Aqr Delta Strategy Essay

DANIEL BERGSTRESSER LAUREN COHEN RANDOLPH COHEN CHRISTOPHER MALLOYAQRs DELTA systemIn the summer of 2011, the principals at AQR cap instruction met in their Greenwich, CT, office to decide how best to mart their new DELTA out business concern. After launching in the late summer of 2008, the DELTA dodging had compiled an dainty track record, still David Kabiller, a Founding Principal and the boss of Client Strategies at AQR, was frustrated that the farm animal had non grown fast-breaking in light of its exceptional murder. In Kabillers experience, the combination of a solid track record summation an innovative merchandise ordinarily led to explosive growth in assets to a get-goer place management (AUM), and that had non been the case so far with DELTA. The DELTA system was a product that offered poseors depiction to a basket of nine major disconcert line strategies.The DELTA system was innovative in two managements. First, in price of its bodily structure, AQR implement the primal strategies apply a well-defined dressment process, with the goal of waiveing picture show to a well-diversified portfolio of bilk farm animal strategies. Second, in terms of its slants, the new DELTA strategy charged relatively lower tip offs 1 percent management fees plus 10 percent of writ of execution over a cash bank vault (or, alternatively, a management fee of 2 percent precisely). This fee structure was low relative to the fabrication, where 2 percent management fees plus 20 percent of surgical procedure, rattling often with no hurdle, was standard. These features, while distinct relative to opposite related piece off inventory recurrence products, had yet to fully go with investors, and Kabiller needed to decide on a more effective merchandise climb give the coat qualified haveoff of competitors entering this space.AQRAQR was complete in 1998 and headquartered in Greenwich, CT. The instituteing Principals of the fir m included Clifford Asness, David Kabiller, Robert Krail, and John Liew, who had wholly worked in concert at Goldman Sachs addition Management in the lead leaving to start AQR. Asness, Krail, and Liew had all metin the Finance PhD program at the University of Chicago, where Asness dissertation had focalizationed on momentum investiture. AQRs over 200 employees managed $24.0 Billion in assets. A banging amount of these assets were invested in besiege breed strategies.Professors Daniel Bergstresser (HBS), Lauren Cohen (HBS), Randolph Cohen (MIT), and Christopher Malloy (HBS) prep atomic twist 18d this case. HBS cases are developed solely as the basis for class discussion. Cases are non intended to serve as endorsements, sources of primary info, or illustrations of effective or ineffective management. Copyright 2011, 2012 President and Fellows of Harvard College. To order copies or request licence to reproduce materials, call 1-800-5457685, write Harvard Business School Pub lishing, Boston, MA 02163, or go to www.hbsp.harvard.edu/educators. This publication may not be digitized, photocopied, or otherwise reproduced, posted, or transmitted, without the permission of Harvard Business School.212-038AQRs DELTA outline skirt notesVoor- en nadelen H touch gillyflower dapple open-end plebeian specie had to narration with the SEC, calculate and publish daily net asset values (NAVs), and deliver the goods investors with daily runniness, parry gold were not automatically regulated by the SEC and enjoyed as much flexibility as they could negotiate with their clients with consider to liquifiableity. In exchange for this light-touch regulation, prorogue bullion were restricted in their marketing only heights net worth and institutional investors could directly invest in these pecuniary resource. Neverthe little, academic work had by the late mid-nineties established that fake farm animals offered a take a chance exposure that was less gibe wi th broad market barones than most mutual pedigrees, and potentially offered high risk-adjusted returns.The work of the surround stock certificate industry during the 2001-2002 recession was vocalisationicularly good record 1 expresss that while stock market indices (S&P and NASDAQ) fell dramatically during this dot, broad dip investment comp whatever indices (e.g., DJCS_ hedge and HFRI_FW, which were intentional to track the general achievement of the put over lineage industry) rose. In reaction to the perception that wangle property truly offered out operation, institutional m iodiney flowed into border bloods during the late 1990s and 2000s, and the size of the industry