Q Group October 19, 2011 Institutional Quality Hedge Funds David A - - PDF document

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Q Group October 19, 2011 Institutional Quality Hedge Funds David A - - PDF document

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Hedge Funds Q Group October 19, 2011 Institutional Quality Hedge Funds David A Hsieh (c) David A. Hsieh, 2011 Do not quote without written permission. Outline Increase presence of institutional investors in hedge funds since 2001.

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SLIDE 1

Hedge Funds

Q Group

October 19, 2011

Institutional Quality Hedge Funds

David A Hsieh (c) David A. Hsieh, 2011

Do not quote without written permission.

(c) David A. Hsieh 2011. Do not distribute or quote. 2

Outline

Increase presence of institutional investors in hedge funds since 2001. Investment experience?? Need: “Market portfolio” ~ CRSP VW index Problem: Incomplete AUM in public database Solution: Add large firms in private database Benefit: “Institutional quality” firms ~ S&P500 Observations on firm size v performance

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Hedge Funds

(c) David A. Hsieh 2011. Do not distribute or quote. 3

Institutional Investors Are Increasing Allocation to Hedge Funds

Allocation to Hedge Funds (% of Assets) 0% 5% 10% 15% 20% 25% 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 University Endowments Defined Benefit Pensions (c) David A. Hsieh 2011. Do not distribute or quote. 4

Investment Experience ?

Q: What is the investment experience of the average dollar invested in hedge funds? A: Need the “market portfolio” of hedge funds, an asset-weighted return ~ CRSP VW index But hedge funds are private investment vehicles. AUM of the industry is incomplete. Need a proxy ~ S&P 500 index

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Hedge Funds

(c) David A. Hsieh 2011. Do not distribute or quote. 5 5

  • I. Sample Construction

Start with Public Databases (3). Add from public sources identities of mega hedge fund firms (2) and their AUM data; collect missing return data from private sources Public database (PD): Merge reporting firms in Barclays Hedge, HFR and Lipper/TASS Verify AUM against II 100, AR BDC where possible. Sort by AUM, and divide into deciles (D01-D10). Add names and AUM of non-reporting large firms in surveys: II 100 and AR BDC. Find funds and returns of non-reporting large firms in private database.

(c) David A. Hsieh 2011. Do not distribute or quote. 6 6

Public Data Set: Reporting Firms/Funds: Year End 2010

Source: # of Firms # of Funds AUM ($b) Barclays 1,314 3,226 $552 HFR 1,805 4,737 $713 Lipper/TASS 1,412 4,122 $717 Merge 2,442 6,606 $1,322

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Hedge Funds

(c) David A. Hsieh 2011. Do not distribute or quote. 7 7

Non-reporting/Private Data Set Mega Firms/Funds: Year End 2010

Source # of Firms AUM ($b) Reporting firms (public) 2,442 1,322 II 100 firm added 54 (out of 100) 592 (out of $1,231) AR BDC firms added 112 (out of 330) 284 (out of $1,701) Total $2,608 $2,199 Non-reporting/Reporting 7% 66% HFN Administrator Survey (AUA) $2,826

(c) David A. Hsieh 2011. Do not distribute or quote. 8 8

Total Number of Firms at Year End 2010

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Hedge Funds

(c) David A. Hsieh 2011. Do not distribute or quote. 9 9

Total AUM at Year End of 2010

(c) David A. Hsieh 2011. Do not distribute or quote. 10

Firm Size Comparison: 2001-2010

1,000 2,000 3,000 4,000 5,000 6,000 7,000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 AUM ($m) Smallest II 100 Smallest AR BDC Smallest D10 Median

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Hedge Funds

(c) David A. Hsieh 2011. Do not distribute or quote. 11 11

Dominance of Mega Firms: 2001-2010

AUM by Decile and Year ($ billion) 500 1,000 1,500 2,000 2,500 3,000 3,500 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 Missing (HFN survey) D10 (non-reporting) D10 (reporting) D01-D09

(c) David A. Hsieh 2011. Do not distribute or quote. 12 12

AUM Concentration: Percent of AUM in Mega Firms (Total Sample)

