Hedge Funds For The Rest Of Us

June 18, 2007


Hedge fund strategies can be extremely powerful tools for portfolio construction. A well-executed hedge fund strategy will deliver two of the most coveted attributes on Wall Street: strong absolute returns and low correlations to other assets. These attributes historically have fueled exponential growth in the hedge fund industry, and today, there are more than 9,000 hedge funds managing over $2 trillion in assets worldwide.1

Surging interest in hedge funds has created significant challenges for the industry. As more and more funds chase the same alpha, industry-wide returns have lagged. As a result, funds have turned to more exotic financial instruments as they search for new sources of alpha, increasing idiosyncratic manager risk. These problems are complicated by a high fee structure that typically charges 2% of assets per year, plus 20% of profits.

There is a growing opportunity for new solutions that enable wider access to hedge fund characteristics at lower costs. Over the past 10 years, the academic community has done substantial research into the tracking and replication of hedge fund results. Recently, several firms have released plans to replicate hedge fund strategies using a variety of equity, fixed-income and derivative products. These products offer the potential for reduced risk, as well as delivering greater transparency and liquidity.

Hedge Fund Industry Landscape

Hedge funds have experienced tremendous growth since the first fund was launched by Alfred W. Jones in 1949. Jones' innovation was to use two strategies generally considered to increase risk—short-selling and leverage—to decrease the risk of an underlying portfolio, laying the groundwork for strong risk-adjusted or hedged returns.

Since Jones' innovation, the hedge fund industry has grown in fits and starts. The onset of derivatives trading in the late-1980s helped set the stage for a huge influx of money managers attracted to the available revenue pool and high fees. That growth accelerated in the late-1990s, and since then, both the assets and the total number of funds have skyrocketed.

Figure 1

The onset of derivatives trading helped set the stage for a huge influx of top money managers attracted to the available revenue pool (and the high fees) from the 1990s to the present time, with assets and the total number of funds skyrocketing. In fact, total assets have quadrupled since 2000, and it is estimated that hedge fund activity actually makes up 30% of total daily trading volume in U.S. markets.2 Net assets of the global hedge fund industry rose by 24% in 2006 and now approaches the $2 trillion USD mark. 3


Sifting through the nearly 10,000 hedge funds makes realizing true individual manager alpha more and more difficult.

Current Industry Issues

As the industry has prospered, it has become increasingly difficult for investors to realize top-tier performance. In fact, the major hedge fund indexes have not meaningfully outpaced the S&P 500 since 2002. Even during the major market downturn around the turn of the millennium, absolute performance fell short of many investors' expectations, hovering at or below the risk-free return rate available from Treasuries. The problem, by most analyses, is simple: hedge funds deliver alpha by capturing inefficiencies in the marketplace. As more funds enter the market, they chase after the same alpha. In this calculus, diminished returns are almost a mathematical necessity.

This issue is compounded by the fact that many top hedge funds are now closed to new investors, limiting access to headline returns. With high fees across the industry, investors are increasingly struggling to capture and maximize the powerful portfolio characteristics promised by hedge fund strategies.

In the last several years, with the dramatic proliferation of funds, results have been less than stellar. Fees, however, have remained high.

Results Come At A High Price

As is often the case in the investment industry, lower-than-expected returns have increased scrutiny on hedge fund fees. Prior to the huge spike in the number of hedge funds this decade, managers were thought of as an elite group, widely recognized as the best of the best in the investment management community. With the growth in the industry, many believe that the talent pool has been diluted, and that this is reflected in the lower returns.

The situation has created a measured level of cost-based investor dissatisfaction with individual managers: 75% of investors say it is difficult to find a manager who satisfies their performance objectives.5 A survey of institutional hedge fund investors found that high fees disproportionately offsetting investment gains was viewed the greatest threat to hedge fund investing.6 While hedge funds can still deliver powerful returns and valuable portfolio characteristics, increasingly, investors are paying alpha fees for beta returns.

