a global perspective

Hedge Fund Industry -a global perspectiveNino Veskovic

Contents  Introduction to Hedge Fund Industry  Some Words of Caution  Hedge Funds Strategies  A Comparison of Different Strategies  The Future Development  Conclusions  References

Source: Adapted from Preqin (2015)

Source: Adapted from Preqin (2015)

Hedge Fund Industry Assets Under Management - Historical Growth of Assets $3,000.00

Billions USD

$2,500.00 $2,000.00 $1,500.00 $1,000.00 $500.00 $1997 1999 2001 2003 2005 2007 2009 1st 3rd 1st 3rd 1st 3rd 1st 3rd 1st 3rd Qtr Qtr Qtr Qtr Qtr Qtr Qtr Qtr Qtr Qtr 2011 2011 2012 2012 2013 2013 2014 2014 2015 2015 Source: the figure is created with the data provided by BarclayHedge (2016a)

Number of Funds in the Lipper TASS Hedge Fund Live, Graveyard, and Combined Databases (February 1997 to August 2007). Number of Lipper TASS Funds Category Definition Live Graveyard Combined 1 Convertible Arbitrage 75 101 176 2 Dedicated Short Bias 17 20 37 3 Emerging Markets 175 174 349 4 Equity Market Neutral 149 182 331 5 Event Driven 257 247 504 6 Fixed Income Arbitrage 134 125 259 7 Global Macro 111 178 289 8 Long/Short Equity Hedge 771 947 1718 9 Managed Futures 173 356 529 10 Multi-Strategy 135 95 30 11 Fund of Funds 704 491 1195 Total 2701 2916 5617 Source: Adapted from Lo (2010)

Breakdown of Lipper TASS Live Funds by Category Multi-Strategy, 5% Managed Futures, 6%

Fund of Funds, 26%

Convertible Arbitrage, 3% Dedicated Short Bias, 1%

Long/Short Equity Hedge, 28%

Emerging Markets, 6%

Equity Market Neutral, 6% Global Macro, 4% Fixed Income Arbitrage, 5%

Event Driven, 10%

Convertible Arbitrage

Dedicated Short Bias

Emerging Markets

Equity Market Neutral

Event Driven

Fixed Income Arbitrage

Global Macro

Long/Short Equity Hedge

Managed Futures

Multi-Strategy

Fund of Funds

Source: Adapted from Lo (2010)

Breakdown of Lipper TASS Graveyard funds by Category Managed Futures, 12%

Multi-Strategy, 3%

Fund of Funds, 18%

Long/Short Equity Hedge, 33%

Convertible Arbitrage, 3% Dedicated Short Bias, 1% Emerging Markets, 6%

Equity Market Neutral, 6% Event Driven, 8% Global Macro, 6% Fixed Income Arbitrage, 4% Convertible Arbitrage

Dedicated Short Bias

Emerging Markets


Event Driven


Global Macro

Long/Short Equity Hedge

Managed Futures

Multi-Strategy

Fund of Funds


Attrition Rates The literature abounds in studies based on attrition rates in hedge funds industry (Lo, 2010; Getmansky, Lo & Mei, 2004; Bianchi & Drew, 2006; Malkiel & Saha, 2005; Liang, 2000; Amin & Kat, 2003; Brown, Goetzmann & Ibbotson, 1999; Chan, Getmansky, Haas, et al., 2005) Getmansky, Lo & Mei (2004) find that The TASS sample shows that attrition rates differ significantly across investment styles, from a low of 5.2% per year on average for convertible arbitrage funds to a high of 14.4% per year on average for managed futures funds. In order to develop a more precise measure that allows for cross-sectional variability in the likelihood of liquidation – as a function of fund characteristics such as assets under management and recent performance - Chan, Getmansky, Haas, et al. (2005) estimate a logit model for hedge-fund liquidations. The logit estimates and implied probabilities suggest that a number of factors influence the likelihood of a hedge fund’s liquidation, including past performance, assets under management, fund flows, and age. Given these factors, our estimates imply that the average liquidation probability for funds in 2004 is over 11%, which is higher than the historical unconditional attrition rate of 8.8%. Chan, Getmansky, Haas, et al. (2005) point out that poor performance leads to the graveyard database. Nevertheless Lo, (2010) argues that funds that are wildly successful are also more likely to leave the live database since they have less motivation to advertise their performance. That leads us to conclusion that the Graveyard database contains not only hedge funds with poor performance but also very successful funds. As noted by Lo (2010), this fact is supported by the fact that in some categories the average mean return in the Graveyard database is the same as or higher than in the Live database, e.g., Convertible Arbitrage, Equity Market Neutral, and Dedicated Shortseller.

