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DANIEL BERGSTRESSER LAUREN COHEN RANDOLPH COHEN CHRISTOPHER MALLOY
AQR’s DELTA Approach
During the summer of 2011, the rules at AQR Capital Administration met inside their Greenwich, COMPUTERTOMOGRAFIE, office to make the decision how far better market all their new DELTA strategy. After launching in the late summer of 2008, the DELTA technique had compiled an excellent track record, but David Kabiller, a Founding Primary and the Mind of Customer Strategies by AQR, was frustrated the fact that fund had not grown faster in light of its exceptional performance.
In Kabiller’s encounter, the mixture of a solid track record plus an innovative product usually led to explosive growth in assets underneath management (AUM), but that had not been the case so far with DELTA. The DELTA strategy was a merchandise that offered investors exposure to a holder of 9 major hedge fund tactics.
The DELTA strategy was innovative in two ways. Initially, in terms of their structure, AQR implemented the underlying tactics using a well-defined investment procedure, with the objective of providing exposure to a well-diversified portfolio of hedge fund tactics. Second, in terms of its fees, the new DELTA strategy recharged relatively reduce fees: 1% management service fees plus 10 % of functionality over a money hurdle (or, alternatively, a management cost of 2 percent only). This fee composition was low relative to the industry, exactly where 2 percent management charges plus 20% of efficiency, often without hurdle, was standard. These features, while distinct relative to other related “hedge fund replication products, got yet to totally resonate with investors, and Kabiller had to decide on a much more effective promoting approach given the large number of competitors entering this space.
AQR
AQR began in 1998 and headquartered in Greenwich, CT. The starting Principals of the firm included Clifford Asness, David Kabiller, Robert Krail, and David Liew, who had all performed together for Goldman Sachs Asset Managing before leaving to start AQR. Asness, Krail, and Liew had most met
in the Financial PhD plan at the University of Chi town, where Asness’ dissertation experienced focused on energy investing. AQR’s over 2 hundred employees maintained $24. 0 Billion in assets. A large number of these possessions were invested in hedge finance strategies.
Teachers Daniel Bergstresser (HBS), Lauren Cohen (HBS), Randolph Cohen (MIT), and Christopher Malloy (HBS) prepared this case. HBS cases are developed solely as the basis for discussion in the classroom. Cases are not intended to function as endorsements, options for primary info, or illustrations of successful or unproductive management. Copyright laws 2011, 2012 Director and Fellows of Harvard College. To order clones or ask for permission to reproduce materials, call 1-800-5457685, write Harvard Business University Publishing, Boston, MA 02163, or go to www.hbsp.harvard.edu/educators. This kind of publication might not be digitized, photocopied, or otherwise reproduced, posted, or transmitted, without the permission of Harvard Business School.
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Hedge money
Voor- en nadelen Hedge Fund:
When open-end shared funds was required to register together with the SEC, compute and post daily net asset ideals (NAVs), and offer investors with daily liquidity, hedge cash were not instantly regulated by the SEC and enjoyed all the flexibility because they could make a deal with their clients with respect to fluid. In exchange just for this light-touch rules, hedge money were limited in their advertising: only wealthy and institutional investors may directly purchase these money. Nevertheless, educational work got by the late 1990s proven that hedge funds provided a risk exposure that was less correlated with wide-ranging market crawls than most mutual cash, and potentially offered excessive risk-adjusted returns.
The overall performance of the hedge fund market during the 2001-2002 recession wasparticularly good; Display 1 demonstrates while currency markets indices (S&P and NASDAQ) fell drastically during this period, wide-ranging hedge fund indices (e. g., DJCS_Hedge and HFRI_FW, which were created to track the entire performance with the hedge account industry) rose. In response to the perception that hedge cash truly provided outperformance, institutional money flowed into hedge funds throughout the late 1990s and 2000s, and the size of the sector grew quickly. Exhibit two charts the expansion in the range of funds and total AUM (assets below management) inside the hedge finance industry since its establishment in 1997. With this growth in assets and managers, questions began to surface area about the role of hedge cash in a portfolio and whether there was other ways to capture those results without being subjected to some of the negatives of hedge fund investment.
Alternatives to hedge money
Although some investors had been attracted to the possibility of obtaining substantial returns and/or low covariance with other purchases of their stock portfolio, many nonetheless found hedge funds themselves to be unappealing. Among the reasons for their distaste were: a) illiquidity, b) minimum investment requirements, c) high fees, d) the difficulty of selecting the right hedge fund job, e) the shortcoming to gain access to good quality funds, and f) the possible lack of established benchmarks in the industry. Many hedge funds only allowed redemptions upon certain dates ” typically at the end of each quarter. Additionally many money had an primary lockup ” that is, shareholders could not redeem from the account for a arranged period after investing; the time was often one year nevertheless some money had zero lockup and more had locked up traders for given that five years.
