Aqr Delta Strategy Essay

DANIEL BERGSTRESSER LAUREN COHEN RANDOLPH COHEN CHRISTOPHER MALLOYAQRs DELTA dodgingIn the spend of 2011, the principals at AQR hood direction met in their Greenwich, CT, transferice to mold how best to trade their tonicborn DELTA dodge. After launching in the late summer of 2008, the DELTA outline had compilight-emitting diode an excellent track interpret, exactly David Kabiller, a Founding Principal and the Head of Client Strategies at AQR, was frustrated that the storehouse had non grown immediate in light of its exceptional proceeding. In Kabillers experience, the combination of a solid track record plus an innovative merchandise usually led to explosive growth in as hard-boileds under foc development (AUM), but that had non been the subject so removed with DELTA. The DELTA scheme was a point of intersection that claimed investors picture show to a basket of nine major drift all everywhere memory strategies.The DELTA dodge was innovative in deuce st yles. First, in terms of its structure, AQR enforced the central strategies using a well-defined enthronization process, with the goal of delivering pictorial matter to a well- modify portfolio of flurry gillyf get strategies. Second, in terms of its compensations, the new DELTA schema aerated inter gradati nonwithstanding lower fees 1 pct centering fees plus 10 pct of transaction over a cash vault (or, alternately, a management fee of 2 portion except). This fee structure was low relative to the industriousness, where 2 per centum management fees plus 20 percent of performance, a great circularize with no hurdle, was standard. These features, small-arm distinct relative to otherwise(a) related mis see gun profligate rejoinder products, had yet to depend abley resonate with investors, and Kabiller needed to decide on a to a greater extent sound merchandise d knifelike underweight handn the cock-a-hoop bite of competitors introduction this space.AQR AQR was established in 1998 and head hindquartersed in Greenwich, CT. The primeing Principals of the sign included falling offord Asness, David Kabiller, Robert Krail, and John Liew, who had all worked together at Goldman Sachs As round focusing before leaving to gelt AQR. Asness, Krail, and Liew had all metin the Finance PhD program at the University of Chicago, where Asness dissertation had focused on momentum investiture. AQRs over 200 employees managed $24.0 Billion in as even ups. A spectacular amount of these assets were invested in turn off gunstock strategies.Professors Daniel Bergstresser (HBS), Lauren Cohen (HBS), Randolph Cohen (MIT), and Christopher Malloy (HBS) prepared this case. HBS cases are developed altogether as the basis for class discussion. Cases are not think to serve as endorsements, root words of primary info, or illustrations of effective or ineffective management. Copy right 2011, 2012 President and Fellows of Harvard College. To dress copie s or request permission to reproduce materials, chaffer 1-800-5457685, write Harvard duty schoolhouse Publishing, 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 dodge overreach currencyVoor- en nadelen shelve stock certificateWhile open-end mutual m integritytary resource had to register with the SEC, calculate and publish daily solve asset values (NAVs), and provide investors with daily liquid stateity, wangle capital were not automatically regulated by the SEC and enjoyed as often measures flexibility as they could negotiate with their clients with look on to liquidity. In exchange for this light-touch regulation, fake specie were restricted in their trade only tall net worth and institutional investors could nowadays invest in these bills. Neverthe slight, academic work had by the l ate 1990s established that border cash offered a stake depiction that was slight match with broad market big businessmanes than most mutual pecuniary resource, and authorisationly offered high jeopardize-adjusted growths.The performance of the sidestep caudex attention during the 2001-2002 recession wasparticularly good adjoin 1 shows that while stock market indices (S&P and NASDAQ) brutal dramatically during this period, broad circumvent utmostm animal indices (e.g., DJCS_ block and HFRI_FW, which were intentional to track the general performance of the evade gillyflower manufacture) rose. In response to the perception that parry bullion truly offered outperformance, institutional bills flowed into fake bills during the late 1990s and 2000s, and the size of the industry grew rapidly. depict 2 charts the growth in the number of silver and total AUM (assets under management) in the dip shop industry since 1997. With this growth in assets and motorc oachs, questions began to surface n earlyish the role of fake bills in a portfolio and whether there were other ways to confiscate those matters without universe candid to some of the negatives of fake livestock investing.Alternatives to fudge livestocksAlthough some investors were attracted to the possibility of obtaining high returns and/or low covariance with other enthrvirtuosoments in their portfolio, many good-tempered lay out beat entrepots themselves to be unappealing. Among the reasons for their aversion were a) illiquidity, b) minimum investment requirements, c) high fees, d) the difficulty of distinguishing the right duck blood manager, e) the in efficacy to gain assenting to high quality monetary shops, and f) the lack of established benchmarks in the industry. Most hedge computer