The Role of Hedge Funds

in the Ongoing Financial Crisis

RESEARCH PAPER

MASTER PROJECT 2009

PROMOTED BY PROF. DR. CONSTANT BECKERS

Koen Van Overloop

Master of Financial Economics

Leuven School of Business & Economics

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KOE" VA" OVERLOOP

The Role of Hedge Funds

in the Ongoing Financial Crisis

ABSTRACT:

This paper analyzes the role of the hedge fund industry in the

current financial crisis. Empirical analysis of monthly hedge

fund index data indicates that the crisis has had a bigger impact

on hedge funds than vice versa. �o evidence is found that the

hedge fund industry bears more responsability for the global

financial turmoil than other private investors, institutional

investors or financial institutions. The data imply that hedge

funds even lowered their market exposure prior to the outbreak

of the subprime crisis, after severe losses in May 2006.

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Introduction

This paper uses monthly index data to analyze hedge fund performance during the 2007-09

financial crisis. The goal is to find out whether hedge funds are responsible for causing some

of the dramatic events of the financial turmoil or have simply been victims of the global

financial meltdown. The first chapter deals with everything there is to know about hedge

funds: characteristics, strategies and impact on the financial markets. The second chapter

presents the data and overall performance of the hedge fund industry between 1994 and 2008.

The final chapter deals with the role of the hedge fund industry in the ongoing financial crisis.

1. Hedge Fund Basics

Hedge funds pool large amounts of capital and use complex investment strategies to invest the

acquired capital. Hedge fund managers enjoy a great deal of freedom: they can take long

and/or short positions, use derivatives and leverage. Hedge funds attempt to find trades that

are almost arbitrage opportunities, so they basically try to earn low-risk profits by taking

advantage of price discrepancies (pricing mistakes) in the markets between securities. Once

mispriced assets are identified, they construct hedges for the positions taken. The result is that

the hedge fund benefits from the mispricing correction whilst being affected by little else.

1.1 Hedge Funds vs. Long-only Funds

Hedge funds essentially have the same economic function as mutual funds, they can privately

issue securities and their investors have to meet requirements set out by the financial

regulator. Hedge funds exist because mutual funds can not work with complex investment

strategies due to strict regulation. The extensive diversification restrictions and disclosure

requirements constrain their ability to exploit perceived opportunities and hedge positions

using derivatives and short-selling. Hedge funds cunningly avoid strict regulation by

operating from tax-havens, limiting the number of potential investors and giving up the right

to make public offerings. In return, hedge funds can take very large positions in the financial

markets with a limited amount of money because they can simultaneously take cash, long and

short positions, as opposed to traditional long-only funds that can only have cash and long

positions. Hedge funds are also allowed to make use of derivatives and leverage for the

purpose of taking both long and short positions in the market. Hedge funds may agree

contractually to disclose some types of information and to provide audited financial

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statements, if they decide that it helps them to recruite investors, but they are not required to

do so.

While mutual funds determine their relative return objectives by using benchmarks, hedge

funds set absolute return targets that are often independent of market conditions (Stulz, 2007).

Hedge fund investors can only withdraw their capital on a monthly or quarterly basis (the

latter are most common), which allows hedge funds to invest in less liquid assets and

securities. The management compensation structures differ as well: mutual funds usually

charge a management fee of a few percent of the managed capital, hedge funds on the other

hand usually charge a fixed fee of ±2% of the managed capital plus a variable fee of ±20% of

any earnings over and above the return target (Strömqvist, 2009).

1.2 Hedge Fund Strategies

Hedge Fund Research Inc. classifies hedge funds into 4 major categories: Equity Hedge,

Event-Driven, Macro and Relative Value (HFR, 2009). Equity Hedge strategies take both

long and short positions in equity and equity derivative securities. Decision are made using

both fundamental and quantitative techniques and strategies can be very diversified or very

focussed on specific sectors. The Equity Hedge category includes strategies like Equity

Market Neutral, Fundamental Value and Short Bias. The second hedge fund category, Event

Driven, consists of funds that take positions in companies that are involved in corporate

transactions like mergers, restructurings, tender offers, shareholder buybacks or companies

that are in financial distress. Event Driven funds are mainly exposed to the credit and equity

markets. The Event Driven category includes strategies like Distressed/Restructuring, Credit

Arbitrage and Merger Arbitrage.

The third category, Macro, consists of funds that make investment decisions by observing

economic variables and by trying to predict the impact of movements in these variables on

equity, currency and commodities. There are some similarities to other categories: like the

first category (Equity Hedge), Macro strategies can use equity securities. They also

sometimes use techniques similar to the ones the Relative Value category (the 4th major

category) employs. Macro strategies distinguish themselves from these categories through

their focus on the underlying economic variables rather than simple pricing discrepancies

between securities.

Relative Value, the last category, mainly consists of fixed income strategies that exploit

pricing and valuation discrepancies in the complex relationship between multiple securities.

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These strategies are often quantitatively driven as they measure the relationship between

instruments in order to identify positions where the spread creates an attractive opportunity.

The hedge fund industry has grown exponentially over the last decade. In 1996,

approximately 2000 hedge funds managed about $135bn, two years ago over 10 000 hedge

funds together managed more than $2,000bn. Hedge funds did not only increase in average

size but the range of strategies adopted also evolved. Figure 1 shows how the industry’s

Assets-Under-Management (net market value in dollars) are distributed over the various

hedge fund strategies. Ten years ago, one third of all hedge funds were global macro funds.

Nowadays global macro funds account for only a small share of the industry, as the most

common strategies are equity-based arbitrage strategies, attempting to track down market

mispricing.

Figure 1: Distribution of total industry-managed capital over strategies (1994-2008)

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

1994 1996 1998 2000 2002 2004 2006 2008

Short Bias

ConvArbitrage

Man Futures

Multi-Strategy

Eq Mkt Neutr

Emerging Mkts

Fix Inc Arbitr

Event Driven

L/S Equity

Global Macro

Source: Credit Suisse / Tremont historical hedge fund sector weights.

1.3 Impact on Financial Markets

Hedge Fund Research estimated that global hedge fund capital in september 2008 was $1.72

trillion. Hedge funds are very active and agressive traders that operate with large sums of

money, which is exactly why the hedge fund industry, and sometimes even an individual

fund, can have a significant impact on financial markets, despite the fact that it is a lot smaller

than the mutual fund industry. Hedge funds have two functions in financial markets:

arbitrager and liquidity provider. Both functions have potential positive and negative effects.

As arbitragers, hedge funds look for mispricings, which they exploit when they occur, hereby

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improving pricing and market efficiency. Unlike most other players, hedge funds are very

active and constantly buying and selling, which helps to provide increased liquidity and

efficient pricing in the markets. The flexibility of hedge funds can also create problems, as

high degrees of leverage entail serious risks: high leveraged funds are more likely to fail if

wrong investments are made. High leverage also increases the risks for the counterparties of

the hedge fund, in that case failure of the fund can have contagion effects that spread fast in

the financial system. The risks linked to high leverage are not the only factor that hedge funds

have to deal with: their extensive use of derivatives is also potentially dangereous. Derivatives

allow hedge funds to take large and risky positions in the market with only a small amount of

capital, this way managers can obtain additional leverage.