Most funds also had a minimum expenditure size of for least $1,000,000. In addition , various investors identified the costs charged simply by hedge funds, which often amounted to 2% of property under management (some cash even incurred the full expense of their functions to their cash, amounting to more than 2% management fees) plus one more 20% of profits generated by the fund, to be excessive and expected to obtain related benefits at a lower cost. Some investors also found the idea of selecting a stock portfolio from the many thousands of available hedge funds to get an daunting task, especially given deficiency of transparency (both as to expenditure process and holdings) that was common among hedge fund managers. And of course actually ifan buyer could recognize a set of funds that made-up an attractive collection, the managers of those cash might not agree to an investment during those times or from that investor. Finally, in contrast to the mutual pay for industry, there is a lack of set up benchmarks intended for hedge cash, making it difficult to assess skill versus good fortune and idiosyncratic versus systematic returns. When hedge finance indices been with us, these were simply peer groupings, not true benchmarks, and were biased with a number of things, including design drift and survivorship bias. In response to criticisms, substitute products had been soon launched into the market.
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Funds of Hedge Cash (FOFs)
One popular alternative to immediate hedge finance investing was the funds of hedge money (FOFs) composition. FOFs was executed to take investors’ money and allocate it among a pick group of hedge funds ” sometimes amongst a small amount (even in the single digits in some cases), and sometimes among hundreds of cash.
onerous= burdensome/ heavy
This method solved many of the issues facing hedge account investors, especially those with simple capital. FOFs had significantly less onerous liquidity rules than individual hedge funds, and FOFs had been less likely to come across liquidity complications than specific funds simply because they could obtain liquidity via a number of root funds. Continue to, FOFs were ultimately susceptible to the root liquidity (both with respect to fluid terms and underlying holdings) of the cash they were purchasing. In addition , a single minimum purchase bought a collection of many cash, and a skilled and ideally expert economical professional, or perhaps team of such experts, selected the funds, and chose allocations among them that (presumably) produced a well-optimized portfolio. Finally, FOF managersclaimed that all their experience and connections presented access to hard-to-enter funds. Therefore FOFs presented an appealing deal, and indeed close to half of all money invested in hedge money came through FOFs. However , many investors were put off by FOF charges, which in the past included an extra layer of fees often as high because half the degree of hedge account fees themselves (thus making total service fees paid about 1 . five times higher than pertaining to direct investing).
Multi-strategy Money
One other approach to obtaining an alternative-investment portfolio while avoiding a number of the challenges of one-strategy-at-a-time creation was to purchase multi-strategy hedge funds. Such offerings were often made by large hedge fund firms that presented a variety of individual strategies. Shareholders might have the possibility to invest in a multi-strategy fund that allocated assets through the different établissement within the organization. One major advantage of multi-strategy funds more than FOFs was fees: multi-strategy funds commonly did not charge an additional charge layer more than the hedge fund charge (as FOFs did). Even more, multi-strategy funds only billed performance service fees when the total investment was in the money; whereas, in the case of FOFs and immediate single strategy investments, an investor could be subject to performance costs even if the net, aggregate performance wasn’t great.
A second potential advantage of multi-strategy funds was at portfolio structure. Not only was your allocation among strategies performed by pros, those pros likely a new high level of insight and visibility in the opportunities available to the individual silo managers. Multi-strategy funds generally offered nearly as good or better liquidity than individual-strategy funds, and of course there were no trouble getting “access towards the underlying managers. Multi-strategy cash appeared to provide strong variation, although inside the famous case of the hedge fund Amaranth, investors believed they were purchasing a diversified portfolio of approaches. However , intense losses with the portfolio’s établissement led to losing approximately 75% of total portfolio worth. Consequently many investors felt they were not truly diversified if they had a large allocation into a multi-strategy account, but this could be potentially mitigated through the correct quantity of openness into the positions andrisks with the portfolio, or, of course , through diversification between several different multi-strategy funds, therefore minimizing sole firm risk.
silos= opslagplaatsen
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One potential concern with multi-strategy funds from the investor’s point of view was the query of collection manager quality. Although it was possible that just one firm can gather under one roof structure the very best managers in a variety of specialties, some traders found this implausible.