Lipper TASS Status Codes for Funds in the Graveyard Database Status Code

Definition

1 2 3

Fund liquidated Fund no longer reporting Unable to contact fund

4

Fund closed to new investment

Fund has merged into another 5 entity 7 Fund dormant 9 Unknown* *Of the 2,916 funds in the Graveyard database, 80 did not have status codes assigned, hence we coded them as 9's ("Unknown")


Annual Frequency Counts of Entries into and Exits out of the Lipper TASS Hedge Fund Combined Database (February 1977 to August 2007)* Year

Existing Funds

New Entries

New Exits

Intra Year Entry and Exit

Total Funds

Attrition Rate (%)

1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007

0 4 6 8 12 15 21 30 45 53 76 109 143 189 305 417 578 838 1092 1337 1565 1842 2056 2336 2598 2998 3402 3954 4538 4743 4503

4 2 2 4 3 6 9 15 8 23 33 34 46 116 112 161 260 273 314 352 384 383 469 490 644 684 819 926 727 433 96

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 19 69 124 107 169 189 228 244 280 267 342 522 673 333

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 1 5 6 9 5 6 4 7 9 11 17 9 1

4 6 8 12 15 21 30 45 53 76 109 143 189 305 417 578 838 1092 1337 1565 1842 2056 2336 2598 2998 3402 3954 4538 4743 4503 4255

2.3 6.3 9.3 6.8 9.2 9.2 9.8 9.4 9.3 7.8 8.6 11.5 14.2 7.4

*The Lipper TASS Graveyard database did not exist prior to 1994' hence attrition rates are available only from 1994 to 2007. Table produced using unfiltered data. Source: Adapted from Lo (2010)

Some Words of Caution

The Survivorship Bias When a fund fails, it is often removed from a database, together with its performance history. Its removal creates a survivorship bias because the database contains only successful funds (Ibbotson et al. 2011).

Backfill Hedge funds tend to start reporting performance after a period of good performance, and that history of good performance (or backfill) may be incorporated into the database (Ibbotson et al. 2011).

Selection Bias It refers to not having a representative sample of funds. Back-end bias can also be a problem if hedge funds stop reporting after a bad month (Ibbotson et al. 2011). A hedge fund could stop reporting after it collects enough investors, which poses an issue for researchers as well.

Reporting Most hedge funds only report into one or two databases. As a result, every database covers a different subset of the hedge fund universe and different researchers may arrive at quite different conclusions simply because different databases were used (Kat, 2006).

Investing in Illiquid Assets Since many hedge funds invest in illiquid assets, their administrations have great difficulty generating up-to-date valuations of their positions (Kat, 2006). As shown in Brooks & Kat (2002), this will lead to very substantial underestimation of hedge fund risk, sometimes as high as 30-40%.

Available Data Since most data vendors only started collecting data on hedge funds around 1994, the available data set on hedge funds is very limited. Several business cycles occurred since then. The return generating process behind hedge funds is still very much a mystery and so far we have little idea what constitutes normal behavior and what not (Kat, 2006).

Funds Following the Same Type of Strategy May still Behave Very Differently Hedge fund investment strategies tend to be quite different from the strategies followed by traditional money managers. In principle, every fund follows its own proprietary strategy, which means that hedge funds are an extremely heterogeneous group (Kat, 2006).

Average correlations between individual hedge funds 1994-2001 MA

DS

EMN

CA

GM

L/S

EM

Merger arbitrage

0.45

0.30

-0.04

0.18

0.07

0.24

0.25

Distressed securities

0.30

0.39

0.18

0.28

0.15

0.32

0.14

Equity mkt. neutral Convertible arbritrage

-0.04

0.18

0.23

0.09

0.03

-0.02

0.05

0.18

0.28

0.09

0.28

0.09

0.23

0.08

Global macro

0.07

0.15

0.03

0.09

0.26

0.09

10.00

Long/short equity

0.24

0.32

-0.02

0.23

0.09

0.24

0.25

Emerging markets

0.29

0.14

0.05

0.08

0.10

0.27

0.52

Source: Adapted from Kat (2006)

Similar Indices from Different Index Providers May Behave Very Differently Given the heterogeneity of each style group and the fact that different databases contain many different funds, however, one can expect substantial differences between indices that aim to cover the same type of strategy (Kat, 2006).

Correlation between global macro hedge fund incices 1994-2001

ZURICH HENNESSEE HFR CSFB/TREMONT TUNA ALTVEST Source: Adapted from Kat (2006)

HENNESSEE

HFR

CSFB/TREMONT

TUNA

ALTVEST

VAN

0.47

0.46

0.29

0.28

0.37

0.12

0.8

0.66

0.39

0.52

0.35

0.73

0.52

0.77

0.55

0.52

0.5

0.35

0.37

0.08 0.51

The True Risk of Hedge Funds Tend to Be Seriously Underestimated A symmetrical distribution will have a skewness equal to zero, while a distribution that implies a relatively high probability of a large loss (gain) is said to exhibit negative (positive skewness. A normal distribution has a kurtosis of 3, while a kurtosis higher than 3 indicates a relatively high probability of a large loss or gain (Kat, 2006).