grew rapidly. represent 2 charts the growth in the number of funds and supplyity AUM (assets below management) in the hedge fund industry since 1997. With this growth in assets and managers, oral sexs began to surface about the map of hedge funds in a portfolio and whether on that point we re other ways to capture those returns without universe exposed to some of the negatives of hedge fund investing.Alternatives to hedge fundsAlthough galore(postnominal) investors were attracted to the possibility of obtaining high returns and/or low covariance with other investments in their portfolio, umteen still set up hedge funds themselves to be unappealing. Among the reasons for their distaste were a) illiquidity, b) token(prenominal) investment requirements, c) high fees, d) the difficulty of selecting the right hedge fund manager, e) the unfitness to gain access to high quality funds, and f) the lack of established benchmarks in the industry. Most hedge funds only allowed redemptions on certain dates often at the end of each quarter. Additionally galore(postnominal) a(prenominal) funds had an sign lockup that is, investors could not redeem from the fund for a set period subsequently investing the period was often adept year though some funds had no lockup and oth ers had locked up investors for as persistent as five years.Most funds also had a nominal investment size of at least $1 million. In addition, more investors lay down the fees charged by hedge funds, which often amounted to 2% of assets under management (some funds however charged the full cost of their operations to their funds, amounting to more than 2% management fees) plus an additional 20% of moolah generated by the fund, to be redundancyive and hoped to obtain similar benefits at a lower cost. Some investors also found the idea of selecting a portfolio from the many thousands of available hedge funds to be an intimidating task, especially given the lack of transparency (both as to investment process and holdings) that was common among hedge fund managers. And of course even ifan investor could identify a set of funds that made up an attractive portfolio, the managers of those funds readiness not convey an investment at that time or from that investor. ultimately, in contrast to the mutual fund industry, there was a lack of established benchmarks for hedge funds, qualification it difficult to assess skill versus luck and idiosyncratic versus taxonomic returns. While hedge fund indices existed, these were just peer groups, not true benchmarks, and were colorful by a number of things, including style drift and survivorship bias. In response to these criticisms, alternative products were soon introduced into the marketplace.2AQRs DELTA Strategy212-038 breeds of outsmart bloodlines (FOFs) hotshot democratic alternative to direct hedge fund investing was the funds of hedge funds (FOFs) structure. FOFs aimed to take investors money and apportion it among a select group of hedge funds sometimes among a small number (even in the iodin digits in some cases), and sometimes among hundreds of funds.onerous= burdensome/ heavyThis speak to solved a number of the issues facing hedge fund investors, especially those with modest capital. FOFs had less o nerous liquidity rules than individual hedge funds, and FOFs were less likely to encounter liquidity problems than individual funds since they could obtain liquidity from a number of underlying funds. Still, FOFs were ultimately subject to the underlying liquidity (both with respect to liquidity terms and underlying holdings) of the funds they were investing in. In addition, a single nominal investment bought a portfolio of many funds, and an experienced and hopefully expert financial professional, or team of much(prenominal) professionals, selected the funds, and chose allocations among them that (presumably) produced a well-optimized portfolio. Finally, FOF managersclaimed that their experience and connections provided access to hard-to-enter funds. and then FOFs presented an appealing package, and indeed pixilated to half of all money invested in hedge funds came by FOFs. However, many investors were put off by FOF fees, which historically included an additional layer of fe es often as high as half the level of hedge fund fees themselves (thus making total fees paid about 1.5 times higher than for direct investing).Multi-strategy lines some other get along to obtaining an alternative-investment portfolio while nullifying some of the challenges of one-strategy-at-a-time creation was to invest in multi-strategy hedge