Hedge fund duplication
Beginning in 2006, several investment administration firms likewise introduced “hedge fund replication products. These types of strategies, applied using water instruments, purported to give shareholders a ‘top-down’ exposure to the broad risk exposures in the hedge account industry. These items could be considered as an effort to provide ‘hedge pay for beta, ‘ or the organized part of hedge fund functionality. The rationale for the products descends from studies of hedge account returns that highlighted the idea that the line among ‘alpha’ and ‘beta, ‘ was potentially fluid. The choice systematic exposures of hedge funds could be viewed as a form of “exotic beta. In the event that hedge fund returns could possibly be approximated with dynamically traded portfolios of liquid assets, then simply investors attracted to hedge fund returns, but potentially looking for a liquid or perhaps low-fee option to actual hedge funds may invest in a ‘hedge fund replication’ product that attempted to simulate hedge fund returns using liquid assets.
These top-down techniques aimed to use statistical ways to create a profile of funding available that got similar overall performance to hedge funds being a class. One particular top-down procedure was to make use of linear regressions, or optimizations, to build a portfolio that had substantial correlations to historical hedge fund earnings. An example of thisapproach consisted of three steps. First one could obtain a long-run time group of returns on the diversified stock portfolio of hedge funds (e. g., the HFRI regular monthly hedge account indices had been commonly used). Then one would obtain earnings on a large numbers of liquid investments-these could be indices of stocks and options (e. g., S&P 500, MSCI EAFE, MSCI Emerging, Russell 2000, etc . ), bonds (e. g., ALL OF US 10-year federal government bonds), values (e. g., EUR-USD Location Exchange Rate), etc . () Finally, one could use a common statistical optimizer, or geradlinig regression, to find the portfolio of liquid purchases (either long or short and at weight loads implied by the statistical analysis) that most tightly replicated the statistical attributes of the hedge fund stock portfolio. Exhibit three or more presents the monthly comes back from a set of indices that had been commonly used intended for hedge pay for replication functions.
1 Particularly, the aim was to make a portfolio that historically transferred as near to one for starters with the hedge fund stock portfolio, so that it got high correlation with the hedge fund portfolio, and yet likewise matched additional “statistical moments, such as volatility, skewness, and kurtosis. Historically, and ideally on the forward-looking basis as well, this portfolio could fulfill a role in the varied portfolio just like the role that hedge money would enjoy. Exhibit 5 plots the recent returning performance of some commonly used hedge fund directories (e. g., DJCS_Hedge, HFRI_FW, and HFRX_Global), which stand for composite indices of specific hedge money and had been designed to observe the overall go back performance in the industry; and a fund-ofhedge funds (FOF) index (HFRI_FOF) built to track the entire return performance of cash of hedge funds. Display 5 reveals the come back performance of four popular hedge fund replication index products, produced by Merrill Lynch, Goldman Sachs, JP Morgan, and Credit Suisse. Exhibit 6th presents the return overall performance of the overall hedge pay for indices alongside the functionality of these hedge fund duplication products.
one particular This is an excerpt from the data. The total data series is in the Schedule Supplement for the case.
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AQR’s approach
For years, the principals at AQR was working on comprehending the underlying characteristics of hedge fund results and exploring the possibility of being able to capture them in a transparent, liquefied and economical way. As a result, they were primarily intrigued by the introduction of such hedge pay for replication items, but soon came to the conclusion that the entirely different approach to providing exposure to the systematic risk factors in the hedge finance industry was needed. Although AQR’s competition focused on the ‘top-down’ items described above, AQR dedicated to creating a ‘bottom-up’ approach that sought to provide significant risk-adjusted returns instead of simply replicating an index by: capturing traditional, liquid hedge fund tactics that were uncorrelated with traditional markets, putting into action them by low cost, then bundling these strategies in a wellconstructed single portfolio focusing on portfolio structure, risk management and trading.
Roots of AQR’s approach
The idea of direct, simplified execution of core hedge finance strategies was hinted in by the groundbreaking work into merger arbitrage of Mark Mitchell and Todd Pulvino. Mitchell and Pulvino had been both past academics (at Harvard Business School and the Kellogg Institution of Management, respectively) whom subsequently collaborated with AQR in 2001. A simple combination arbitrage strategy, for example , worked as follows: following the announcement by simply Firm A of a wish to acquire Organization B, the merger arbitrageur made a purchase with the target Firm B shares while shorting the acquirer Firm A’s shares (if the purchase was to come in in money, the arbitrageur merely acquired Firm M shares with out shorting Company A).
