Advances in Portfolio Construction and Implementation

384 Pages·2003·1.692 MB·English

by  Alan Scowcroft, Stephen Satchell

ADVANCES IN PORTFOLIO
CONSTRUCTION AND
IMPLEMENTATION
Butterworth-Heinemann Finance
aims and objectives
• books based on the work of financial market practitioners,and academics
• presenting cutting edge research to the professional/practitionermarket
• combining intellectualrigour and practical application
• covering the interaction between mathematical theory and financial practice
• to improve portfolio performance, risk management and trading book performance
• covering quantitativetechniques
market
Brokers/Traders; Actuaries; Consultants; Asset Managers; Fund Managers; Regulators;
Central Bankers; Treasury Officials; Technical Analysts;and Academics for Masters in
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series titles
Return Distributionsin Finance
DerivativeInstruments: theory, valuation,analysis
Managing DownsideRisk in Financial Markets: theory, practice & implementation
Economics for Financial Markets
Performance Measurement in Finance: firms, funds and managers
Real R&D Options
Forecasting Volatilityin the Financial Markets
Advanced Trading Rules
Advances in Portfolio Construction and Implementation
series editor
Dr Stephen Satchell
Dr Satchell is the Reader in Financial Econometrics at Trinity College, Cambridge;
VisitingProfessoratBirkbeckCollege,CityUniversityBusinessSchoolandUniversity
of Technology, Sydney. He also works in a consultative capacity to many firms, and
edits the journal Derivatives: use, trading and regulations and the Journal of Asset
Management.
ADVANCES IN PORTFOLIO
CONSTRUCTION AND
IMPLEMENTATION
Edited by
Stephen Satchell
Alan Scowcroft
AMSTERDAM BOSTON HEIDELBERG LONDON NEWYORK OXFORD
PARIS SANDIEGO SANFRANCISCO SINGAPORE SYDNEY TOKYO
Butterworth-Heinemann
An imprint of Elsevier
Linacre House, Jordan Hill, Oxford OX2 8DP
200 Wheeler Road, Burlington MA 01803
First published2003
Copyright  2003, Elsevier Ltd. All rights reserved
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British Library Cataloguing in Publication Data
Advances in portfolio construction and implementation
1. Portfolio management 2. Risk management
I. Satchell, Stephen E. II. Scowcroft, A.
332.6
ISBN 0 7506 5448 1
Library of Congress Cataloguing in Publication Data
A catalogue record for this book is availablefrom the Library of Congress
ISBN 0 7506 5448 1
ForinformationonallButterworth-Heinemannfinancepublications
visitourwebsiteatwww.bh.com/finance
Typeset by Laserwords Private Limited, Chennai, India
Printed and bound in Great Britain
Contents
List of Contributors xi
Introduction xvii
1 A review of portfolio planning: models and systems 1
Gautam Mitra
1.1 Introduction and Overview 2
1.2 Alternative Computational Models 4
1.3 Symmetric and Asymmetric Measures of Risk 14
1.4 Computational Models in Practice 18
1.5 Preparation of Data: Financial Data Marts 22
1.6 Solution Methods 25
1.7 Computational Experience 27
1.8 Discussions and Conclusions 32
1.9 Appendix 1: Piecewise Linear Approximation of the
Quadratic Form 32
1.10 Appendix 2: Comparative Computational Views
of the Alternative Models 34
References 37
Web References 39
Acknowledgements 39
2 Generalized mean-variance analysis and robust portfolio
diversification 40
Stephen M Wright andS E Satchell
2.1 Introduction 41
2.2 Generalized Mean-Variance Analysis 44
vi Contents
2.3 The State Preference Theory Approach to Portfolio
Construction 46
2.4 Implementation and Simulation 48
2.5 Conclusions and Suggested Further Work 53
References 54
3 Portfolio construction from mandate to stock weight:
a practitioner’s perspective 55
Dr Julian Coutts
3.1 Introduction 56
3.2 Allocating Tracking Error for Multiple Portfolio Funds 58
3.3 Tracking Errors for Arbitrary Portfolios 64
3.4 Active CAPM, or How Far Should a Bet be Taken? 82
3.5 Implementing Ideas in Real Stock Portfolios 89
3.6 Conclusions 92
References 94
4 Enhanced indexation 95
Alan Scowcroftand JamesSefton
4.1 Introduction 96
4.2 Constructing a Consistent View 97
4.3 Enhanced Indexing 103
4.4 An Illustrative Example: Top-down or Bottom-up? 106
4.5 Conclusions 119
4.6 Appendix 1: Derivation of the Theil–Goldberger