funds. Such offerings were often made by large hedge fund firms that offered a transition of individual strategies. Investors might have the option to invest in a multi-strategy fund that divvy upd assets crosswise the several(predicate) silos within the firm. bingle major value of multi-strategy funds over FOFs was fees multi-strategy funds typically did not charge an additional fee layer over and above the hedge fund fee (as FOFs did). Further, multi-strategy funds only charged act fees when the total investment was in the money whereas, in the case of FOFs and direct single strategy investments, an investor could be subject to a ccomplishment fees even if the net, aggregate performance wasnt positive.A second potential advantage of multi-strategy funds was in portfolio construction. Not only was the allocation among strategies performed by professionals, those professionals likely had a high level of insight and visibility into the opportunities available to the individual silo managers. Multi-strategy funds broadly speaking offered as good or better liquidity than individual-strategy funds, and of course there was no trouble gaining access to the underlying managers. Multi-strategy funds appeared to offer dependable diversification, although in the famous case of the hedge fund Amaranth, investors thought they were investing in a diversified portfolio of strategies. However, extreme losses in one of the portfolios silos led to the loss of approximately 75% of total portfolio value. accordingly many investors mat they were not truly diversified if they had a large allocation to a multi-strategy fund, bu t this could be potentially mitigated done the right amount of transparency into the positions andrisks of the portfolio, or, of course, through diversification among several different multi-strategy funds, thereby minimizing single firm risk.silos= opslagplaatsen3212-038AQRs DELTA Strategy i potential concern with multi-strategy funds from the investors point of view was the question of portfolio manager quality. Although it was possible that a single firm could gather under one roof the very best managers in a variety of specialties, some investors found this implausible. besiege fund replicationStarting in 2006, a number of investment management firms also introduced hedge fund replication products. These strategies, implemented using liquid instruments, purported to give investors a top-down exposure to the broad risk exposures of the hedge fund industry. These products could be viewed as an effort to provide hedge fund beta, or the taxonomical part of hedge fund performance. The rationale for these products originated from studies of hedge fund returns that highlighted the idea that the line between alpha and beta, was potentially fluid. The alternative systematic exposures of hedge funds could be viewed as a kind of exotic beta. If hedge fund returns could be approximated with dynamically traded portfolios of liquid assets, then investors attracted to hedge fund returns, but potentially looking for a liquid or low-fee alternative to unquestionable hedge funds could invest in a hedge fund replication product that attempted to mimic hedge fund returns using liquid assets.These top-down approaches aimed to use statistical methods to create a portfolio of liquid assets that had similar performance to hedge funds as a class. One top-down approach was to use linear regressions, or optimizations, to build a portfolio that had high correlational statisticss to historical hedge fund returns. An example of thisapproach consisted of tierce steps. First one wou ld obtain a presbyopic-run time serial publication of returns on a diversified portfolio of hedge funds (e.g., the HFRI monthly hedge fund indices were commonly used). Then one would obtain returns on a large number of liquid investments-these could be indexes of stocks (e.g., S&P 500, MSCI EAFE, MSCI Emerging, Russell 2000, etc.), bonds (e.g., US 10-year government bonds), currencies (e.g., EUR-USD Spot Exchange Rate), etc. () Finally, one would use a standard statistical optimizer, or linear regression, to find the portfolio of liquid investments (either long or short and at weights implied by the statistical analysis) that most well-nigh replicated the statistical characteristics of the hedge fund portfolio. Exhibit 3 presents the monthly returns from a set of indices that were commonly used for hedge fund replication purposes.1 Specifically, the goal was to create a portfolio that historically moved as close to one for one with the hedge fund portfolio, so that