Commonly upon the announcement from the merger, the buying price of the target shares would not rise all the way to the price that would be suitable if the combination were certain to be accomplished. When Mitchell and Pulvino studied the merger accommodement industry, they will found that merger accommodement strategies performed deliver substantial risk-adjusted comes back. Specifically, the expected returns of adding merger arbitrageinvestments into place was high, and while raise the risk was greater than one may possibly naturally possess expected ” because mergers tended to be able to up precisely at times of market pressure, and therefore the combination arbitrage technique had even more beta, or perhaps market coverage, than might be presumed ” nevertheless that they found that even accounting for this risk, the functionality of a naïve merger accommodement strategy that invested in just about every deal was substantial.
Mitchell and Pulvino also viewed the performance of genuine merger arbitrage funds. A merger arbitrage fund would be expected to add alpha by correctly determining which mergers were basically likely to achieve completion compared to the market awaited. So , for instance , if the industry pricing of a deal was such that the expected go back would be zero if the combination was 90% likely to be finished, the merger arbitrageur’s work was to make an effort to figure out if in fact the merger was substantially much more than 90% more likely to go through, substantially less than 90%, or about 90%, then invest just in all those deals that were substantially more than 90% prone to go through. What Mitchell and Pulvino found was that combination arbitrage money made funds, but that they can did not present an capability to forecast which mergers would close over and above the market’s ability. That may be, the outperformance that merger arbitrageurs were generating was no greater than the outperformance that might be generated with a simple strategy that bought every focus on and shorted every prospective buyer, particularly net of costs.
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This exposed the door to a potential method for the duplication of combination arbitrage: merely participate in every merger accommodement deal that met a couple of basic displays (e. g., size and liquidity). The advantage to investors would be a probably more varied portfolio of merger offers than will be obtained from a fund administrator who simply selected a subset with the deals, and in addition potentially less fees, because there was no need to pay an analystto determine which usually mergers were more or less more likely to succeed. With this being a template, you could easily envision a whole roster of potential hedge account strategies that could be captured in a systematic way (e. g., long worth stocks and short development stocks, transformable arbitrage, carry trades, tendency following trades and deals exploiting additional wellknown empirical asset costs anomalies). Because the early function into combination arbitrage, AQR had put in years exploring these other time-honored hedge account strategies that could be captured in the bottomup.
Bottom-Up versus Top-Down
AQR preferred their very own bottom-up approach for a number of reasons. First, they believed that many hedge fund strategies earned earnings for bearing a fluid risk high grade, which you could not really earn by simply trading solely in liquid instruments as in the hedge fund replication methods. For example , in order to capture the comes back from a convertible connect that exchanged at a discount to fair value because of a fluid risk superior, you had to own the convertible bond, not simply liquid assets that had been correlated with the convertible connection. Second, as top-down strategies aimed to increase correlations with recent earlier hedge account performance, these approaches had been necessarily backwardlooking and based on what hedge funds had been doing in past times. By contrast, should you ran you see, the strategies, you could respond to market opportunities instantly.
Finally and possibly most importantly, AQR felt which the hedge account indices upon which most top-down replication strategies were based a new variety of biases (e. g., survivorship bias), had excessive exposure to traditional markets (i. e., collateral and credit beta) and in addition tended to reflect the weights of the most well-liked strategies. Since these popular strategies were crowded with many trades, the expected comes back on these types of strategies in the years ahead were probably lower. To put it briefly, while that they shared the noble goals of top-down replication items (i. e., attempting to provide liquid, transparent exposure to hedge fund strategies at a lesser fee), AQR felt which the approach had fundamental imperfections or, while Cliff Asness put it in a speech in October 3 years ago on hedge fund replication, “Not Everything That Can Be Done Should Be Done.
AQR’s DELTA Strategy
In late 2007, AQR decided to target their many years of research in capturing the classical hedge fund tactics in a systematic way above the bottom up by simply “creating our very own product that could seek to deliver these approaches in a risk-balanced and efficiently implemented way. AQR viewed their very own “DELTA item as better than the newly-introduced replication goods that were getting marketed since offering ‘hedge fund beta. ‘ Actually AQR staff bristled at comparisons between the existing hedge fund duplication products and their very own DELTA merchandise. To ensure that AQR was having a broad way and to steer clear of being insular, they shaped an external exhortatory committee made up of some very seasoned hedge pay for investors to assist guide the development of the product. The DELTA brand was an acronym that reflected the product’s qualities: ‘Dynamic, Financially Intuitive, Liquid, Transparent and Alternative. ‘ The profile was designed to always be uncorrelated with all the overall stock exchange, and will be diversified throughout nine broad strategy classes: a Fixed Salary Relative Worth strategy, a Managed Futures approach, a Global Macro strategy
insular = bekrompen
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an Growing Markets strategy, a Long/Short equity approach, a Dedicated Short Bias strategy, an Collateral Market Simple strategy, a Convertible Arbitrage strategy, and an Event Powered strategy.
