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Market Risk Management for Hedge Funds -Foundations of the Style and ImplicitValue-at-Risk
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  • Wiley

More About This Title Market Risk Management for Hedge Funds -Foundations of the Style and ImplicitValue-at-Risk

  • English

English

This book provides a cutting edge introduction to market risk management for Hedge Funds, Hedge Funds of Funds, and the numerous new indices and clones launching coming to market on a near daily basis.  It will present the fundamentals of quantitative risk measures by analysing the  range of Value-at-Risk (VaR) models used today, addressing the robustness of each model, and looking at new risk measures available to more effectively manage risk in a hedge fund portfolio.
The book begins by analysing the current state of the hedge fund industry - at the ongoing institutionalisation of the market, and at its latest developments.  It then moves on to examine the range of risks, risk controls, and risk management strategies currently employed by practitioners, and focuses on particular risks embedded in the more classic investment strategies such as Long/Short, Convertible Arbitrage, Fixed Income Arbitrage, Short selling and risk arbitrage.  Addressed along side these are other risks common to hedge funds, including liquidity risk, leverage risk and counterparty risk.

The book then moves on to examine more closely two models which provide the underpinning for market risk management in investment today - Style Value-at-Risk and Implicit Value-at-Risk.  As well as full quantitative analysis and backtesting of each methodology, the authors go on to propose a new style model for style and implicit Var, complete with analysis, real life examples and backtesting.  The authors then go on to discuss annualisation issues and risk return before moving on to propose a new model based on the authors own Best Choice Implicit VaR approach, incorporating quantitative analysis, market results and backtesting and also its potential for new hedge fund clone products.

This book is the only guide to VaR for Hedge Funds and will prove to be an invaluable resource as we embark into an era of increasing volatility and uncertainty.

 

  • English

English

François Duc is head of the Risk Advisory Desk for alternative investments of UBP (Union Bancaire Privée), the second largest worldwide investor in hedge funds. Prior to joining UBP in October 2005, Francois was responsible for the quantitative analysis and risk management at Banque SYZ & Co. In addition, he has written articles in finance, statistics and general equilibrium theory for various publications and is co-editor of a book on a learning process. Francois did his PhD in Econometrics at Geneva University where he was Assistant Professor in Statistics.

Yann Schorderet works as a quantitative strategist at Banque Mirabaud & Cie. From June 2004 to June 2006, he was a member of both the Risk Advisory team and the Quantitative Team at UBP (Union Bancaire Privée). In 2003, he acted as a quantitative analyst in a start-up company specialised in funds of hedge funds. Prior to that, he was Assistant Professor in the Department of Econometrics of the University of Geneva and the Laboratoire d’Economie Appliquée. From 2001 to 2002, he carried out post-doctoral research at the University of California, San Diego. He holds a PhD in econometrics and statistics from the University of Geneva. Yann is a CFA charterholder.

  • English

English

Contents

Acknowledgements

1 Introduction

Part I Fundamentals for Style and Implicit Values-at-Risk

2 Ongoing Institutionalization

2.1 Hedge funds industry size and asset flows

2.2 Style distribution

2.3 2006-2007 structural developments

2.4 Are hedge funds becoming decent?

2.5 Funds of hedge funds persistence

3 Heterogeneity of Hedge Funds

3.1 Testing sample

3.2 Smoothing effect of a restrictive classification

3.3 Heterogeneity revealed through Modern Cluster Analysis

3.4 Appendix A: Indices sample

4 Active and Passive Hedge Fund Indices

4.1 Illusions fostered by active hedge fund indices

4.2 Passive indices and the illusion of being clones

4.3 Conclusion

5 The Four Dimensions of Risk Management for Hedge Funds

5.1 Operational and structural risk

5.2 Risk control

5.3 Delegation risk

5.4 Direct investment risk

5.5 Conclusion

5.6 Appendix B: Risks embedded with some classical alternative strategies

5.7 Appendix C: Other common risks to hedge funds

Part II Style Value-at-Risk

6 The Original Style VaR Revisited 77

6.1 The Multi-Index Model

6.2 The Style Value-at-Risk

6.3 Backtesting revisited

7 The New Style Model

7.1 Extreme Value Theory

7.2 Risk consolidation

7.3 The New Style Model

7.4 Appendix D: Algorithms for the elemental percentile method

7.5 Appendix E: Copulas

8 Annualization Problem

8.1 Annualization of the main statistical indicators assuming i.i.d.

8.2 Annualization of Value-at-Risk assuming i.i.d.

8.3 Annualization without assuming i.i.d.

8.4 Applications to the Style Value-at-Risk

8.5 Appendix F: annualization of excess kurtosis  

8.6 Appendix G: Drost and Nijman Theorem

Part III Implicit Value-at-Risk

9 The Best Choice Implicit Value-at-Risk

9.1 Alternative style analysis and BCI Model

9.2 Theoretical framework of BCIM

9.3 Best Choice Implicit VaR

9.4 Empirical Tests

10 BCI Model and Hedge Fund Clones

10.1 Ten-Factor Model

10.2 Non-Linear Model

11 Risk Budgeting

11.1 Value-at-Risk of a multi-managers portfolio

11.2 Risk decomposition: 'before and after' attribution

11.3 Risk decomposition: closed form attribution

12 Value-at-Risk Monitoring

12.1 Analyzing graveyards and hedge funds demise

12.2 The probit model

12.3 Empirical evidence

12.4 Implications for portfolio management

13 Beyond Value-at-Risk

13.1 2007–2008 liquidity crisis and hedge funds

13.2 Mechanical stress test

13.3 Liquidity-adjusted Value-at-Risk

13.4 Limit of liquidity-adjusted Value-at-Risk and liquidity scenario

Bibliography

Index

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