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Issues with Hedge Fund
Performance
Ezra Zask
Ezra Zask Research Associates
February 2016
Introduction
• Yale Endowment Model
• Changing Measurement of Hedge Fund Performance
• Home Run Years
• Absolute Return Years
• Alpha Years
• Portfolio Diversification Years
• Analysis of Hedge Fund Benefits
• Flies in the Ointment on Hedge Fund Benefits
• Hedge Funds in Investment Portfolios
Yale Endowment Model
• During his 19 years as CIO, the Yale Endowment portfolio dramatically
outperformed virtually every other large endowment as well as the traditional
60/40 portfolio.
• Swensen attributes his success to large investments in alternatives, including
hedge funds
Benefits Attributed to Hedge Funds
• Hedge funds provide higher returns and alpha than other investments
• Hedge funds provide absolute returns, showing positive returns under all market
conditions
• Hedge funds provide principal risk protection insurance because they suffer
smaller declines than other investments during market downturns
• Hedge funds improve the risk adjusted returns of a portfolio because of their low
correlation with other investments
Representative Studies of the Portfolio Benefits of
Hedge Funds
• The Value of the Hedge Fund Industry to Investors, Markets and the Broader Economy,
Center for Hedge Fund Research, Imperial College, 2012; with KPMG and AIMA
• Hedge Funds as Diversifiers in Institutional Portfolios, Commonfund, August 2013
• Apples to Apples: How to better understand hedge fund performance; AIMA, 2014
• Hedge Fund Investing: How to Optimize Your Portfolio, Credit Suisse, 2012
• Hedge Funds in Strategic Asset Allocation, LYXOR Research, March 2014
• Quant Corner: the ABCs of Hedge Funds: Alphas, Betas and Costs; Roger Ibbotson, Peng
Chen and Kevin Zhu, Morningstar Investment Observer
• The Case for Hedge Funds, Goldman Sachs Asset Management, 2013
• Essentials of Alternatives, Guggenheim Investments, 2012
• The New Diversification: Open Your Eyes to Investments, a Conversation with Professor
Christopher Geczy, BlackRock, 2013
Hedge Funds1.0
• Hedge Fund 1.0, which was dominant in the 1980’s and 1990’s,
touted the outsized return that were available through hedge fund
investments. George Soros and Julian Robertson were the models for
investors.
• However, as the hedge fund field became crowded, they were forced
to compete in well-arbitraged markets and these outsized returns
became more and more rare. The process was accelerated by the
larger scale of funds who were unable to meaningfully invest in small
markets.
Hedge Fund 2.0
• Hedge Fund 2.0 focused on the downside protection and absolute return
measure of hedge fund performance. as indicated by their relatively small
losses compared to other investments during the Asian crisis of 1998 and
the Internet bubble of 2001.
• This hedge fund meme was exploded during the Credit Crisis in 2008 when
hedge funds as a group lost over 20%. (While still lower than the S&P loss
of over 40%, the loss was not supposed to occur under hedge fund 2.0)
• Hedge fund 2.0 also included the notion that hedge funds added the
elusive and sought after investment alpha (returns above market returns)
which ostensibly resulted from manager skill or unexploited market
opportunities. This alleged benefit was also whittled away as new sources
of beta were identified (specific to hedge fund strategies and markets) and
reduced the size of the alpha.
Hedge Fund Alpha and Outperformance
The Downside Risk Protection Years
• Exhibit 2: Hedge Funds Have Experienced Smaller Declines During Equity Drawdowns
Exhibit 1: HFRI Historical Annual Returns
Hedge Fund 3.0
• In hedge fund 3.0 performance no longer holds hedge funds to a benchmark or, indeed, any
return criteria. The performance criteria of hedge fund 3.0 is summarized in a recent paper
published by the Alternative Investment Management Association (AIMA), a hedge fund industry
group, and the Chartered Alternative Investment Association (CAIA), which provides certification
for alternative investments. The paper is titled “Portfolio Transformers: Examining the Role of
Hedge Funds and Diversifiers in an Investor Portfolio.”
• Hedge funds are touted as either portfolio diversifiers or investment substitutes (for traditional
stocks and bonds).