Functionality
AQR decided to go forward with the creation of the DELTA strategy in the late summer of 2008. Simply by October one particular, 2008, the portfolio was fully spent and had started to make a background. At the time, employees at AQR had bothered that this could be “the most severe possible a chance to be introducing a product designed to capture classical hedge pay for strategies. Nonetheless, the DELTAportfolio performed well in the fourth quarter of 2008 right after its launch, an impressive feat given the turbulence available in the market. Exhibit 7 charts the monthly functionality of the DELTA strategy seeing that inception. Exhibit 8 reveals the organic monthly results of the DELTA strategy, in comparison 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, that were designed to monitor the overall performance of the hedge fund industry). Exhibit almost eight also reveals the “beta of the DELTA strategy with respect to these numerous market and hedge finance indices, although Exhibit 9 graphs the cumulative go back performance of the DELTA approach relative to these indices.
Marketing DELTA
Although DELTA was away to a wonderful start, Kabiller felt like it absolutely was underperforming it is potential. By summer of 2011, inspite of its good performance, progress in DELTA’s AUM was modest. Following giving it a wide range of thought, Kabiller identified three primary issues AQR faced in convincing investors to allocate capital to DELTA. First, many of his institutional clients acquired grown very comfortable selecting a set of hedge funds and paying both of them management and satisfaction fees. Exhibit 10 gives the recent annual returns of some of the largest U. S. hedge funds, most of whom got delivered good returns over time. Kabiller was convinced that a person of DELTA’s major possessions was the ability to deliver hedge account returns having a significantly reduced fee composition. But many of his institutional clients experienced difficulty assessing just how significant an advantage this kind of provided DELTA. For instance, when a client picked the two percent management charge with no functionality fee structure, how much larger could they will expect their very own after-fee results to be?
Provided that performance costs were commonly only paid out on earnings in excess of a cash challenge, was a 20% performance cost really that costly to finance investors? Related considerations placed on investors that invested generally through Funds of Hedge Funds. These investment cars typically added a part of fees on top of the after-fee functionality of their hedge fund opportunities ” commonly a one percent management cost and a ten percent performance fee. Due to DELTA’s multi-strategy investment strategy, its after-fee performance will need to perhaps become benchmarked against those of fund-of-funds alternatives.
Conveying to this kind of investors the fee good thing about DELTA in simple terms ” for instance, how much better their competitors’ pre-fee results needed to be than those of DELTA to balance the cost differential ” would go a long way in persuasive them that DELTA was your superior strategy. A second obstacle in marketing DELTA was the emergence with the so-called hedge fund duplication strategies. These strategies were almost the polar contrary of the fund-of-funds ” they’d modest fees and, because they replicated hedge finance returns employing highly liquid indices, they faced small in the way of fluid risk. Institutional investors interested in low-fee contact with hedge pay for returns discovered these products eye-catching, and Kabiller found that challenging to convey the advantages of the DELTA way. His disposition was to concentrate on two key limitations of hedge pay for replication. First, he believed they counted heavily within the historical romantic relationship between hedge fund results and main stock and bond marketplace indices. Towards the extent that the relationship had not been stable, several
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or the magnitude that a significant fraction of hedge pay for movements could not be captured by a suitable combination of these kinds of indices, the replication strategy would be limited in its capacity to truly deliver in real time some of the returns staying earned by the average hedge fund trader. Second, set up strategy can replicate a large fraction of the monthly fluctuations in performance of the average hedge fund, Kabiller felt it was likely a “top-down way would be limited in replicating the actual border, or “alpha, in the average hedge fund. Whether or not much of the hazards to which hedge funds had been exposed could possibly be found in wide-ranging stock and bond industry indices, it was unlikely that any of the educational or fluidity edges that they possessed would seem in the earnings of these directories. A final problem Kabiller faced in the advertising of DELTA was it is track record. Even though it had outdone the wide HFRI index since its inception in the land of 08, the track record was still a reasonably limited 1. Moreover, because the central benefit of the product was its capability to match common hedge finance returnswith humble fees, the outperformance ironically posed some thing of a obstacle for DELTA. Kabiller believed it would be important to understand their source before determining if it was a great aberration or whether they possessed a lasting edge in accordance with the index of hedge funds. While Kabiller appeared out past his infinity pool and into the calm waters from the Long Island Sound, he worried that with out a proper knowledge of these issues, many rough sales conferences lay ahead for him and his DELTA team.