Headline Risk

The recent collapse of high-profile hedge funds underscored the idiosyncratic risk of single fund investing, especially in highly leveraged strategies. The Wall Street Journal called 2006 the year of the "billion dollar blowup," as nine funds with over $1 billion in assets closed their doors. Leading the charge was the energy market trader Amaranth Advisors, which managed $9 billion in assets and whose collapse made headlines around the world. In what amounts to be a generally unregulated environment, 83 funds ceased operations during 2006.7

Figure 3

Access Issues

Historically, hedge fund strategies have been accessible only to institutional, high net worth investors and the financial advisors that serve that industry segment. In 1982, the Securities and Exchange Commission (SEC) restricted access to these funds to accredited investors, defined as investors with at least $1 million in investment assets or a trailing income stream of over $200,000 per year. Recently, the SEC announced a proposed rule that would require accredited hedge fund investors to have investment portfolios of at least $2.5 million. This would leave a vast majority of retail investors underserved and with essentially no access to the powerful benefits achieved in hedge fund investing.

Powerful Demand Drivers

Despite these problems, there is a huge and growing demand for hedge fund investments. One reason is that assets that have traditionally provided low-correlated returns, such as commodities and international equities, have been increasingly trading in line with U.S. equity markets. Either way, more and more investors are seeking alternative investments. Industry research suggests that high net worth investors are allocating upward of 20% of assets into alternative investment strategies—up from just 3% in 2000.8 For the retail investor, and even for the moderately wealthy, this number has been closer to 0%.

A Huge Market Opportunity

Investors are already underserved by alternative investments and hedge funds, and a recent SEC proposal to increase the minimum asset requirement to $2.5 million could create a huge demand-side void among alternative investment product providers. Investors will need alternative solutions to deliver the powerful return and risk management characteristics offered by effectively implemented hedge fund strategies. Delivering a lower-cost hedge fund solution that enables access to a wider range of potential investors could result in a huge, and previously untapped, market opportunity.

Figure 3_

Synthetic Hedge Funds

A solution to the many problems faced by the hedge fund industry is emerging at a number of Wall Street firms: synthetic hedge funds. Synthetic hedge funds deliver hedge fund-like returns without the attendant risks, and do so in a structure that makes them available to the retail market at a much lower cost and with increased liquidity and flexibility.

Academic Support

Academic research suggests that hedge funds are ripe for replication. Synthetic models are able to replicate the returns of hedge fund indexes using liquid securities that capture alternative investment beta and deliver similar portfolio characteristics. In fact, several leaders in financial engineering at the most prestigious academic institutions around the globe have been working on the analysis and development of synthetic hedge funds.9

Replication Industry Landscape

To date, there have been two types of synthetic strategies released to the market. The first strategy, which uses factor models, aims to track historical returns of hedge fund indexes using a dynamic portfolio of more liquid securities—early models employ regression-based analysis to combine long/short equities, bonds, commodities, currencies and derivatives. The second strategy, trade replication, targets the pool of assets actually held by hedge fund managers, essentially creating passively managed hedge funds. Yet, both approaches have limitations and can share some of the risk, complications and lack of transparency all too familiar to actual hedge fund investors.

Following the lead from academia, some of the largest global investment management firms charged into synthetic hedge fund development. Both Merrill Lynch and Goldman Sachs have entered the market, and JPMorgan recently announced that it was looking at the space. These models have been focused on institutional investors and take advantage of derivatives to target the reproduction of the hedge fund universe.

Recently, IndexIQ Inc. announced a third variation that generally follows the factor method, but does so using highly liquid, publicly available exchange-traded funds (ETFs). This approach also addresses some of the shortcomings highlighted by other academics in the hedge fund replication community.

Hedge fund replication strategies solve many of the industry's most significant problems, and can address the huge (and possibly growing) demand gap from both advisors and investors outside the ultra high net worth community.

The ETF Approach

IndexIQ was able to develop an algorithm that replicates and models the six top hedge fund investment categories as well as a composite of those strategies, using highly liquid core ETFs. The algorithm selects from the available array of ETFs covering commodities, currencies, stocks, bonds,and real estate, using distinct risk-return and correlation metrics. The use of ETFs, rather than derivative contracts, means that investable products tied to these strategies should be more liquid, more attractively priced and more highly diversified than replication strategies that rely on derivative contracts.