•
From Alpha to Smart Beta: The Economist
THE INDUSTRY’S LANGUAGE IS CHANGING
February 18th, 2012
Dear Investor,
In line with the rest of our industry we are making some changes to the language we use in our marketing and
communications. We are writing this letter so we can explain these changes properly. Most importantly, Zilch Capital used to
refer to itself as a “hedge fund” but 2008 made it embarrassingly clear we didn't know how to hedge. At all. So like many others,
we have embraced the title of “alternative asset manager”. It's clunky but ambiguous enough to shield us from criticism next
time around. We know we used to promise “absolute returns” (ie, that you would make money regardless of market conditions)
but this pledge has proved impossible to honour. Instead we're going to give you “risk-adjusted” returns or, failing that,
“relative” returns. In years like 2011, when we delivered much less than the S&P 500, you may find that we don't talk about
returns at all.
It is also time to move on from the concept of delivering “alpha”, the skill you've paid us such fat fees for. Upon reflection, we
have decided that we're actually much better at giving you “smart beta”. This term is already being touted at industry
conferences and we hope shortly to be able to explain what it means. Like our peers we have also started talking a lot about
how we are “multi-strategy” and “capital-structure agnostic”, and boasting about the benefits of our “unconstrained”
investment approach. This is better than saying we don't really understand what's going on.
Some parts of the lexicon will not see style drift. We are still trying to keep alive “two and twenty”, the industry's shorthand for
2% management fees and 20% performance fees. It is, we're sure you'll agree, important to keep up some traditions. Thank you
for your continued partnership.
Zilch Capital LLC”
Flies in the Ointment of
Hedge Fund Performance
Dispersion of Hedge Fund Returns and the
Importance of Manager Selection
David Swensen and many others have pointed out the wide dispersion of manager returns and
the importance of selecting top performing managers to attain the benefits imputed to hedge
funds. In fact, Swensen clearly points out that the success of his program depends on Yale’s
ability to identify and invest in top-tier performing funds.
However, selecting future winners among hedge funds (or mutual funds) is exceedingly difficult,
compounded by the fact that many of the best performing funds are either closed to new
investors, require high minimum investments and/or lock-up periods, or charge high fees.
Quartile Dispersion of Returns by Strategy
Dispersion of Hedge Fund Performance
Hitting a Moving Target: Lack of Persistence in
Performance
Paradoxically, it turns out that the familiar disclaimer that accompanies all performance results – that past
performance is not indicative of future performance – turns out to be absolutely true.
research reports that a fund’s performance ranking in one period compared to its peers provides very little
information content for its ranking in subsequent periods. In other words, choosing funds on the basis of their
past performance is effectively a random process.
For example, looking at data over the period 1990–2012, only 21% of first-quartile performers in one year
remained first-quartile performers in the next, as shown in below. Conversely, 23% of bottom-quartile per-
formers made the top quartile the next year.
Hedge Fund Index Data Bias
Hedge funds suffer from a number of well-known data biases
Selection Bias
Because hedge funds are not required to report their performance, there is a bias towards
reporting from better-performing funds, although this is mitigated by the non-reporting of
some of the largest and most successful funds such as those managed by Soros, Kovner,
Robertson, etc. A related problem is that relatively few funds report to all the major data
providers, which makes the use of any one database problematic.
Survivorship Bias
Each year, hundreds of hedge funds go out of business, which means that an analysis based
only on active funds excludes those funds who are most likely to have performed poorly.
The result would be to overstate the gains to hedge fund investors. This bias is sometimes
overcome by including the performance of funds that have closed. However, this brings up
the newly discovered “delisting bias” discussed below.
Hedge Fund Index Data Bias (2)
• Reporting Bias
This bias is a variation on survivorship bias and typically leads to index performance
looking better in down markets than it should. The idea is that in a month when a
fund has performed poorly it is less likely to report its return, thus understating the
loss to the index during the period. The failure of funds to report could be due to
outright fund failures as well as reluctance to report poor results.
• Backfill Bias
This bias occurs when a hedge fund is added to the index and its historical returns
are “backfilled” into the data. This bias is sometimes referred to as “Instant
History” bias. Typically, a hedge fund begins reporting to a database after a period
of good performance; as such, the historical performance of those indices that
backfill will be higher than those who report contemporaneously. Similar to
survivorship bias, backfill bias leads to overstated returns and understated risk.
Grasping at Straws: Can one benefit from the small fund
“premium”?
A tremendous amount of ink has been spilt touting the superior returns achieved on average by small and
newer hedge funds and mutual funds compared to older and larger funds.[1] However, there has not been an
action plan on how investors can benefit from this “fact” nor enough discussion of the potential risks of
following this strategy.
The analyses of this topic claim that there is a modestly higher return generated by small hedge funds.