151 164 227 252 309 331 369 358 355 451 1026 1132 1269 1421 1650 1761 2049 2140 2185 2443

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Hedge Funds

(c) David A. Hsieh 2011. Do not distribute or quote. 13

Firm Survival Probabilities, by AUM Decile

0.0 0.2 0.4 0.6 0.8 1.0 1 2 3 4 5 6 7 8 9 Years since decile formation D10 D09 D08 D07 D06 D05 D04 D03 D02 D01

(c) David A. Hsieh 2011. Do not distribute or quote. 14

Annual Entry and Exit Rates, by AUM Decile

0.1 0.2 0.3 0.4 0.5 0.6 D01 D02 D03 D04 D05 D06 D07 D08 D09 D10 Entry Exit

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Hedge Funds

(c) David A. Hsieh 2011. Do not distribute or quote. 15

Annual Transition Rates, by AUM Decile

0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 D01 D02 D03 D04 D05 D06 D07 D08 D09 D10 Down 1 Stay Up 1

(c) David A. Hsieh 2011. Do not distribute or quote. 16

Qualitative Characteristics

Large firms manage >80% of AUM. Large firms survive longer. Large firms tend to stay large. Large firms have less entry and less exit. Institutional investors prefer large firms. Possible reasons: cost, career concerns, etc.

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Hedge Funds

(c) David A. Hsieh 2011. Do not distribute or quote. 17

Firm as the Unit of Analysis

We propose to study firms, rather than funds, for two reasons. Demand side: institutional investors look at firms and strategies, not single funds. Supply side: if Berk and Green (2004) applies to funds, one way to increase firm size is to add funds, typically with different styles. Information: 13/F, II 100, AR BDC @ firm level.

(c) David A. Hsieh 2011. Do not distribute or quote. 18

  • II. Performance in Firms with AUM >$50m

Small firms are hard to follow, due to high entry and exit rates. Small firms’ data are hard to verify. Indexers have imposed size cut offs. We do the same here. Start AUM at $50m. Sort firms in PD by deciles: E01, E02, …, E10 Add non-reporting II 100 and AR BDC firms.

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Hedge Funds

(c) David A. Hsieh 2011. Do not distribute or quote. 19

Annual Excess Returns by AUM Decile

0% 1% 2% 3% 4% 5% 6% 7% E01 E02 E03 E04 E05 E06 E07 E08 E09 E10 II100 II100_R II100_NR Mean+1s Mean Mean-1s

(c) David A. Hsieh 2011. Do not distribute or quote. 20

Sharpe Ratio by AUM Decile

0.00 0.20 0.40 0.60 0.80 1.00 1.20 E01 E02 E03 E04 E05 E06 E07 E08 E09 E10 II100 II100_R II100_NR

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Hedge Funds

(c) David A. Hsieh 2011. Do not distribute or quote. 21

Major Risk Exposures of Hedge Funds

Equity risk: S&P500 Russell 2000 – S&P500 Emerging market equity Bond risk: 10 year treasury Moody’s Baa – 10 year treasury Volatility: Straddles on FX, 3m rates, bonds These are meant to capture common exposures in the industry.

(c) David A. Hsieh 2011. Do not distribute or quote. 22

Russell 2000-S&P 500 Exposure

  • 0.35
  • 0.25
  • 0.15
  • 0.05

0.05 0.15 0.25 E01 E02 E03 E04 E05 E06 E07 E08 E09 E10 II100 II100_R II100_NR Beta(RL-SP)+1s Beta(RL-SP) Beta(RL-SP)-1s

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Hedge Funds

(c) David A. Hsieh 2011. Do not distribute or quote. 23

Credit Spread Exposure

0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35 E01 E02 E03 E04 E05 E06 E07 E08 E09 E10 II100 II100_R II100_NR