1.4 Accusations of Market Manipulation by Hedge Funds

Over the past 20 years, hedge funds were often accused of market manipulation: critics said

that high-leveraged hedge funds used speculative attacks to manipulate asset prices and

financial bubbles. Large scale speculative attacks inject a great deal of uncertainty in the

financial system and often generate herd behaviour. The use of derivatives and high leverage

in the hedge industry makes it possible even for single hedge funds to adopt immense

positions on the market for only a small capital contribution. Few outsiders know exactly how

much capital hedge funds hold, what strategies they use and how much leverage is used. This

veil of secrecy under which the hedge fund industry has operated does not facilitate

investigations about its role in any financial crisis (Trejos, 2008). Four important financial

crises of the last 20 years will be briefly discussed, with a focus on hedge fund involvement.

(a) European Currency Crisis in 1992

The currency crisis in 1992 is a perfect example of how the behavior of an individual hedge

fund can have a profound influence on prices. Quantum Fund, a global macro fund lead by

George Soros, speculated against several fixed European exchange rates in the early 1990s.

Soros was convinced that the exchange rates did not correspond with the macroeconomic

conditions in those particular countries. When Quantum Fund sold large volumes of currency

in 1992, Sweden and the UK were forced to abandon the fixed exchange rates and the value

of these currencies declined rapidly. Quantum Fund was able to make billions and Soros’

speculative attacks came under heavy criticism. Soros responded that the valuation of the

currencies was obviously incorrect and an adjustment of the currency prices was bound to

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occur sooner or later. While it is true that the speculative attacks of Quantum Fund had a

significant impact on currency prices, this alone can hardly be labeled ‘manipulation’ as the

bubble was obviously the result of an erroneous monetary policy and a price adjustment was

needed to bring the currency prices closer to their fundamental values.

If global macro funds artificially created the bubble for their own gain, then strong positions

taken right before the bubble bursted should pay off in the form of very high fund returns.

Yet, this strong increase is only noticeable in returns of Quantum Fund and not in the global

macro index. The global macro index increased with less than 5% during the entire currency

crisis and the subsequent months (the 2nd half of 1992). It is therefore reasoneable to assume

that the average global macro hedge fund did not abnormally benefit from the 1992 currency

crisis (Strömqvist, 2009).

(b) Asian Crisis in 1997

Several South-East Asian countries had large deficits on their current accounts in the mid

1990s. Combined with their fixed exchange rates against the US dollar this caused a financial

bubble to develop. The bubble exploded after Thailand devaluated its currency in the summer

of 1997, quickly followed by Malaysia and South-Korea, with dramatic price effects on the

financial markets.

Figure 2: Cumulative returns, Asian crisis (index May 1997 = 100)

20

40

60

80

100

120

140

160

Jul 1997 Jan 1998 Jul 1998 Jan 1999

Hedge Fund index Emerging Markets index Global Macro index

Source: Hedge Fund Research Inc.

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Hedge fund performance in this period is shown in Figure 2 and presents a positive and

stabile growth in returns, although performance was not very good compared to the previous

years. Emerging Market hedge funds performed very bad: cumulative returns had dropped

with 40% between May 1997 and September 1998. The bursting of the financial bubble

caused major asset price adjustments and some market participants accused hedge funds of

collectively speculating against the Asian economies. These allegations were even

investigated in 1998 by the IMF (Strömqvist, 2009). However, Eichengreen et al (1998) did

not found evidence of a collective attempt by hedge funds to undermine the Asian economies

through herd behavior, speculative attacks or positive feedback trading. Fung & Hsieh (2000)

used regression analysis to test for negative correlation between Asian currency innovations

and hedge fund returns, however the results did not indicate any involvement of hedge funds

in collective speculative attacks on Asian markets. Lindgren (1999) concluded that hedge

funds did not play a prominent role in the Asia crisis; the financial bubble bursted as

international investors panicked and quickly extracted all their capital out of South-East Asia.

(c) Long-Term Capital Management (1998)

Long-Term Capital Management was a well-known arbitrage hedge fund that exploited

mispricings, mainly in bond markets, but almost went bankrupt in August 1998. At that time,

the fund had an extremely high degree of leverage of 25 times the value of the equity. LTCM

got in trouble when market conditions changed radically after the Russian financial collapse.

In the end, the Federal Reserve was forced to intervene in order to ensure financial stability by

bailing out LTCM. The collapse of LTCM showed the potential systemic risk posed by the

hedge fund industry. Bankrupt hedge funds with a high degree of leverage can drag down

other funds and market counterparts in their fall, for example when large open positions have

to be liquidated at fire sale prices. This could seriously damage the counterparty and also

affect the value of similar assets in the markets. These direct losses are catastrophical if they

cause more defaults or threaten systemically important institutions. Other market participants,

besides creditors and counterparties of the defaulting firm, can be affected indirectly through

adjustments of asset prices, liquidity strains and changes in market uncertainty (Bernanke,

2006).

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(d) Dot-com Bubble (2000-01)

An IT-related speculative bubble had been developing on the Western stock markets since

1995 as the new Internet-related sector experienced explosive growth and increasing

popularity. The prices of dot-com shares kept rising throughout 1999 and reached extremely

high levels in March 2000. The market trend then suddenly reversed as investors realized that

the market values of shares were disconnected from the fundamental values and prices started

to decrease rapidly.

Figure 3: Cumulative returns, Dotcom crisis (index Jan 1999 = 100)

70

80

90

100

110

120

130

140

150

160

Jan 1999 Jul 1999 Jan 2000 Jul 2000 Jan 2001 Jul 2001

Hedge Funds MSCI World Russell 3000 Global Macro

Sources: Hedge Fund Research Inc. & Thomson Datastream

Figure 3 shows something interesting: the hedge fund index grows at a similar rate as equity

indices before the bubble bursted. By March 2000, investors started dumping assets in the

markets which caused prices of IT-related shares to fall heavily causing crashes on Western

stock markets. In comparison, the hedge fund index only lost a few procent in that month and

quickly recovered to show positive growth. This strange relationship between the indices

seems to indicate that hedge funds took significant long positions during the bubble but left

the stock markets before the turning point in March 2000. Brunnermeier & Nagel (2004)

found evidence supporting the hypothesis that hedge funds held long positions in IT-stocks

but reduced their holdings before the crash.

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This shows that hedge funds did not observe these events from the sideline but were actively

involved in these events, but it is very hard to find out whether they manipulated the financial

bubble and markets to make profits. There is some evidence for rejecting the hypothesis of a

collective speculative attack on IT-related shares. The fact that hedge funds increased their

holdings in IT-shares during the bubble shows that they did not consider themselves

influential enough to cause the market to crash. This is important: if hedge funds had not sold

their entire IT-holdings when the bubble bursted, they would not gain from going short and

thus push prices down because they still had long positions. So a collective speculative attack

by the hedge fund industry on IT-shares can be ruled out. It is impossible to say something

about the involvement of specific individual hedge funds (Brunermeier & Nagel, 2004).

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2. Hedge Fund Performance Since 1994

2.1 Data

The data used are monthly rate of returns of global, regional and sectoral hedge fund indices,

provided by Hedge Fund Research Inc, a research firm on alternative investments. Data

before 1994 were excluded and the database does not include data prior to that year. The

unreliability of data before 1994 is extensively discussed by Fung & Hsieh (2000), Liang

(2000) and Li & Kazemi (2007).

Hedge fund data is generally of poor quality as it suffers from various biases of which

survivorship bias is the most prominent. Survivorship bias is often defined as the difference in

fund returns between the surviving funds and the dissolved funds (Ackermann et al, 1999) or

the difference between the returns of the surviving funds and all funds (Liang, 2000).

Backfilling bias is caused by the backfilling of historical returns when new funds are added to

the database (Eling, 2008). For example single strategy hedge fund returns, especially prior to

1994, are upwardly biased between 50 and 300 basis points per year according to various

academic papers on the subject (Ineichen & Silberstein, 2008).

