The Risks of Portfolios of Hedge Funds

Drago IndjicFauchier Partners

PRMIA, 14 May 2003, London

El Pais, 24 Feb 2003

• Don’t believe everything you read

– Negative media bias

– Cliché: “LTCM”, “Soros”, “Courtisans” …

= Investor education, academic research

1 Speculators

2 Early 21c.

Risk

100

125

150

175

200

225

250

Apr-95 Oct-95 Apr-96 Oct-96 Apr-97 Oct-97 Apr-98 Oct-98 Apr-99 Oct-99 Apr-00 Oct-00 Apr-01 Oct-01 Apr-02 Oct-02

HFRI FOF Offshore MSCI

Source: HFR, Pertrac, Fauchier

• Hedge fund industry

• Investment strategies

• Investor’s perspective

• Data, Transparency and Estimation Risks

• Hedge fund risk

• Portfolios of Hedge funds

(Any HF investors or FoHF in the audience?)

3 Content

• Unregulated private placements

– (e.g.) A pooled investment vehicle that is privately organised,

administered by professional investment managers, and not

widely available to the public

• “Extralegality” (de Soto) => Frontier Creativity

– Less restrictive liquidity, borrowing, derivatives … (taxation)

– Creative investment strategies – efficient capital utilisation

– Perpetual innovation inefficiencies

• Consider only hedged (off-shore) funds

4 Hedged Funds

• The most dynamic sector of asset management today

– Decreasing sell side research coverage; Higher servicing profitability

• Regulators “lagging”

– SEC: May 14/15 – “raising bar”?

• Sustained growth

– Highly creative and talented manager’s end game: “personal”

styles

– Owner/Manager mentality

– Self-Regulation by adapting capacity, liquidity, fees

5 Industry

Estimated Assets Asset Flows

Estimated Hedge Fund Asset Growth and Flow 1990 - 2002

Estimated Number of Hedge Funds (ex FOF) 1990 - 2002

6

$38,910$58,370

$95,720

$167,790 $167,360$185,750

$256,720

$367,560 $374,770

$456,430$487,580

$536,060

$622,304

$27,861

$36,918 -$1,141 $14,698

$57,407

$91,431 $4,406

$54,847$20,353

$46,544

$99,436

$8,463

$0

$100,000

$200,000

$300,000

$400,000

$500,000

$600,000

$700,000

1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002

Ass

ets

(In

$

MM

)

530694

937

1,277

1,654

2,006

2,3922,564

2,848

3,1023,335

3,904

4,598

0

500

1,000

1,500

2,000

2,500

3,000

3,500

4,000

4,500

5,000

1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002

Numb

er of

Fund

sN

um

ber

of

Fun

ds

2003

• Tass Asset Flows Report™ 4Q2002 3493 total -1337 “dead”=

2156 “live” funds

• HFR 2002 Industry Report: 4598 funds (exc. FoF)

(AUM most probably underestimated)

7 Hedge Fund Environment

BillionsUSD

Tass HFR

2001 $261 $536

2002 $310 $622

• Contra:– HF are “alternative investment strategies”: too

heterogeneous, dynamic, evolving, with no brands• Pro:

– Absolute returns paradigm, Ineichen (2002) • Specific liquidity (“mark-to-market”) and

drawdown preferences– Very different sources of α, uncorrelated, –ve β,

better Ω … ran by non-consensus thinkers in small enterprises

Another Asset Class?

8

• Hedge Fund (HF) “Indexes”– Composites of actively managed portfolio returns– Over a dozen commercial indices– Investible? Transparent? Capacity? – No independent verification– Enforcing “relative” rather than “absolute” return

viewpoint• Evolving strategies

– E.g. Quantitative credit arb, macro equilibrium models– Many styles within strategy (inc. different fund of funds

styles)– “Strategy drift” detection

9 Investment Strategies

Equity Hedge38.52%

Emerging Markets (Total) 5.53%

Distressed Securities2.74%

Equity Market Neutral5.94%

Equity Non-Hedge7.84%

Event-Driven 7.28%

FI: Arbitrage 2.78%

FI: Convertible Bonds0.25%

FI: Diversified 2.56%

FI: High Yield 1.14%

FI: MBS 1.37%

Convertible Arbitrage3.70%

Short Selling0.76%Sector (Total) 6.71%

Macro 2.15%

Market Timing 3.65%

Merger Arbitrage 3.78%

Regulation D 0.52%

Relative Value Arbitrage 2.77%

Merger Arbitrage 0.60% Fixed Income (Total) 3.24%

Event Driven 3.84%

Relative Value Arbitrage 10.08%

Sector (Total) 0.24%

Macro71.07%

Equity Non-Hedge 0.60%

Equity Market Neutral 1.68%

Equity Hedge 5.28%Short Selling 0.12%

Convertible Arbitrage 0.48%

Distressed Securities 2.40% Emerging Markets (Total)