However, this finding holds for small funds in aggregate, combining the results of dozens or hundreds of these
funds. However, it is impossible to invest in any representative sampling of small funds, which means that
investors must select a handful from the hundreds that are included in this studies. However, because the
dispersion of returns for small funds is even greater than for larger funds, the only way to capture the small
size premium is to correctly identify the top tier funds. However, picking the top performers is even more
difficult in the case of small funds because they tend to be relatively new, they typically have short track
records, small staff and infrastructure and may be difficult to find since they may not even be reporting to the
hedge fund performance services such as HFR.
Simon Lack: Hedge Fund Promise
In a trenchant critique of hedge funds Simon Lack, formerly a senior
executive in JP Morgan’s hedge fund group, presents an analysis in his
book “The Hedge Fund Promise,” that shows that by his calculations,
hedge fund investors only receive a small fraction of any gains made by
hedge funds, while the hedge fund managers walk away with the great
majority (perhaps as much as 80-90%). This disproportionate share
comes largely from the fact that hedge fund managers are in the
enviable position of sharing in the upside by getting 20% of any profits,
while only investors suffer the downside. Over time, he finds, this
results in all the gains going to hedge fund managers
A Leap of Faith: It all comes Down to Manager
Selection and Portfolio Construction
• The combination of manager dispersion and lack sustainability (when combined with the data
problems discussed below) make it appear that reaping the benefits of alternative investments is
extremely difficult, if not impossible. It is instructive to look at how Goldman Sachs reconciles the
rosy picture of hedge fund benefits with the problems of identifying top performing managers
and finding the correct asset allocation:
Key Elements of a Hedge Fund Solution
Manager Selection
• “Manager selection begins with sourcing. … Quality sourcing is often dependent on the breadth
and depth of the relationships an investor has established with managers, with clients, and in the
market generally…Once an opportunity is identified, a robust evaluation process must ensue. This
process should be repeatable and scalable, and evolve over time…In many ways, due diligence is a
search for a consistent story across all areas of a manager.
• The exclusion of managers from consideration can be as important a result of the process as the
selection of outperformers…Oftentimes, the evaluation process is defined as much by steering
clear of these poor investments as by making sure to identify the most compelling of
opportunities.”
Hedge Funds in Portfolios
The Pensions Institute Studies
• A series of studies released in June 2014 in conjunction with the efforts of U.K. pension funds to measure the cost/benefit of
using outside managers in selecting mutual funds provided alarming evidence of the inability of these managers to justify
their fees. The studies, which were conducted at the Pensions Institute, based at the Cass Business School in London,
examined 516 UK equity funds between 1998 and 2008, and found that just 1% of managers were able to return more than
the trading and operating costs they incurred. But even those managers pocketed for themselves any value they added in
fees, leaving nothing for the investor. All the other managers failed to deliver any outperformance – either from stock
selection or from market timing.
• Star managers are, to quote the report, “incredibly hard to identify”. Furthermore, it takes 22 years of performance data to
be 90% sure that a particular manager’s outperformance is genuinely down to skill.
• Perhaps the most alarming conclusion was that not only were the vast majority of managers unlucky (i.e., their results could
be explained by random chance), but they were “genuinely unskilled” in that their performance was even worse than
predicted by random chance.
• Improved Inference in the Evaluation of Mutual Fund Performance using Panel Bootstrap Methods
David Blake, Tristan Caulfield, Christos Ioannidis and Ian Tonks (June 2014)
Discussion Paper PI-1405; The Pensions Institute, Cass Business School, City University London
• Two new methodologies are introduced to improve inference in the evaluation of mutual fund performance against
benchmarks. First, the benchmark models are estimated using panel methods with both fund and time effects. Second, the
non-normality of individual mutual fund returns is accounted for by using panel bootstrap methods. We also augment the
standard benchmark factors with fund-specific characteristics, such as fund size. Using a dataset of UK equity mutual fund
returns, we find that fund size has a negative effect on the average fund manager’s benchmark-adjusted performance.
Further, when we allow for time effects and the non-normality of fund returns, we find that there is no evidence that even
the best performing fund managers can significantly out-perform the augmented benchmarks after fund management
charges are taken into account.
Investment Managers have Behavioral Biases Too
• Manager selection is notoriously difficult in the case of hedge funds given
their lack of transparency and open-ended mandate.
• I have become a firm believer in the findings of behavioral finance as they
related to trading and managing investments. Most of the literature on the
subject is aimed at dissecting the behavior of retail investors and traders
while portfolio managers have escaped largely unscathed. However,
portfolio managers and investors operating in the alternative investment
space are subject to the same behavioral heuristics as any other economic
actor.