it had high cor relation with the hedge fund portfolio, and yet also conditioned other statistical moments, such as volatility, skewness, and kurtosis. Historically, and ideally on a antecedent-looking basis as well, this portfolio would fulfill a role in the diversified portfolio similar to the role that hedge funds would play. Exhibit 4 p big moneys the recent return performance of a few commonly used hedge fund indices (e.g., DJCS_ skirt, HFRI_FW, and HFRX_Global), which gibe composite indices of individual hedge funds and were designed to track the overall return performance of the industry 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 performance of cardinal popular hedge fund replication index products, produced by Merrill Lynch, Goldman Sachs, JP Morgan, and trust Suisse. Exhibit 6 presents the return performance of the overall hedge fund indices alongside the performance of these hedge fund replication products.1 This is an quote of the data. The full data series is in the Spreadsheet Supplement to the case.4AQRs DELTA Strategy212-038AQRs approachFor years, the principals at AQR had been working on understand the underlying nature of hedge fund returns and exploring the possibility of universe able to capture them in a transparent, liquid and cost effective way. Thus, they were ab initio intrigued by the introduction of these hedge fund replication products, but very soon came to the conclusion that an entirely different approach to delivering exposure to the systematic risk factors of the hedge fund industry was needed. Whereas AQRs competitors focused on the top-down products described above, AQR focused on creating a bottom-up approach that sought to deliver significant risk-adjusted returns instead of only when replicating an index by capturing classical, liquid hedge fund strategies that were uncorrelated with traditional markets, implementin g them at low cost, and then bundling these strategies into a wellconstructed single portfolio focusing on portfolio construction, risk management and trading.Origins of AQRs approachThe idea of direct, simplified implementation of spirit hedge fund strategies was hinted at by the pioneering work into conjugation merchandise of Mark Mitchell and Todd Pulvino. Mitchell and Pulvino were both former academics (at Harvard Business School and the Kellogg School of Management, respectively) who after teamed up with AQR in 2001. A artless union arbitrage strategy, for example, worked as follows after the announcement by Firm A of a trust to acquire Firm B, the union arbitrageur made a procure of the scar Firm B shares while shorting the acquirer Firm As shares (if the acquisition was to be made in cash, the arbitrageur except purchased Firm B shares without shorting Firm A).Typically upon the announcement of the merger, the price of the target shares would not rise all the way to the price that would be reserve if the merger were sure to be completed. When Mitchell and Pulvino studied the merger arbitrage industry, they found that merger arbitrage strategies did deliver substantial risk-adjusted returns. Specifically, the expected returns of putting merger arbitrageinvestments into place was high, and while the risk was higher than one might naturally have expected because mergers tended to break up exactly at times of market stress, and therefore the merger arbitrage strategy had more beta, or market exposure, than might be presumed nevertheless they found that even accounting for this risk, the performance of a nave merger arbitrage strategy that invested in every deal was substantial.Mitchell and Pulvino also looked at the performance of existent merger arbitrage funds. A merger arbitrage fund would be expected to add alpha by correctly identifying which mergers were more or less likely to achieve completion than the market anticipated. So, for examp le, if the market price of a deal was such that the expected return would be aught if the merger was 90% likely to be completed, the merger arbitrageurs job was to try to figure out whether in fact the merger was substantially more than 90% likely to go through, substantially less than 90%, or about 90%, and then invest only in those deals that were substantially more than 90% likely to go through. What Mitchell and Pulvino found was that merger arbitrage funds made money, but that they did not show an dexterity to forecast which mergers would close over and above the markets qualification. That is, the outperformance that merger arbitrageurs were generating was no greater than the outperformance that would be