The HFR dataset provides information about hedge funds both living and dead. It is known to

have a lower attrition rate compared to other frequently used databases such as TASS (see

Liang (2000)), which suggests that fewer dissolved funds are concluded compared to other

databases. Using the HFR database limits the problems caused by survivorship bias. HFR

tries to mitigate the problem of spurious inferences caused by survivorship-related issues a la

Brown et al. (1992), (1999) by including data on both living as well as dead hedge funds.

2.2 Overall Performance between 1994 and 2008

Hedge funds on average have performed well over the last 15 years compared to mutual funds

or to the whole stock market (Strömqvist, 2009). Table 1 presents the descriptive statistics of

the hedge fund indices: the first panel for all hedge fund strategy indices, the second panel for

the funds of funds index and the last panel for 5 passive benchmark indices. The MSCI World

Index contains a number of 'world' stocks from all developed markets (as defined by MSCI)

and serves as the worldwide equity market proxy. The index is a common benchmark for

global stock funds and securities from 23 countries are included. The MSCI World ex US

Index excludes the United States and MSCI Europe contains only European stocks). All

MSCI indices used here are for the period 1994-2008 and were calculated in US dollar. The

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J.P. Morgan Global Government Bond Index contains bonds issued worldwide by national

governments and this paper uses this index as a proxy for a global risk-free rate of return. The

remaining two benchmarks are two American indices (NYSE Composite Index and S&P500

Composite Index) and are both considered important worldwide.

Table 1: Descriptive Statistics for Monthly Returns Strategies & Benchmarks (1994-2008)

Mean Return

(%)

St. Dev (%)

Skew-ness

Excess Kurtosis

Jarque-Bera prob.

Mean Excess Return

Sharpe Ratio

Mean Diff.

Return

Mkt. Share3

All Hedge Funds 1 0.78 2.13 -0.70 2.71 0.00 0.67 0.31 0.57 67 %

Distressed 0.73 1.81 -1.82 6.71 0.00 0.62 0.34 0.54 6.1 %

Emerging Mkts 0.68 4.00 -2.07 12.83 0.00 0.57 0.14 0.39 12 %

Eq Long/Short 0.89 2.72 -0.21 2.37 0.00 0.77 0.28 0.65 8.7 %

Eq Mkt. Neutral 0.55 0.94 -0.21 1.50 0.00 0.44 0.47 0.40 2.1 %

Event Driven 0.84 2.02 -1.40 4.58 0.00 0.72 0.36 0.63 6.3 %

Fix Inc Arbitr. 0.46 1.93 -5.10 36.77 0.00 0.35 0.18 0.26 4.3 %

Global Macro 0.79 1.99 0.09 1.01 0.02 0.68 0.34 0.59 3.6 %

Multi-Strategy 0.47 1.26 -3.26 17.63 0.00 0.36 0.29 0.31 7.0 %

All Fund of Funds 2 0.47 1.83 -0.69 3.57 0.00 0.36 0.20 0.28 33 %

Benchmark Indices

MSCI World 0.32 4.54 -0.87 4.41 0.00 0.21 0.05 0.00

MSCI World ex US 0.23 4.69 -0.70 2.65 0.00 0.12 0.03 -0.10

MSCI Eur 0.42 4.94 -0.74 2.50 0.00 0.30 0.06 0.08

JPM Glob Gov Bonds 0.11 2.03 0.27 -0.24 0.27 0.00 0 -0.09

NYSE Comp. 0.50 4.61 -1.17 5.95 0.00 0.39 0.08 0.18

S&P 500 Comp. 0.47 4.81 -0.89 4.59 0.00 0.36 0.07 0.14

Sources: Barclayhedge.com, Hedge Fund Research Inc. and Thomson Datastream. 1 Fund weighted composite

index that includes 2000 constituent funds, excl. funds of funds). 2 Fund of funds composite index that includes 800

constituent funds, excl. hedge funds). 3Market share = % of total industry-managed assets (hedge funds + funds of

funds, in $) managed by funds of that strategy (in Q2 2008). Retrieved on March 11, 2009 from

http://www.barclayhedge.com/research/indices/ghs/ mum/hf_ Money_Under_ Management.html.

Columns 2 to 5 of Table 1 show the first four moments of the return distribution: the mean,

standard deviation, skewness and excess kurtosis (kurtosis minus 3). Column 6 shows the

Jarque-Bera probability that the returns are normally distributed. Column 7 shows the mean

excess return (the average difference between the return and the risk-free rate of return) that

was used to calculate the Sharpe ratio’s in Column 8. The Sharpe ratio (or reward-to-

variability ratio) is a measure of excess return, or risk premium, per additional unit of risk.

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Sharpe’s (1966) original index is defined as follows:

where is the asset return, is the risk free rate of return. The Sharpe ratios in column 8

were calculated using the mean monthly return of fund or benchmark index as return R, the

mean monthly return on the JPM Global Government Bond Index as a proxy for the risk-free

rate of return and the standard deviation of the monthly index/fund returns . Column 9 of

Table 1 presents the mean differential return, the excess return over a benchmark portfolio

with the same risk, defined as:

.

The MSCI World Index was used as world equity market proxy. The mean differntial return is

an alternative for the Sharpe ratio, and in most cases will not generate qualitatively different

results as the Sharpe ratio, but the oucome can slightly differ when you make rankings of

funds or strategies. The global fund weighted index for the hedge industry generated a mean

monthly return of 0.78%, which is about 9.36% annually (assuming that investors can only

reinvest profits or withdraw capital on an anual basis), while Funds of Funds generated a

mean monthly return of 0.47% (5.64% annually).

The best performing strategies were Equity Long/Short (0.89% monthly, 10.68% annually),

Event Driven (0.84% monthly, 10.08% annually) and Global Macro (0.79% monthly, 9.48%

annually). The least best performing hedge fund strategies are Fixed Income Arbitrage (0.46%

monthly, 5.52% annually) and Multi-Strategy (0.47% monthly, 5.64% annually). The

strategies from the Equity Hedge category, Equity Long/Short and Equity Market Neutral,

performed well relative to the equity benchmarks (MSCI World and S&P 500). The Fixed

Income Convertible Arbitrage strategy was one of the least best performing hedge fund

strategies, but the strategy still performed very well relative to the fixed income benchmark,

the JPMorgan Global Government Bonds Index (0.11% monthly, 1.32% annually).

It is clear that hedge funds on average generate higher returns than the market benchmarks,

but its also important to see how volatile these returns are compared to the benchmarks. The

global fund weighted index has a standard deviation little over 2%, which is about the same as

the standard deviation of the bond market benchmark and half of the equity market

benchmark standard deviations. So hedge funds on average do not only generate higher

returns, but these returns are also significantly less volatile than the market returns. The

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performance measurement results provide significant evidence of superior hedge fund

performance over longer periods of time: both hedge funds and funds of funds generate

relatively high returns with low volatility when compared to the benchmarks.