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Display 1 Cumulative Return Functionality of Hedge Fund Indices versus Wall street game Indices, for more than 10 years.
Cumulative Go back Performance of Hedge Pay for Indices Vs Stock Market Directories 500
435.00
400 350 300 250 2 hundred 150 90 50 zero 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
Source: Bloomberg.
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Exhibit a couple of Total Number of Hedge Cash and Total AUM (Assets Under Management)
for the Hedge Fund Sector, since 1997.
Development in Hedge Fund Market (1997-2010)
12, 000 $2, five-hundred. 00
twelve, 000
Number of Hedge Funds
almost eight, 000 $1, 500. 00 6, 000 $1, 1000. 00 5, 000 $500. 00
Hedge Fund AUM (in Great $)
$2, 000. 00
Number of Hedge Funds Hedge Fund AUM
2, 500
1997 1998 1999 2150 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010
$-
Supply: Created by simply casewriters employing data by Hedge Pay for Research, www.hedgefundresearch.com, accessed August 2011.
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-11-
Show 3 Research of Regular monthly Returns in Indices Frequently used for Hedge Fund Duplication (1996-2011). The complete data series is included in the Spreadsheet Supplement to the circumstance MSCI NA 7. 6% -0. 6% 1 . 1% 5. 2% 0. 1% 0. 9% -6. 2% 2 . 6% 1 . 4% -1. 4% 1 . seven percent 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. five per cent 0. 5% 15. 0% -0. 5% 0. five per cent 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. five per cent -2. 0% -2. five per cent -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 . seven percent -0. seven percent 3. 3% 5. 7% 2 . 8% -2. 0% 1 . 3% 2 . 0% 0. 8% 4. 0% -0. 7% ¦ 5. 0% installment payments on your 4% ¦ 7. 6% -2. 0% ¦ 0. 8% zero. 0% ¦ 2 . 8% -2. 1% ¦ 4. 6% -1. 2% three or more. 7% -1. 7% 5. 6% 2 . 8% 0. 9% 1 ) 2% installment payments on your 2% 2 . 9% 0. 9% some. 1% zero. 4% 0. 0% ¦ -0. seven percent -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. seven percent 0. 4% -4. 4% 2 . 1% 0. 8% 0. 4% 0. 4% 1 . five per cent 0. 0% -0. five per cent -0. 3% -1. 0% -1. 4% 3. 5% -1. 2% 5. 3% 3. 9% 1 . five per cent 2 . 6% 0. 0% 0. 2% -1. seven percent -0. 6% 4. 5% -1. 4% -1. 0% 2 . 8% 3. 0% 1 . 8% 0. 9% 1 . 0% -0. five per cent -0. 2% -3. 6% -1. 1% -3. 7% -0. 3% 3. seven percent -0. 2% 3. 4% 0. 9% 0. 4% 5. 1% MSCI EAFE RUSSELL 2000 S&P US TREAS 2YR ALL OF US TREAS 10YR CURRENCY
HFRI
HFRI FOF
HFRI FW
1/31/1996
1 . 1%
installment payments on your 7%
2 . 9%
2/29/1996 3/29/1996
2 . 8% 1 ) 9%
-0. 6% 1 ) 0%
1 ) 2% 1 . 5%
4/30/1996 5/31/1996
five. 3% several. 7%
three or more. 1% 1 ) 5%
5. 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 10/31/1996
2 . 2% 1 . 6%
1 . 2% 1 . 6%
2 . 1% 1 . 0%
11/29/1996 12/31/1996 ¦
1 . 7% 0. 8%
installment payments on your 3% 0. 7% ¦
2 . 1% 1 . 3% ¦
1/31/2011 2/28/2011
0. 4% 1 . 3%
0. 1% 0. 8%
0. 4% 1 ) 2%
3/31/2011 4/29/2011
zero. 5% 1 ) 3%
-0. 1% 1 ) 2%
zero. 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 12/30/2011
5. 9% -2. 0% -0. 9%
1 ) 1% -1. 0% -0. 4%
2 . 7% -1. 3% -0. 4%
1/31/2012
3. 8%
1 . 9%
2 . 6%
Source: Thomson Reuters Datastream.
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Exhibit 4
Total Return Overall performance of General Hedge Finance Indices, since June 3 years ago.
Recent Performance of Hedge Fund Directories
120 110 95 DJCS_Hedge 85 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_FOF
Source: Bloomberg.