0.36%

10 Estimated Strategy Composition by AUM 1990

Estimated Strategy Composition by # of Funds (ex FOF) 2002

2003

Assets (in $MM)

Convertible Arbitrage

Distressed Securities

Emerging Markets (Total)

Equity Hedge

Equity Market Neutral

Event-Driven

Fixed Income: Arbitrage

Macro

Merger Arbitrage

Regulation D

Sector (Total)

Short Selling

Fund of Funds

RVA

FI: Convertible Bonds

FI: Mortgage-Backed

Fixed Income: High Yield

Market Timing

Equity Market Neutral: StatArb

Fixed Income: Diversified

Equity Non-Hedge

($60,000) ($40,000) ($20,000) $0 $20,000 $40,000 $60,000 $80,000 $100,000 $120,000

Convertible Arbitrage

Emerging Markets (Total)

Equity Non-Hedge

Event-Driven

Fixed Income: Arbitrage

Fixed Income: Diversified

Fixed Income: High Yield

Market Timing

Merger Arbitrage

Regulation D

Equity Hedge

Equity Market Neutral

Short Selling

Equity Market Neutral: Stat Arb

RVA

Fixed Income: MBS

FI: Convertible Bonds

Distressed Securities

Sector (Total)

Macro

($6,000) ($3,000) $0 $3,000 $6,000 $9,000 $12,000 $15,000

Assets (in $MM)

Fund of Funds

11 Estimated Net Asset Flow by Strategy 2002

Estimated Net Asset Flow by Strategy Q4

2002

2003

Convertible Arbitrage

Distressed Securities Emerging Markets (Total)

Equity Non-Hedge

FI: Diversified

FI: Mortgage-Backed

Fund Weighted Comp. Index

Reg. D

Relative Value Arb

Sector (Total)

Short Selling

Equity Hedge

Equity Market Neutral

Event Driven

FI: Arbitrage

FI: Convertible Bonds

FI: High Yield

Fund of Funds

Lehman Gov/Credit

Macro

Market Timing

Merger Arbitrage

S&P 500

Statistical Arbitrage

-25%

-20%

-15%

-10%

-5%

0%

5%

10%

15%

20%

25%

0% 3% 6% 9% 12% 15% 18% 21%

STD (%)

Retur

n (%

)

Convertible Arbitrage

Distressed Securities

Emerging Markets (Total)

Equity Non-Hedge

Fund Weighted Comp. Index

Reg. D

Sector (Total)

Short Selling

Equity Hedge

Equity Market Neutral Event Driven

FI: Arbitrage

FI: Convertible Bonds

FI: Diversified

FI: High Yield

FI: Mortgage-Backed

Fund of Funds

Lehman Gov/Credit

Macro

Merger ArbitrageRelative Value Arb

Statistical Arbitrage

0%

3%

6%

9%

12%

0% 5% 10% 15% 20% 25% 30%

STD (%)

Retur

n (%)

12 2002 HFRI Index Risk Return Comparison 5 Year Annualised (1998 – 2002)

2002 HFRI Index Risk Return Comparison

2003

AIMA Strategy Definitions

• An index family for every commercial data source: too many indices but a lack of definitions

• Ad-hoc committee under the under the auspices of AIMA called for “Expressions of interest” in April 2003

• ‘Non-commercial’, coordinated long-term research effort leading to the development of a set of definition "guidelines"

• Survey planned during 3Q03

13

• How? – “DIY”, advisor, specialist?– “Fund of funds” (FoHF) route

• Passive: Indexed– Pools of managed accounts– Which “index” and “HF Tracking error”?

• Active: Portfolio of funds– “Off the shelf”– Tailor made and managed

• Structured – What type of security do you own? – Total costs?