Skewness, a measure of the asymmetry of the returns’ probability distribution, is negative for

all hedge fund strategies, except for Global Macro strategies (skewness close to zero). Fixed

Income Convertible Arbitrage strategies show very negative skewness. Kurtosis is a measure

of the peakedness of the returns’ probability distribution: a high kurtosis distribution has a

sharper peak and long fat tails, while a low kurtosis distribution has a more rounded peak and

short thin tails. The normal distribution has a kurtosis of 3, so it is more interesting to observe

the excess kurtosis (kurtosis minus 3). The bond market benchmark is slightly platykurtotic,

meaning that it has a slightly negative excess kurtosis. All other benchmarks and hedge fund

strategies are leptokurtotic, meaning that they have a positive excess kurtosis. The Equity

Market Neutral and Global Macro strategies are slightly leptokurtotic while most strategies

have very leptokurtotic. Emerging Markets, Fixed Income Convertible Arbitrage and Multi-

Strategy have very high excess kurtosis, ranging from 17.63 to 36.77. It was already obvious

that the returns of most hedge funds and funds of funds are not normally distributed. This is

confirmed by the Jarque-Bera normality test results: the probabilities that returns are normally

distributed are equal to or close to zero for all benchmarks and strategies, except for the bond

market benchmark (p-value = 0.27). The Sharpe ratio, which takes investment risk into

account, shows that all hedge fund strategies offer a good tradeoff between return and risk,

relative to the benchmarks. The hedge fund strategies with the best Sharpe ratios are Equity

Market Neutral (0.47), Event Driven (0.36), Distressed (0.34) and Global Macro (0.34). The

lowest Sharpe ratio is obtained by Emerging Markets (0.14) and Fixed Income (0.18). Most

hedge fund strategies provide a very high Sharpe ratio compared to the benchmark indices.

Table 2 presents the correlations of hedge fund strategies and the market benchmark indices.

Hedge funds in general show strong positive correlation with equity market indices: between

0.4 and 0.5, and weak negative correlation with the bond market benchmark (-0.09). The

strategies with very strong equity market correlations (> 0.5) are Distressed, Event Driven,

Equity Market Long/Short, Fixed Income and Multi-Strategy. Equity Market Neutral and

Global Macro strategies show the weakest equity market correlations: 0.25 and 0.26. So these

two strategies managed to be partially equity market independent, but did not succeed to be

100% market neutral.

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Table 2: Correlations Strategies & Benchmarks (1994-2008)

MSCI WORLD

MSCI EX US

MSCI EUR

JPM GGB

NYSE

S&P

500

DISTRESSED 0.56 0.55 0.56 -0.05 0.57 0.53

EMERGING MKTS 0.45 0.45 0.44 -0.05 0.42 0.40

EQ LONG/SHORT 0.51 0.49 0.49 0.00 0.47 0.49

EQ MKT NEUTR 0.25 0.23 0.24 -0.01 0.29 0.26

EVENT DRIVEN 0.58 0.54 0.55 0.00 0.58 0.56

FIX INC. ARBIT 0.51 0.48 0.49 0.03 0.55 0.50

GLOBAL MACRO 0.26 0.27 0.31 0.10 0.23 0.22

MULTI-STRAT. 0.56 0.55 0.56 -0.02 0.56 0.52

ALL HEDGE FUNDS 0.46 0.47 0.45 -0.09 0.45 0.42

FUNDS OF FUNDS 0.52 0.52 0.52 -0.04 0.48 0.47

Sources: Hedge Fund Research Inc. and Thomson Datastream

Table 3 shows the correlations of hedge fund strategies and market indices for the years in the

sample period when the general market climate was bullish (1994-1999, 2002-2006), Table 4

on the next page for the years in the sample period when the market climate was bearish

(2000-02, 2007-09). When comparing both tables, the first remarkable observation is the fact

that the correlations of hedge fund strategies with global equity markets are generally a lot

stronger during bearish periods than during bullish periods! Even the correlation of Equity

Market Neutral with equity markets increases from 0.22 to 0.27, although this is a moderate

increase compared to most other strategies.

Table 3: Correlations in Bull Markets (1994-99, 2002-06)

MSCI WORLD

MSCI EX US

MSCI EUR

JPM GGB

NYSE COMP.

S&P 500 COMP.

DISTRESSED 0.46 0.42 0.44 0.00 0.51 0.46

EMERGING MKTS 0.37 0.35 0.32 -0.08 0.38 0.35

EQ LONG/SHORT 0.45 0.38 0.38 0.03 0.45 0.47

EQ MKT NEUTR 0.22 0.19 0.24 0.07 0.24 0.23

EVENT DRIVEN 0.51 0.43 0.43 0.04 0.54 0.53

FIX INC. ARBIT 0.42 0.36 0.38 0.12 0.46 0.44

GLOBAL MACRO 0.34 0.33 0.37 0.11 0.33 0.31

MULTI-STRAT. 0.48 0.47 0.49 -0.03 0.47 0.43

ALL HEDGE FUNDS 0.40 0.38 0.37 -0.09 0.44 0.39

FUNDS OF FUNDS 0.44 0.40 0.41 -0.01 0.44 0.42

Sources: Hedge Fund Research Inc. and Thomson Datastream

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Table 4: Correlations in Bear Markets (2000-02, 2007-09)

MSCI WORLD

MSCI EX US

MSCI EUR

JPM GGB

NYSE COMP.

S&P 500

DISTRESSED 0.63 0.67 0.66 -0.16 0.55 0.58

EMERGING MKTS 0.59 0.65 0.67 0.00 0.49 0.48

EQ LONG/SHORT 0.53 0.59 0.59 -0.08 0.45 0.44

EQ MKT NEUTR 0.27 0.26 0.22 -0.15 0.25 0.34

EVENT DRIVEN 0.63 0.66 0.67 -0.09 0.56 0.58

FIX INC. ARBIT 0.61 0.62 0.61 -0.05 0.57 0.64

GLOBAL MACRO 0.03 0.08 0.11 0.05 -0.02 -0.03

MULTI-STRAT. 0.61 0.62 0.63 -0.05 0.56 0.62

ALL HEDGE FUNDS 0.49 0.54 0.51 -0.12 0.40 0.41

FUNDS OF FUNDS 0.58 0.65 0.65 -0.11 0.49 0.50

Sources: Hedge Fund Research Inc. and Thomson Datastream

Global Macro is the only hedge fund strategy that manages to offer its investors an actual

equity market ‘hedge’, as in offering them limited potential losses and at the same time

unlimited potential profits. During bullish periods, Global Macro funds show moderate

positive correlation with global equity markets (between 0.3 and 0.4) and weak positive

correlation with global bond markets (0.1). In contrast: during bearish periods the strategy

manages to become almost global equity market neutral: this correlation (MSCI World) drops

from 0.34 to 0.03. The correlation with the MSCI World ex US Index also goes down

drastically from 0.33 to 0.08, which is a smaller decrease than the decrease of correlation,

with MSCI World, but still a large decrease. Global Macro even shows slightly negative

correlation with U.S. equity markets during bearish periods: the correlation decreases from

0.31 to a staggering -0.03!

2.3 Market Adjusted Model

First, a market adjusted model is estimated, the regression specification is as following:

To estimate the market adjusted model, the excess returns (over the risk free return) of the

hedge fund strategy indices are regressed on the excess returns of a world equity market

benchmark index: the MSCI World Index. The above model was also estimated with

additional benchmarks for bonds (JPMorgan GGB index) and commodities (Goldman Sachs

Commodity Index indices) but these coefficients were nowhere near significant.

16

The CAPM model predicts that all α’s will be equal to 0. According to the CAPM only the β’s

should matter, as they measure the sensitivity of the sector returns relative to the global stock

market returns. Estimation results are presented in Table 5: the estimated alpha’s can be found

in column 2, the beta’s and Adjusted R² can be found in columns 3 and 4.

