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Hedge funds are the fastest growing sector of the financial industry, and possibly the least understood. In this book, as a follow-on to Hedge Funds: Myths and Limits, the author provides a primer on the quantitative nature of these alternative investments.

Written by an author experienced as both a practitioner and academic, Hedge Funds: Quantitative Insights provides a step-by-step introduction on how quantitative tools can be applied to hedge fund investing. Divided into three parts, the book begins with coverage of the measurement of risk-adjusted returns for hedge funds. The focus is not on determining whether hedge funds outperform or under-perform traditional markets, but rather on understanding the real meaning of performance statistics used by hedge fund managers and quantitative analysts. The second part of the book examines the risk exposures of hedge funds, and subsequently, their return drivers. The final part of the book enters the field of portfolio construction and asset allocation.

Hedge Funds: Quantitative Insights is essential reading for finance practitioners, including portfolio managers, qualitative and quantitative analysts, consultants and investors - both institutional and private. It could also prove useful to students of finance who want a better understanding of what goes on in the hedge fund world.

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Product Details

  • ISBN-13: 9780470856673
  • Publisher: Wiley
  • Publication date: 7/28/2004
  • Series: Wiley Finance Series, #248
  • Edition number: 1
  • Pages: 354
  • Product dimensions: 6.97 (w) x 9.90 (h) x 1.07 (d)

Meet the Author

François-Serge Lhabitant, PhD, has substantial experience in risk management and alternative investments, as both a practitioner and academic. Formerly, he was a Director at UBS/Global Asset Management and a Member of Senior Management at Union Bancaire Privée, in charge of the quantitative analysis and the management of dedicated hedge fund portfolios. He is currently a professor of Finance at the EDHEC Business School (France) and at the University of Lausanne (Switzerland), and a senior advisor to Kedge Capital Partners.

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Read an Excerpt

Hedge Funds

Quantitative Insights
By François-Serge Lhabitant

John Wiley & Sons

ISBN: 0-470-85667-X

Chapter One

Characteristics of Hedge Funds

I don't play the game by a particular set of rules; I look for changes in the rules of the game. A global macro manager

While their mainstream popularity seems to be a new phenomenon, hedge funds have been around for more than 50 years. Indeed, Alfred Winslow Jones, journalist, sociologist and fund manager, is credited with establishing the first hedge fund as a general partnership in 1949. He operated in complete secrecy until 1966. Then, an article penned by Carol J. Loomis in the April edition of Fortune Magazine, entitled "The Jones that Nobody Keeps Up With", exposed to the public his unique and highly successful strategy ("speculative instruments for conservative purposes"), along with his truly astounding return rates. Since then, the number of hedge funds and the size of their assets have soared, particularly since the early 1990s. Estimates suggest there are now over 6000 active hedge funds managing around $600 billion in assets, compared with the 68 funds that existed in 1984.

Several factors may explain the extraordinary development of hedge funds over recent years. First of all, there was the unprecedented wealth creation that occurred during the equity bull market of the 1990s. That significantly expanded the base of "sophisticated" investors, especially high networth private investors, and fundamentally altered the way people in the workaday world viewed their money and finances.

In addition, there was an unprecedented generational shift of wealth through inheritance, as the parents of baby boomers progressively left their assets to their children. These new investors were typically more sophisticated and had a higher tolerance for risk than the previous generation, but were also more demanding in terms of investment performance. This boded well for hedge funds and other alternative investments, which generally targeted higher absolute returns thanks to their flexibility and lack of constraints.

It was also at this time that the first institutional investors started showing a greater interest in hedge funds. In particular, in September 1999, the pension fund CalPERS raised the ceiling on its alternative investments allocation to $11.0 billion, that is, 6% of its total assets. This amount included about $1.0 billion specifically allocated to hedge funds.