14 Creating Exposure

• Two hedge funds• A Hedge fund Index, S&P 500-hedged• Selection of a dozen funds from “platform”,

wrapped• Five funds, 8 x levered portfolio• Single-strategy, multi-manager (levered)• Any including a fund that rebates 50% of fee

to anyone

15FoHF Examples

• Business rather than investment management:– Seeding, incubation, equity stakes

– Capacity marketing, fees splits – Selection vintage year

• Asset gatherers: – Collecting fees on gross assets?– Layered fees transparency (e.g. structured

products)– 2nd level Performance fee– Hurdle, Highwatermark

16Investment Biases

• Collection of HF accounts – a trivial solution?• Portfolio construction biases

– “Products” or portfolios? – Captive market?– Can “good” funds be included?– Where is manager self-invested?

• Should “on going” Due Diligence be outsourced?

17 Managed Account “Platforms”

• Data: not liquid market prices but performance estimates of “hyperactive” portfolios skilfully managed in different, very personal styles

• Problematic valuation: IAFE Hedge Fund Valuation Practice recommendations

• Hedge fund strategy modelling– Multifactor models: R2 from 0.1 to 0.9?– Option replication (Naik and Agrawal, 2001)– Calibration: NAV (RiskData) or model exposure

data

18Data and Modelling

• No unique answer– “Those people who need it will find managers who will

provide it”– “Those managers who won’t give it will be able to find

investors who don’t need it”– Greatest fear: hedge fund ruin (default)– Aggregated disclosure– Mutual trust: the “agent” in real-time dialogue

• Full Transparency Paradox– Un-actionable without active overlays– Diminishing need for managers if operating “active”

overlay?

19Transparency Debate

Fund ExposureHigh Low Average Close

Long Exposure %Short Exposure %Net Futures %Net options %Gross %Net %Cash %

Month end - Industry Sector/Asset type/Credit ExposureTop 5 Sectors Long Short Gross Net

12345

Sum

Month end - Country ExposureTop 5 Countries Long Short Gross Net

12345

Long/Short Equity Report Template

Concentration at month endLong portfolio top 5 Short Portfolio top 5Names % by Value % by Value

1 12 23 34 45 5

Sum Sum#Long #Short Total number of positions

Long Beta Short Beta

Perfomance Attribution - monthMonth Year to date

Long Gross (Y/N) ?Short Net (Y/N) ?Futures/OptionsCurrency

Intra month variation Fund Equity at month endHigh Low ($m) Net change ($m)

Daily NAV Equity

20Hedge Fund Exposures

Source: Fauchier

0%

25%

50%

75%

100%

Long / Short Sector/Asset Country Top 10 #positions Attribution stdev(NAV)

Reported Not Reported n/a

21 Transparency Compliance(2002)

Source: Fauchier

Estimation Risk

• Taboo topic: non-asymptotical statistics, very short and noisy data samples

• Volatility and VaR – Figlewski (2003)

• Portfolio - Kempf (2002)The equal weighting is theoretically optimal solution

when data and forecasts are not reliable

22

• Estimate correlation: n=12 data points: “ρ=0” ↔ ρ∊[-0.3, 0.3] (85%)

“secretary problem” - but fund may be already closed

-0.7 -0.2 0.3 0.8Estimated Correlation

-0.8

-0.6

-0.4

-0.2

0.0

0.2

0.4

0.6

0.8

1.0

Correlation Confidence Intervals

95% confidence level

Co

rrela

tion

Co

nfide

nce

Inte

rva

l

corr=-0.7 corr=-0.2 corr=0.3 corr=0.8

+/-0.0

+/-0.1

+/-0.2

+/-0.3

+/-0.4

+/-0.5

Confid

ence

In

terv

al

Correlation Confidence Intervals

number of samples

95% confidence level

n=25

n=50

# months

Es

tim

ate

d c

orre

lati

on

0 20 40 60 80 100 120

-1.0

-0.5

0.0

0.5

Estimated Correlations for Zero Correlation Data

23 Small sample bias

24Correlation Matrix1 April 2001 to 31 March 2003

Strategy ID M M M ELB ELB ELB EHH EHH EHH EHL EHL ESB SC END END MS MS MS MS FRI

Strategy ID Fund ID FPAM 1 869 342 1079 91 628 1481 912 1102 240 951 267 970 1019 1385 354 54 293 639 226 1011

M 869 -0.02 1.00 -0.14 0.45 0.21 0.01 -0.30 0.32 -0.16 -0.18 -0.39 0.35 0.70 -0.45 0.10 0.48 -0.51 -0.42 -0.31 -0.62 -0.34