• The importance of these findings for manager selection is also reinforced
by the study cited earlier indicating that managers are selected by “soft”
factors other than performance statistics, leaving the playing field wide
open to subjective selection criteria. (See Picking Winners).
• See also “Dispersion: Measuring Market Opportunity,” S&P Dow Jones
Indices, December 2013 and “At the Intersection of Diversification,
Volatility and Correlation,” S&P Dow Jones Indices, April 2014.
Behavioral Biases in Manager Selection
• Specifically in the case of choosing managers, the following behavior may influence the choice, often to the detriment of
the investor:
• Framing – how a concept is presented to individuals matters in their decision making
• Anchoring – becoming fixated on past information and using that information to make inappropriate decisions. Investors
may become fixated on what the price of a security “should” be and hold on until the price is achieved. When forming an
estimate, people start from an initial (possibly) arbitrary value and then adjust, but only slowly. One form of this is the
slowness with which investors react to company announcements.
• Representativeness – placing undue weight on more recent experience and ignoring the importance of long-term averages. This is
sometimes known as the “law of small numbers.” One form of this bias is the “hot-hand” fallacy that attributes staying power to short term
results. Another is to assume that a stock market rally will persist indefinitely.
• Hindsight Bias – a particularly nasty bias in which events are viewed as more predictable after the result is known.
• Confirmation Bias – people selectively evaluate information in ways that support their pre-conceived conclusions, ignoring or discounting
information that may lead to questioning the conclusion. This is especially true if tied into a “narrative” or story, which people related to on
a more visceral level than technical information.
• Loss Aversion – people feel losses more acutely than gains and will take irrational steps to avoid this feeling. For example, people tend to
hang on to loosing paper positions to avoid the pain of realizing actual losses. Loss aversion may also sometimes lead to inaction to avoid
losses.
• Herding – individuals and institutions find comfort in taking actions that conform to those of relevant reference groups. Even hedge funds
seem to buy and sell the same stocks at the sametime, tracking each other’s investment strategies. Herding has been used to account for
asset bubbles and for “affinity fraud” as in the case of Madoff.
• A comprehensive summary of the field of behavioral finance is offered by Daniel Kahneman, Nobel Prize Winner in Economics, in Thinking,
Fast and Slow, New York: Farrar, Straus and Giroux, 2011.
Overconfidence: Only 25% of Managers can be in
the top 25% of managers
• As noted above, virtually every investment managers touts their
ability to select top tier managers. However, the reality is that only
25% of them will select a top quartile fund while fully 50% will select
a fund in the bottom half of the potential managers. The claims of
investment managers are certainly partly explained by the
competitive nature of attracting assets in the asset management
industry. However, they also stem from a behavioral heuristic known
as “overconfidence” that leads investment managers (along with
most other people) to assume that they can defy the evidence that
they are more likely to choose a poor performer than a top
performer.
AIMA Study
The benefits for investors that result from including hedge funds in their portfolios include the following:
•a source of diversification
• substitutes for traditional stocks, bond investments. The paper is titled “Portfolio Transformers:
Examining the Role of Hedge Funds and Diversifiers in an Investor Portfolio.” Hedge funds are touted as
either portfolio diversifiers or investment substitutes (for traditional stocks and bonds).
“Such hedge fund strategies ought to reduce the overall volatility (i.e. reduce the risk) of the portfolio’s public markets
allocation, with a more attractive risk/reward profile. Other hedge fund strategies may have a low correlation to equity and
credit markets and offer a higher probability of generating out-sized returns (albeit by taking on a higher level of risk).
Employing this approach (where hedge funds take on the role of a substitute or complement the equity or fixed income
portfolio) offers the plan a way of reducing the volatility (risk) within their public equity allocation, with little if any reduction
in the portfolio’s total performance.”
(Source: “Portfolio Transformers: Examining the Role of Hedge Funds and Diversifiers in an Investor Portfolio.”)
Alternative Investments and Modern
Portfolio Theory
Modern portfolio theory (MPT) is a theory of finance that attempts to maximize portfolio expected
return for a given amount of portfolio risk, or minimize risk for a given level of expected return, by
choosing the proportions of various assets. First formulated by Harry Markowitz in his seminal
article, “Portfolio Selection" in the 1952 Journal of Finance, MPT is a mathematical formulation of
the concept of diversification in investing, with the aim of selecting a collection of investment assets
that has collectively lower risk than any individual asset. This is possible, intuitively speaking,
because different types of assets often change in value in opposite ways. Modern portfolio theory
states that any asset that is uncorrelated (or more accurately not very highly correlated) to other
assets in a portfolio places the resulting portfolio in a more favorable position on the efficient
frontier, resulting in a portfolio that has a more favorable risk/return profile than the original
portfolio.

