them in a transparent, liquid and price effective means. Thus, they were initially intrigued by the introduction of those hedge fund replication merchandise, however very quickly came to the conclusion that a wholly completely different approach to delivering publicity to the systematic danger elements of the hedge fund business was wanted. Whereas AQR’s opponents centered on the ‘top-down’ products described above, AQR focused on creating a ‘bottom-up’ method that sought to deliver significant risk-adjusted returns instead of simply replicating an index by: capturing classical, liquid hedge fund methods that were uncorrelated with traditional markets, implementing them at low value, and then bundling these strategies right into a wellconstructed single portfolio specializing in portfolio construction, risk administration and buying and selling.

Origins of AQR’s approach

The idea of direct, simplified implementation of core hedge fund strategies was hinted at by the pioneering work into merger arbitrage of Mark Mitchell and Todd Pulvino. Mitchell and Pulvino were each former lecturers (at Harvard Business School and the Kellogg School of Management, respectively) who subsequently teamed up with AQR in 2001. A easy merger arbitrage technique, for instance, labored as follows: after the announcement by Firm A of a desire to acquire Firm B, the merger arbitrageur made a purchase of the target Firm B shares whereas shorting the acquirer Firm A’s shares (if the acquisition was to be made in money, the arbitrageur merely purchased Firm B shares with out shorting Firm A).

Typically upon the announcement of the merger, the worth of the target shares would not rise all the way in which to the price that may be appropriate if the merger had been positive to be accomplished. When Mitchell and Pulvino studied the merger arbitrage business, they discovered that merger arbitrage strategies did deliver substantial risk-adjusted returns. Specifically, the expected returns of placing merger arbitrage investments into place was excessive, and while the danger was greater than one might naturally have anticipated — as a result of mergers tended to break up precisely at instances of market stress, and due to this fact the merger arbitrage strategy had extra beta, or market publicity, than could be presumed — nevertheless they discovered that even accounting for this threat, the performance of a naïve merger arbitrage technique that invested in each deal was substantial.

Mitchell and Pulvino additionally appeared at the performance of actual merger arbitrage funds. A merger arbitrage fund could be anticipated to add alpha by accurately figuring out which mergers have been roughly likely to obtain completion than the market anticipated. So, for example, if the market pricing of a deal was such that the expected return could be zero if the merger was 90% prone to be completed, the merger arbitrageur’s job was to strive to determine whether in fact the merger was considerably greater than 90% more doubtless to undergo, substantially less than 90%, or about 90%, and then invest only in these deals that were substantially more than 90% likely to undergo. What Mitchell and Pulvino found was that merger arbitrage funds made money, however that they didn’t present an ability to forecast which mergers would shut over and above the market’s capability. That is, the outperformance that merger arbitrageurs had been generating was no higher than the outperformance that might be generated by a simple strategy that bought each target and shorted every bidder, significantly internet of fees.

This opened the door to a potential technique for the replication of merger arbitrage: merely participate in each merger arbitrage deal that met a set of fundamental screens (e.g., size and liquidity). The profit to traders can be a potentially more diversified portfolio of merger offers than would be obtained from a fund supervisor who only chosen a subset of the deals, and also doubtlessly far decrease charges, as a end result of there was no have to pay an analyst to determine which mergers had been kind of more likely to succeed. With this as a template, one might easily think about an entire roster of potential hedge fund methods that might be captured in a systematic way (e.g., long worth stocks and short development stocks, convertible arbitrage, carry trades, pattern following trades and trades exploiting different wellknown empirical asset pricing anomalies). Since the early work into merger arbitrage, AQR had spent years researching these different classical hedge fund strategies that might be captured from the bottomup.

Bottom-Up versus Top-Down

AQR preferred their bottom-up approach for a variety of causes. First, they felt that many hedge fund strategies earned returns for bearing a liquidity threat premium, which you can not earn by buying and selling solely in liquid instruments as in the hedge fund replication strategies. For example, in order to seize the returns from a convertible bond that traded at a discount to truthful worth due to a liquidity risk premium, you wanted to own the convertible bond, not simply liquid assets that were correlated with the convertible bond. Second, since top-down strategies aimed to maximize correlations with latest past hedge fund performance, these approaches have been essentially backwardlooking and based on what hedge funds had been doing prior to now. By contrast, if you ran the precise methods, one could reply to market opportunities instantly.

Finally and maybe most importantly, AQR felt that the hedge fund indices upon which most top-down replication methods had been primarily based had quite lots of biases (e.g., survivorship bias), had an extreme amount of exposure to conventional markets (i.e., fairness and credit beta) and also tended to replicate the weights of the most well-liked strategies. Since these in style methods were crowded with many trades, the expected returns on these strategies going ahead had been probably decrease. In short, while they shared the noble goals of top-down replication merchandise (i.e., attempting to supply liquid, transparent exposure to hedge fund methods at a decrease fee), AQR felt that the approach had basic flaws or, as Cliff Asness put it in a speech in October 2007 on hedge fund replication, “Not Everything That Can Be Done Should Be Done.”