An ETF-based replication strategy can offer improved transparency and real-time pricing relative to hedge fund products. These solutions also help to fill both a product and a service gap in the industry, helping investors access a lower-cost, lower-risk solution to a wide array of investors.

How It Works

In developing each of the underlying hedge fund replication strategies, HedgeIQ analyzes key attribution factors for each hedge fund strategy, as reflected in the CS/Tremont Hedge Fund Index series, and then compares these attributes to the pool of potential asset classes. The returns on the selected asset classes are then analyzed and rebalanced using regression techniques to determine the asset class mixes that most effectively replicate each strategy index.

Results And Analytics

The IndexIQ Strategies aim to capture the benefits of hedge fund investing in a low-cost package. As the trailing 3-year performance shows, each of the strategies is able to effectively track and replicate its underlying hedge fund index, delivering similar results in terms of performance, risk and portfolio statistics. Figure 4 details the performance of the seven strategies versus the comparable CS/Tremont Investable Index. While the reported HedgeIQ performance does not reflect management fees, the low-fee structure of synthetic hedge funds should allow the strategies to retain comparable performance and portfolio and risk metrics.

Composite Strategy Analytics

Given the bottom-up process of portfolio construction for the Composite Strategy, the results underscore the ability of the product to capture, synthesize and deliver the results of each index strategy as well as for the overall industry. Look at the trailing 3-year results of the HedgeIQ Composite strategy relative to the CS/Tremont Investable Hedge Fund (Figure 4). Note: All Hedge IQ results are hypothetical and based on backtesting. The performance of the hedge fund indexes is net of fees. (Figure 5): Tracking error is HedgeIQ results relative to the noted benchmark. Index, the Strategy outpaces the index with slightly higher risk levels. While trailing the performance of the Goldman Sachs hedge fund replication strategy, named Absolute Return Tracker (ART), it does so with significantly lower levels of risk. Importantly, this plays out in a higher risk/reward ratio, lower standard deviation and higher Sharpe ratio, reflecting its ability to capture the core performance characteristics of a true "hedge" strategy. The HedgeIQ Composite Strategy is able to capture the risk and return characteristics of the entire universe using a bottom-up approach to portfolio construction.

Figure 4

Figure 5

Addressing Common Industry Pitfalls

The synthetic replication of hedge fund indexes addresses some of the common overarching issues in the hedge fund space, including idiosyncratic manager risk, high fees, and the difficulty of separating true alpha from beta (and paying appropriately for both types of returns). But there are a number of factors to watch closely when evaluating individual replication strategies.

Tracking Error

For example, the goal of IndexIQ Strategies is to provide a "hedge fund-like" return that captures the core performance characteristics of individual hedge funds strategies. This includes absolute returns, but also trends, standard deviations and reactions to different kinds of market situations. As displayed in Figure 6 10, certain strategies track absolute returns better than others, which is not surprising when you consider the nature of different hedge fund strategies. However, the goal is not to precisely track the index; rather, it is to capture the performance characteristics of the hedge fund strategy, including the correlations, risk/reward tradeoffs and the tendency to trade in one direction or the other during certain market climates.

Hedge Fund Correlation

Correlation is an extremely important issue for the hedge fund community. Most hedge fund investors are seeking the benefits of alternative investments as a complement to a core portfolio of both bonds and stocks precisely because of the correlation benefits hedge funds provide. A recent paper released by Harry Kat targeted many of the early stage hedge fund replicators by documenting higher-than-desired correlation results with the broad markets. 11 It should not be altogether surprising that replicators correlate more closely with equities, as replicators use market-based instruments and do not have access to the full array of investment possibilities that hedge funds consider. As a result, investors searching for a replication strategy should closely consider the correlation performance of those tools. Aside from the Market Neutral strategy 12, the IndexIQ products produce close correlations with their hedge fund counterparts. That they report slightly higher correlation to the broad market is not surprising, given their ETF construction.

The strategies deliver comparable correlation results while investing in highly-liquid and transparent ETF securities.