Sharpe Ratios and Alphas of Hedge Funds Can Be Highly Misleading There tends to be a clear relationship between a fund’s Sharpe ratio and the skewness and kurtosis of that fund’s return distribution. High Sharpe ratios tend to go together with negative skewness and high kurtosis. The main problem with Alpha lies in the choice of return generating factors (Kat, 2006). We indeed have a little idea what factors really generate hedge fund returns.

One Has to Invest at Least 20% in Hedge Funds for It to Make a Difference Kat (2006) points out that allocating 5% or 10% to hedge funds changes very little. Only if we invest 20% or more in hedge funds do we see significant changes in the standard deviation, skewness and kurtosis. However most investors invest between 1% and 5% in hedge funds.

Volatility Is Sometimes Desirable Many investors consider upside and downside deviations from the mean return to have very different qualities. Investors can earn large returns from upside volatility, so this “risk” is seen as very different from the downside volatility that causes investor losses. (Black, 2004) This brings to calculation of downside semivariance, where only negative returns are included in the standard deviation calculation. 𝑆𝑡𝑎𝑛𝑑𝑎𝑟𝑑 𝑑𝑒𝑣𝑖𝑎𝑡𝑖𝑜𝑛 = σ = 𝐷𝑜𝑤𝑛𝑠𝑖𝑑𝑒 𝑠𝑒𝑚𝑖𝑣𝑎𝑟𝑖𝑎𝑛𝑐𝑒 =

𝑛 𝑖=1

𝑟𝑖 − 𝑟𝑚𝑒𝑎𝑛 𝑛−1

𝑛 𝑖=1 𝑚𝑖𝑛

𝑟𝑖 − 𝑟 ∗ , 𝑜 𝑛−1

2

2

𝐷𝑜𝑤𝑛𝑠𝑖𝑑𝑒 𝑑𝑒𝑣𝑖𝑎𝑡𝑖𝑜𝑛 = 𝑑𝑜𝑤𝑛𝑠𝑖𝑑𝑒 𝑠𝑒𝑚𝑖𝑣𝑎𝑟𝑖𝑎𝑛𝑐𝑒

Sortino Ratio The purpose of risk management and subsequent risk measures is to avoid large downside risk, so a performance metric that punishes excessive positive returns while missing excessive downside risk is flawed. The Sortino ratio offers a better measure of risk (Rollinger & Hoffman, 2013). As shown in the paper by Sortino & Price (1994) Sortino ratio offers valuable information not available from traditional risk measures. 𝑟𝑒𝑡𝑢𝑟𝑛𝐴𝑐𝑡𝑢𝑎𝑙 − 𝑟𝑒𝑡𝑢𝑛𝑅𝑖𝑠𝑘−𝑓𝑟𝑒𝑒 𝑆𝑜𝑟𝑡𝑖𝑛𝑜 𝑟𝑎𝑡𝑖𝑜 = 𝑑𝑜𝑤𝑛𝑠𝑖𝑑𝑒 𝑑𝑒𝑣𝑖𝑎𝑡𝑖𝑜𝑛𝑅𝑒𝑡𝑢𝑟𝑛

Hedge Funds Strategies

 Long/Short Equity Strategies  Dedicated Short  Equity Market Neutral  Distressed Securities  Merger Arbitrage  Convertible Arbitrage  Fixed Income Arbitrage  Emerging Markets  Global Macro  Managed Futures and Commodity Trading Advisors (CTAs) The list of strategies is based on the book by Lhabitant (2006)

Long/Short Equity Strategies

In the world of hedge funds, the term “equity strategies” is almost synonymous with long/short equity, also known as “equity hedge” (Lhabitant, 2006). The Long and short equity strategy of hedge fund investing has a long history. According to Mirabile (2013), the first person credited with setting up a hedge fund in the United States, Alfred Winslow Jones, ran a long and short equity strategy. LongShort equity hedge funds both buy and short sell stocks, with the ability to adjust their positions given their views on the direction of the equity market (Black, 2004).

*Alfred

Winslow Jones (9 September 1900 2 June 1989), a sociologist, author, and financial journalist, is credited with forming the first modern hedge fund and is widely regarded as the father of the hedge fund industry (Financial Times, 2007; Wikipedia, 2016) .

Source: Adapted from Lhabitant (2006)

Performance comparison of the CS/Tremont Long/Short Equity Index, the S&P 500 and the Citigroup World Government Bond Index, 1994-2005. Adopted from Lhabitant (2006)

Return (% p.a.) Volatility (% p.a.) Skewness Kurtosis Normally distributed?