Mixed Estimator 120
4.7 Appendix 2: Optimization 121
References 123
Notes 124
5 Portfolio management under taxes 125
Dan diBartolomeo
5.1 Introduction 125
5.2 Do Taxes Really Matter to Investors and Managers? 126
5.3 The Core Problems 127
5.4 The State of the Art 128
5.5 The Multi-Period Aspect 130
5.6 Loss Harvesting 132
5.7 After-Tax Benchmarks 132
Contents vii
5.8 Conclusions 133
References 133
6 Using genetic algorithms to construct portfolios 135
Dr T Wilding
6.1 Limitations of Traditional Mean-Variance Portfolio
Optimization 135
6.2 Selecting a Method to Limit the Number of Securities
in the Final Portfolio 141
6.3 Practical Construction of a Genetic Algorithm-Based
Optimizer 145
6.4 Performance of Genetic Algorithm 150
6.5 Conclusions 158
References 159
7 Near-uniformly distributed, stochastically generated portfolios 161
Richard Dawsonand RichardYoung
7.1 Introduction – A Tractable N-Dimensional Experimental
Control 162
7.2 Applications 163
7.3 Dynamic Constraints 165
7.4 Results from the Dynamic Constraints Algorithm 173
7.5 Problems and Limitations with Dynamic Constraints
Algorithm 174
7.6 Improvements to the Distribution 175
7.7 Results of the Dynamic Constraints with Local
Density Control 180
7.8 Conclusions 185
7.9 Further Work 185
7.10 Appendix 1: Review of Holding Distribution in Low
Dimensions with Minimal Constraints 186
7.11 Appendix 2: Probability Distribution of Holding
Weight in Monte Carlo Portfolios in N Dimensions
with Minimal Constraints 189
7.12 Appendix 3: The Effects of Simple Holding Constraints
on Expected Distribution of Asset Holding Weights 190
7.13 Appendix 4: Properties of Hyper-Solids 191
References 192
Notes 192
viii Contents
8 Modelling directional hedge funds–mean, variance and
correlation with tracker funds 193
Emmanuel Acar
8.1 Introduction 193
8.2 Mean and Variance of Directional Strategies 194
8.3 Correlation with Tracker Fund 196
8.4 Parameters Estimation 198
8.5 Optimal Allocation 199
8.6 An Empirical Application to the Currency Markets 207
8.7 Conclusions 208
8.8 Appendix 1: Mean and Variance of Directional
Strategies 209
8.9 Appendix 2: Correlation with Tracker Fund 210
8.10 Appendix 3: Optimal Allocation 212
References 213
Notes 214
Acknowledgements 214
9 Integrating market and credit risk in fixed income portfolios 215
Alla Giland Yuri Polyakov
9.1 Introduction 215
9.2 How to Measure Market and Credit Risk 216
9.3 The Ways of Constructing Loss Distributions 218
9.4 Components of Credit Risk 220
9.5 Portfolio Approach 227
9.6 Conclusions 232
9.7 Appendix 233
References 240
Notes 242
10 Incorporating skewness and kurtosis in portfolio optimization:
a multidimensional efficient set 243
Gustavo M de Athayde andRenato G Floˆres, Jr
10.1 Introduction 243
10.2 The Algebra of Multivariate Moments 246
10.3 The Portfolio Frontier: Expected Return, Skewness and
Kurtosis 248
10.4 Conclusion 256
References 256
Notes 257
Contents ix
11 Balancing growth and shortfall probability in continuous time
active portfolio management 258
Sid Browne
11.1 Introduction 258
11.2 Some Basics 259
11.3 Active Portfolio Management 261
11.4 Trading off Risk and Return in Active Portfolio
Management: Fractional Objectives 265
11.5 Risk-Constrained Minimal Time 266
References 268
12 Assessing the merits of rank-based optimization for
portfolio construction 269
Soosung Hwang,Stephen E Satchell andStephen M Wright
12.1 Introduction 269
12.2 Optimal Portfolio with Ranks 270
12.3 Empirical Tests 273
12.4 Conclusions 288
References 289
Notes 289
13 The mean-downside risk portfolio frontier: a non-parametric
approach 290
Gustavo M de Athayde
13.1 Introduction 290
13.2 The Mean-DSR Portfolio Frontier: The Traditional
Approach 293
13.3 The Multivariate Case 297
13.4 A Kernel Approach 299
13.5 The Kernel Approach to the Multivariate Case 303
13.6 The Mean-DSR Portfolio Frontier Using Kernel Estimates 305
13.7 Asset Pricing 306
13.8 Conclusion 308
References 308
14 Some exact results for efficient portfolios with given returns 310
G H Hillier and S E Satchell
14.1 Introduction 310
14.2 Properties of the Risk Estimator 313
14.3 Properties of the Estimated Portfolio Weights 317
14.4 The Riskless Asset Case 321