Addressing Auto Correlation

A widely discussed aspect of the analysis of hedge fund replication strategies is autocorrelation. Some of the obvious allure of the space is to capture the benefits of the low correlation of hedge fund assets relative to broad equity market indexes. Yet, academic research shows that some of this low correlation is a result of inaccurate or stale pricing of illiquid securities. When older prices are used, it serves to skew the timing of portions of period returns behind broader market trends. In a 2001 paper, Asness, Krail, and Liew examined this phenomenon, documenting that reported hedge fund index returns are not only a function of current period returns, but also of the returns of prior periods as stale prices catch up to the market.13

Currently, hedge fund industry standards for pricing and performance reporting may serve to understate risk and correlation results.

Figure 6

Figure 7

Solving the Serial Correlation Problem

To the extent that lagged marking is widespread, hedge fund risk would then be understated as it is inferred from historical monthly data. It also follows that historical risk-adjusted performance would be overstated. This presents an additional challenge in the replication of hedge fund indexes, as the industry is trying to deliver a solution with a low correlation to the overall market. Yet, many of the current replication strategies do not adjust for autocorrelation.

The IndexIQ approach takes advantage of an innovative modeling tactic that corrects for the industry's serial correlation in appropriate strategies, adjusting for the artificial portion of the low correlation derived from manager-specific mark-to-market behavior. The IndexIQ solution is the first to address and adjust reported returns for this issue, and although it may be at the cost of increased risk and correlation numbers, the results will better reflect the actual investment characteristics of hedge fund strategies.


The hedge fund industry has grown rapidly throughout the last 15 years, and is in the midst of a natural and cyclical product evolution. With a huge increase in both assets under management and the sheer number of funds, it is becoming increasingly difficult for hedge funds to realize the necessary alpha to support their high relative fee structure.

Supported by a range of recent academic research and modeling techniques, hedge fund replication strategies have entered the market in recent months. These products synthesize the results of the hedge fund market and fill huge gaps in supply and demand by enabling hedge fund-like results to be delivered to a broader audience of investors. Hedge fund replication strategies promise to deliver the powerful investment characteristics of hedge funds at a much lower cost and with additional liquidity and transparency. They also deliver these benefits without the idiosyncratic risk of individual hedge fund investing.

As products mature, the opportunities for passive management arise. Just as we have seen the advantages of index-based investment strategies for mutual funds, similar advantages— lower costs, greater transparency and higher liquidity —will accrue to hedge funds as well. There will always be a space for high-performing hedge funds to serve sophisticated investors, but there is growing room and heightened demand for sophisticated hedge fund replication strategies to bring the well-known benefits of hedge funds to a broader audience of investors.

Performance Notes

Note: All returns for the HedgeIQ strategies are backtested hypothetical total returns, excluding taxes, fees and transaction costs. Annual returns are annualized monthly returns; annual volatility is annualized monthly standard deviations; Sharpe ratio is defined as the excess return over the risk-free return from 1-month T-bills and standard deviation; the risk/reward ratio is annual returns divided by annual volatility.


1 Institutional Investor Hedge Fund Daily March 2007
2 Forbes.com February 22, 207
3 Fund number data provided by Investopedia November 2005
4 CS/Tremont Non-Investable Index
5 Investment News January 11, 2007
6 2007 State Street Hedge Fund Research Study
7 Wall Street Journal March 21, 2007
8 Cap Gemini World Wealth Report 2006
9 Hedge fund replication strategies: implications for investors and regulators, Fung and Hsieh; Who Needs Hedge Funds?, Kat and Palaro and Alternative Routes to Hedge Fund Return Replication, Kat; Can Hedge fund Returns Be Replicated?: The Linear Case, Hasanhodzic and Lo
10 Tracking error is defined as the annualized volatility of the difference between the returns on the HedgeIQ strategy and the corresponding Tremont index.
11 Alternative Routes to Hedge Fund Return Replication, Harry Kat
12 Market Neutral classes will often be the most difficult to match correlations, as this segment relies so heavily on active security selection techniques
13 Do Hedge Funds Hedge?

Robert Whitelaw is the Edward C. Johnson 3rd Professor of Entrepreneurial Finance and Co-Chair of the Finance Department, Leonard N. Stern School of Business, New York University; he is also chief investment strategist of IndexIQ, developer of the HedgeIQ strategies.

Sujeet Banjaree is vice president of Product Development at IndexIQ

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