Table 5: Market Adjusted Model (1994-2008)

α

β1

Adj. R²

DISTRESSED 0.55 ** 0.36 ** 0.40

EMERGING MARKETS 0.47 0.51 ** 0.30

EQUITY LONG/SHORT 0.69 ** 0.42 ** 0.37

EQUITY MKT NEUTRAL 0.40 ** 0.21 ** 0.20

EVENT-DRIVEN 0.64 ** 0.38 0.43

FIXED INC ARBITRAGE 0.28 0.34 ** 0.37

GLOBAL MACRO 0.63 ** 0.24 ** 0.19

MULTI 0.30 * 0.30 ** 0.36

FUND WEIGHTED COMP 0.59 ** 0.36 ** 0.36

FUND OF FUNDS 0.29 0.34 ** 0.37

Sources: Hedge Fund Research Inc. and Thomson Datastream.

*(* *) indicates significance at the 5 % (1%) level

Strong evidence of superior hedge fund performance is found using the market adjusted

model: all estimated alpha’s are positive. The alpha of the fund weighted composite index

(which represents the entire hedge fund industry) is positive and statistically significant at the

1% confidence level. Five strategies (Distressed, Equity L/S, Equity Market Neutral, Event

Driven, Global Macro) are statistically significant at the 1% confidence level and one strategy

at the 5% confidence level (Multi-Strategy). The Fund of Funds index generates a positive

alpha but it is not statistically significant. The third column of Table 5 presents the beta

estimations, which were all statistically significant at the 1% confidence level with the

exception of the Event-Driven beta. Equity Market Neutral (0.21) and Global Macro (0.24)

have the lowest beta, Emerging Markets (0.51) and Equity Long/Short (0.42) have the highest

beta. It is quite obvious that none of the strategies comes anywhere near total market

neutrality.

The Adjusted R² indicates the fraction of variance in the returns that can be explained by

innovations in the model factors, so basically it tells us to what extent systematic risk explains

the hedge fund strategy returns. The Adjusted R² varies between 0.19 (Global Macro) and

17

0.49 (Distressed). The Fund Weighted Composite index has an Adjusted R² of 0.36, so 36%

of the variance of its returns can be explained by innovations in the MSCI World index, the

global equity market benchmark. The R² of the Fund of Funds index is about the same. So we

can say that a significant part of hedge fund returns depends on the global equity market

returns but the industry also generates a signifcant positive return that can not be explained by

the returns of global equity markets. For the strategies, the model is quite powerful for

Distressed, Equity Long/Short, Event Driven, Fixed Income Arbitrage and Multi. These

results are as expected, as it was already shown in the previous section that Global Macro

Hedge Funds & Equity Market Neutral Funds had weak correlation with global equity

markets, which implies low systematic (or market) risk and thus a low R². (1-R²) can be

interpreted as the idiosyncratic risk with respect to a particular hedge fund strategy. The low

value of R² does not necessarily mean that the CAPM predictions are not valid, it simply

suggests that the strategy returns are characterized by a large idiosyncratic risk component.

2.4 Measurement of Performance Persistence

The estimated market adjusted model in the previous section provided a positive and

significant α for 5 of the 8 hedge fund strategies. Does this automatically imply that hedge

fund returns are characterized by performance persistence? A way to find out whether there is

performance persistence is to test if past performance is a good predictor for performance in

the next period (see e.g. Grinblatt & Titman 1993, Kahn & Rudd 1995 and Brown et al.

1999). The statistical significance of the relationship between performance in a certain period

and performance in the previous period can be established on the basis of ex post values,

using the following regression:

with and respectively representing the returns in the periods t and t-1. Returns during

the current period are regressed on the returns of the previous period, a positive significant

slope coefficient indicates performance persistence. The statistical significance of the β’s can

be tested using the T-statistic: a T-value greater than 1.96 (2.57) indicates significant

persistence at the 5% (1%) confidence level. α is the part of the return that can not be

explained by the return of the previous period. Hedge fund strategies that are faily illiquid by

nature (e.g. fixed income-convertible arbitrage) are expected to show higher persistence than

more liquid fund. Short-term persistence is reported by nearly all studies but evidence for

18

long-term persistency is mixed. For each fund strategy, estimations were done using monthly

returns (raw, excess over market and over riskfree-rate) for horizons of 1, 3, 6 and 12 months,

can be found in the tables in the appendix. Performance persistence has been very high over

the last 2 years (2006-08) with a significant β (1% level) of 0.48, also the Adjusted R² was

relatively high compared to other subperiods. Monthly and semi-annual Equity Hedge returns

are persistent over the whole sample period, as shown by the positive and significant β’s (at

the 1% confidence level). The Global Macro category generates large and highly significant

α’s (1% level) for the whole sample period, for all subperiods and over all horizons. During

the total sample period, Global Macro funds generate returns that are persistent, both in the

short and the long run, but that can not be predicted just by looking at their past performance.

Clearly there must be other variables that can help to explain these high returns.

The relatively low R² in the estimation results of the market adjusted model (see previous

section) and the relatively weak correlation with the market benchmarks in Table 2 indicate

that the benchmark indices do not help to predict changes in Macro Hedge returns in the

following period. Macro-economic variables like interest rates, production, inflation and oil

prices are possibilities. Finally, Fixed-Income Arbitrage returns are not as high as the average

returns over all fund styles, but they are highly persistent for horizons of 1 month (β = 0.59), 3

months (β = 0.70) and 6 months (β = 0.96). The high values for the Adjusted R² indicate that

for any given period, the return can partially be predicted by using the return of the previous

period. Overall, the Adjusted R² are fairly low for all hedge fund styles, periods and horizons.

This could be explained by the fact that changes in hedge fund returns are caused by

combinations of multiple variables. Alternatively, the Adjusted R² are low because the OLS

estimation method relies on the normality assumption. It is generally known that hedge fund

returns are not normally distributed, but are negatively skewed.

Table 6 provides a complete overview of performance persistence for (excess) returns of all

fund strategies for horizons of 1, 3 and 6 months. The extensive results can be found in Table

7 and 8 in the Appendix. The table allows us to compare persistence of total monthly returns,

excess returns over the risk free rate and excess returns over the market rate (MSCI World

Index). Looking at monthly excess returns over the risk free rate (column 6 of Table 6), the

hedge fund industry shows persistent performance over the total sample period and mainly in

bullish markets; the same is found for Funds of Funds. Distressed, Equity Long/Short and

Event-Driven strategies also show performance persistence for the total sample period and in

19

bullish markets. Fixed Income Arbitrage shows persistent performance for the total sample

period between 1994 and 2008. No evidence whatsoever is found for performance persistence

regarding the monthly excess returns over the market rate (MSCI World index) in column 7 of

Table 6, which can be thought of as alpha. The results discussed above point to the existence

of short-term persistence in total monthly returns, but little evidence is found for the existence

of long-term persistence in total monthly returns or persistence in monthly excess returns over

the risk free rate or the market rate.

Table 6: Performance Persistence Overview

MONTHLY RETURNS MONTHLY

EXCESS RETURN

1M 3M 6M RF RMSCI

Distressed 1994-2008 � � � � �

Bullish ↗ � � � � �

Bearish ↘ � � � � �

Emerg Mkts 1994-2008 � � � � �

Bullish ↗ � � � � �

Bearish ↘ � � � � �

Equity L/S 1994-2008 � � � � �

Bullish ↗ � � � � �

Bearish ↘ � � � � �

Eq. Mkt Neut. 1994-2008 � � � � �

Bullish ↗ � � � � �

Bearish ↘ � � � � �

Event-Driven 1994-2008 � � � � �

Bullish ↗ � � � � �

Bearish ↘ � � � � �

Fix Inc Arbitr 1994-2008 � � � � �

Bullish ↗ � � � � �

Bearish ↘ � � � � �

Global Macro 1994-2008 � � � � �

Bullish ↗ � � � � �

Bearish ↘ � � � � �

Multi-Strat 1994-2008 � � � � �

Bullish ↗ � � � � �

Bearish ↘ � � � � �

All Hedge Funds

1994-2008 � � � � �

Bullish ↗ � � � � �

Bearish ↘ � � � � �

Funds of Funds 1994-2008 � � � � �

Bullish ↗ � � � � �

Bearish ↘ � � � � �

The � symbol indicates performance persistence of the monthly (excess)

returns that is statistically significant at the ≤ 5% confidence level.