M 342 0.19 -0.14 1.00 0.39 -0.20 -0.09 0.29 -0.07 -0.07 0.11 0.17 -0.12 -0.21 0.31 0.17 -0.06 0.38 0.16 0.16 0.27 0.14

M 1079 0.14 0.45 0.39 1.00 0.26 0.24 0.03 0.27 -0.20 -0.16 0.01 0.19 0.44 -0.18 0.20 0.32 -0.24 -0.28 -0.03 -0.21 0.13ELB 91 0.43 0.21 -0.20 0.26 1.00 0.42 -0.09 0.57 0.23 0.45 0.09 0.37 0.49 -0.12 0.08 0.54 -0.40 -0.13 -0.38 -0.13 -0.20ELB 628 0.55 0.01 -0.09 0.24 0.42 1.00 0.18 0.12 -0.01 0.40 0.60 0.47 0.02 0.30 0.67 0.14 0.05 0.20 0.14 0.27 0.14

ELB 1481 0.25 -0.30 0.29 0.03 -0.09 0.18 1.00 -0.44 -0.04 0.07 0.41 0.21 -0.39 0.14 0.20 -0.45 0.18 -0.08 0.25 0.17 0.33

EHH 912 0.25 0.32 -0.07 0.27 0.57 0.12 -0.44 1.00 -0.00 0.20 -0.21 0.08 0.74 -0.17 -0.05 0.77 -0.33 0.07 -0.51 -0.13 -0.47

EHH 1102 0.13 -0.16 -0.07 -0.20 0.23 -0.01 -0.04 -0.00 1.00 0.33 0.19 -0.12 -0.03 0.15 -0.04 0.19 0.05 0.26 -0.29 0.12 -0.29

EHH 240 0.60 -0.18 0.11 -0.16 0.45 0.40 0.07 0.20 0.33 1.00 0.50 0.29 0.05 0.29 0.36 0.20 0.15 0.33 0.07 0.36 -0.14

EHL 951 0.65 -0.39 0.17 0.01 0.09 0.60 0.41 -0.21 0.19 0.50 1.00 0.49 -0.37 0.52 0.59 -0.19 0.46 0.41 0.40 0.56 0.05

EHL 267 0.57 0.35 -0.12 0.19 0.37 0.47 0.21 0.08 -0.12 0.29 0.49 1.00 0.25 0.07 0.59 0.16 -0.07 -0.14 0.24 0.03 -0.07

ESB 970 0.00 0.70 -0.21 0.44 0.49 0.02 -0.39 0.74 -0.03 0.05 -0.37 0.25 1.00 -0.53 -0.07 0.78 -0.69 -0.25 -0.51 -0.58 -0.48

SC 1019 0.61 -0.45 0.31 -0.18 -0.12 0.30 0.14 -0.17 0.15 0.29 0.52 0.07 -0.53 1.00 0.45 -0.27 0.81 0.63 0.52 0.86 0.20

END 1385 0.67 0.10 0.17 0.20 0.08 0.67 0.20 -0.05 -0.04 0.36 0.59 0.59 -0.07 0.45 1.00 -0.16 0.38 0.34 0.46 0.40 0.21

END 354 0.11 0.48 -0.06 0.32 0.54 0.14 -0.45 0.77 0.19 0.20 -0.19 0.16 0.78 -0.27 -0.16 1.00 -0.53 -0.02 -0.58 -0.28 -0.50

MS 54 0.45 -0.51 0.38 -0.24 -0.40 0.05 0.18 -0.33 0.05 0.15 0.46 -0.07 -0.69 0.81 0.38 -0.53 1.00 0.54 0.62 0.85 0.31

MS 293 0.45 -0.42 0.16 -0.28 -0.13 0.20 -0.08 0.07 0.26 0.33 0.41 -0.14 -0.25 0.63 0.34 -0.02 0.54 1.00 0.21 0.64 -0.05

MS 639 0.24 -0.31 0.16 -0.03 -0.38 0.14 0.25 -0.51 -0.29 0.07 0.40 0.24 -0.51 0.52 0.46 -0.58 0.62 0.21 1.00 0.57 0.43

MS 226 0.58 -0.62 0.27 -0.21 -0.13 0.27 0.17 -0.13 0.12 0.36 0.56 0.03 -0.58 0.86 0.40 -0.28 0.85 0.64 0.57 1.00 0.36

FRI 1011 -0.03 -0.34 0.14 0.13 -0.20 0.14 0.33 -0.47 -0.29 -0.14 0.05 -0.07 -0.48 0.20 0.21 -0.50 0.31 -0.05 0.43 0.36 1.00