generated by a simple strategy that bought every target and shorted every bidder, particularly net of fees.5212-038AQRs DELTA StrategyThis opened the door to a potential strategy for the replication of merger arbitrage simply participate in every merger arbitrage deal that met a set of basic screens (e.g., size and liquidity). The benefit to investors would be a potentially more diversified portfolio of merger deals than would be obtained from a fund manager who only selected a subset of the deals, and also potentially far lower fees, because there was no need to pay an analystto determine which mergers were more or less likely to succeed. With this as a template, one could easily imagine a whole scroll of potential hedge fund strategies that could be captured in a systematic way (e.g., long value stocks and short growth stocks, standardized arbitrage, take up trades, trend following trades and trades exploiting other wellknown empirical asset pricing anomalies). Since the beforehand(predicate) work into merger arbitrage, AQR had spent years researching these other classical hedge fund strategies that could be captured from the bottomup.Bottom-Up versus Top-DownAQR preferred their bottom-up approach for a variety of reasons. First, they felt that many hedge fund strategies realise returns for bearing a liquidity risk premium, which you could not earn by trading solely in liquid instruments as in the hedge fund replication methods. For example, in order to capture the returns from a convertible bond that traded at a discount to fair value because of a liquidity risk premium, you needed to own the convertible bond, not simply liquid assets that were correlated with the convertible bond. Second, since top-down methods aimed to maximize correlations with recent last(prenominal) hedge fund performance, these approaches were necessarily backwardlooking and based on what hedge funds were doing in the past. By contrast, if you ran the actual strategies, one could respond to market opportunities immediately.Finally and perhaps most importantly, AQR felt that the hedge fund indices upon which most top-down replication strategies were based had a variety of biases (e.g., survivorship bias), had too much exposure to traditional market s (i.e., equity and credit beta) and also tended to reflect the weights of the most popular strategies. Since these popular strategies were crowded with many trades, the expected returns on these strategies going forward were potentially lower. In short, while they shared the noble goals of top-down replication products (i.e., attempting to provide liquid, transparent exposure to hedge fund strategies at a lower fee), AQR felt that the approach had fundamental 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.AQRs DELTA StrategyIn late 2007, AQR decided to focus their years of research on capturing the classical hedge fund strategies in a systematic way from the bottom up by creating our own product that would seek to deliver these strategies in a risk-balanced and efficiently implemented way. AQR viewed their DELTA product as superscript to the newly-introduced replication products that were being marketed as offering hedge fund beta. In fact, AQR staff bristled at comparisons between the existing hedge fund replication products and their DELTA product. To ensure that AQR was taking a broad approach and to avoid being insular, they formed an external advisory committee made up of some very seasoned hedge fund investors to help orient the development of the product. The DELTA name was an acronym that reflected the products characteristics Dynamic, Economically Intuitive, Liquid, Transparent and Alternative. The portfolio was designed to be uncorrelated with the overall stock market, and would be diversified across nine broad strategy classes a Fixed Income Relative rate strategy, a Managed Futures strategy, a Global Macro strategy,insular = bekrompen6AQRs DELTA Strategy212-038an Emerging Markets strategy, a Long/Short equity strategy, a Dedicated Short Bias strategy, an Equity Market Neutral strategy, a Convertible Arbitrage strategy, and an Event Driven strategy. effectAQR decided to go beforehand with the creation of the DELTA strategy in the late summer of 2008. By October 1, 2008, the portfolio was fully invested and had begun to compile a track record. At the time, the staff at AQR had worried that this might be the worst possible time to be launching a product designed to capture classical hedge fund strategies. Nonetheless, the DELTAportfolio performed well in the fourth quarter of 2008 