Hedge Fund Modelling and Analysis using MATLAB E-Book

Paul Darbyshire

• Herausgeber: John Wiley & Sons
• Kategorie: Fachliteratur
• Serie: Wiley Finance Series
• Sprache: Englisch

Seitenzahl: 267

Veröffentlichungsjahr: 2014

Beschreibung

The second book in Darbyshire and Hampton's Hedge Fund Modelling and Analysis series, Hedge Fund Modelling and Analysis Using MATLAB® takes advantage of the huge library of built-in functions and suite of financial and analytic packages available to MATLAB®. This allows for a more detailed analysis of some of the more computationally intensive and advanced topics, such as hedge fund classification, performance measurement and mean-variance optimisation. Darbyshire and Hampton's first book in the series, Hedge Fund Modelling and Analysis Using Excel & and VBA, is seen as a valuable supplementary text to this book. Starting with an overview of the hedge fund industry the book then looks at a variety of commercially available hedge fund data sources. After covering key statistical techniques and methods, the book discusses mean-variance optimisation, hedge fund classification and performance with an emphasis on risk-adjusted return metrics. Finally, common hedge fund market risk management techniques, such as traditional Value-at-Risk methods, modified extensions and expected shortfall are covered. The book's dedicated website, www.darbyshirehampton.com provides free downloads of all the data and MATLAB® source code, as well as other useful resources. Hedge Fund Modelling and Analysis Using MATLAB® serves as a definitive introductory guide to hedge fund modelling and analysis and will provide investors, industry practitioners and students alike with a useful range of tools and techniques for analysing and estimating alpha and beta sources of return, performing manager ranking and market risk management.

Leseprobe

For other titles in the Wiley Finance series

please see www.wiley.com/finance

Hedge Fund Modelling and Analysis Using MATLAB®

Paul Darbyshire

David Hampton

This edition first published 2014 © 2014 John Wiley & Sons, Ltd

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ISBN 978-1-119-96737-8 (hbk) ISBN 978-1-119-96768-2 (ebk) ISBN 978-1-119-96767-5 (ebk) ISBN 978-1-118-90502-9 (ebk)

Cover images reproduced by permission of Shutterstock.com

To Mum & Dad

Thank you for all your love and support, as always.

P.D.

To Marie-Christine, Juliette and Antoine, with my unconditional love.

D.H.

CONTENTS

Preface

MathWorks Contact Information

1. MATLAB

®

  Source Code

2. MATLAB

®

  User-Defined Functions

3. Hypothetical Hedge Fund Data

4. Book Website

CHAPTER 1 The Hedge Fund Industry

1.1 What are Hedge Funds?

1.2 The Structure of a Hedge Fund

1.3 The Global Hedge Fund Industry

1.4 Specialist Investment Techniques

1.5 New Developments for Hedge Funds

Notes

CHAPTER 2 Hedge Fund Data Sources

2.1 Hedge Fund Databases

2.2 Major Hedge Fund Indices

2.3 Database and Index Biases

2.4 Benchmarking

Notes

CHAPTER 3 Statistical Analysis

3.1 Basic Performance Plots

3.2 Probability Distributions

3.3 Probability Density Function

3.4 Cumulative Distribution Function

3.5 The Normal Distribution

3.6 Visual Tests for Normality

3.7 Moments of a Distribution

3.8 Covariance and Correlation

3.9 Linear Regression

Notes

CHAPTER 4 Mean-Variance Optimisation

4.1 Portfolio Theory

4.2 Efficient Portfolios

Notes

CHAPTER 5 Performance Measurement

5.1 The Intuition Behind Risk-Adjusted Returns

5.2 Absolute Risk-Adjusted Return Metrics

5.3 Market Model Risk-Adjusted Return Metrics

5.4 MAR and LPM Metrics

5.5 Multi-Factor Asset Pricing Extensions

Notes

CHAPTER 6 Hedge Fund Classification

6.1 Financial Instrument Building Blocks and Style Groups

6.2 Hedge Fund Clusters and Classification

Notes

CHAPTER 7 Market Risk Management

7.1 Value-at-Risk

7.2 Traditional VaR Methods

7.3 Modified VaR

7.4 Expected Shortfall

7.5 Extreme Value Theory

Notes

References

Index

End User License Agreement

List of Tables

Chapter 1

Table 1.1

Chapter 2

Table 2.1

Table 2.2

Table 2.3

Table 2.4

Table 2.5

Chapter 3

Table 3.1

Chapter 5

Table 5.1

Table 5.2

Table 5.3

Table 5.4

Table 5.5

Table 5.6

Table 5.7

Table 5.8

Table 5.9

Table 5.10

Table 5.11

Table 5.12

Table 5.13

Table 5.14

Table 5.15

Table 5.16

Table 5.17

Table 5.18

Table 5.19

Table 5.20

Table 5.21

Chapter 6

Table 6.1

Table 6.2

Chapter 7

Table 7.1

Table 7.2

List of Illustrations

Chapter 1

Figure 1.1

A schematic of the typical structure of a hedge fund

Figure 1.2

Growth in the global hedge funds industry since 2000

Figure 1.3

Geographical locations of hedge fund

Figure 1.4

Growth of the North American hedge fund industry since 2000

Figure 1.5

Growth of the European hedge fund industry since 2000

Figure 1.6

Growth of the Asian hedge fund industry since 1999

Figure 1.7

Growth in number of UCITS III hedge funds since December 2007

Figure 1.8

UCITS III hedge funds by investment strategy

Chapter 2

Figure 2.1

Historical asset weights by investment strategy for the DJCS Hedge Fund Index

Figure 2.2

The Liquid Alternative Beta Index Model

Figure 2.3

Hypothetical performance of the CS LAB Index from Jan 1998 to Dec 2009 and actual historical performance from Jan 2010 through July 2010