Correlation:Average correlation with all funds 0.30 -0.08 0.06 0.07 0.09 0.23 0.04 0.01 0.01 0.18 0.25 0.18 -0.07 0.22 0.27 -0.01 0.15 0.15 0.13 0.22 0.02MSCI The World Index - Gross -0.14 -0.65 0.06 -0.35 -0.52 -0.02 0.33 -0.82 -0.03 -0.13 0.33 -0.20 -0.92 0.38 0.11 -0.84 0.55 0.13 0.58 0.46 0.62SSB WGBI 5+ year sector in USD 0.03 0.56 -0.13 0.32 0.18 0.12 -0.63 0.39 -0.26 0.01 -0.15 0.14 0.52 -0.26 0.09 0.40 -0.21 -0.01 -0.09 -0.30 -0.39

Notes: CorrelationEstimation Error <10% >20% <20% <10%

2. The strategies formerly known as Restructuring (R) and Credit Arbitrage (CA) Positive 0 Negative

have been re-classified as Specialist Credit (SC) and Fixed Income (FI) respectively. Correlation band >0.66 <-0.42 <-0.66

4. A blank cell denotes that no meaningful correlation exists for the period of the report.

1. Assuming 90% confidence level and 10% error monthly data points, correlations greater than +/-0.42 (0.66) are eestimated with less than 20% (10%) error.

3. The correlation matrix is generated from 24 data points.

FPAM 1 CORRELATION MATRIX1 April 2001 to 31 March 2003

The table shows the correlation between;(i) FPAM1 and certain funds contained in FPAM1 (where sufficient data is available)(ii) the funds contained in FPAM1 with each other(iii) FPAM1 and various indices(iv) the funds and various indices.