20

3. The Global Financial Crisis of 2007-2009

3.1 Subprime Mortgage Crisis

During the 1990ies, Western economies accomplished strong economic growth, booming

financial markets (for example the dot-com hype) and low interest rates. After the dot-com

bubble bursted in 2001, Americans considered real estate to be a good and safe investment.

The subsequent high speculative demand for houses pushed real estate prices through the

roof. The New York Times reported in September 1999 that Fannie Mae (biggest U.S.

underwriter of mortgages) had been under increasing pressure from the Clinton

Administration to expand mortgage loans among low and moderate income people. Banks

issued countless subprime mortgage loans, often floating rate debt, to people with no income,

no job or assets. Mortgages were bundled and securitized on large scale, then sold as Credit

Default Swaps, which were basically securitized mortgages with low risks. CDS were

designed to shift the default risk to a third party and were considered almost riskless.

Government-sponsored companies like Fannie Mae and Freddie Mac labeled CDS’s as near

risk free securities and sold huge amounts to financial institutions, investment funds, hedge

funds and pension funds worldwide. For some time, this was actually a win-win situation:

banks got a higher return on equity from savers, households and companies got more and

cheaper credit, and investment funds and institutional investors got higher returns.

In 2006, reality kicked in and the American real estate market started to deteriorate as

property prices plummeted. The effects for U.S. consumers were desastrous: millions of

subprime debtors experienced payment problems. In a bullish real estate market, subprime

debtors could simple sell their house to pay off their mortgage when they faced payment

problems and even make a profit on the sale. However, in the bearish real estate market, this

bail-out method does not work anymore, simply because property values unavoidably

decrease in the time period between purchase and sale. Many subprime debtors had to cease

payments which undermined CDS prices. In July 2007, investors suddenly lost all confidence

in CDS-back securities and in a wave of mass hysteria, investors and near-bankrupt

investment funds started unwinding positions and dumping their assets on the markets.

21

3.2 The Story of 2008-09

Confidence in the financial system ebbed and credit markets continued to seize up in 2008, a

year characterized by extreme market volatility and unprecedented worldwide government

intervention. Bear Stearns, one of the largest global investment banks and brokerage firms,

collapsed in March 2008 and was sold for peanuts to JPMorgan Chase. In September 2008,

the financial crisis deepened as global equity markets crashed and numerous financial

institutions and companies went bust. Lehman Brothers filed for Chapter 11 bankruptcy

protection and was hereby responsible for the largest bankruptcy in the history of the United

States. Lehman Brothers controlled approximately 5% of global prime brokerage business at

that time. Barclays agreed to purchase Lehman Brothers’ North-American activities, while

Merrill Lynch was sold to Bank of America.

September 2008 was also the scenery of an unprecendented wave of government intervention,

as the United States federal government bailed out AIG, Fannie Mae and Freddie Mac, while

Icelandic banks were nationalized and our national pride Fortis faced partial nationalization.

In the same month, the ‘investment bank era’ ended as Goldman Sachs and Morgan Stanley

became regular commercial banks. The U.S. government passed the Emergency Economic

Stabilization Act in October, which is commonly referred to as a bailout of the U.S. financial

system. The law authorized the Treasury department to spend up to $700 billion for

purchasing mortgage-backed securities and other distressed assets. Meanwhile, governments

worldwide implemented restrictions on short-selling and central banks started cutting interest

rates in an attempt to calm down the financial markets. In December, the largest investor

fraud ever was revealed as Bernard Madoff was arrested and accused of running an alleged

Ponzi scheme.

3.3 Hedge Fund Performance in 2008-09

The hedge fund industry had been spared throughout 2007, but the financial turmoil that

started in the summer of 2008 had a serious impact on hedge funds. Figure 4 on the next page

shows the cumulative returns of the HFRI Hedge Fund Index with two equity market

benchmarks, namely the MSCI World Index and the S&P 500 Composite Index.

22

Figure 4: Cumulative returns, index July 2007 = 100 (July 2007 – Dec. 2008)

50

60

70

80

90

100

110

Jul 2007 Nov 2007 Mar 2008 Jul 2008 Nov 2008

M S C I W o rld S & P 5 0 0 H ed ge F und Ind ex

S o urc e s : H e d ge F und R e se a rc h Inc . & Tho mso n D a ta s tre a m

The negative effect of the Lehman Brothers bankruptcy on the overall hedge fund industry

was mitigated by the fact that many hedge funds had started with prime broker diversification

after Bear Stearns collapsed (Credit Suisse Tremont Hedge Index LLC, 2009). Smaller hedge

funds that relied on only a few brokers were hit harder, resulting in significant losses for

hedge fund strategies with a large percentage of smaller funds. Convertible Arbitrage funds

were seriously affected by the global bans on short selling, but the overall impact on hedge

fund performance was limited because the measures were often of a temporary nature and

were only applied on new positions in the market. Government intervention provided

liquidity, especially for asset-backed securities, and could help to improve market conditions.

A possible investment shift from government bonds to asset-backed securities would create

new opportunities for the Relative Value hedge funds. The multi-billion dollar Madoff

scandal affected some individual hedge funds whose assets were managed by Madoff

Investment Securities. The scandal will also have an impact on all hedge funds, as it will most

likely lead to increased regulation for the entire industry in the nearby future, which could

boost investor confidence and help to end the industry’s asset outflows after it lost 29% ($582

billion) of its assets in 2008. The elevated market volatility had a de-leveraging effect on

many hedge funds and the unwinding of positions was reinforced by more restrictive lending

and higher borrowing costs because of the banking crisis (Strömqvist, 2009).

23

Figure 5: Cumulative Returns of Best & Worst Performing Strategies (Jul ’07 – April ’09)

-50

-40

-30

-20

-10

0

10

20

30

40

Jul 2007 Oct 2007 Jan 2008 Apr 2008 Jul 2008 Oct 2008 Jan 2009 Apr 2009

Convertible ArbitrageCS|T Hedge Fund Index

Dedicated ShortEmerging Markets

Equity Market NeutralManaged Futures

Source: Credit Suisse Tremont Hedge Fund Indices

Figure 5 presents the performance of winners and losers of the hedge fund industry in 2008.

Despite the bad performance of hedge funds as an asset class, there were still some strategies

that consistently performed well in 2008: Managed Futures, a sector that typically performs

well in bearish markets, generated an annual return of 18.33% and the Dedicated Short Bias

strategy generated an annual return of 14.87%. Managed Futures funds benefited from their

short positions in commodity and equity, and long positions in treasury bonds and US dollar

trades. Dedicated Short funds benefited from the sharp equity market downturn. However,

these two winners make up less than 5% of the hedge fund industry, the positive effect is

therefore not noticeable in the Broad Index (CS|T Hedge Index, 2009). The hedge fund

strategies that got hit hard included Convertible Arbitrage, Emerging Markets and Equity

Market Neutral. Emerging Markets funds (annual return -30.41%) generated strong negative

returns as a result of the strong US dollar and decreasing commodity prices. Convertible

Arbitrage funds (annual return -31.59%) were significantly affected worldwide by the

restrictions on the short-selling of equity.