immediately after its launch, an impressive feat given the turbulence in the market. Exhibit 7 charts the monthly performance of the DELTA strategy since inception. Exhibit 8 shows the raw monthly returns of the DELTA strategy, compared to the raw monthly returns of stock market indices (S&P and NASDAQ) and broad hedge fund indices (e.g., DJCS_ shelve and HFRI_FW, which were designed to track the overall performance of the hedge fund industry). Exhibit 8 also presents the beta of the DELTA strategy with respect to these versatile market and hedge fund indices, while Exhibit 9 graphs the accumulative return performance of the DELTA strategy relative to these indices.Marketing DELTAAlthough DELTA was off to a great start, Kabiller felt like it was underperforming its potential. By the summer of 2011, despite its excellent performance, growth in DELTAs AUM had been modest. After giving it a lot of thought, Kabiller identified three primary challenges AQR faced in convincing investors to allocate capital to DELTA. First, many of his institutional clients had grown very comfortable selecting a set of hedge funds and paying them both management and performance fees. Exhibit 10 presents the recent annual returns of some of the largest U.S. hedge funds, many of whom had delivered stellar returns over time. Kabiller was convinced that one of DELTAs major assets was its ability to deliver hedge fund returns with a significantly lower fee structure. But many of his institutional clients had difficulty assessing just how large an advantage this prov ided DELTA. For instance, if a client selected the two percent management fee with no performance fee structure, how much higher could they expect their after-fee returns to be? prone that performance fees were typically only paid on returns in excess of a cash hurdle, was a twenty percent performance fee really that costly to fund investors? Related considerations applied to investors that invested primarily through origins of Hedge entrepots. These investment vehicles typically added a layer of fees on top of the after-fee performance of their hedge fund investments typically a one percent management fee and a ten percent performance fee. Due to DELTAs multi-strategy investment approach, its after-fee performance should perhaps be benchmarked against those of fund-of-funds alternatives. imparting to such investors the fee advantage of DELTA in simple terms for instance, how much better their competitors pre-fee returns needed to be than those of DELTA to offset the fee differe ntial 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 were almost the polar opposite of the fund-of-funds they had modest fees and, because they replicated hedge fund returns using highly liquid indices, they faced little in the way of liquidity risk. Institutional investors interested in low-fee exposure to hedge fund returns found these products attractive, and Kabiller found it challenging to convey the advantages of the DELTA approach. His inclination was to focus on two key limitations of hedge fund replication. First, he felt they relied heavily on the historical relationship between hedge fund returns and major stock and bond market indices. To the extent that the relationship was not stable, 7212-038AQRs DELTA Strategyor to the extent that a large fraction of hedge fund movements could not be captured by an conquer combi nation of these indices, the replication approach would be limited in its ability to truly deliver in real time the actual returns being earned by the average hedge fund investor. Second, even if the strategy could replicate a large fraction of the monthly fluctuations in performance of the average hedge fund, Kabiller felt it was likely that a top-down approach would be limited in replicating the actual edge, or alpha, of the average hedge fund. Even if much of the risks to which hedge funds were exposed could be found 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 final examination challenge Kabiller faced in the marketing of DELTA was its track record. Although it had outpaced the broad HFRI index since its inception in the fall of 2008, the track record was still a fairly limited one. Moreover, since the central appeal of the product was its ability to match average hedge fund returnswith modest fees, the outperformance ironically posed something of a challenge for DELTA. Kabiller felt it would be critical to understand its source before determining 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 worried that without a proper grasp of these issues, many