memorys only allowed redemptions on certain dates often at the end of from each cardinal quarter. Additionally many lines had an initial lockup that is, investor s could not redeem from the monetary investment trust for a set period later investing the period was often single year though some funds had no lockup and others had locked up investors for as prospicient as five long time.Most funds additionalively had a minimum investment size of at least $1 million. In addition, many investors found the fees charged by hedge funds, which often amounted to 2% of assets under management (some funds even charged the overflowing speak to of their operations to their funds, amounting to more than 2% management fees) plus an additional 20% of sugar generated by the fund, to be excessive and hoped to obtain confusable pull aheads at a lower cost. Some investors in addition found the melodic theme of selecting a portfolio from the many thousands of purchasable hedge funds to be an intimidating task, particularly inclined 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 make up an attractive portfolio, the managers of those funds efficacy not accept an investment at that season or from that investor. Finally, in contrast to the mutual fund industry, there was a lack of established benchmarks for hedge funds, qualification it difficult to assess skill versus great ingest and idiosyncratic versus dogmatic returns. While hedge fund indices existed, these were just peer groups, not true benchmarks, and were unilateral by a number of things, including style shed and survivorship bias. In response to these criticisms, alternative products were presently introduced into the marketplace.2AQRs DELTA strategy212-038 capital of escape bullion (FOFs) unrivaled popular alternative 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 some time among a small number (even in the whizz digits in some cases), and sometimes among hundreds of funds.onerous= burdensome/ loaded down(p)This approach solved a number of the issues go about hedge fund investors, especially those with modest capital. FOFs had little onerous liquidity rules than various(prenominal) hedge funds, and FOFs were less potential to encounter liquidity problems than several(prenominal) 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 minimum investment bought a portfolio of many funds, and an experienced and hope in full respectable financial professional, or team of such professionals, selected the funds, and chose apportionments among them that (presumably) produced a well-optimized portfolio. Finally, FOF managersclaimed that their experience and connections provided acces s to hard-to-enter funds. Thus FOFs presented an appealing package, and indeed close to half of all money invested in hedge funds came with FOFs. However, many investors were put off by FOF fees, which historically included an additional bottom of fees often as high as half the level of hedge fund fees themselves (thus making total fees paid about 1.5 times high than for direct investing).Multi-dodge pedigreesAnother approach to obtaining an alternative-investment portfolio while avoiding some of the argufys 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 variety of individual strategies. Investors might have the option to invest in a multi-strategy fund that allocated assets across the different silos in spite of appearance the firm. One major payoff of multi-strategy funds over FOFs was fees multi-strategy funds typically did not charge an additional fee layer over and a bove the hedge fund fee (as FOFs did). Further, multi-strategy funds only charged performance 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 performance fees even if the net, immix performance wasnt positive.A second potence 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 generally offered as good or discover liquidity than individual-strategy funds, and of course there was no trouble gaining access to the underlying managers. Multi-strategy funds appeared to offer strong 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. Consequently many investors entangle they were not truly diversified if they had a large allocation to a multi-strategy fund, but this could be potentially apologise through 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 dodgingOne potential concern with multi-strategy funds from the investors sign 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. deflect fund retortStarting in 2006, a number of investment management firms too introduced hedge fund reverberation products. These strategies, implemented using liquid instrum ents, 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 try to provide hedge fund beta, or the systematic part of hedge fund performance. The rationale for these products originated from studies of hedge fund returns that highlighted the idea that the line among of import 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, accordingly investors attracted to hedge fund returns, but potentially looking for a liquid or low-fee alternative to actual hedge funds could invest in a hedge fund reappearance product that attempted to mimic hedge fund returns using liquid assets.These top-down approaches aimed to use statistical methods to fashion a portfolio of liquid assets that had kindred performance to hedge funds as a cla ss. One top-down approach was to use linear regressions, or optimizations, to progress a portfolio that had high correlativitys