Transcript Content

The Risks of Portfolios of Hedge Funds
Drago Indjic
Fauchier Partners
PRMIA, 14 May 2003, London
1
Speculators
• Don’t believe everything you read
– Negative media bias
– Cliché: “LTCM”, “Soros”,
“Courtisans” …
= Investor education, academic
research
El Pais, 24 Feb 2003
2
Early 21c. Risk
250
225
200
175
150
125
HFRI FOF Offshore
MSCI
100
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
Source: HFR, Pertrac, Fauchier
3
Content
• 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?)
4
Hedged Funds
• 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
5
Industry
• 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
Estimated Hedge Fund Asset Growth
and Flow 1990 - 2002
Estimated Number of Hedge Funds (ex
FOF) 1990 - 2002
6
5,000
$700,000
4,598
$622,304
4,500
$487,580
$99,436
$456,430
$367,560 $374,770
$400,000
$46,544
$54,847
$300,000
$256,720
$200,000
$167,790 $167,360
$95,720
$100,000
$38,910
$58,370
$36,918 -$1,141
$91,431
Number of Funds
$500,000
Number of Funds
$536,060
Assets (In $MM)
Assets (In $MM)
$600,000
$20,353
$4,406
$185,750
3,904
4,000
3,500
3,335
3,102
2,848
3,000
2,564
2,392
2,500
2,006
2,000
1,654
1,500
1,277
$57,407
937
1,000
$14,698
694
530
$27,861
500
$8,463
$0
0
1990
1991
1992
1993
1994
Estimated Assets
2003
1995
1996
Estimated Assets
1997
1998
Asset Flows
Asset Flow
1999
2000
2001
2002
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
7
•
•
Hedge Fund Environment
Tass Asset Flows Report™
4Q2002
3493 total -1337 “dead”=
2156 “live” funds
Billions
USD
Tass
HFR
2001
$261
$536
HFR 2002 Industry Report:
4598 funds (exc. FoF)
2002
$310
$622
(AUM most probably
underestimated)
8
•
•
Another Asset Class?
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
9
•
•
Investment Strategies
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
Estimated Strategy Composition
by # of Funds (ex FOF) 2002
Short Selling
0.76%
Sector (Total) 6.71%
Relative Value Arbitrage
2.77%
10
Convertible Arbitrage
3.70%
Convertible Arbitrage
0.48%
Distressed Securities
2.74%
Regulation D 0.52%
Emerging Markets (Total)
5.53%
Merger Arbitrage 3.78%
Estimated Strategy Composition by
AUM 1990
Distressed Securities
Emerging Markets (Total)
2.40%
0.36%
Equity Hedge 5.28%
Short Selling 0.12%
Sector (Total) 0.24%
Equity Market Neutral
1.68%
Relative Value Arbitrage
10.08%
Equity Non-Hedge 0.60%
Event Driven 3.84%
Market Timing 3.65%
Merger Arbitrage 0.60%
Macro 2.15%
Fixed Income (Total)
3.24%
FI: MBS 1.37%
FI: High Yield 1.14%
FI: Diversified 2.56%
Equity Hedge
38.52%
FI: Convertible Bonds
0.25%
FI: Arbitrage 2.78%
Event-Driven 7.28%
Equity Non-Hedge
7.84%
2003
Equity Market Neutral
5.94%
Macro
71.07%
Estimated Net Asset Flow by
Strategy Q4 2002
11
Estimated Net Asset Flow by
Strategy 2002
Assets (in $MM)
($6,000)
($3,000)
$0
$3,000
$6,000
Assets (in $MM)
$9,000
$12,000
$15,000
($60,000)
($40,000)
($20,000)
$0
Convertible Arbitrage
$20,000
$40,000
$60,000
$80,000
$100,000
$120,000
Convertible Arbitrage
Distressed Securities
Distressed Securities
Emerging Markets (Total)
Emerging Markets (Total)
Equity Hedge
Equity Hedge
Equity Market Neutral
Equity Market Neutral
Equity Non-Hedge
Equity Non-Hedge
Event-Driven
Event-Driven
Fixed Income: Arbitrage
Fixed Income: Arbitrage
FI: Convertible Bonds
FI: Convertible Bonds
Fixed Income: Diversified
Fixed Income: Diversified
Fixed Income: High Yield
Fixed Income: High Yield
Fixed Income: MBS
FI: Mortgage-Backed
Macro
Macro
Market Timing
Market Timing
Merger Arbitrage
Merger Arbitrage