Beta(Baa-TY)+1s Beta(Baa-TY) Beta(Baa-TY)-1s

(c) David A. Hsieh 2011. Do not distribute or quote. 24

Emerging Market Equity Exposure

0.00 0.05 0.10 0.15 0.20 0.25 E01 E02 E03 E04 E05 E06 E07 E08 E09 E10 II100 II100_R II100_NR Beta(IFC-Rf)+1s Beta(IFC-Rf) Beta(IFC-Rf)-1s

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Hedge Funds

(c) David A. Hsieh 2011. Do not distribute or quote. 25

Monthly Alpha vs 8 Risk Factors

  • 0.30%
  • 0.20%
  • 0.10%

0.00% 0.10% 0.20% 0.30% 0.40% E01 E02 E03 E04 E05 E06 E07 E08 E09 E10 II100 II100_R II100_NR

Alpha+1s Alpha Alpha-1s

(c) David A. Hsieh 2011. Do not distribute or quote. 26

Bull vs Bear Market Exposure

  • 0.35
  • 0.25
  • 0.15
  • 0.05

0.05 0.15 0.25 E01 E02 E03 E04 E05 E06 E07 E08 E09 E10 II100 II100_R II100_NR

Beta(RL-SP)-Bull Beta(RL-SP) Beta(RL-SP)-Bear

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Hedge Funds

(c) David A. Hsieh 2011. Do not distribute or quote. 27

Return Comparison Across AUM Deciles

Excess return, Sharpe ratio, and alpha: U-shaped pattern across deciles. Large firms have less equity exposure. Large firms have more credit spread exposure. All firms have strong emerging market exposure. Equity risk is lower in bear market. Implication: equal weighting across funds puts most of the weight on small firms.

(c) David A. Hsieh 2011. Do not distribute or quote. 28

  • III. Delisting Bias of Firms >$50m AUM

Debate on delisting bias: funds stop reporting due to bad returns vs good returns From private sources: 1,373 funds (share classes) have 15,371 monthly returns after delisting from public databases. 410 are still alive. Worst: -100%. Best: 84.15%. Average: 0.27% Delisting bias is negligible!!!

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Hedge Funds

(c) David A. Hsieh 2011. Do not distribute or quote. 29

  • IV. Institutional Quality Firms:

The “S&P500” Analog

Institutional Quality (“IQ”) firms = all firms with AUM higher than the E09-E10 cutoff. In numbers: 8-10% of all firms (80 – 218 firms) Manage 60-75% of the AUM. AUM-weighted return of IQ firms ~ S&P 500.

(c) David A. Hsieh 2011. Do not distribute or quote. 30

Number of IQ firms by year

50 100 150 200 250 2001 2002 2003 2004 2005 2006 2007 2008 2009 Reporting Non-reporting II100 Non-reporting ARBDC

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Hedge Funds

(c) David A. Hsieh 2011. Do not distribute or quote. 31

IQ firms as percent of all firms

0% 20% 40% 60% 80% 100% 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010

By AUM By # of firms

(c) David A. Hsieh 2011. Do not distribute or quote. 32

Comparison with Selected Indices

4.3% 4.4% 4.5% 4.6% 4.7% 4.8% 4.9% 5.0% 5.1% 5.2% 5.3% 5.4% IQ HFRI DJCSI DJCSMS 0.70 0.72 0.74 0.76 0.78 0.80 0.82 0.84 0.86 0.88 0.90 0.92 Excess Return (Left scale) Sharpe Ratio (Right scale)

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Hedge Funds

(c) David A. Hsieh 2011. Do not distribute or quote. 33 33

Conclusions: adding missing mega firms

Good news: adding ~100 non-reporting mega firms greatly increase AUM coverage of assets in the industry. Bad news: commercial databases’ share of total industry AUM is declining. Good news: reporting and non-reporting firms of similar size have similar survival/performance characteristics. Bad news: survival and performance differ across firm

  • size. So weighting scheme is relevant.

(c) David A. Hsieh 2011. Do not distribute or quote. 34 34

Conclusions: adding missing mega firms

Good news: An AUM-weighted portfolio of IQ firms provides a good proxy of the market portfolio of hedge funds and only requires collecting data from a manageable number of non-reporting firms.