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Issues with hedge fund performance

  • 1. Issues with Hedge Fund Performance Ezra Zask Ezra Zask Research Associates February 2016
  • 2. Introduction • Yale Endowment Model • Changing Measurement of Hedge Fund Performance • Home Run Years • Absolute Return Years • Alpha Years • Portfolio Diversification Years • Analysis of Hedge Fund Benefits • Flies in the Ointment on Hedge Fund Benefits • Hedge Funds in Investment Portfolios
  • 3. Yale Endowment Model • During his 19 years as CIO, the Yale Endowment portfolio dramatically outperformed virtually every other large endowment as well as the traditional 60/40 portfolio. • Swensen attributes his success to large investments in alternatives, including hedge funds
  • 4. Benefits Attributed to Hedge Funds • Hedge funds provide higher returns and alpha than other investments • Hedge funds provide absolute returns, showing positive returns under all market conditions • Hedge funds provide principal risk protection insurance because they suffer smaller declines than other investments during market downturns • Hedge funds improve the risk adjusted returns of a portfolio because of their low correlation with other investments
  • 5. Representative Studies of the Portfolio Benefits of Hedge Funds • The Value of the Hedge Fund Industry to Investors, Markets and the Broader Economy, Center for Hedge Fund Research, Imperial College, 2012; with KPMG and AIMA • Hedge Funds as Diversifiers in Institutional Portfolios, Commonfund, August 2013 • Apples to Apples: How to better understand hedge fund performance; AIMA, 2014 • Hedge Fund Investing: How to Optimize Your Portfolio, Credit Suisse, 2012 • Hedge Funds in Strategic Asset Allocation, LYXOR Research, March 2014 • Quant Corner: the ABCs of Hedge Funds: Alphas, Betas and Costs; Roger Ibbotson, Peng Chen and Kevin Zhu, Morningstar Investment Observer • The Case for Hedge Funds, Goldman Sachs Asset Management, 2013 • Essentials of Alternatives, Guggenheim Investments, 2012 • The New Diversification: Open Your Eyes to Investments, a Conversation with Professor Christopher Geczy, BlackRock, 2013
  • 6. Hedge Funds1.0 • Hedge Fund 1.0, which was dominant in the 1980’s and 1990’s, touted the outsized return that were available through hedge fund investments. George Soros and Julian Robertson were the models for investors. • However, as the hedge fund field became crowded, they were forced to compete in well-arbitraged markets and these outsized returns became more and more rare. The process was accelerated by the larger scale of funds who were unable to meaningfully invest in small markets.
  • 7. Hedge Fund 2.0 • Hedge Fund 2.0 focused on the downside protection and absolute return measure of hedge fund performance. as indicated by their relatively small losses compared to other investments during the Asian crisis of 1998 and the Internet bubble of 2001. • This hedge fund meme was exploded during the Credit Crisis in 2008 when hedge funds as a group lost over 20%. (While still lower than the S&P loss of over 40%, the loss was not supposed to occur under hedge fund 2.0) • Hedge fund 2.0 also included the notion that hedge funds added the elusive and sought after investment alpha (returns above market returns) which ostensibly resulted from manager skill or unexploited market opportunities. This alleged benefit was also whittled away as new sources of beta were identified (specific to hedge fund strategies and markets) and reduced the size of the alpha.