CS/Tremont Equity Market Neutral

S&P 500

Citigroup WGBI

11.90 10.72 0.23 3.90 No

8.55 16.00 -0.58 0.61 No

5.87 6.74 0.37 0.37 Yes

0.59

0.05

Correlation with strategy Positive months frequency Best month performance (%) Average positive month performance (%) Upside participation

67% 13.01 2.41

62% 9.67 3.44 74%

58% 5.94 1.73 254%

Negative months frequency Worst month performance (%) Average negative month performance (%) Downside participation

33% -11.43 -1.95

38% -14.58 -3.53 -319%

42% -4.28 -1.18 -373%

Max. drawdown (%) Value at Risk (1-month, 99%)

-15.05 -5.96

-46.28 -10.24

-7.94 -3.36





Strategy Long biased

Characteristics and Profiles of the Various Types of Long and Short Equity Funds. Adopted from Mirabile (2013) Description Characteristics Examples Directional bets on individual stocks with leverage Long-term Positions in IBM, Microsoft, Apple and limited short selling unless as a market hedge Fidelity State Street

Variable bias

Short-term short positions ETFs or indices as a temporary hedge against volatility or uncertainty Gross exposure can be above 100% of assets under management due to leverage Individual bets on the success or failure of specific Long IBM and Short Apple with a variable portfolio beta exposure Lone Pine equities designed to generate alpha from both long the S&P 500. Net exposure to the equity market is generally less than Maverick and short positions based on either fundamental or 100% of assets under management and typically is between 20% and Tiger Management technical indicators 50% of assets management

Classic or quantitative Individual long and short positions in specific Classic market neutral funds use individual long and short positions Algert Coldiron equity market neutral companies are optimized in a portfolio to minimize to create a portfolio that is market value and beta neutral Investors Two Sigma market value neutral and beta exposure AQR Quantitative funds use statistical models to create a large number of relatively small long and short positions that are market value and beta neutral Risk Arbitrage Invest in target companies subject to an announced Long positions in target companies are offset by short positions in Brencourt takeover bid acquirer for a "riskless" arbitrage profit if the deal is completed at the announced terms Equity event-driven Invest in specific companies that are likely to have Long or short company's exposure to binary events that will have a Stonerise Partners a material change in profits and price based on significant positive or negative impact on the stock price Edenbrook Capital specific events such as a regulatory change, patent Pershing Square approval, litigation outcome, strategic repositions, spin-offs Short bias

Exclusively invests via short selling of overvalued A small number of highly concentrated short sales in individual Kynikos Associates equities companies that are expected to significantly underperform the market

A Summary of the Skills and Staffing Requirements That Are Unique to Long and Short Equity Style. Adopted from Mirabile (2013) Strategy

Unique Staffing Skills and Organization Components

Long biased

Deep fundamental and technical research staff organized by industry or sector

Variable biased or classic equity market neutral fund

Deep research capacity and ability to create alpha-generating short selling ideas plus dedicated trading and securities lending and margin financing expertise and operations staff

Quantitative equity market neutral

Quantitative finance modelers, database administrators, and computer programmers, plus electronic trading and algorithmic trading skills

Risk arbitrage

Senior traders with strong ties to Wall Street and senior securities lending and prime brokerage relationship managers and operations staff

Equity event-driven

Deep industry expertise, value investing background and strategy skills, legal capacity and regulatory contacts

Dedicated Short

A hedge fund strategy that maintains a net short exposure to the market through a combination of short and long positions. A dedicated short bias investment strategy attempts to capture profits when the market declines, by holding investments that are overall biased to the short side (Investopedia, 2016). Connolly & Hutchinson (2011) conclude that DSB hedge funds are a significant source of diversification for equity market investors and produce statistically significant levels of alpha.

As noted in an article by Business Insider (2014), investors who make a living betting that stock prices will fall are happy to forget 2013: The S&P 500 gained nearly 30 percent while Credit Suisse's index of hedge funds with a dedicated short bias lost 25 percent.


Performance comparison of the CS/Tremont Dedicated Short Index, the S&P 500 and the Citigroup World Government Bond Index, 1994-2005. Adopted from Lhabitant (2006)



S&P 500

Citigroup WGBI

-2.03 18.6 0.84 2.08 No

8.55 16.00 -0.58 0.61 No

5.87 6.74 0.37 0.37 Yes

-0.76

0.00


46% 22.71 4.17

62% 9.67 3.44 -48%

58% 5.94 1.73 8%


54% -8.69 -3.62

38% -14.58 -3.53 -141%

42% -4.28 -1.18 -172%

Max. drawdown (%)

-46.55 -8.25

-46.28 -10.24

-7.94 -3.36

Value at Risk (1-month, 99%)






Equity market-neutral funds are by far the most successful hedge fund strategy tracked by the CSFB/Tremont Hedge Fund Index when measured by the Sharpe Ratio (Black, 2004). Lhabitant (2006) points out that the goal of equity market neutral managers is precisely to avoid any net market exposure in their portfolio. When correctly implemented, it offers the promise of true absolute returns (the alpha) without having to bear the market sensitivity (the beta). But beware! “Market neutral” has become a catch-all marketing term which embeds several different investment approaches with varying degrees of risk and neutrality (Lhabitant, 2006).