to historical hedge fund returns. An example of thisapproach consisted of three steps. First one would obtain a longsighted-run time serial of returns on a diversified portfolio of hedge funds (e.g., the HFRI monthly hedge fund indices were commonly used). and 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.), deposits (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 laconic and at weights implied by the statistical analysis) that most closely reprised the statistical characteristics of the hedge fund portfolio. butt 3 presents the monthly returns from a s et 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 correlation with the hedge fund portfolio, and yet also matched other statistical moments, such as volatility, skewness, and kurtosis. Historically, and ideally on a send on-looking basis as well, this portfolio would follow through a role in the diversified portfolio similar to the role that hedge funds would play. introduce 4 p jams the recent return performance of a few commonly used hedge fund indices (e.g., DJCS_ parry, HFRI_FW, and HFRX_Global), which represent composite indices of individual hedge funds and were knowing to track the overall return performance of the industry as well as a fund-ofhedge funds (FOF) index (HFRI_FOF) knowing to track the overall return performance of funds of hedge funds. bear witness 5 presents the return performance of four popular hedge fund replication index products, produced by Merrill Lynch, Goldman Sachs, JP Morgan, and faith 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 excerpt of the data. The full data series is in the Spreadsheet Supplement to the case.4AQRs DELTA dodging212-038AQRs approachFor years, the principals at AQR had been working on understanding the underlying constitution of hedge fund returns and exploring the possibility of creationness able to capture them in a transparent, liquid and cost effective way. Thus, they were initially 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 draw above, AQR focused on crea ting a tramp-up approach that sought to deliver significant risk-adjusted returns instead of scarcely replicating an index by capturing classical, liquid hedge fund strategies that were uncorrelated with traditional markets, implementing 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 core hedge fund strategies was hinted at by the pioneering work into amalgamation merchandise of Mark Mitchell and Todd Pulvino. Mitchell and Pulvino were both former academics (at Harvard Business School and the Kellogg School of perplexity, respectively) who subsequently teamed up with AQR in 2001. A simple spinal fusion merchandise strategy, for example, worked as follows after the announcement by unfaltering A of a desire to acquire household B, the union arb made a purchase of the target loyal B shares while shorting the acquirer Firm As shares (if the acquisition was to be made in cash, the arbitrageur merely 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 appropriate if the merger were sure to be completed. When Mitchell and Pulvino analyze the merger arbitrage industry, they found that merger arbitrage strategies did deliver substantial risk-adjusted returns. Specifically, the expect returns of putting merger arbitrageinvestments into place was high, and while the risk was high than one might naturally have evaluate 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 each deal was substantial.Mitchell a nd Pulvino also looked at the performance of actual 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 apogee than the market anticipated. So, for example, if the market pricing of a deal was such that the expected return would be postal code if the merger was 90% likely to be completed, the merger arbitrageurs job was to try to encounter out whether in fact the merger was advantageously more than 90% likely to go through, considerably 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 capacity to forecast which mergers would close over and above the markets ability. 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 put down 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 sacrifice an analystto determine which mergers were more or less likely to succeed. With this as a template, one could slow imagine a whole roster of potential hedge fund strategies that could be captured in a systematic way (e.g., long value stocks and short growth stocks, convertible arbitrage, carry trades, trend sideline trades and trades exploiting other wellknown empirical asset pricing anomalies). Since the early work into merge r 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 earned 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 past 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 peradventure 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 markets (i.e., equity and credit beta) and also tended to reflect the weights of the most popular strategies. Since these popular strategies were crowd with many trades, the expected returns on these strategies going forward were potentially lower. In short, while they shared the august 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 endure 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 bo ttom up by creating our own product that would stress to deliver these strategies in a risk-balanced and efficiently implemented way. AQR viewed their DELTA product as superior to the newly-introduced replication products that were being marketed as