rough sales meetings lay ahead for him and his DELTA team.8AQRs DELTA Strategy212-038Exhibit 1 Cumulative deliver Performance of Hedge Fund Indices versus Stock Market Indices, since 1996.Cumulative harvest-tide Performance of Hedge Fund Indices Versus Stock Market Indices 500450four hundred 350 300 250 200 150 100 50 0 199601 199609 199705 199801 199809 199905 200001 200009 200105 200201 200209 200305 200401 200409 200505 200601 200609 200705 200801 200809 200905 201001 201009 201105 NASDAQ S&P_Index DJCS_Hedge HFRI_FW cu m Bloomberg.9212-038AQRs DELTA StrategyExhibit 2 summate Number of Hedge Funds and Total AUM (Assets Under Management)for the Hedge Fund Industry, since 1997.Growth in Hedge Fund Industry (1997-2010)12,000 $2,500.0010,000Number of Hedge Funds8,000 $1,500.00 6,000 $1,000.00 4,000 $500.00Hedge Fund AUM (in Billions $)$2,000.00Number of Hedge Funds Hedge Fund AUM2,0001997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010$-Source Created by casewriters using data from Hedge Fund Research, www.hedgefundresearch.com, accessed August 2011.10212-038-11-Exhibit 3 Excerpt of Monthly pass bys on Indices Commonly Used for Hedge Fund riposte (1996-2011). The full data series is contained in the Spreadsheet Supplement to the case MSCI EM 7.6% -0.6% 1.1% 5.2% 0.1% 0.9% -6.2% 2.6% 1.4% -1.4% 1.7% 1.0% -2.1% -1.4% 4.3% 0.8% -1.6% -1.9% -0.9%-7.3% -7.4% 9.1% -3.8% 0.0% 7.4% 3.9% 7.0% 6.2% -2.5% 0.5% 15.0% -0.5% 0.5% 10.9% -0.2% 1.0% 4.5% -8.7% -4.3% -8.8% -11.4% -5.4% -7.0% -1.3% - 1.2% -3.5% -2.0% -2.5% -3.7% -1.1% -1.7% -2.0% 0.4% 0.1% 0.2% 0.4% -0.1% 0.0% 0.0% 0.0% 0.1% -2.8% 2.0% 2.4% 2.6% 0.0% 3.0% -0.1% 0.5% 1.6% 2.4% -0.3% 5.4% 2.4% 3.4% 0.2% -0.1% -0.4% 0.0% 0.0% 1.6% 2.7% -0.7% 3.3% 5.7% 2.8% -2.0% 1.3% 2.0% 0.8% 4.0% -0.7% 4.0% 2.4% 7.6% -2.0% 0.8% 0.0% 2.8% -2.1% 4.6% -1.2% 3.7% -1.7% 5.6% 2.8% 0.9% 1.2% 2.2% 2.9% 0.9% 4.1% 0.4% 0.0% -0.7% -0.2% 1.1% 1.7% -0.9% -0.8% 0.6% -1.2% 1.4% 0.0% 1.0% 0.3% 0.0% 1.0% -4.9% 0.9% -4.2% -8.8% 5.7% 0.4% -4.4% 2.1% 0.8% 0.4% 0.4% 1.5% 0.0% -0.5% -0.3% -1.0% -1.4% 3.5% -1.2% 5.3% 3.9% 1.5% 2.6% 0.0% 0.2% -1.7% -0.6% 4.5% -1.4% -1.0% 2.8% 3.0% 1.8% 0.9% 1.0% -0.5% -0.2% -3.6% -1.1% -3.7% -0.3% 3.7% -0.2% 3.4% 0.9% 0.4% 5.1% MSCI EAFE RUSSELL 2000 S&P 500 US TREAS 2YR US TREAS 10YR CURRENCYHFRIHFRI FOFHFRI FW1/31/19961.1%2.7%2.9%2/29/1996 3/29/19962.8% 1.9%-0.6% 1.0%1.2% 1.5%4/30/1996 5/31/19965.3% 3.7%3.1% 1.5%4.0% 3.1%6/28/1996 7/31/1996 8/30/1996-0.7% -2.9% 2.6%0.4% -1.9% 1.5%0.2% -2.1% 2.3%9/30/1996 10/31/1 9962.2% 1.6%1.2% 1.6%2.1% 1.0%11/29/1996 12/31/1996 1.7% 0.8%2.3% 0.7% 2.1% 1.3% 1/31/2011 2/28/20110.4% 1.3%0.1% 0.8%0.4% 1.2%3/31/2011 4/29/20110.5% 1.3%-0.1% 1.2%0.1% 1.5%5/31/2011 6/30/2011 7/29/2011-1.3% -1.3% -0.3%-1.1% -1.3% 0.4%-1.2% -1.2% 0.2%8/31/2011 9/30/2011-4.9% -6.0%-2.6% -2.8%-3.2% -3.9%10/31/2011 11/30/2011 12/30/20114.9% -2.0% -0.9%1.1% -1.0% -0.4%2.7% -1.3% -0.4%1/31/20123.8%1.9%2.6%Source Thomson Reuters Datastream.212-038AQRs DELTA StrategyExhibit 4Cumulative takings Performance of general Hedge Fund Indices, since June 2007.Recent Performance of Hedge Fund Indices cxx 110 100 DJCS_Hedge 90 80 70 60 200706 200708 200710 200712 200802 200804 200806 200808 200810 200812 200902 200904 200906 200908 200910 200912 201002 201004 201006 201008 201010 201012 201102 201104 201106 HFRI_FW HFRX_Global HFRI_FOFSource Bloomberg.12AQRs DELTA Strategy212-038Exhibit 5Cumulative cash in ones chips Performance of Hedge Fund Replication Indices, since June 2007.Recent Performan ce of Hedge Fund Replication Products130 long hundred110100 90 80 70 60 200706 200708 200710 200712 200802 200804 200806 200808 200810 200812 200902 200904 200906 200908 200910 200912 201002 201004 201006 201008 201010 201012 201102 201104 201106 ML GS JPM CSSource Bloomberg.13212-038AQRs DELTA StrategyExhibit 6 Comparison of Cumulative Return Performance of Overall Hedge Fund Indices versus Hedge Fund Replication Indices, since June 2007.Comparison of Recent Performance of Hedge Fund Indices Versus Hedge Fund Replication Products 130 120 110 100 90 80 70 60 200706 200708 200710 200712 200802 200804 200806 200808 200810 200812 200902 200904 200906 200908 200910 200912 201002 201004 201006 201008 201010 201012 201102 201104 201106 DJCS_Hedge HFRI_FW HFRX_Global HFRI_FOF ML GS JPM CSSource Bloomberg.14AQRs DELTA Strategy212-038Exhibit 7Monthly Return Performance of AQR DELTA strategy, Since Inception.AQR DELTA Return Performance5.00%4.00%3.00% 2.00% 1.00% 0.00% -1.00% -2.00% -3.00% -4 .00%Source Company documents.15212-038AQRs DELTA StrategyExhibit 8 Monthly Return Performance (and