Source: Fauchier

Weekly vs Monthly Data

ViewDifference between Weekly and Monthly Correlation Values

BoyerAllanPacificCaduceus CanyonCSFB DaedalusDoubleBlackDiamondEgertonFRI Gruss JGDYork LansdowneEuropeanPerryEuropeanPerryPartners Raptor Seminole SRGlobal StAlbans StandardPacific TTAsiaWPG BoyerAllanPacific0 -0.24 -0.21 -0.04 0.11 0.21 -0.34 -0.01 -0.25 -0.10 -0.18 -0.05 -0.26 -0.20 -0.14 -0.27 -0.10 -0.19 -0.34 -0.35Caduceus -0.24 0 -0.27 -0.15 0.26 0.33 -0.11 0.02 -0.35 -0.07 0.06 0.13 -0.06 -0.29 0.02 -0.09 0.05 0.16 -0.34 -0.34Canyon -0.21 -0.27 0 -0.44 -0.09 0.16 -0.24 0.17 -0.08 -0.27 -0.05 -0.13 -0.25 -0.12 -0.04 0.06 -0.14 0.11 -0.04 -0.04CSFB -0.04 -0.15 -0.44 0 -0.15 0.10 -0.31 0.17 -0.23 -0.08 0.16 0.11 -0.33 -0.04 -0.14 0.09 -0.42 0.12 0.05 -0.07Daedalus 0.11 0.26 -0.09 -0.15 0 -0.37 -0.16 -0.51 0.17 -0.16 -0.11 -0.74 -0.45 0.16 0.03 0.33 -0.35 -0.03 -0.21 0.03DoubleBlackDiamond0.21 0.33 0.16 0.10 -0.37 0 0.30 -0.14 0.56 -0.08 0.21 -0.13 -0.06 0.31 0.21 0.10 -0.12 0.14 0.22 0.24Egerton -0.34 -0.11 -0.24 -0.31 -0.16 0.30 0 -0.01 -0.16 -0.13 -0.08 -0.19 -0.29 0.10 -0.02 0.07 -0.10 -0.02 0.02 0.00FRI -0.01 0.02 0.17 0.17 -0.51 -0.14 -0.01 0 0.00 -0.02 -0.04 0.17 0.22 -0.20 0.02 -0.03 -0.25 -0.18 -0.09 -0.30Gruss -0.25 -0.35 -0.08 -0.23 0.17 0.56 -0.16 0.00 0 -0.23 -0.03 0.14 -0.02 -0.09 -0.35 0.04 -0.07 0.19 -0.16 -0.08JGDYork -0.10 -0.07 -0.27 -0.08 -0.16 -0.08 -0.13 -0.02 -0.23 0 -0.05 -0.01 -0.18 0.13 -0.33 0.00 -0.18 0.17 0.17 -0.41LansdowneEuropean-0.18 0.06 -0.05 0.16 -0.11 0.21 -0.08 -0.04 -0.03 -0.05 0 0.05 -0.08 -0.01 -0.17 -0.37 -0.18 -0.19 0.06 -0.51PerryEuropean-0.05 0.13 -0.13 0.11 -0.74 -0.13 -0.19 0.17 0.14 -0.01 0.05 0 -0.12 0.49 0.03 0.08 -0.56 0.18 -0.02 -0.14PerryPartners -0.26 -0.06 -0.25 -0.33 -0.45 -0.06 -0.29 0.22 -0.02 -0.18 -0.08 -0.12 0 0.27 -0.06 0.08 -0.28 0.05 0.05 -0.05Raptor -0.20 -0.29 -0.12 -0.04 0.16 0.31 0.10 -0.20 -0.09 0.13 -0.01 0.49 0.27 0 0.13 -0.20 0.12 -0.12 -0.18 -0.08Seminole -0.14 0.02 -0.04 -0.14 0.03 0.21 -0.02 0.02 -0.35 -0.33 -0.17 0.03 -0.06 0.13 0 -0.15 -0.14 0.19 -0.05 -0.30SRGlobal -0.27 -0.09 0.06 0.09 0.33 0.10 0.07 -0.03 0.04 0.00 -0.37 0.08 0.08 -0.20 -0.15 0 0.33 -0.30 -0.21 -0.34StAlbans -0.10 0.05 -0.14 -0.42 -0.35 -0.12 -0.10 -0.25 -0.07 -0.18 -0.18 -0.56 -0.28 0.12 -0.14 0.33 0 -0.11 0.30 0.14StandardPacific -0.19 0.16 0.11 0.12 -0.03 0.14 -0.02 -0.18 0.19 0.17 -0.19 0.18 0.05 -0.12 0.19 -0.30 -0.11 0 0.04 0.10TTAsia -0.34 -0.34 -0.04 0.05 -0.21 0.22 0.02 -0.09 -0.16 0.17 0.06 -0.02 0.05 -0.18 -0.05 -0.21 0.30 0.04 0 -0.15WPG -0.35 -0.34 -0.04 -0.07 0.03 0.24 0.00 -0.30 -0.08 -0.41 -0.51 -0.14 -0.05 -0.08 -0.30 -0.34 0.14 0.10 -0.15 0

From Feb 2001 to Jan 2003 (24 monthly or 108 weekly data values)

Surprising differences in certain fund correlations pairs

25

Source: Fauchier

Weekly HF “Indexes”

-0.04 -0.02 0.00 0.02 0.04

M

0

10

20

30

-0.03 -0.02 -0.01 0.00 0.01 0.02 0.03

EHL

0

10

20

30

40

50

60

Equally weighted index of weekly returns: non-normality

26

Source: Fauchier

Keating and Shadwick (2002)

27 Omega Ratio

• HF are SME (~7 people => no IT, client service …)– Can portfolio manager run (grow) a small business?– “Disgraceful aging”

• Total Hedge Fund Risk =– Market Risk + Operational Risk– Operational Risk >> Market Risk – Principal/Agency Problem

• Balance “Qualitative and Quantitative” Risks

28Hedge Fund Risk

29 The Real Risk

($1,000)

$0

$1,000

$2,000

$3,000

$4,000

$5,000

$6,000

$7,000

$8,000

$9,000

$0.0

$10.0

$20.0

$30.0

$40.0

$50.0

$60.0

$70.0

$80.0

• Primary (individual hedge fund level): – Many market risks are (most often) hedged– Balance sheet dynamics: leverage and hedge skills– Kept in check by Prime Broker margin policy

• Secondary (portfolio of funds level):– Risk measurement + portfolio management – Operational risk management

30Risk Management

• Mandatory: Prime brokers– Are VaR and margin policy private information not to

be disclosed (timely) to (all) investors?• Optional: Third party “Risk aggregators”

– HF → TTP → Investor– New generation fund administrators?