After March 2000, the growth of the hedge fund industry continued. However, the motives for investing had changed dramatically: investors were then looking for an effective means of diversification to protect their capital from falling equity markets and depressed bond yields. In addition, sub-par performance in traditional asset categories started luring institutional investors toward absolute return strategies, and more specifically hedge funds. Until then, alternative investments had primarily focused on private equity and real estate.

The needs of these new investors - quite different from those of the wealthy private clients - triggered a process that led to several changes in the hedge fund industry. Many hedge funds became more mature, and put in place stable investment processes, lower leverage, improved transparency and effective risk management to satisfy the high standards and rigorous selection processes of large institutions. In addition, many traditional financial institutions began to develop funds of hedge funds as part of their global product range, and offered them to their retail and affluent clients.

The total assets now managed by hedge funds may still seem small with respect to the $3.8 trillion allocated to more traditional strategies by institutional investors alone, or the $6.3 trillion of assets under management in the mutual fund industry. But the double-digit growth in asset size and the increasing popularity of hedge funds have also brought about a change in the attitude of regulators, who now regularly scrutinize the secretive world of alternative investments on both sides of the Atlantic Ocean. Nevertheless, the increased market volatility, the corporate activity and the extreme valuations (both on the upside and on the downside) continue to offer unrivaled opportunities for talented portfolio managers to exploit anomalies in the markets. As a consequence, the number of hedge funds should keep growing, and their strategies become more prominent and more popular in the near future.


Originally, hedge funds were so named because their investment strategy aimed at systematically reducing risk with respect to the direction of the market by pooling investments in a mix of short and long market positions. However, in today's world, many "hedge funds" are not actually hedged, and the term has become a misnomer.

Surprisingly, though, there is no commonly accepted definition of what exactly a hedge fund is. To confuse matters further, the term "hedge fund" has different meanings on each side of the Atlantic. In Europe, a "hedge fund" denotes any offshore investment vehicle whose strategy goes beyond buying and holding stocks or bonds and that has an absolute (i.e. non-benchmark-related) performance goal. In the United States, a hedge fund is typically a domestic limited partnership that is not registered with the Securities and Exchange Commission (SEC) and whose manager is rewarded by an incentive fee and has a broad array of securities and investment strategies at his disposal.

In this book, we have adopted the following pragmatic definition as a starting point:

Hedge funds are privately organized, loosely regulated and professionally managed pools of capital not widely available to the public

The private nature of hedge funds is the key issue in this definition, and we believe that most of the other characteristics of hedge funds follow directly from it. Indeed, as long as the general public has no access to a private pool, regulators do not consider the pool as a traditional investment vehicle (e.g. a SICAV, an OPCVM, a mutual fund, etc.) and conclude that there is no need to regulate it or require regular specific disclosure. This makes sense, because the pool only caters to high net worth individuals and institutions through private placements, and these investors are likely to be educated enough to assess the risk of their own investments.


The pool is not subject to the requirements imposed on registered investment companies and, therefore, its manager may pursue any type of investment strategy. In particular, he may concentrate its portfolio in a handful of investments, use leverage, short selling and/or derivatives, and even invest in illiquid or non-listed securities. This is in total contrast to mutual funds, which are highly regulated and do not have the same breadth of investment instruments at their disposal.

The pool manager has the primary goal of achieving a target rate of return, whatever happens on the market. This is what is meant by "absolute return". Falling markets are no more an excuse for poor performance, as the manager has the latitude to go short if he wants to. To attract the most skilled managers in the industry, the pool offers some performance fees (typically 20% or more of the hedge fund's annual profits) rather than asset-based fees (typically 1% or 2% of the assets). Assuming a 5% net trading profit for a hedge fund, the total fee would be equal to 200 basis points (1% management fee, plus 20% of the 5% performance) per annum. This would amount to more than five times the fees for most traditional, active equity products. But high fees will also attract managers with poorly established and executed strategies, potentially resulting in grim surprises for their investors. Hence, most hedge funds request their manager to invest a large fraction of his personal wealth in the fund alongside other investors. In addition, a hurdle rate of return must usually be achieved or any previous losses recouped before the performance fee is paid.