Regulation D
Regulation D
RVA
RVA
Sector (Total)
Sector (Total)
Short Selling
Short Selling
Fund of Funds
Equity Market Neutral: Stat Arb
Equity Market Neutral: StatArb
Fund of Funds
2003
2002 HFRI Index Risk Return
Comparison
2002 HFRI Index Risk Return
Comparison 5 Year Annualised (1998 –
2002)
12
25%
12%
Short Selling
Convertible Arbitrage
Reg. D
Equity Hedge
20%
15%
Lehman Gov/Credit
FI: Diversified
10% FI: Arbitrage
Convertible Arbitrage Macro
Lehman Gov/Credit
9%
FI: Diversified
Relative Value Arb
FI: Mortgage-Backed
Macro
FI: High Yield
Relative Value Arb
Emerging Markets (Total)
Equity Market Neutral
Equity Market Neutral
Fund Weighted Comp. Index
Fund of Funds
Merger Arbitrage
0%
0%
3%
6%
9%
12%
15%
18%
21%
Market Timing Statistical Arbitrage
-5%
Equity Hedge
Return (%)
Return (%)
5%
Distressed Securities
Sector (Total)
Merger Arbitrage
Fund Weighted Comp. Index
Event Driven
Short Selling
Distressed Securities
6%
Fund of Funds
Equity Non-Hedge
FI: Mortgage-Backed
Event Driven
Equity Non-Hedge
Reg. D
-10%
Statistical Arbitrage
Sector (Total)
3%
FI: Arbitrage
-15%
FI: High Yield
FI: Convertible Bonds
FI: Convertible Bonds
-20%
Emerging Markets (Total)
S&P 500
-25%
0%
STD (%)
2003
0%
5%
10%
15%
STD (%)
20%
25%
30%
13
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
14
Creating Exposure
•
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?
15
•
•
•
•
•
•
FoHF Examples
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
16
•
Investment Biases
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
17
Managed Account “Platforms”
•
•
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?
18
Data and Modelling
• 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
19
Transparency Debate
•
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?
20
Hedge Fund Exposures
Long/Short Equity Report Template
Fund Exposure
High
Low
Average
Close
Long Exposure %
Short Exposure %
Net Futures %
Net options %
Gross %
Net %
Cash %
Month end - Industry Sector/Asset type/Credit Exposure
Top 5 Sectors
Long
Short
Gross
1
2
3
4
5
Sum
Month end - Country Exposure
Top 5 Countries
Long
1
2
3
4
5
Source: Fauchier
Short
Gross
Net
Net
Concentration at month end
Long portfolio top 5
Names
% by Value
1
2
3
4
5
Sum
#Long
Long Beta
Perfomance Attribution - month
Month
Long
Short
Futures/Options
Currency
Short Portfolio top 5
% by Value
1
2
3
4
5
Sum
#Short
Short Beta
Total number of positions
Year to date
Gross (Y/N) ?
Net (Y/N) ?
Intra month variation
High
Daily NAV
Fund Equity at month end
($m)
Net change ($m)
Low
Equity
21
Transparency Compliance
(2002)
100%
75%
50%
25%
0%
Long / Short
Sector/Asset
Country
Reported
Source: Fauchier
Top 10
#positions
Not Reported
n/a
Attribution
stdev(NAV)
22
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
Small sample bias
23
• Estimate correlation: n=12 data points:
“ρ=0” ↔ ρ∊[-0.3, 0.3] (85%)
Estimated Correlations for Zero Correlation Data
Correlation Confidence Intervals
Correlation Confidence Intervals
95% confidence level
95% confidence level
0.5
1.0
+/-0.5
0.8
-0.2
am
pl
es
0.0
n
Confidence Interval
12
n=
0.2
nu
m
be
ro
fs
Correlation Confidence Interval
0.0
-0.5
+/-0.4
0.4
5
=2
n=
50
-0.4
-0.6
number of samples
+/-0.3
n=12
n=25
+/-0.2
n=50
+/-0.1
-0.8
+/-0.0
-1.0
Estimated correlation
0.6
0
20
40
60
# months
80
100
120
-0.7
-0.2
0.3
Estimated Correlation
0.8
“secretary problem” - but fund may be already closed
corr=-0.7
corr=-0.2
corr=0.3
corr=0.8
24
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.