Performance comparison of the CS/Tremont Equity Market Neutral Index, the S&P 500 and the Citigroup World Government Bond Index, 1994-2005. Adopted from Lhabitant (2006)



S&P 500

Citigroup WGBI

9.92 2.96 0.34 0.38 Yes

8.55 16.00 -0.58 0.61 No

5.87 6.74 0.37 0.37 Yes

0.36

0.09


84% 3.26 1.03

62% 9.67 3.44 55%

58% 5.94 1.73 159%


16% -1.15 -0.43

38% -14.58 -3.53 -118%

42% -4.28 -1.18 -244%


-3.55 -1.00

-46.28 -10.24

-7.94 -3.36


Monthly returns of the CS/Tremont Equity Market Neutral Index, 1994-2005 by Lhabitant (2006) 1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

Jan

-0.52

0.47

2.10

3.17

0.91

0.69

1.42

2.13

0.12

0.31

0.82

0.35

Feb

0.24

0.94

1.59

1.97

1.85

0.61

0.79

0.89

0.03

-0.06

0.79

1.02

Mar

-0.24

2.92

1.65

-1.15

1.97

1.35

2.24

0.92

0.80

0.79

-0.11

0.43

Apr

0.25

2.27

1.29

1.21

0.29

2.02

1.44

1.44

0.53

0.40

-0.34

-0.22

May

-0.11

0.41

1.14

3.03

1.31

1.44

1.46

0.64

1.29

1.22

0.21

-0.34

Jun

0.70

1.52

0.24

1.18

0.47

1.92

1.82

0.29

0.52

0.46

0.84

0.21

Jul

-1.00

0.55

0.60

3.26

-0.10

1.66

1.23

0.22

1.84

0.68

0.31

0.33

Aug

-0.99

0.68

1.48

-0.92

-0.85

1.11

1.43

1.01

0.57

0.06

2.13

0.86

Sep

-0.94

-0.57

1.32

1.81

0.95

0.22

-0.14

-0.05

-0.03

1.06

0.54

0.90

Oct

-0.37

0.28

1.11

0.81

2.48

0.82

0.81

0.72

0.41

0.67

0.03

0.83

Nov

-0.30

0.29

2.00

-0.38

2.10

1.56

0.28

0.82

0.31

0.33

0.26

0.18

Dec

1.27

0.81

0.95

0.04

1.24

0.96

1.28

-0.08

0.82

0.93

0.86

1.44

Total

-2.02

11.04

16.60

14.82

13.32

15.32

14.98

9.30

7.44

7.06

6.50

6.14

S&P 500

-1.54

34.11

20.26

31.01

26.67

19.53

-10.14

-13.04

-23.37

26.38

8.99

3.00

WGBI

2.34

19.04

3.62

0.23

15.30

-4.27

1.59

-0.99

19.49

14.91

10.35

-6.88



Distressed Securities

Distressed securities may be an attractive investment option for sophisticated investors who are looking for a bargain and are willing to accept some risk (BarclayHedge, 2016b). Distressed securities are primarily debt securities which originate from companies that are in the process of reorganization or liquidation under local bankruptcy law, or companies engaged in other extraordinary transactions such as balance sheet restructurings (Casa, Rechsteiner & Lehmann, 2008). Historically, distressed securities have traded at deep discounts to a rational assessment of their risk-adjusted value for a number of reasons (hedgefund-index.com, 2016).

Companies can become distressed for any number of reasons such as (Casa, Rechsteiner & Lehmann, 2008): •Too much leverage on their balance sheet •Liquidity problems •Credit downgrades •Poor operating performances that require reorganization •Accounting irregularities •Inadequate cash flows •Competitive pressure

Trading in distressed securities is highly inefficient, partly because of forced selling. When a security defaults or is downgraded, investors such as high yield mutual funds, endowments, CLOs and any other investor whose mandates does not permit them to hold such securities are frequently obliged to sell them, often at a discount.


Performance comparison of the CS/Tremont Event Driven: Distressed Index, the S&P 500 and the Citigroup World Government Bond Index, 1994-2005. Adopted from Lhabitant (2006)



S&P 500

Citigroup WGBI

13.44 6.8 -2.89 18.7 No

8.55 16.00 -0.58 0.61 No

5.87 6.74 0.37 0.37 Yes

0.55

-0.05


81% 4.10 1.68

62% 9.67 3.44 79%

58% 5.94 1.73 228%


19% -12.45 -1.42

38% -14.58 -3.53 254%

42% -4.28 -1.18 342%


-14.32 -4.06

-46.28 -10.24

-7.94 -3.36





Merger Arbitrage

Alternative Investment Management Association Canada (2007) explains merger arbitrage, or risk arbitrage as it is sometimes referred, as a strategy that attempts to capture a spread between the price at which a company (target) trades after a transaction is announced, and the price at which an acquiring company (the acquirer) has announced it will pay for that target firm upon closing of a transaction (at a date in the future). Merger arbitrage is classed as a type of event-driven investing, in that it seeks to exploit pricing inefficiencies that can occur before or after a corporate event such as a merger, acquisition, spinoff, or bankruptcy. As such, it is a hybrid between arbitrage-based strategies (considered low-risk/low potential return) and eventdriven strategies, which are considered high risk/high potential return (HedgeThink, 2014).