  • 8. Hedge Fund Alpha and Outperformance
  • 9. The Downside Risk Protection Years • Exhibit 2: Hedge Funds Have Experienced Smaller Declines During Equity Drawdowns Exhibit 1: HFRI Historical Annual Returns
  • 10. Hedge Fund 3.0 • In hedge fund 3.0 performance no longer holds hedge funds to a benchmark or, indeed, any return criteria. The performance criteria of hedge fund 3.0 is summarized in a recent paper published by the Alternative Investment Management Association (AIMA), a hedge fund industry group, and the Chartered Alternative Investment Association (CAIA), which provides certification for alternative investments. The paper is titled “Portfolio Transformers: Examining the Role of Hedge Funds and Diversifiers in an Investor Portfolio.” • Hedge funds are touted as either portfolio diversifiers or investment substitutes (for traditional stocks and bonds). •
  • 11. From Alpha to Smart Beta: The Economist THE INDUSTRY’S LANGUAGE IS CHANGING February 18th, 2012 Dear Investor, In line with the rest of our industry we are making some changes to the language we use in our marketing and communications. We are writing this letter so we can explain these changes properly. Most importantly, Zilch Capital used to refer to itself as a “hedge fund” but 2008 made it embarrassingly clear we didn't know how to hedge. At all. So like many others, we have embraced the title of “alternative asset manager”. It's clunky but ambiguous enough to shield us from criticism next time around. We know we used to promise “absolute returns” (ie, that you would make money regardless of market conditions) but this pledge has proved impossible to honour. Instead we're going to give you “risk-adjusted” returns or, failing that, “relative” returns. In years like 2011, when we delivered much less than the S&P 500, you may find that we don't talk about returns at all. It is also time to move on from the concept of delivering “alpha”, the skill you've paid us such fat fees for. Upon reflection, we have decided that we're actually much better at giving you “smart beta”. This term is already being touted at industry conferences and we hope shortly to be able to explain what it means. Like our peers we have also started talking a lot about how we are “multi-strategy” and “capital-structure agnostic”, and boasting about the benefits of our “unconstrained” investment approach. This is better than saying we don't really understand what's going on. Some parts of the lexicon will not see style drift. We are still trying to keep alive “two and twenty”, the industry's shorthand for 2% management fees and 20% performance fees. It is, we're sure you'll agree, important to keep up some traditions. Thank you for your continued partnership. Zilch Capital LLC”
  • 12. Flies in the Ointment of Hedge Fund Performance
  • 13. Dispersion of Hedge Fund Returns and the Importance of Manager Selection David Swensen and many others have pointed out the wide dispersion of manager returns and the importance of selecting top performing managers to attain the benefits imputed to hedge funds. In fact, Swensen clearly points out that the success of his program depends on Yale’s ability to identify and invest in top-tier performing funds. However, selecting future winners among hedge funds (or mutual funds) is exceedingly difficult, compounded by the fact that many of the best performing funds are either closed to new investors, require high minimum investments and/or lock-up periods, or charge high fees. Quartile Dispersion of Returns by Strategy
  • 14. Dispersion of Hedge Fund Performance
  • 15. Hitting a Moving Target: Lack of Persistence in Performance Paradoxically, it turns out that the familiar disclaimer that accompanies all performance results – that past performance is not indicative of future performance – turns out to be absolutely true. research reports that a fund’s performance ranking in one period compared to its peers provides very little information content for its ranking in subsequent periods. In other words, choosing funds on the basis of their past performance is effectively a random process. For example, looking at data over the period 1990–2012, only 21% of first-quartile performers in one year remained first-quartile performers in the next, as shown in below. Conversely, 23% of bottom-quartile per- formers made the top quartile the next year.
  • 16. Hedge Fund Index Data Bias Hedge funds suffer from a number of well-known data biases Selection Bias Because hedge funds are not required to report their performance, there is a bias towards reporting from better-performing funds, although this is mitigated by the non-reporting of some of the largest and most successful funds such as those managed by Soros, Kovner, Robertson, etc. A related problem is that relatively few funds report to all the major data providers, which makes the use of any one database problematic. Survivorship Bias Each year, hundreds of hedge funds go out of business, which means that an analysis based only on active funds excludes those funds who are most likely to have performed poorly. The result would be to overstate the gains to hedge fund investors. This bias is sometimes overcome by including the performance of funds that have closed. However, this brings up the newly discovered “delisting bias” discussed below.
  • 17. Hedge Fund Index Data Bias (2) • Reporting Bias This bias is a variation on survivorship bias and typically leads to index performance looking better in down markets than it should. The idea is that in a month when a fund has performed poorly it is less likely to report its return, thus understating the loss to the index during the period. The failure of funds to report could be due to outright fund failures as well as reluctance to report poor results. • Backfill Bias This bias occurs when a hedge fund is added to the index and its historical returns are “backfilled” into the data. This bias is sometimes referred to as “Instant History” bias. Typically, a hedge fund begins reporting to a database after a period of good performance; as such, the historical performance of those indices that backfill will be higher than those who report contemporaneously. Similar to survivorship bias, backfill bias leads to overstated returns and understated risk.
  • 18. Grasping at Straws: Can one benefit from the small fund “premium”? A tremendous amount of ink has been spilt touting the superior returns achieved on average by small and newer hedge funds and mutual funds compared to older and larger funds.[1] However, there has not been an action plan on how investors can benefit from this “fact” nor enough discussion of the potential risks of following this strategy. The analyses of this topic claim that there is a modestly higher return generated by small hedge funds. However, this finding holds for small funds in aggregate, combining the results of dozens or hundreds of these funds. However, it is impossible to invest in any representative sampling of small funds, which means that investors must select a handful from the hundreds that are included in this studies. However, because the dispersion of returns for small funds is even greater than for larger funds, the only way to capture the small size premium is to correctly identify the top tier funds. However, picking the top performers is even more difficult in the case of small funds because they tend to be relatively new, they typically have short track records, small staff and infrastructure and may be difficult to find since they may not even be reporting to the hedge fund performance services such as HFR.