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Show 5
Total Return Efficiency of Hedge Fund Replication Indices, seeing that June 2007.
Recent Efficiency of Hedge Fund Duplication Products
130 120
110
100 80 80 seventy 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 CS
Source: Bloomberg.
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Exhibit 6 Comparison of Cumulative Return Efficiency of Overall Hedge Pay for Indices versus Hedge Fund Replication Indices, since Summer 2007.
Comparison of Recent Performance of Hedge Fund Directories Versus Hedge Fund Replication Products 130 120 one hundred ten 100 80 80 seventy 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 CS
Source: Bloomberg.
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212-038
Exhibit six
Monthly Come back Performance of AQR DELTA strategy, Seeing that Inception.
AQR DELTA Returning Performance
5. 00%
4. 00%
three or more. 00% installment payments on your 00% 1 ) 00% zero. 00% -1. 00% -2. 00% -3. 00% -4. 00%
Source: Business documents.
15
212-038
AQR’s DELTA Strategy
Display 8 Month-to-month Return Overall performance (and Beta) of AQR DELTA technique compared to Market Indices (S&P, NASDAQ) and Hedge Finance Indices (DJCS_Hedge, HFRI_FW), seeing that 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 Normal
DELTA 1 . 22% 1 . 72% four. 05% installment payments on your 79% -0. 10% installment payments on your 32% three or more. 09% -0. 35% 1 . 78% 1 ) 93% 4. 48% 2 . 70% -0. 31% zero. 96% 0. 55% -0. 66% -0. 27% 2 . 23% 2 . 18% -3. 37% 1 ) 39% 1 ) 62% installment payments on your 02% three or more. 33% 2 . 47% 1 . 03% 1 . 93% -0. 41% -0. 45% zero. 92% 2 . 31% -0. 84% 1 ) 32%
NASDAQ -17. 73% -10. 77% 2 . 70 percent -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% six. 19% 1 . 78% a few. 04% -0. 04% 3. 32% -1. 33% 1 . 19% zero. 09 0. 25 0. 28
S&P_Index -16. 94% -7. 48% 0. 78% -8. 59% -10. 00% 8. 54% 9. 39% 5. 31% 0. 02% 7. 41% 3. 36% 3. 57% -1. 98% 5. 74% 1 . 78% -3. 70 percent 2 . 85% 5. 88% 1 . 48% -8. twenty percent -5. 39% 6. 88% -4. 74% 8. 76% 3. 69% -0. 23% 6. 53% 2 . 26% 3. twenty percent -0. 10% 2 . 85% -1. 35% 0. 64% 0. 2009 0. twenty eight 0. 32
DJCS_Hedge -6. 30% -4. 15% -0. 03% 1 . 09% -0. 88% zero. 65% 1 ) 68% 4. 06% 0. 43% installment payments on your 54% 1 . 53% three or more. 04% 0. 13% 2 . 11% 0. 88% zero. 17% 0. 68% installment payments on your 22% 1 . 24% -2. 76% -0. 84% 1 ) 59% zero. 23% a few. 43% 1 . 92% -0. 18% 2 . 90% 0. 69% 1 ) 38% zero. 12% 1 . 80% -0. 96% zero. 64% 0. 25
HFRI_FW -6. 84% -2. 67% 0. 15% -0. 09% -1. 21% 1 . 66% 3. 60 per cent 5. 15% 0. 25% 2 . 50 percent 1 . thirty percent 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. 25
DELTA’s Beta with: DJCS_Hedge’s Beta with: HFRI_FW’s Beta with: Resource: Company documents.
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AQR’s DELTA Strategy
212-038
Exhibit 9 Cumulative Go back Performance of AQR DELTA Strategy vs Market Indices (S&P and NASDAQ) and Hedge Fund Indices (DJCS_Hedge and HFRI_FW), since August 2008
Total Return Efficiency of DELTA versus Industry and Hedge Fund Indices 180
one hundred sixty 140 120 100 85 60 40
twenty 0
DELTA NASDAQ S&P_Index DJCS_Hedge HFRI_FW
Source:
Bloomberg and company documents.