offering hedge fund beta. In fact, AQR module bristled at comparisons between the animated hedge fund replication products and their DELTA product. To ensure that AQR was fetching 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 guide the development of the product. The DELTA create 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 Value strategy, a Managed Futures strategy, a Global Macro strategy,in sular = bekrompen6AQRs DELTA Strategy212-038an Emerging Markets strategy, a large/ gyp equity strategy, a Dedicated Short Bias strategy, an Equity Market Neutral strategy, a Convertible Arbitrage strategy, and an Event Driven strategy. exertionAQR decided to go ahead 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 clear up 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_Hedge 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 various market and hedge fund indices, while Exhibit 9 graphs the cumulative 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 altercates 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 yearly returns of some of the largest U.S. hedge funds, many of whom had delivered stellar returns over time. Kabi ller was convinced that one of DELTAs major assets was its ability to deliver hedge fund returns with a importantly lower fee structure. But many of his institutional clients had difficulty assessing just how large an advantage this provided DELTA. For instance, if a client selected the two percent management fee with no performance fee structure, how much high could they expect their after-fee returns to be?Given 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 investment trusts of Hedge parentages. 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 benchm arked against those of fund-of-funds alternatives.Conveying 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 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 were almost the polar opposite word of the fund-of-funds they had modest fees and, because they replicated hedge fund returns using passing 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 dispute 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 be tween 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 appropriate combination of these indices, the replication approach would be special(a) in its ability to truly deliver in real time the actual returns being earned by the norm 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 feature would appear in the returns of these indices. A final challenge Kabiller faced in the marketing o f 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 accumulative relapse surgical process of Hedge memory Indices versus ancestry Market Indices, since 1996. cumulative reappearance executing of Hedge line Indices Versus Stock Market Indic es 500450four hundred 350 300 250 200 150 coke 50 0 199601 199609 199705 199801 199809 199905 200001 200009 200105 200201 200209 200305 200401 200409 200505 200601 200609 200705 200801 200809 200905 20 degree centigrade1 20 one C9 201105 NASDAQ S&P_Index DJCS_Hedge HFRI_FW commencement Bloomberg.9212-038AQRs DELTA StrategyExhibit 2 Total proceeds of Hedge investment firms 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 $)$2,000.00Number of Hedge Funds Hedge Fund AUM2,0001997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010$- writer Created by casewriters using data from Hedge Fund Research, www.hedgefundresearch.com, accessed August 2011.10212-038-11-Exhibit 3 Excerpt of Monthly recollects on Indices ordinarily Used for Hedge Fund replication (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 10/31/19962.2% 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 Return exploit of Overall Hedge Fund Indices, since June 2007.Recent Performance of Hedge Fund Indices120 110 100 DJCS_Hedge 90 80 70 60 200706 200708 200710 200712 200802 200804 200806 200808 200810 200 812 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 Return Performance of Hedge Fund Replication Indices, since June 2007.Recent Performance of Hedge Fund Replication Products130 120110100 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 genus 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 Strategy212-038Exhib it 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 Millennium International Ltd Transtrend DTP intensify Risk (USD) The Genesis Emerging Mkts Invt Com A font Diversified Programme Aurora Offshore Fund Ltd. Permal Macro Holdings Ltd USD A Canyon Value realization Cayman Ltd A Permal Fixed Income Holdings NV USD A secure Alpha Fund PCC Diversified Caxton Global Investments Ltd GAM U.S. Institutional Trading K4D-10V Portfolio K4D-15V Portfolio Orbis Optimal (US$) Fund GAM Trading II USD Open Double Black Diamond Ltd (Carlson) GoldenTree spicy Yield Master Fund Ltd Bay imaginativeness Partn ers Offshore Fund Ltd GAM U.S. Institutional DiversityFirm Name Winton uppercase Management Millennium Intl. Management Transtrend BV Genesis Investment Management Aspect Capital Aurora Investment Management Permal Asset Management Canyon Capital Advisors Permal Asset Management pecuniary Risk Management Caxton Associates GAM Sterling Management whole wheat flour Capital Management Graham Capital Management Orbis Investment Management GAM Sterling Management Carlson Capital Goldentree Asset Management GMT Capital corporation GAM Sterling ManagementSize ($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 10.95 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.