Performance comparison of the CS/Tremont Event Driven: Risk Arbitrage Index, the S&P 500 and the Citigroup World Government Bond Index, 1994-2005. Adopted from Lhabitant (2006)



S&P 500

Citigroup WGBI

7.72 4.31 -1.26 6.5 No

8.55 16.00 -0.58 0.61 No

5.87 6.74 0.37 0.37 Yes

0.45

-0.02


80% 3.81 1.05

62% 9.67 3.44 39%

58% 5.94 1.73 108%

Negative months frequency Worst month performance (%)

20% -6.15

38% -14.58

42% -4.28

Average negative month performance (%) Downside participation

-1.05

-3.53

-1.18

-165%

-427%


-7.6 -2.70

-46.28 -10.24

-7.94 -3.36







Convertible Arbitrage

The hedge fund style that looks to exploit pricing inefficiencies related to convertible securities is commonly referred to as convertible arbitrage (Mirabile, 2013). The following text, provided by Palmer Square Capital Management (2012) might give us a good insight into Convertible Arbitrage Strategy: “In an environment dominated by uncertainty, historically low interest rates and "risk-on, risk-off," an unlevered convertible bond arbitrage strategy offers investors the potential to capture meaningful yield and potential upside while maintaining strong downside protection. In fact, greater market volatility actually increases the opportunity set for this strategy to create value” (p. 2).


Performance comparison of the CS/Tremont Convertible Arbitrage Index Index, the S&P 500 and the Citigroup World Government Bond Index, 1994-2005. Adopted from Lhabitant (2006)



S&P 500

Citigroup WGBI

8.61 4.89 -1.32 3.01 No

8.55 16.00 -0.58 0.61 No

5.87 6.74 0.37 0.37 Yes

0.14

0.00


76% 3.57 1.29

62% 9.67 3.44 39%

58% 5.94 1.73 122%


24% -4.68

38% -14.58

42% -4.28

-1.22

-3.53

-1.18

216%

-395%

-46.28 -10.24

-7.94 -3.36

Average negative month performance (%) Downside participation Max. drawdown (%) Value at Risk (1-month, 99%)

-12.04 -4.03






Fixed-income arbitrage is an investment strategy that exploits pricing differentials between fixed-income securities (BarclayHedge, 2016c).

Fixed income arbitrage attempts to capture mispricing which develop between related classes of fixed income securitiesmispricing which may be exploited, on a leveraged basis, for significant returns. This general strategy type includes basis (e.g., cash vs. futures), yield-curve and credit spread trading, as well as volatility arbitrage. An unusually high degree of leverage is often available, and often emphasized, in fixed income arbitrage (www.hedgefund-index.com, 2016).


Performance comparison of the CS/Tremont Fixed Income Arbitrage Index, the S&P 500 and the Citigroup World Government Bond Index, 1994-2005. Adopted from Lhabitant (2006)



S&P 500

Citigroup WGBI

6.28 3.88 -3.10 16.41 No

8.55 16.00 -0.58 0.61 No

5.87 6.74 0.37 0.37 Yes

0.03

-0.10


80% 2.02 0.92

62% 9.67 3.44 34%

58% 5.94 1.73 119%


20% -6.96

38% -14.58

42% -4.28

-1.08

-3.53

-1.18

-9%

-215%

-46.28 -10.24

-7.94 -3.36

Average negative month performance (%) Downside participation Max. drawdown (%) Value at Risk (1-month, 99%)

-12.47 -3.11


Source: Adapted from Lhabitant, (2006)



Emerging Markets

Emerging Market strategy refer to hedge funds either based in emerging markets or based outside of emerging market territories (such as London and New York) but investing into them. The study, carried out by Lazard Asset Management LLC (2014), points out that EM can be a source of opportunity for those hedge fund managers with the specialized skills, experience, and local knowledge to exploit it. As noted in Forbes (2014), after a three year lull, endowment and foundation money is ready to return to emerging markets. According to a survey by NEPC, a Boston-based financial consultancy, over 30% of respondents think that emerging market hedge funds will provide superior returns over the next five to seven years. Good news for emerging market fund managers.