18
212-038
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Show 10
Gross annual Returns of Largest Hedge Funds (%)
Fund Term Winton Futures and options USD Cls B Millennium International Limited Transtrend DTP ” Improved Risk (USD) The Genesis Emerging Mkts Invt Com A Aspect Diversified Programme Aurora Offshore Finance Ltd. Permal Macro Loge Ltd CHF A Canyon Value Realization Cayman Limited A Permal Fixed Salary Holdings NV USD A Absolute Alpha dog Fund PCC Diversified Caxton Global Assets Ltd GAM U. T. Institutional Trading K4D-10V Stock portfolio K4D-15V Collection Orbis Maximum (US$) Finance GAM Trading II UNITED STATES DOLLAR Open Double Black Diamond Ltd (Carlson) GoldenTree Excessive Yield Expert Fund Ltd Bay Source Partners Overseas Fund Ltd GAM U. S. Institutional Diversity
Company Name Winton Capital Administration Millennium Intl. Management Transtrend BV Genesis Investment Administration Aspect Capital Aurora Expenditure Management Permal Asset Supervision Canyon Capital Advisors Permal Asset Supervision Financial Risk Management Caxton Co-workers GAM Sterling Management Graham Capital Supervision Graham Capital Management Orbis Investment Management GAM Sterling Management Carlson Capital Goldentree Asset Administration GMT Capital Corp GAM Sterling Administration
Size ($Bil) 9. 89 8. 84 8. 37 6. seventy 5. 71 5. 56 5. thirty-five 5. twenty-one 4. fifty-one 4. 47 4. forty five 3. 57 3. 54
three or more. 54 3. 43 a few. 09 installment payments on your 98 installment payments on your 65 2 . 45 installment payments on your 43
2001 7. 14 15. 26 26. 36 4. sixty two 15. seventy nine 9. 82 14. 66 12. 69 11. 40 9. 33 31. forty one 16. 34 6. forty five 39. 31 29. 01 14. 78 11. 94 18. 35 29. thirty-two 9. 56
2002 18. 34 on the lookout for. 61 21. 26 -1. 77 19. 19 1 . 31 almost 8. 03 your five. 21 12. 47 six. 36 26. 44 12. 69 18. 76 43. 71 12. 15 15. 55 2 . 12 6. 24 zero. 03 5. 95
2003 27. 75 10. fifth there’s 89 8. twenty four 61. 98 20. fifty nine 13. 49 12. 56 21. 87 17. fifty nine 8. ’07 8. 09 14. 74 8. 46 21. sixty 10. 84 14. 49 7. sixty two 31. forty two 23. 24 14. 62
2004 twenty-two. 63 14. 68 12. 82 31. 53 -7. 72 almost eight. 15 four. 86 13. 56 on the lookout for. 37 4. 06 9. 97 three or more. 55 5. 56 -0. 43 2 . 25 3. 84 4. 70 being unfaithful. 89 twenty seven. 97 six. 14
2005 9. 73 11. 31 5. 99 37. 86 12. 01 9. 47 10. 66 8. 35 7. 69 7. 00 8. 03 4. 98 -7. 52 -16. ninety-seven 8. 70 4. 80 5. ’08 13. thirty five 30. 96 10. 48
2006 18. 83 sixteen. 43 doze. 04 40. 22 12. 84 12. 95 being unfaithful. 48 13. 08 15. 48 8. 94 13. 17 eight. 68 your five. 02 6. 64 5. 95 several. 44 twenty one. 12 13. 21 twenty-one. 65 18. 74
2007 17. ninety-seven 10. 99 22. 37 31. 68 8. 18 13. 14 8. 90 7. 52 8. 42 16. thirty-three 1 . 06 9. twenty four 11. 62 16. 57 6. 98 7. 93 15. 96 4. 60 19. 84 7. 76
2008 twenty. 99 -3. 04 twenty nine. 38 -49. 30 twenty-five. 42 -21. 69 -5. 16 -28. 36 -18. 40 -23. 02 12. 96 7. 57 21. 82 thirty five. 67 -2. 49 a few. 78 -12. 40 -38. 60 -20. 88 -13. 96
2009 -4. 63 16. 28 -11. 28 90. forty-four -11. twenty-four 21. 26 9. 83 55. twenty 27. 32 10. fifty-one 5. 83 8. 32 1 . 41 3. eleven 9. 92 6. 55 28. 34 69. 94 56. 70 6. 78
2010 13. 46 13. 22 13. 89 25. 06 12-15. 36 7. 31 6. 38 13. 46 15. 40 your five. 36 11. 42 six. 80 2 . 46 5. 58 -3. 93 5. 97 being unfaithful. 30 23. 61 15. 90 -1. 14
2011 6. up to 29 8. 39 -8. 66 -15. 29 4. 51 -6. 01 -3. 27 -4. 66 -5. twenty-eight -2. summer -2. 40
-2. 32 -4. eleven -2. 67 -4. nineteen -2. seventy nine
Source: Morningstar Hedge Account Database, seen January 2012.
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