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The Risks of Portfolios of Hedge Funds. Drago Indjic Fauchier Partners. PRMIA, 14 May 2003, London. Don’t believe everything you read Negative media bias Cliché: “LTCM”, “Soros”, “Courtisans” … = Investor education, academic research . Speculators. 1. El Pais, 24 Feb 2003.

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The risks of portfolios of hedge funds

The Risks of Portfolios of Hedge Funds

Drago Indjic

Fauchier Partners

PRMIA, 14 May 2003, London


Don’t believe everything you read

Negative media bias

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

= Investor education, academic research

Speculators

1

El Pais, 24 Feb 2003


Early 21c. Risk

2

Source: HFR, Pertrac, Fauchier


Content

3

  • 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?)


Hedged Funds

4

  • 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


Industry

5

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

Estimated Hedge Fund Asset Growth and Flow 1990 - 2002

6

Assets (In $MM)

Number of Funds

Estimated Assets

Asset Flows

2003


Hedge Fund Environment

7

  • Tass Asset Flows Report™ 4Q2002

    3493 total -1337 “dead”=2156 “live” funds

  • HFR 2002 Industry Report:

    4598 funds (exc. FoF)

    (AUM most probably underestimated)


Another Asset Class?

8

  • 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


Investment Strategies

9

  • 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 AUM 1990

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

10

2003


Estimated Net Asset Flow by Strategy 2002

Estimated Net Asset Flow by Strategy Q4 2002

11

Fund of Funds

2003


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

2002 HFRI Index Risk Return Comparison

12

2003


Aima strategy definitions
AIMA Strategy Definitions (1998 – 2002)

13

  • 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


Creating Exposure (1998 – 2002)

14

  • 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?


FoHF Examples (1998 – 2002)

15

  • 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


Investment Biases (1998 – 2002)

16

  • 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


Managed Account “Platforms” (1998 – 2002)

17

  • 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?


Data and Modelling (1998 – 2002)

18

  • 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


Transparency Debate (1998 – 2002)

19

  • 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?


Long/Short Equity Report Template (1998 – 2002)

Hedge Fund Exposures

20

Source: Fauchier


Transparency Compliance (1998 – 2002)

(2002)

21

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

Estimation Risk

22


Small sample bias noisy data samples

23

  • Estimate correlation: n=12 data points:

    “ρ=0” ↔ ρ∊[-0.3, 0.3] (85%)

    “secretary problem” - but fund may be already closed


Correlation Matrix noisy data samples

1 April 2001 to 31 March 2003

24

Source: Fauchier


Weekly vs monthly data view
Weekly vs Monthly Data View noisy data samples

25

Surprising differences in certain fund correlations pairs

Source: Fauchier


Weekly hf indexes
Weekly HF “Indexes” noisy data samples

26

Equally weighted index of weekly returns: non-normality

Source: Fauchier


Omega Ratio noisy data samples

27

Keating and Shadwick (2002)


Hedge Fund Risk noisy data samples

28

  • 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


The Real Risk noisy data samples

29


Risk Management noisy data samples

30

  • 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


Market Risks noisy data samples

31

  • 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


Operational Risks (1) noisy data samples

32

  • 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


Operational Risks (2) noisy data samples

33

  • 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…)


Funds of Hedge Funds noisy data samples

34

  • 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


Portfolio Construction noisy data samples

35

  • “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


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

Portfolio Estimation Risk

36

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


Portfolio Construction inhomogeneity

37


Operational Risk Optimality inhomogeneity

38

  • 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)


Calendar Liquidity Constraints inhomogeneity

39

M/M+30/15

Sept 03

March 04

Jan 03

July 03

Nov 03

Jan 04

March 03

May 03

M/M+60/20

March 04

Sept 03

Jan 03

Jan 04

July 03

Nov 03

March 03

May 03

2/Q+60

March 04

Sept 03

Jan 03

Jan 04

July 03

Nov 03

March 03

May 03

Source: Fauchier


Manager Research and inhomogeneity

Monitoring

40

Number of meetings

Total number of meetings

Source: Fauchier


Conclusion inhomogeneity

41

  • 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


Bibliography - Introduction inhomogeneity

42

  • 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


Bibliography - Research inhomogeneity

43

  • 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


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