Chicago, (April 7, 2016), Hedge Fund Research Inc. Strongest gain for HFRI Emerging Markets Index since May 2009; HFRI Equity, Event Driven & RVA all post sharp gains, Macro falls Emerging Markets hedge funds posted strong gains in March, leading industry-wide gains as equity and commodity markets reversed early quarter declines to conclude the first quarter, according to data released today by HFR®, the established global leader in the indexation, analysis and research of the global hedge fund industry. The HFRI Emerging Markets Index advanced +6.9 percent for the month, offsetting steep losses from January and bringing YTD performance to +0.8 percent. March represents the strongest month of performance for Emerging Markets (EM) since the Index gained +9.6 percent in May 2009. Hedge funds posted strong gains across Equity, Event Driven and Relative Value strategies, with the HFRI Fund Weighted Composite Index® advancing +1.8 percent in March, the strongest gain for the FWC since February 2015.


Performance comparison of the CS/Tremont Emerging Market Index, the S&P 500 and the Citigroup World Government Bond Index, 1994-2005. Adopted from Lhabitant (2006)



MSCI Emerging Markets

S&P 500

8.36 18.16 -0.66 4.64 No

2.28 26.74 -0.82 2.12 No

8.55 16.00 -0.58 0.61 No

0.78

0.48


63% 16.42 3.47

60% 13.55 4.56 200%

62% 9.67 3.44 125%


38% -23.03 -3.69

40% -29.29 -5.73 21%

38% -14.58 -3.53 -298%


-45.15 -9.89

-58.37 -16.14

-46.28 -10.24





Global Macro

The global macro hedge fund strategy is one of the more opportunistic and unconstrained hedge fund strategies whereby managers canvass the global economic landscape and seek to pro t from macroeconomic imbalances and geopolitical events (Crystal Capital Partners LLC, 2015). The evolution and development of systematic macro strategies can be tied to the growth of the futures contract, one of the instruments primarily traded to execute systematic macro strategies (Kamunya, 2014).

ONE OF THE ONLY INVESTMENT STRATEGIES THAT HAS STOOD OUT... HAS BEEN GLOBAL MACRO There are three primary reasons why global macro generally has outperformed other investment strategies (Casano, 2010): 1. Global macro benefits from a sustained increased volatility in currencies, interest rates, commodities, and equity markets.

2. As an investment strategy, it has a low correlation to equities. 3. It tends to perform well when markets are driven by overall macroeconomic themes rather than by individual booms-up fundamental analysis.

Hedge fund managers are great thinkers and great risk-takers, forming views on the world markets and implementing them aggressively. At least, that is the commonly held view of many outside the industry. Although the hedge fund sector is a lot more diverse in reality, it is a fair description of exponents of the strategy known as global macro (Financial Times, 2011). Global macro hedge fund managers do indeed construct grand global matrices – albeit usually supported by sophisticated models – and use them to trade bonds, equities, currencies and just about any other asset (Financial Times, 2011).


Performance comparison of the CS/Tremont Global Macro, the S&P 500 and the Citigroup World Government Bond Index, 1994-2005. Adopted from Lhabitant (2006)



S&P 500

Citigroup WGBI

13.54 11.66 0.03 2.79 No

8.55 16.00 -0.58 0.61 No

5.87 6.74 0.37 0.37 Yes

0.23

-0.13


73% 10.60 2.44

62% 9.67 3.44 83%

58% 5.94 1.73 241%


27% -11.55 -2.45

38% -14.58 -3.53 714%

42% -4.28 -1.18 352%


-26.78 -7.03

-46.28 -10.24

-7.94 -3.36





Managed Futures and Commodity Trading Advisors (CTAs)

As explained by BarclayHedge (2016c), “Managed futures” refers to an asset class offered by professional money managers who are known as “commodity trading advisors” (CTAs). Generally speaking, a CTA fund is a hedge fund that uses futures contracts to achieve its investment objective. These funds’ managers run different strategies using futures contracts, options on futures contracts and FX forwards. CTAs were initially commodityfocused but they now invest across all futures markets, e.g. commodities, equities and currencies. The market for managed futures accounts has grown tremendously since the first long-term trend follower started in the late 1940s. Advances in technology and the global integration of financial markets have since opened up new opportunities in futures trading. According to BarclaysHedge, assets under management in managed futures accounts grew from $0.31bn in 1980 to $320 billion as of the third quarter of 2011 (Morningstar, 2012).