  • 19. Simon Lack: Hedge Fund Promise In a trenchant critique of hedge funds Simon Lack, formerly a senior executive in JP Morgan’s hedge fund group, presents an analysis in his book “The Hedge Fund Promise,” that shows that by his calculations, hedge fund investors only receive a small fraction of any gains made by hedge funds, while the hedge fund managers walk away with the great majority (perhaps as much as 80-90%). This disproportionate share comes largely from the fact that hedge fund managers are in the enviable position of sharing in the upside by getting 20% of any profits, while only investors suffer the downside. Over time, he finds, this results in all the gains going to hedge fund managers
  • 20. A Leap of Faith: It all comes Down to Manager Selection and Portfolio Construction • The combination of manager dispersion and lack sustainability (when combined with the data problems discussed below) make it appear that reaping the benefits of alternative investments is extremely difficult, if not impossible. It is instructive to look at how Goldman Sachs reconciles the rosy picture of hedge fund benefits with the problems of identifying top performing managers and finding the correct asset allocation: Key Elements of a Hedge Fund Solution Manager Selection • “Manager selection begins with sourcing. … Quality sourcing is often dependent on the breadth and depth of the relationships an investor has established with managers, with clients, and in the market generally…Once an opportunity is identified, a robust evaluation process must ensue. This process should be repeatable and scalable, and evolve over time…In many ways, due diligence is a search for a consistent story across all areas of a manager. • The exclusion of managers from consideration can be as important a result of the process as the selection of outperformers…Oftentimes, the evaluation process is defined as much by steering clear of these poor investments as by making sure to identify the most compelling of opportunities.”
  • 21. Hedge Funds in Portfolios
  • 22. The Pensions Institute Studies • A series of studies released in June 2014 in conjunction with the efforts of U.K. pension funds to measure the cost/benefit of using outside managers in selecting mutual funds provided alarming evidence of the inability of these managers to justify their fees. The studies, which were conducted at the Pensions Institute, based at the Cass Business School in London, examined 516 UK equity funds between 1998 and 2008, and found that just 1% of managers were able to return more than the trading and operating costs they incurred. But even those managers pocketed for themselves any value they added in fees, leaving nothing for the investor. All the other managers failed to deliver any outperformance – either from stock selection or from market timing. • Star managers are, to quote the report, “incredibly hard to identify”. Furthermore, it takes 22 years of performance data to be 90% sure that a particular manager’s outperformance is genuinely down to skill. • Perhaps the most alarming conclusion was that not only were the vast majority of managers unlucky (i.e., their results could be explained by random chance), but they were “genuinely unskilled” in that their performance was even worse than predicted by random chance. • Improved Inference in the Evaluation of Mutual Fund Performance using Panel Bootstrap Methods David Blake, Tristan Caulfield, Christos Ioannidis and Ian Tonks (June 2014) Discussion Paper PI-1405; The Pensions Institute, Cass Business School, City University London • Two new methodologies are introduced to improve inference in the evaluation of mutual fund performance against benchmarks. First, the benchmark models are estimated using panel methods with both fund and time effects. Second, the non-normality of individual mutual fund returns is accounted for by using panel bootstrap methods. We also augment the standard benchmark factors with fund-specific characteristics, such as fund size. Using a dataset of UK equity mutual fund returns, we find that fund size has a negative effect on the average fund manager’s benchmark-adjusted performance. Further, when we allow for time effects and the non-normality of fund returns, we find that there is no evidence that even the best performing fund managers can significantly out-perform the augmented benchmarks after fund management charges are taken into account.
  • 23. Investment Managers have Behavioral Biases Too • Manager selection is notoriously difficult in the case of hedge funds given their lack of transparency and open-ended mandate. • I have become a firm believer in the findings of behavioral finance as they related to trading and managing investments. Most of the literature on the subject is aimed at dissecting the behavior of retail investors and traders while portfolio managers have escaped largely unscathed. However, portfolio managers and investors operating in the alternative investment space are subject to the same behavioral heuristics as any other economic actor. • The importance of these findings for manager selection is also reinforced by the study cited earlier indicating that managers are selected by “soft” factors other than performance statistics, leaving the playing field wide open to subjective selection criteria. (See Picking Winners). • See also “Dispersion: Measuring Market Opportunity,” S&P Dow Jones Indices, December 2013 and “At the Intersection of Diversification, Volatility and Correlation,” S&P Dow Jones Indices, April 2014.