Strategy ID
Correlation Matrix
FPAM 1 CORRELATION MATRIX
1 April 2001 to 31
March2001
2003to 31 March 2003
1 April
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
M
M
ELB
ELB
ELB
EHH
EHH
EHH
EHL
EHL
ESB
SC
END
END
MS
MS
MS
MS
FRI
869
342
1079
91
628
1481
912
1102
240
951
267
970
1019
1385
354
54
293
639
226
1011
-0.02
0.19
0.14
0.43
0.55
0.25
0.25
0.13
0.60
0.65
0.57
0.00
0.61
0.67
0.11
0.45
0.45
0.24
0.58
-0.03
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
-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
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
0.13
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
-0.20
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
-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
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
-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
-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
-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
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
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
-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
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
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
-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
-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
-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
-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
-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
0.30
-0.14
0.03
-0.08
-0.65
0.56
0.06
0.06
-0.13
0.07
-0.35
0.32
0.09
-0.52
0.18
0.23
-0.02
0.12
0.04
0.33
-0.63
0.01
-0.82
0.39
0.01
-0.03
-0.26
0.18
-0.13
0.01
0.25
0.33
-0.15
0.18
-0.20
0.14
-0.07
-0.92
0.52
0.22
0.38
-0.26
0.27
0.11
0.09
-0.01
-0.84
0.40
0.15
0.55
-0.21
0.15
0.13
-0.01
0.13
0.58
-0.09
0.22
0.46
-0.30
0.02
0.62
-0.39
Estimation Error
<10%
>20%
<20%
<10%
Correlation band
Positive
>0.66
<-0.42
Negative
<-0.66
Correlation:
Average correlation with all funds
MSCI The World Index - Gross
SSB WGBI 5+ year sector in USD
Notes:
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.
2. The strategies formerly known as Restructuring (R) and Credit Arbitrage (CA)
have been re-classified as Specialist Credit (SC) and Fixed Income (FI) respectively.
3. The correlation matrix is generated from 24 data points.
4. A blank cell denotes that no meaningful correlation exists for the period of the report.
Source: Fauchier
Correlation
0
25
Weekly vs Monthly Data
View
Difference between Weekly and Monthly Correlation Values
BoyerAllanPacific
Caduceus
CanyonCSFB
BoyerAllanPacific 0 -0.24 -0.21 -0.04
Caduceus
-0.24
0 -0.27 -0.15
Canyon
-0.21 -0.27
0 -0.44
CSFB
-0.04 -0.15 -0.44
0
Daedalus
0.11 0.26 -0.09 -0.15
DoubleBlackDiamond
0.21 0.33 0.16 0.10
Egerton
-0.34 -0.11 -0.24 -0.31
FRI
-0.01 0.02 0.17 0.17
Gruss
-0.25 -0.35 -0.08 -0.23
JGDYork
-0.10 -0.07 -0.27 -0.08
LansdowneEuropean
-0.18 0.06 -0.05 0.16
PerryEuropean
-0.05 0.13 -0.13 0.11
PerryPartners-0.26 -0.06 -0.25 -0.33
Raptor
-0.20 -0.29 -0.12 -0.04
Seminole
-0.14 0.02 -0.04 -0.14
SRGlobal
-0.27 -0.09 0.06 0.09
StAlbans
-0.10 0.05 -0.14 -0.42
StandardPacific
-0.19 0.16 0.11 0.12
TTAsia
-0.34 -0.34 -0.04 0.05
WPG
-0.35 -0.34 -0.04 -0.07
Daedalus
DoubleBlackDiamond
EgertonFRI
Gruss
0.11 0.21 -0.34 -0.01 -0.25
0.26 0.33 -0.11 0.02 -0.35
-0.09 0.16 -0.24 0.17 -0.08
-0.15 0.10 -0.31 0.17 -0.23
0 -0.37 -0.16 -0.51 0.17
-0.37
0 0.30 -0.14 0.56
-0.16 0.30
0 -0.01 -0.16
-0.51 -0.14 -0.01
0 0.00
0.17 0.56 -0.16 0.00
0
-0.16 -0.08 -0.13 -0.02 -0.23
-0.11 0.21 -0.08 -0.04 -0.03
-0.74 -0.13 -0.19 0.17 0.14
-0.45 -0.06 -0.29 0.22 -0.02
