Empirical Analysis of Fund of Hedge Funds (Tass database)

Presented to:

Research Project andWorking Paper

Presenter: Florian BoehlandtUniversity: University of Stellenbosch – Business SchoolSupervisor: Prof Eon Smit

Prof Niel KrigeResearch Title: A Risk-Return Assessment of Fund of Hedge

Funds in Comparison to Single Hedge Funds – An Empirical Analysis

Contact: 14959747@sun.ac.za

‘In the business world, the rearview mirror is always clearer than the windshield’

- Warren Buffett -

Research Purpose

1. Comparative time series analysis of Fund of Hedge Funds vs. Single Manager Funds

2. Estimating the impact of leverage on downside volatility and risk

3. Constructing style indices from risk parameters and AUM weightings

4. Automating data import and data analysis for future quantitative analysis (‘dashboard’)

Code Execution (1/2)

Data Import •Extract relevant data from Access (SQL)•Import data as Pivot table report

Data Treatment •Test for serial correlation / normality•Calculate adjusted excess returns

Data Analysis •Select funds with consistent data series •Determine fund specific risk parameters

Code Execution (2/2)

Weighting •Estimate weighted average parameters•Construct style indices

Comparative Analysis •Calculate within-group variation•Calculate between-group variation

Data Output •Tabular display of aggregate results•Construction of line - bar charts

Hedge Fund Categories (TASS)

Categories

Directional

Dedicated Short Bias

Global Macro

Emerging Markets

Global Macro

Long / Short Equity

Managed Futures

Fund of Hedge Funds Market Neutral

Equity Market Neutra

l

Event Drive

n

Event Driven

Convertible Arbitrage

Fixed Income Arbitra

ge

Data Import

•Code•Fund (Name)•Main Strategy

Information

•MM_DD_YYYY (Date)•Yield•Ptype (ROI or AUM)

Performance

•Leverage (Yes/No)System

Information

Access Database Excel Pivot table report

Risk-Return Parameters (1/2)

• Return on Investment• Downside Risk

– Standard Deviation– Downside Deviation– Value at Risk– Modified Value at Risk

• Maximum Continuous Drawdown

Risk-Return Parameters (2/2)

• 3-Factor Regression– Regression Alpha– Average Error term– Information Ratio

Adaptation Current Research

t – test (betweenstrategies)

UnbalancedANOVA (withinand betweentreatments)

t – test (leveragevs. no leverage)

t – test forequal means

t – test forequal means

t – test forequal means

Statistical Tests

Strategy 1Leverage

Strategy 1No

Leverage

t – test forequal means

Strategy 2Leverage

Strategy 2No

Leverage

Step 1: Copy folder to desktop or hard drive

User Guide (1/4)

Step 2: Manual amendments to source code

User Guide (2/4)

'***********************************************'-->RAWDATA()'Rotate through PivotItems Strategy'1 = Convertible Arbitrage'2 = Dedicated Short Bias'3 = Emerging Markets'4 = Equity Market Neutral'5 = Event Driven'6 = Fixed Income Arbitrage'7 = Fund of Funds'8 = Global Macro'9 = Long/Short Equity'10 = Managed Futures'***********************************************'set index and endloopi to stategy in focus (e.g. 7 for Fund of Funds)'set endloopj and startloopj to strategies compared'e.g. comparing Fund of Hedge Funds to Fixed Income Arbitrage :

index = 7endloopi = 7endloopj = 7startloopj = 6

Step 3: Open spreadsheet shell and start execution

User Guide (3/4)

Step 4: Fill in Userform

User Guide (4/4)

Select hard drive

Select file path

Select parameter

Example Output (1/2)

1/1/1994 7/1/1995 1/1/1997 7/1/1998 1/1/2000 7/1/2001 1/1/2003 7/1/2004 1/1/2006 7/1/200750

100

150

200

250

300

350

400

450

500

550

600

Fund of Funds

Convertible Arbitrage

Dedicated Short Bias

Emerging Markets

Equity Market Neutral

Event Driven

Fixed Income Arbitrage

Global Macro

Long/Short Equity

Managed Futures

S&P 500 DRI Index

Example Output (2/2)

04/01/199807/01/199910/01/2000 01/01/200204/01/2003 07/01/200410/01/200501/01/200704/01/2008

-15-10-505

1015

00.0050.010.0150.020.0250.030.0350.04

Fixed Income Arbitrage

Test

sta

tistic

Fund of Funds

FoH

F 36

m V

olat

ility

04/01/1998 07/01/1999 10/01/2000 01/01/2002 04/01/2003 07/01/2004 10/01/2005 01/01/2007 04/01/2008

-15-10-505

1015

-0.2-0.100.10.20.30.40.50.6

Global Macro

Test

sta

tistic

Fund of Funds

FoH

F 36

m IR

Joint starting point

Significance

Empirical Findings (1/2)

• Measures of volatility and downside risk were significantly improved for FoHFs, compared to their single-strategy peers

• No evidence was found that FoHF strategies overcharge for risk diversification benefits

• With reference to continuous drawdown, attrition rates and VaR, FoHFs are a valuable supplement to the institutional portfolio

Empirical Findings (2/2)

• It could not be established whether gearing affected hedge fund performance – either favourably or adversely

• Some statistical evidence could be found of a higher exposure of leveraged funds to the recent subprime crisis

Extended Research

• Hedge Fund Linear Pricing Models– Sharpe Factor Model (Sharpe, 1992)– Constrained Regression (Otten, 2000)– Fama-French Factor Model (Fama, 1992)

• Factor Component Analysis (Fung, 1997)• Simulation of Trading component (lookback

straddle)

Prediction Models

Prediction Models

AR

ARMA

ARIMA

GLS

Univariate

Multivariate

Conditional

PCA Polynomial Fitting

Taylor Series

Higher Co-Moments

Constrained

Lagrange

KKT

Simulation

Sources

Fama, E.F. & French, K.R. 1992. The Cross-Section of Expected Stock Returns. Journal of Finance, 47(2), June, 427-465. [Online] Available: http://links.jstor.org/sici?sici=0022-1082%28199206%2947%3A2%3C427%3ATCOESR%3E2.0.CO%3B2-N

Fung, W. & Hsieh, D.A. 1997. Empirical characteristics of dynamic trading strategies: the case of hedge funds. Review of Financial Studies, 10(2), Summer, 275-302. [Online] Available: http://faculty.fuqua.duke.edu/~dah7/rfs1997.pdf

Otten, R. & Bams, D. 2000. Statistical Tests for Return-Based Style Analysis. Paper delivered at EFMA 2001 Lugano Meetings, July. [Online] Available: http://papers.ssrn.com/sol3/papers.cfm?abstract_id=277688

Sharpe, W.F. 1992. Asset allocation: management style and performance measurement. Journal of Portfolio Management, Winter, 7-19. [Online] Available: www.uic.edu/classes/fin/fin512/Articles/sharpe.pdf