Equity Market Neutral funds are the last in the list of losing sectors, which quite frankly

comes as a surprise. Their losses were almost exclusively caused by the Madoff scandal, as

several large Equity Market Neutral funds had their assets managed by Madoff Investment

Securities (CS|T Hedge Index, 2009).

24

3.4 The Role of Hedge Funds in 2008-09

It is really hard to say something meaningful about the role of hedge funds in the ongoing

financial turmoil, as they are not exchange traded funds. Only monthly returns reported by

hedge fund managers are available and Managers will not always report results honestly. One

can not even be sure whether a hedge fund manager actually employs the strategy that he

claims to employ. Also, nowadays equity markets can lose half of their total value in less than

a month. All these problems make monthly data pretty useless for analyzing causality. It is

impossible to say something about causality using regression analysis: we can not say whether

the plummeting equity markets pulled hedge funds down or vice versa.

We can start by wondering whether hedge funds are capable of threatening global financial

stability. Despite the exponential growth of the industry, hedge funds still only account for a

small fraction of total managed capital compared to mutual funds and pension funds. Major

market movements like in September/October 2008 are thus only possible when several types

of investors follow the same market trends. In December 2007, the largest hedge fund in the

world was JPMorgan Asset Management. Its managed capital at that time was only 2% of the

capital managed by Barclays Global Investors, the largest mutual fund in the world. Its

reasonable to assume that hedge funds can only have a limited influence on financial markets.

The strongest argument for the claim that the hedge fund industry did not drive the ongoing

financial crisis is the fact that it performed bad in 2008 (Strömqvist, 2009).

Fig. 6: "et Asset Value of Fund strategies for 2000-09 (Index Jan 1994 = 100)

0

100

200

300

400

500

600

700

Jan 2000 Jan 2002 Jan 2004 Jan 2006 Jan 2008

Emerging Markets

L/S Equity

Global Macro

All Hedge Funds

Source: Credit Suisse/Tremont Hedge Fund Indices

25

As you can see in Figure 6, net asset value of hedge funds started to decrease rapidly in 2008.

However, the fact that hedge funds have been affected by the financial crisis does not

necessarily rule out that they played an important role in the development of the banking

crisis. For example, the Bear Stearn funds were funds that had provided liquidity for the

complex credit instruments prior to their demise. Also, Bear Stearns collapsed because of

panic following massive short-sales and put option purchases in the days before the stock’s

price crashed. This could have been the work of one or more hedge funds with bad intentions,

because few other market players would be able to hide involvement: the lack of regulation in

the hedge fund industry is to blame for this loophole.

3.5 Systematic Risk During the Financial Crisis

It is only possible to say something about the role of hedge funds in the current financial crisis

if we can say something about their market exposure. According to a report issued by the

International Swaps and Derivatives Association (ISDA) in September 2006, the global

notional value of credit derivatives outstanding increased with 52% in the first 6 months of

2006 to an estimated $26 trillion. Hennessee Group LLC, an adviser to hedge fund investors,

noted in October 2006 that hedge funds had increased their exposure to credit derivatives and

it expressed concerns about the fact that many funds were inexperienced within the

derivatives markets. Hennessee also noted that the use of credit default swaps (CDS) had

become widespread in the early 2000s, by credit-oriented hedge funds and also increasingly

by long/short equity funds. Credit derivatives were the perfect instrument for a hedge fund to

lower the credit risk in its portfolio, however Hennessee was convinced that hedge funds

seriously under-priced credit risk (Hennessee Group, 2006).

The market adjusted model from the previous chapter was re-estimated but now for a 12-

month moving window for the period between January 2006 and December 2008. Figure 7

and 8 show estimation results of the 12-month rolling alpha and beta of the excess returns

(over risk free rate) for the hedge fund industry and funds of funds. The market adjusted

model estimation results showed that hedge funds have generated a significant positive alpha

between 1994 and 2008. Figure 7 shows that hedge funds managed to generate a significant

positive alpha throughout 2006 and 2007, but by early 2008 the industry’s alpha became

negative. The alpha rose briefly became positive again in September 2008, as hedge funds did

not experience a decline that was as strong as the equity market decline. However, it became

negative again in the last months of 2008.

26

Fig. 7: Rolling 12-m Alpha and Beta of Hedge Fund Excess Monthly Returns (2006-08)

-0.8

-0.4

0.0

0.4

0.8

1.2

Jan 2006 Jul 2006 Jan 2007 Jul 2007 Jan 2008 Jul 2008

Alpha Hedge Funds Beta Hedge Funds

Source: Hedge Fund Research Inc.

Fig. 8: Rolling 12-m Alpha and Beta of Fund of Funds Excess Monthly Returns (2006-08)

-1.2

-0.8

-0.4

0.0

0.4

0.8

1.2

Jan 2006 Jul 2006 Jan 2007 Jul 2007 Jan 2008 Jul 2008

Alpha Funds of Funds Beta Funds of Funds

Source: Hedge Fund Research Inc.

The hedge fund industry’s beta, a measure of the sensitivity of the industry’s returns to equity

market returns, the systematic risk, was 0.35 on average and remained fairly stabile between

2006 and 2008. Fund of Funds also generated a positive significant alpha between 1994 and

2008, however the alpha was significantly smaller than the alpha generated by the hedge fund

industry. The alpha of Funds of Funds reached a minimum in May 2006 of -0.8, as certain

strategies performed very bad in that month because of falling prices of stocks, oil and metals

(Bloomberg News, 2006). The bad performance in May 2006 can also explain the decreasing

27

beta in Figure 7: most likely hedge funds got more cautious after the losses suffered and

responded by lowering their market exposure. Apart from the negative alpha in May 2006,

funds of funds generated a significant positive alpha untill early 2008. However, as the crisis

continued to create turmoil on financial markets, the alpha became negative in March 2008

and kept on decreasing untill the end of the year. The Fund of Funds alpha reached a

minimum in December 2008 of -0.6. The beta of Funds of Funds also decreased in May 2006,

as with the hedge funds’ beta in Figure 7, remaining fairly low untill May 2007, when the beta

started increasing. Market exposure tripled between May 2007 and August 2007, right around

the period when the subprime mortgage crisis surfaced and the TED-spread (spread between

the short-term LIBOR rate and return on a ‘riskless’ Treasury Bill) skyrocketed. The beta of

funds of funds stabilized at the level of August 2007 (0.55) untill the end of 2008, when it

slightly decreased to 0.3.

Figure 9 to 12 show estimations of the 12-month rolling alpha and beta of the excess returns

(over risk free rate) of four hedge fund strategies: Emerging Markets, Equity Market Neutral,

Equity Long/Short and Global Macro. Emerging Markets funds were able to generate a

positive significant alpha (except for May 2006) up untill the end of 2007. The alpha was

even exceptionally high in the second half of 2007, but by early 2008 the alpha started

decreasing rapidly. The alpha of Emerging Markets became negative in the middle of 2008

and kept decreasing untill it reached -1 in December 2008. The beta in the beginning of the

period was around 0.6, reached a maximum of 1.2 in May 2006 but quickly decreased to 0.4.

This level was maintainted untill July 2007, after which the market exposure slightly

increased and stayed stabile around 0.5 untill the end of 2008. The alpha and beta of Equity

Market Neutral funds in Figure 10 are much more volatile than those of Emerging Markets.