Beta) of AQR DELTA strategy compared to Market Indices (S&P, NASDAQ) and Hedge Fund Indices (DJCS_Hedge, HFRI_FW), since October 2008.Date 200810 200811 200812 200901 200902 200903 200904 200905 200906 200907 200908 200909 200910 200911 200912 201001 201002 201003 201004 201005 201006 201007 201008 201009 201010 201011 201012 201101 201102 201103 201104 201105 AverageDELTA 1.22% 1.72% 4.05% 2.79% -0.10% 2.32% 3.09% -0.35% 1.78% 1.93% 4.48% 2.70% -0.31% 0.96% 0.55% -0.66% -0.27% 2.23% 2.18% -3.37% 1.39% 1.62% 2.02% 3.33% 2.47% 1.03% 1.93% -0.41% -0.45% 0.92% 2.31% -0.84% 1.32%NASDAQ -17.73% -10.77% 2.70% -6.38% -6.68% 10.94% 12.35% 3.32% 3.42% 7.82% 1.54% 5.64% -3.64% 4.86% 5.81% -5.37% 4.23% 7.14% 2.64% -8.29% -6.55% 6.90%-6.24% 12.04% 5.86% -0.37% 6.19% 1.78% 3.04% -0.04% 3.32% -1.33% 1.19% 0.09 0.25 0.28S&P_Index -16.94% -7.48% 0.78% -8.57% -10.99% 8.54% 9.39% 5.31% 0.02% 7.41% 3.36% 3.57% -1.98% 5.74% 1.78% -3.70% 2.85% 5.88% 1.48% -8.20% -5.39% 6.88% -4.74% 8.76% 3.69% -0.23% 6.53% 2.26% 3.20% -0.10% 2.85% -1.35% 0.64% 0.09 0.28 0.32DJCS_Hedge -6.30% -4.15% -0.03% 1.09% -0.88% 0.65% 1.68% 4.06% 0.43% 2.54% 1.53% 3.04% 0.13% 2.11% 0.88% 0.17% 0.68% 2.22% 1.24% -2.76% -0.84% 1.59% 0.23% 3.43% 1.92% -0.18% 2.90% 0.69% 1.38% 0.12% 1.80% -0.96% 0.64% 0.25HFRI_FW -6.84% -2.67% 0.15% -0.09% -1.21% 1.66% 3.60% 5.15% 0.25% 2.50% 1.30% 2.79% -0.20% 1.52% 1.28% -0.76% 0.66% 2.49% 1.19% -2.89% -0.95% 1.61% -0.13% 3.48% 2.14% 0.19% 2.95% 0.41% 1.23% 0.06% 1.45% -1.18% 0.66% 0.25DELTAs Beta with DJCS_Hedges Beta with HFRI_FWs Beta with Source Company documents.16AQRs DELTA Strategy212-038Exhibit 9 Cumulative Return Performance of AQR DELTA Strategy versus Market Indices (S&P and NASDAQ) and Hedge Fund Indices (DJCS_Hedge and HFRI_FW), since October 2008Cumulative Return Performance of DELTA versus Market and Hedge Fund Indices 180160 140 120 100 80 60 4020 0DELTA NASDAQ S& P_Index DJCS_Hedge HFRI_FWSourceBloomberg and company documents.17212-038-18-Exhibit 10Annual Returns of Largest Hedge Funds (%)Fund Name Winton Futures USD Cls B millenary International Ltd Transtrend DTP intensify Risk (USD) The Genesis Emerging Mkts Invt Com A Aspect Diversified political platform forenoon Offshore Fund Ltd. Permal Macro Holdings Ltd USD A Canyon esteem Realization Cayman Ltd A Permal Fixed Income Holdings NV USD A Absolute of import Fund PCC Diversified Caxton Global Investments Ltd GAM U.S. Institutional Trading K4D-10V Portfolio K4D-15V Portfolio Orbis Optimal (US$) Fund GAM Trading II USD Open Double Black Diamond Ltd (Carlson) GoldenTree highschool Yield Master Fund Ltd Bay Resource Partners Offshore Fund Ltd GAM U.S. Institutional DiversityFirm Name Winton Capital Management Millennium Intl. Management Transtrend BV Genesis Investment Management Aspect Capital Aurora Investment Management Permal Asset Management Canyon Capital Advisors Permal Asset M anagement Financial Risk Management Caxton Associates GAM Sterling Management graham flour Capital Management Graham Capital Management Orbis Investment Management GAM Sterling Management Carlson Capital Goldentree Asset Management GMT Capital Corp GAM Sterling ManagementSize ($Bil) 9.89 8.84 8.38 6.70 5.71 5.56 5.35 5.21 4.51 4.47 4.40 3.57 3.543.54 3.43 3.09 2.98 2.65 2.45 2.432001 7.11 15.26 26.36 4.62 15.79 9.82 14.66 12.69 11.50 9.33 31.41 16.34 6.45 39.31 29.01 14.78 11.94 18.30 29.32 9.562002 18.34 9.61 26.26 -1.77 19.19 1.31 8.03 5.21 10.47 6.36 26.44 10.69 18.76 43.71 12.15 10.55 2.12 6.24 0.03 4.952003 27.75 10.89 8.48 61.98 20.59 13.58 12.56 21.87 17.59 8.07 8.09 14.74 8.46 21.60 10.84 14.49 7.62 31.42 23.24 14.602004 22.63 14.68 12.82 31.53 -7.72 8.15 4.86 13.56 9.37 4.06 9.97 3.55 5.56 -0.43 2.25 3.84 4.70 9.89 27.97 6.142005 9.73 11.31 5.99 37.86 12.01 9.47 10.65 8.35 7.69 7.00 8.03 4.98 -7.52 -16.97 8.60 4.80 5.08 13.35 30.95 10.482006 17.83 16.43 12.04 30.22 12.84 1 0.95 9.48 14.08 10.48 8.94 13.17 8.68 5.02 6.64 4.95 7.44 21.12 13.21 21.65 16.742007 17.97 10.99 22.38 31.68 8.18 13.14 8.90 7.52 8.42 16.33 1.06 9.48 11.62 16.57 6.98 7.93 15.96 4.60 19.84 7.762008 20.99 -3.04 29.38 -49.30 25.42 -21.69 -5.16 -28.36 -18.40 -23.02 12.96 7.57 21.82 35.67 -2.49 5.78 -12.40 -38.60 -20.88 -13.962009 -4.63 16.28 -11.27 90.44 -11.24 21.26 9.83 55.20 27.32 10.51 5.83 8.32 1.41 3.11 9.92 6.55 28.34 69.94 56.60 6.782010 14.46 13.22 14.89 25.06 15.36 7.31 6.38 13.46 10.40 5.36 11.42 7.80 2.46 4.58 -3.93 5.97 9.30 23.61 15.90 -1.142011 6.29 8.39 -8.65 -15.29 4.51 -6.01 -3.27 -4.66 -5.28 -2.06 -2.40-2.32 -4.11 -2.67 -4.19 -2.79Source Morningstar Hedge Fund Database, accessed January 2012.