Performance comparison of the CS/Tremont Managed Futures, the S&P 500 and the Citigroup World Government Bond Index, 1994-2005. Adopted from Lhabitant (2006)



S&P 500

Citigroup WGBI

6.37 12.75 0.04 0.40 Yes

8.55 16.00 -0.58 0.61 No

5.87 6.74 0.37 0.37 Yes

-0.16

0.35


56% 9.95 2.92

62% 9.67 3.44 39%

58% 5.94 1.73 -13%


44% -9.35 -2.36

38% -14.58 -3.53 -469%

42% -4.28 -1.18 261%


-17.74 -8.04

-46.28 -10.24

-7.94 -3.36






A Comparison of Different Strategies

Table of Sharpe ratios by strategy. (MSCI, TASS, CSFB/Tremont, http://www.hedgeindex.com) Adopted from Black (2004) CSFB/Tremont Equity Mkt Ntrl

2.07

MSCI Discretionary Trading

1.42

CSFB/Tremont Convertible Arbitrage

1.31

CSFB/Tremont Distressed

1.25

CSFB/Tremont Event Driven

1.13

CSFB/Tremont-Multi Strategy

1.12

CSFB/Tremont E.D. Multi-Strategy

0.92

CSFB/Tremont Global Macro

0.89

CSFB/Tremont Risk Arbitrage

0.88

CSFB/Tremont Hedge Fund Index

0.80

CSFB/Tremont Long/Short Equity

0.72

MSCI Systematic Trading

0.66

CSFB/Tremont Fixed Inc Arb

0.66

TASS Fund of Funds

0.52

S&P 500

0.44

MSCI World Sovereign Debt

0.34

CSFB/Tremont Managed Futures

0.29

CSFB/Tremont Emerging Markets CSFB/Tremont Ded Short Bias -0.50

0.19 -0.23 0.00

0.50

1.00

1.50

2.00

2.50

Table of Sortino ratios by strategy. (MSCI, TASS, CSFB/Tremont, http://www.hedgeindex.com) Adopted from Black (2004) CSFB/Tremont Equity Mkt Ntrl

8.02


0.55


2.23

CSFB/Tremont Multi-Strategy

1.97


1.96


1.74


1.66


1.65


1.58


1.55


1.47

CSFB/Tremont E.D Multi-Strategy

1.39

TASS Fund of Funds

1.06


0.92


0.77

S&P 500

0.76


0.54

CSFB/Tremont Emerging Markets

0.31

CSFB/Tremont Ded Short Bias -0.46 -1.00

0.00

1.00

2.00

3.00

4.00

5.00

6.00

7.00

8.00

9.00

Table of skewness by strategy. (MSCI, TASS, CSFB/Tremont, http://www.hedgeindex.com) Adopted from Black (2004) CSFB/Tremont Fixed Inc Arb

-3.58


-3.52


-2.80

CSFB/Tremon E.D. Multi-Strategy

-2.68


-1.70


-1.40


-1.30


-1.30

S&P 500

-0.60


-0.58

TASS Fund of Funds

-0.17


-0.04


0.01


0.13

CSFB/Tremont Equity Mkt Ntrl

0.13


0.22


0.40


0.74

CSFB/Tremont Ded Short Bias -4.00

0.90 -3.50

-3.00

-2.50

-2.00

-1.50

-1.00

-0.50

0.00

0.50

1.00

1.50

Table of kurtosis by strategy. (MSCI, TASS, CSFB/Tremont, http://hedgeindex.com) Adopted from Black (2004) CSFB/Tremont Event Driven

22.86


19.43


16.28


16.24


6.69


5.77


4.47


3.62


3.25


3.19

TASS Fund of Funds

2.23

CSFB/Tremont Ded Short Bias

2.10


1.99


1.81


1.71


0.49


0.40

S&P 500

0.22


0.18 0.00

5.00

10.00

15.00

20.00

25.00

Table of % winning months by strategy. (MSCI, TASS, CSFB/Tremont, http://www.hedgeindex.com) Adopted from Black (2004) CSFB/Tremont Multi-Strategy

83.6%


83.3%


82.5%


81.6%


78.9%

CSFB/Tremint Risk Arbitrage

78.9%


77.2%


76.3%


74.4%


70.2%


69.3%

TASS Fund of Funds

65.8%


64.9%

S&P 500

62.3%


58.8%


57.0%


57.0%


55.4%

CSFB/Tremont Ded Short Bias 0.0%

47.4% 10.0%

20.0%

30.0%

40.0%

50.0%

60.0%

70.0%

80.0%

90.0%

The Future Development

Today, the major source of future growth for hedge funds clearly seems to be institutional investors, i.e. pension and benefit plans, endowments and foundations, insurance companies and corporations (Lhabitant 2006). It is believed that those institutions will even more increased the amount of money allocated to alternative investments. However, several issues are still present, such as (i) the lack of transparency, (ii) the lack of regulation and risk control and (iii) the high level of fees.

Conclusions

The hedge fund industry is changing rapidly in response to many influences and demands. The critical mass needed and the barriers to get an edge that is sustainable (Mirabile, 2013). Regulation still poses significant problem among both regulators and investors. The high level of secrecy is still present, even though more and more information is required, especially by large institutional investors such as pension funds, etc. Eventually, in order to collect more money, hedge funds’ managers will must to reveal their strategies to investors. There is much more research yet to be done, since this industry is relatively new in the financial world.

Thank you!

References

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