• Voluntary: Customised risk reporting– IAFE IRC and AIMA: Strategy-specific templates

31Market Risks

• Age and stability– Immature business models– Incentives, succession planning

• Capacity– “Chicken & Egg” capacity games:

• Day 1 fund closures, secondary market– Big isn’t beautiful: median AUM $40m– “Know your client”: max. two dozen investors

• Liquidity– Lockups, penalties, gates, suspended and forced

redemption rights

32Operational Risks (1)

• Organisational Structure– Legal structure– Performance fee models

• Counterparties– Fund administration, Audit, Prime

Broker• Manager Utility: “Path-Dependant”

– Risk aversion = f ( ΔAUM, Losing streak, YTD, Wealth…)

33Operational Risks (2)

• FoHF A ≠ FoHF B– % own (or owned) funds, %funds of funds,

% multi-strategy funds …

– Liquidity, costs (fee sources)• Portfolio Analysis

– Performance Attribution: Manager selection vs Strategy allocation

– Turnover (usually low), ROCE– Style analysis

• Monitoring

– In-situ: business and operational risk

34Funds of Hedge Funds

• “One size doesn’t fit all”– Single-strategy, multi-manager: mitigate

decision making?– “All weather”

– Tailor-made

• Levered or not?

• “Optimised” or not?• Avoid behavioural biases

35Portfolio Construction

• Kempf (2002): Optimal portfolios for data length T, market inhomogeneity τ, identical prior mean.

Case τ =0 τ→∞

T=0 Minimum variance Equally weighted

T→∞ Minimum variance Two-step Markowitz

• Comment: funds of hedge funds are in T→0/τ→∞

36Portfolio Estimation Risk

0.02

0.03

0.04

0.05

207 515 117 215 309

Distribution of Portf olio Weights

37Portfolio Construction

• Constrained optimisation– Asymmetric calendar trading constraints

(illiquidity)– Inherent slippage

• Not mean-variance but scheduling and constraint programming

• Monitoring Costs: Communication density

– #meetings/funds/year/analyst(s)

38 Operational Risk Optimality

M/M+30/15

March 04Jan 03 March 03 May 03 Sept 03 Nov 03July 03 Jan 04

Jan 03 March 03 May 03 Sept 03 Nov 03July 03 Jan 04 March 04

Jan 03 March 03 May 03 Sept 03 Nov 03July 03 Jan 04 March 04

M/M+60/20

2/Q+60

39 Calendar Liquidity Constraints

Source: Fauchier

40 Manager Research andMonitoring

Total number of meetings

Number of meetings

0

10

20

30

40

50

60

70

80

90

100

Jan-

01

Apr-0

1

Jul-0

1

Oct-0

1

Jan-

02

Apr-0

2

Jul-0

2

Oct-0

2

Per

Mo

nth

0

200

400

600

800

1000

1200

Cu

mu

lati

ve

Managers' Office

Fauchier Partners

Seminars

Source: Fauchier

• Balance true risks and costs– Attention to vested business

interests and incentives (are we all “eating our own cooking”?)

– Quantitative, but also confident

• Product divergence– “Optimal” transparency– Commoditisation vs

customisation

41 Conclusion

• AIMA (2002) A Guide to Fund of Hedge Funds Management and Investment

• AIMA (2003) Hedge Fund Strategy Definition Standardisation

• Inechien, A. (2002) Absolute Returns, Wiley

• L’ Habitant, F.-S. (2002) Hedge Funds: Myths and Limits, Wiley

• Rahl, L. (2003) Hedge Fund Risk Transparency, Risk Books

42 Bibliography - Introduction

• Figlewski, S. (2003) Assessing the Risk in Risk Assessments, IAFE/ PRMIA Seminar, April 23rd, NYC

• Kempf, A., Memmel, C. (2002) On the Estimation of the Global Minimum Variance Portfolio, Discussion Paper 2002-2, Uni. Koeln

• Keating, C., Shadwick, W. (2002) “Omega: A Universal Performance Measure” Journal of Performance Measurement, Spring 2002

• Lo, A. (2002) Risk Management for Hedge Funds: Introduction and Overview, AIMR

• Naik, N., Agrawal, V. (2001) Performance Evaluation of Hedge Funds with Option-based and Buy-and-Hold Strategies, LBS

43 Bibliography - Research