0.16 0.31 0.10 -0.20 -0.09
0.03 0.21 -0.02 0.02 -0.35
0.33 0.10 0.07 -0.03 0.04
-0.35 -0.12 -0.10 -0.25 -0.07
-0.03 0.14 -0.02 -0.18 0.19
-0.21 0.22 0.02 -0.09 -0.16
0.03 0.24 0.00 -0.30 -0.08
JGDYork
LansdowneEuropean
PerryEuropean
PerryPartners
Raptor Seminole
SRGlobal
StAlbans
StandardPacific
TTAsiaWPG
-0.10 -0.18 -0.05 -0.26 -0.20 -0.14 -0.27 -0.10 -0.19 -0.34 -0.35
-0.07 0.06 0.13 -0.06 -0.29 0.02 -0.09 0.05 0.16 -0.34 -0.34
-0.27 -0.05 -0.13 -0.25 -0.12 -0.04 0.06 -0.14 0.11 -0.04 -0.04
-0.08 0.16 0.11 -0.33 -0.04 -0.14 0.09 -0.42 0.12 0.05 -0.07
-0.16 -0.11 -0.74 -0.45 0.16 0.03 0.33 -0.35 -0.03 -0.21 0.03
-0.08 0.21 -0.13 -0.06 0.31 0.21 0.10 -0.12 0.14 0.22 0.24
-0.13 -0.08 -0.19 -0.29 0.10 -0.02 0.07 -0.10 -0.02 0.02 0.00
-0.02 -0.04 0.17 0.22 -0.20 0.02 -0.03 -0.25 -0.18 -0.09 -0.30
-0.23 -0.03 0.14 -0.02 -0.09 -0.35 0.04 -0.07 0.19 -0.16 -0.08
0 -0.05 -0.01 -0.18 0.13 -0.33 0.00 -0.18 0.17 0.17 -0.41
-0.05
0 0.05 -0.08 -0.01 -0.17 -0.37 -0.18 -0.19 0.06 -0.51
-0.01 0.05
0 -0.12 0.49 0.03 0.08 -0.56 0.18 -0.02 -0.14
-0.18 -0.08 -0.12
0 0.27 -0.06 0.08 -0.28 0.05 0.05 -0.05
0.13 -0.01 0.49 0.27
0 0.13 -0.20 0.12 -0.12 -0.18 -0.08
-0.33 -0.17 0.03 -0.06 0.13
0 -0.15 -0.14 0.19 -0.05 -0.30
0.00 -0.37 0.08 0.08 -0.20 -0.15
0 0.33 -0.30 -0.21 -0.34
-0.18 -0.18 -0.56 -0.28 0.12 -0.14 0.33
0 -0.11 0.30 0.14
0.17 -0.19 0.18 0.05 -0.12 0.19 -0.30 -0.11
0 0.04 0.10
0.17 0.06 -0.02 0.05 -0.18 -0.05 -0.21 0.30 0.04
0 -0.15
-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
Source: Fauchier
Weekly HF “Indexes”
26
60
30
50
40
20
30
20
10
10
0
0
-0.04
-0.02
0.00
M
0.02
0.04
-0.03
-0.02
-0.01
0.00
EHL
0.01
0.02
Equally weighted index of weekly returns: non-normality
Source: Fauchier
0.03
27
Omega Ratio
Keating and Shadwick (2002)
28
Hedge Fund Risk
•
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
29
$9,000
$8,000
The Real Risk
$80.0
$70.0
$7,000
$60.0
$6,000
$5,000
$4,000
$3,000
$50.0
$40.0
$30.0
$2,000
$20.0
$1,000
$0
($1,000)
$10.0
$0.0
30
Risk Management
•
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
31
•
•
•
Market Risks
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
32
Operational Risks (1)
•
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
33
•
•
•
Operational Risks (2)
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…)
34
•
•
•
Funds of Hedge Funds
FoHF A ≠ FoHF B
– % own (or owned) funds, %funds of funds, % multistrategy 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
35
•
Portfolio Construction
“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
36
Portfolio Estimation Risk
• 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→∞
37
Portfolio Construction
0.02
0.03
0.04
0.05
Distribution of Portf olio Weights
207
515
117
215
309
38
Operational Risk Optimality
• 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)
39
Calendar Liquidity Constraints
M/M+30/15
March 03
May 03
July 03
Sept 03
Nov 03
Jan 04
March 04
March 03
May 03
July 03
Sept 03
Nov 03
Jan 04
March 04
March 03
May 03
July 03
Sept 03
Nov 03
Jan 04
March 04
Jan 03
M/M+60/20
Jan 03
2/Q+60
Jan 03
Source: Fauchier
40
Manager Research and
Monitoring
Number of meetings
Total number of meetings
Managers' Office
Fauchier Partners
1200
100
Seminars
90
1000
80
800
60
600
50
40
400
30
20
200
10
0
0
1
-0
n
Ja
pr
A
Source: Fauchier
01
1
l-0
u
J
O
1
-0
ct
2
-0
n
Ja
A
pr
02
2
l-0
u
J
O
2
-0
ct
Cumulative
Per Month
70
41
Conclusion
• 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
42
Bibliography - Introduction
• 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
43
Bibliography - Research
• 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