In late 2007, AQR decided to focus their years of analysis on capturing the classical hedge fund strategies in a systematic means from the bottom up by “creating our own product that may search to deliver these methods in a risk-balanced and efficiently implemented means.” AQR considered their “DELTA” product as superior to the newly-introduced replication merchandise that have been being marketed as offering ‘hedge fund beta.’ In reality, AQR workers bristled at comparisons between the existing hedge fund replication products and their DELTA product. To make sure that AQR was taking a broad method and to keep away from being insular, they shaped an external advisory committee made up of some very seasoned hedge fund traders to assist information the development of the product. The DELTA name was an acronym that reflected the product’s characteristics: ‘Dynamic, Economically Intuitive, Liquid, Transparent and Alternative.’ The portfolio was designed to be uncorrelated with the general inventory market, and could be diversified across nine broad strategy courses: a Fixed Income Relative Value technique, a Managed Futures technique, a Global Macro technique, an Emerging Markets strategy, a Long/Short fairness strategy, a Dedicated Short Bias strategy, an Equity Market Neutral strategy, a Convertible Arbitrage strategy, and an Event Driven strategy.


AQR determined to go ahead with the creation of the DELTA strategy in the late summer time of 2008. By October 1, 2008, the portfolio was totally invested and had begun to compile a track document. At the time, the employees at AQR had nervous that this could be “the worst attainable time to be launching a product designed to capture classical hedge fund methods.” Nonetheless, the DELTA portfolio carried out nicely in the fourth quarter of 2008 instantly after its launch, a powerful feat given the turbulence available within the market. Exhibit 7 charts the month-to-month efficiency of the DELTA technique since inception. Exhibit 8 exhibits the uncooked monthly returns of the DELTA technique, in comparability with the raw month-to-month returns of inventory market indices (S&P and NASDAQ) and broad hedge fund indices (e.g., DJCS_Hedge and HFRI_FW, which have been designed to track the overall efficiency of the hedge fund industry). Exhibit eight additionally presents the “beta” of the DELTA technique with respect to those numerous market and hedge fund indices, while Exhibit 9 graphs the cumulative return efficiency of the DELTA strategy relative to these indices.

Marketing DELTA

Although DELTA was off to an excellent start, Kabiller felt prefer it was underperforming its potential. By the summer of 2011, despite its wonderful performance, development in DELTA’s AUM had been modest. After giving it lots of thought, Kabiller identified three primary challenges AQR faced in convincing traders to allocate capital to DELTA. First, lots of his institutional shoppers had grown very comfy choosing a set of hedge funds and paying them both management and efficiency charges. Exhibit 10 presents the recent annual returns of some of the largest U.S. hedge funds, a lot of whom had delivered stellar returns over time. Kabiller was convinced that considered one of DELTA’s main assets was its ability to ship hedge fund returns with a considerably lower fee structure. But lots of his institutional clients had issue assessing just how massive an advantage this supplied DELTA. For instance, if a consumer chosen the 2 p.c management fee with no efficiency charge construction, how much higher might they expect their after-fee returns to be?

Given that efficiency fees have been sometimes only paid on returns in extra of a cash hurdle, was a twenty p.c performance charge really that pricey to fund investors? Related considerations utilized to traders that invested primarily via Funds of Hedge Funds. These funding vehicles typically added a layer of charges on prime of the after-fee efficiency of their hedge fund investments – sometimes a one % administration payment and a ten p.c efficiency fee. Due to DELTA’s multi-strategy investment approach, its after-fee efficiency should maybe be benchmarked in opposition to those of fund-of-funds alternate options.

Conveying to such investors the charge advantage of DELTA in simple terms – for example, how much better their competitors’ pre-fee returns needed to be than these of DELTA to offset the charge differential – would go a long way in convincing them that DELTA was the superior approach. A second challenge in marketing DELTA was the emergence of the so-called hedge fund replication strategies. These strategies had been virtually the polar reverse of the fund-of-funds – that they had modest fees and, because they replicated hedge fund returns using extremely liquid indices, they faced little in the way of liquidity threat. Institutional investors thinking about low-fee exposure to hedge fund returns discovered these products enticing, and Kabiller discovered it difficult to convey the benefits of the DELTA method. His inclination was to focus on two key limitations of hedge fund replication. First, he felt they relied closely on the historical relationship between hedge fund returns and major inventory and bond market indices. To the extent that the connection was not secure, or to the extent that a big fraction of hedge fund actions couldn’t be captured by an acceptable mixture of those indices, the replication approach can be restricted in its capability to actually ship in real time the actual returns being earned by the average hedge fund investor. Second, even when the technique may replicate a large fraction of the month-to-month fluctuations in performance of the common hedge fund, Kabiller felt it was likely that a “top-down” method would be restricted in replicating the actual edge, or “alpha,” of the average hedge fund. Even if much of the dangers to which hedge funds had been uncovered could be present in broad stock and bond market indices, it was unlikely that any of the informational or liquidity edges they possessed would appear in the returns of these indices. A ultimate challenge Kabiller confronted in the advertising of DELTA was its track record. Although it had outpaced the broad HFRI index since its inception in the fall of 2008, the observe document was still a reasonably restricted one. Moreover, since the central appeal of the product was its capability to match common hedge fund returns with modest fees, the outperformance paradoxically posed something of a problem for DELTA. Kabiller felt it might be crucial to grasp its supply before figuring out whether it was an aberration or whether they possessed a sustainable edge relative to the index of hedge funds. As Kabiller looked out beyond his infinity pool and into the calm waters of the Long Island Sound, he nervous that and not utilizing a proper grasp of these points, many rough sales meetings lay ahead for him and his DELTA staff.

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