Equity Market Neutral funds were able to generate a positive alpha up untill July 2007 (except

for May 2006). The alpha kept decreasing between July 2007 and March 2008, when it

reached a level of -0.5, but it recovered in the second half of 2008. The alpha became positive

again during the banking crisis and reached 0.45 in November 2008.

28

Fig. 9: Rolling 12-m Alpha and Beta of Emerging Markets Excess Returns (2006-08)

-1.5

-1.0

-0.5

0.0

0.5

1.0

1.5

Jan 2006 Jul 2006 Jan 2007 Jul 2007 Jan 2008 Jul 2008

Alpha Emerging Markets Funds Beta Emerging Markets Funds

Source: Hedge Fund Research Inc.

Fig. 10: Rolling 12-m Alpha and Beta Equity Market "eutral Excess Returns (2006-08)

-0.6

-0.4

-0.2

0.0

0.2

0.4

0.6

0.8

1.0

Jan 2006 Jul 2006 Jan 2007 Jul 2007 Jan 2008 Jul 2008

Alpha Equity Market Neutral Beta Equity Market Neutral

Source: Hedge Fund Researc Inc

The next month the Madoff scandal erupted and some important Equity Market Neutral funds

had money that was managed by Madoff’s company. Consequently, the alpha decreased

rapidly in December 2008. Looking at the beta in Figure 10, it is obvious that Equity Market

Neutral funds were all but market neutral between 2006 and 2008. The beta was very high in

May 2006, after which it rapidly decreased to 0.1. Equity Market Neutral funds managed to

maintain this level but the market exposure suddenly increased again in May and June 2007,

to 0.4. It was only by October 2008 that the beta of Equity Market Neutral decreased,

29

reaching 0.2 by December 2008. Figure 11 shows the rolling 12-month alpha and beta of

monthly excess returns of Equity Long/Short funds between 2006 and 2008.

Fig. 11: Rolling 12-m Alpha and Beta Equity L/S Excess Returns (2006-08)

-0.8

-0.4

0.0

0.4

0.8

1.2

Jan 2006 Jul 2006 Jan 2007 Jul 2007 Jan 2008 Jul 2008

Alpha Equity Long/Short Beta Long/Short

Source: Hedge Fund Research Inc.

The evolution of the Equity L/S alpha is similar to the alpha of Funds of Funds in Figure 8:

high in the first months of 2006 and decreasing sharply in May 2006, after which it quickly

recovers. Between June 2006 and December 2008, the alpha decreases at a fairly constant

rate, from 1 to -0.7. The evolution of the beta of Equity Long/Short is also similar to the

evolution of the Fund of Funds’ beta. Figure 12 shows the alpha and beta for the monthly

excess returns of Global Macro funds and clearly shows how well this strategy has performed

during the financial crisis. The alpha dropped from 0.5 to -0.75 between April and May 2006,

but the next month the alpha had increased back to 0.7. During the rest of the 2.5 years of the

period, Global Macro funds managed to generate a positive or slightly negative alpha. It is

remarkable that the worser the situation on the financial markets, the better Global Macro

funds performed. Global Macro funds experienced a significant decrease from 0.7 to 0.3

during the banking crisis in September 2008 but the next month the alpha rose sharply again,

ending at 0.5 in December 2008. The beta was 0.5 in January 2006 and increased rapidly in

May 2006. By June the beta of Global Macro funds had dropped to 0.25 and this level was

maintained untill June 2007, when the beta increased to 0.5. The beta remained stabile at this

level but started to decrease slowly in the first months of 2008, reaching 0.1 in December

2008.

30

Figure 12: Rolling 12-m Alpha and Beta Global Macro Excess Returns (2006-08)

-1.0

-0.5

0.0

0.5

1.0

Jan 2006 Jul 2006 Jan 2007 Jul 2007 Jan 2008 Jul 2008

Alpha Global Macro Beta Global Macro

Source: Hedge Fund Research Inc.

When looking at the previous six graphs, the same pattern can be observed: a high beta before

May 2006, a sharp decline during May 2006, a stabile period untill May/June 2007. Around

the time that the subprime crisis struck the financial markets, the beta of most hedge funds

increased slightly and then decreased slowly in the final 1.5 years. Most hedge funds were

clearly affected by the industry crisis in May 2006: Hedge Fund Research Inc. and Bloomberg

News reported that hedge funds showed the worst performance in this month since the

Dotcom crisis in 2000.

So it looks like most hedge funds responded by lowering their market exposure in the second

half of 2006 and the first half of 2007. It was almost impossible not to be affected by the

subprime crisis but overall it seems that the decrease of market exposure prior to the crisis is

the factor that made it possible for hedge funds to limit their losses in this period. However,

we know from Hennessee Group (2006) that Credit Arbitrage and Equity Long/Short funds

increased their exposure to credit derivatives in the first half of 2006. So it seems that these

hedge funds responded to the losses of May 2006 by lowering exposure to equity and

increasing exposure to credit default swaps and similar securities, that were considered more

safe at that time. This is very clear from the evolution of the beta of Equity Long/Short funds

in Figure 11: once the subprime crisis started mid 2007, these strategies paid the price for

their increased exposure to credit derivatives when their market exposure almost tripled

between May and August 2007 from 0.2 to 0.5.

31

So most of the hedge funds took the right decision when lowering their market exposure, but

certain strategies like Credit Arbitrage and Equity Long/Short chose the worst possible

securities to lower their market exposure. However, by looking at the beta for the whole

hedge fund industry in Figure 7, it can be concluded that the negative effects of the wrong

decisions made by a few strategies were not strong enough to drag the entire hedge fund

industry down. The beta of the industry slightly increased when the subprime crisis started but

by early 2008 the beta was lower and kept decreasing throughout 2008.

Keeping this in mind, it is hard to find support for the hypothesis that the hedge fund industry

would have been responsible for the steep decline of the financial markets. One might even

say that by limiting their market exposure prior to the outbreak of the subprime mortgage

crisis, hedge funds probably even confined the market downfall in some way. If hedge funds

had not lowered their market exposure, then the global financial crash might have been even

more extreme. If Credit Arbitrage and Equity Long/Short had not turned to credit derivatives

in 2006 to lower market exposure, the hedge fund industry would have performed even better

relative to the market.

32

4. Conclusion

Empirical analysis of monthly hedge fund index data indicates that the crisis has had a bigger

impact on hedge funds than vice versa. Hedge funds saw almost one third of their assets

disappear and performance in 2008 was the worst in recent hedge fund history (since 1994).

In the past 2 years, media often deemed hedge funds responsible for the major downturn in

financial markets by stating that the industry had taken too much risks. The results in this

paper present a different story: hedge funds took measures after the bad performance in May

2006 and lowered their market exposure. Despite the fact that some hedge fund strategies

sought refuge in credit derivatives, the industry’s systematic risk drastically decreased prior to

the subprime mortgage crisis that started mid 2007. We can only guess what would have

happened if the hedge fund industry had not taken these measures after May 2006. Maybe

they would have suffered more severe losses, this could have pushed financial markets even

deeper when the subprime crisis and the banking crisis in the fall of 2008 started.

No evidence is found that the hedge fund industry bear more responsability for the global

financial turmoil than other institutional investors and financial institutions. However, the fact

that hedge funds have been affected by the financial crisis does not necessarily rule out that

they played an important role in the development of the banking crisis. The herd behavior and

panic on the financial markets could easily have been exploited by individual hedge funds or

groups of hedge funds, for example by naked short-selling and phantom stock scams.

However, it would be wrong to judge the hedge fund industry based on alleged wrongdoings

of individual funds.

33

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