  • 24. Behavioral Biases in Manager Selection • Specifically in the case of choosing managers, the following behavior may influence the choice, often to the detriment of the investor: • Framing – how a concept is presented to individuals matters in their decision making • Anchoring – becoming fixated on past information and using that information to make inappropriate decisions. Investors may become fixated on what the price of a security “should” be and hold on until the price is achieved. When forming an estimate, people start from an initial (possibly) arbitrary value and then adjust, but only slowly. One form of this is the slowness with which investors react to company announcements. • Representativeness – placing undue weight on more recent experience and ignoring the importance of long-term averages. This is sometimes known as the “law of small numbers.” One form of this bias is the “hot-hand” fallacy that attributes staying power to short term results. Another is to assume that a stock market rally will persist indefinitely. • Hindsight Bias – a particularly nasty bias in which events are viewed as more predictable after the result is known. • Confirmation Bias – people selectively evaluate information in ways that support their pre-conceived conclusions, ignoring or discounting information that may lead to questioning the conclusion. This is especially true if tied into a “narrative” or story, which people related to on a more visceral level than technical information. • Loss Aversion – people feel losses more acutely than gains and will take irrational steps to avoid this feeling. For example, people tend to hang on to loosing paper positions to avoid the pain of realizing actual losses. Loss aversion may also sometimes lead to inaction to avoid losses. • Herding – individuals and institutions find comfort in taking actions that conform to those of relevant reference groups. Even hedge funds seem to buy and sell the same stocks at the sametime, tracking each other’s investment strategies. Herding has been used to account for asset bubbles and for “affinity fraud” as in the case of Madoff. • A comprehensive summary of the field of behavioral finance is offered by Daniel Kahneman, Nobel Prize Winner in Economics, in Thinking, Fast and Slow, New York: Farrar, Straus and Giroux, 2011.
  • 25. Overconfidence: Only 25% of Managers can be in the top 25% of managers • As noted above, virtually every investment managers touts their ability to select top tier managers. However, the reality is that only 25% of them will select a top quartile fund while fully 50% will select a fund in the bottom half of the potential managers. The claims of investment managers are certainly partly explained by the competitive nature of attracting assets in the asset management industry. However, they also stem from a behavioral heuristic known as “overconfidence” that leads investment managers (along with most other people) to assume that they can defy the evidence that they are more likely to choose a poor performer than a top performer.
  • 26. AIMA Study The benefits for investors that result from including hedge funds in their portfolios include the following: •a source of diversification • substitutes for traditional stocks, bond investments. The paper is titled “Portfolio Transformers: Examining the Role of Hedge Funds and Diversifiers in an Investor Portfolio.” Hedge funds are touted as either portfolio diversifiers or investment substitutes (for traditional stocks and bonds). “Such hedge fund strategies ought to reduce the overall volatility (i.e. reduce the risk) of the portfolio’s public markets allocation, with a more attractive risk/reward profile. Other hedge fund strategies may have a low correlation to equity and credit markets and offer a higher probability of generating out-sized returns (albeit by taking on a higher level of risk). Employing this approach (where hedge funds take on the role of a substitute or complement the equity or fixed income portfolio) offers the plan a way of reducing the volatility (risk) within their public equity allocation, with little if any reduction in the portfolio’s total performance.” (Source: “Portfolio Transformers: Examining the Role of Hedge Funds and Diversifiers in an Investor Portfolio.”)
  • 27. Alternative Investments and Modern Portfolio Theory Modern portfolio theory (MPT) is a theory of finance that attempts to maximize portfolio expected return for a given amount of portfolio risk, or minimize risk for a given level of expected return, by choosing the proportions of various assets. First formulated by Harry Markowitz in his seminal article, “Portfolio Selection" in the 1952 Journal of Finance, MPT is a mathematical formulation of the concept of diversification in investing, with the aim of selecting a collection of investment assets that has collectively lower risk than any individual asset. This is possible, intuitively speaking, because different types of assets often change in value in opposite ways. Modern portfolio theory states that any asset that is uncorrelated (or more accurately not very highly correlated) to other assets in a portfolio places the resulting portfolio in a more favorable position on the efficient frontier, resulting in a portfolio that has a more favorable risk/return profile than the original portfolio.