Figure 2.4

A schematic of the CS LAB Index construction process

Figure 2.5

The growth of $1000 since inception of the HFRI Fund Weighted Composite Index and Fund of Funds Composite Index against the S&P 500

Figure 2.6

A dynamic, bottom-up approach to HFRX index construction

Figure 2.7

FTSE Hedge Index quantitative and qualitative index construction

Figure 2.8

The family of GAI Investable Indices

Figure 2.9

Schematic of the fund selection process

Figure 2.10

A schematic of the MSCI investable index construction methodology

Chapter 3

Figure 3.1

Bar chart of the monthly returns for a hypothetical CTA Index (2008–2013)

Figure 3.2

The VAMI plot for a hypothetical CTA Index of monthly returns (2008–2013)

Figure 3.3

Histogram plot for a hypothetical CTA Index of monthly returns (2008–2013)

Figure 3.4

Several samples taken from the population of the data set

Figure 3.5

The PDF and interval [

a

,

b

]

Figure 3.6

The relationship between the PDF and CDF

Figure 3.7

The central limit theorem

Figure 3.8

The normal distribution

Figure 3.9

Empirical vs. normal distribution for a hypothetical CTA Index (2008–2013)

Figure 3.10

Normal probability plot for a hypothetical CTA Index (2008–2013)

Figure 3.11

Positive and negative skew

Figure 3.12

Positive, negative and zero kurtosis

Figure 3.13

Some typical correlation plots

Figure 3.14

Simple linear regression

Figure 3.15

A residual plot

Figure 3.16

The linear regression plot and model

Chapter 4

Figure 4.1

Risk-return scatter plot for 10 hypothetical hedge funds

Figure 4.2

The efficient frontier and minimum variance portfolio

Figure 4.3

Mean-variance efficient frontier

Figure 4.4

Random portfolios within the mean-variance efficient frontier

Chapter 5

Figure 5.1

VAMI for Two CTAs: Manager A and B

Figure 5.2

CTAs plotted in mu-sigma space

Figure 5.3

The SML for the market (zero alpha), Hedge Fund A and Hedge Fund B

Figure 5.4

The GH1 metric and alpha measure

Figure 5.5

The M2 metric and alpha measure

Figure 5.6

The GH2 metric and alpha measure

Chapter 6

Figure 6.1

Pie chart of each main instrument group

Figure 6.2

New funds added monthly (right side) and funds closed down (left side) from 1991 to 2011 in the Eurekahedge database

Figure 6.3

Hurst data time series showing how the volatility of each time series increases as the Hurst exponent decreases from 0.75 to 0.25 in decrements of 0.05

Figure 6.4

Hurst data set Euclidian dendrogram

Figure 6.5

City Block dendrogram

Figure 6.6

Mahalanobis dendrogram

Figure 6.7

Correlation dendrogram

Figure 6.8

Correlation dendrogram for the 10 hypothetical hedge funds

Figure 6.9

Euclidean dendrogram for the 10 hypothetical hedge funds

Figure 6.10

Euclidian dendrogram for the monthly futures data

Figure 6.11

Correlation dendrogram for the monthly futures data or “How a Diversified CTA Sees the World”

Figure 6.12

French30 Euclidian dendrogram

Figure 6.13

French30 correlation dendrogram or “How a French Long-Short Equity Manager sees the World”

Figure 6.14

Eurekahedge fund correlation dendrogram or “How a Fund of Hedge Funds Manager sees the World”

Chapter 7

Figure 7.1

VaR at the 95% and 99% confidence levels

Figure 7.2

Estimated 5% worse case losses for a hypothetical CTA index (2008–2013)

Figure 7.3

Histogram showing monthly VaR using historic simulation

Figure 7.4

Histogram showing monthly VaR using the parametric method

Figure 7.5

Histogram plot showing monthly MVaR

Figure 7.6

Comparison of ES and VaR at the 95% confidence level

Figure 7.7

Monthly ES at 95% confidence level

Figure 7.8

The “child” and “parent” distributions

Figure 7.9

Hypothetical hedge fund losses over 100 days

Figure 7.10

The largest losses in each 10-day block

Figure 7.11

Losses over a threshold

Figure 7.12

The random variable

X

and threshold

u

Guide

Cover

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Preface

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Preface

This book is a practical introduction to modelling and analysing hedge funds based on the MATLAB® technical computing environment. MATLAB® is a high-level language and interactive environment for numerical computation, visualisation and programming. Using MATLAB®, you can analyse data, develop algorithms and create models and applications. The language, tools and built-in maths functions enable you to explore multiple approaches and reach a solution faster than with spreadsheets or traditional programming languages, such as C/C++ or Java. MATLAB is the foundation for all products, including Simulink and can be extended with add-on products for a whole range of applications, including statistics, computational finance and optimisation.