To allow managers to focus on investments and performance rather than on cash management, the pool may impose long-term commitments and a minimum notice time for any redemption by its investors. This feature also provides the hedge funds with the flexibility to invest in securities that are relatively illiquid from the long-term point of view. Finally, as it is almost unregulated, the pool does not have to report and disclose its holdings and positions. This feature contributed significantly to the mystery that surrounded hedge funds, a trait that attracted individual investors while at the same time keeping institutional investors away. However, institutional investors are gaining ground in obtaining greater transparency and thus are getting increasingly involved in hedge fund investing.


Although the term "hedge funds" is often used generically, in reality hedge funds are not all alike. In fact, there exist a plethora of investment styles with very different approaches and objectives, and the returns, volatilities and risk vary enormously according to the fund managers, the target markets and the investment strategies. Some hedge funds may be non-directional and less volatile than traditional bond or equity markets, while others may very well be completely directional and display a much higher volatility. Many managers even pretend to have their own, unique investment styles. Therefore, "one size fits all" does not apply in the evaluation process or in the arena of risk management.

As it is critical to have a basic understanding of the underlying hedge fund strategies and their differences in order to develop a coherent plan to exploit the opportunity offered by hedge funds, consultants, investors and managers alike often segregate the hedge fund market into a range of investment styles. Unfortunately, there is no accepted norm to classify the different hedge fund strategies, and each consultant, investor, manager or hedge fund data provider may use his own classification. In the following, for the sake of simplicity, we have classified hedge funds into four main strategies: tactical trading, equity long/short, event-driven and relative value arbitrage. A fifth category comprises funds that follow more than one strategy as well as funds of funds. We do not claim that this classification is better than existing ones. It is just a working tool that is compatible with most existing classifications.

1.2.1 The tactical trading investment style

The tactical trading investment style refers to strategies that speculate on the direction of market prices of currencies, commodities, equities and/or bonds on a systematic or discretionary basis. Global macro investing and commodity trading advisors (CTAs) are the predominant styles in this category.

Global macro managers tend to make leveraged, directional, opportunistic investments in global currency, equity, bond and commodity markets on a discretionary basis. They usually rely on a top-down global approach and base their trading views on fundamental economic, political and market factors. Their portfolios are large in size but concentrated, relying heavily on derivatives (options, futures and swaps). Global macro managers are by no means homogenous in the specific strategies they employ, but their goal tends to be high returns with a more liberal attitude toward risk than other hedge fund categories. Due to their discretionary approach, the quality of the manager is the sole key to a fund's success.

Commodity trading advisors and managed futures managers primarily trade listed commodity and financial futures contracts on behalf of their clients. As with global macro managers, CTAs are by no means homogenous, but are usually split into two groups: systematic traders and discretionary traders. Systematic traders believe that future price movements in all markets may be more accurately anticipated by analyzing historical price movements within a quantitative framework. Hence, they rely heavily on computer-generated trading signals to maintain a systematic and disciplined approach, and often use multiple systems in order to reduce volatility and produce more stable returns. In contrast, discretionary traders base their trading decisions on fundamental and technical market analysis, as well as on their experience and trading skills developed over the years (Figure 1.1).

1.2.2 The equity long/short style

As their title indicates, long/short equity managers invest in equities, and combine long investments with short sales to reduce but not eliminate market exposure. Indeed, long/short strategies are not automatically market neutral. Most funds tend to have a net long exposure (more long gross exposure than short gross exposure), which implies that they can have significant correlation with traditional markets, and therefore experience large downturns at exactly the same times as major market downturns. However, a few funds also aggressively use their ability to be net short.

The long/short equity style can be divided into several sub-strategies:

Regionally or industry focused managers specialize in a region (e.g. Asia, Europe), a country (e.g. the United States) or a specific industry (e.g. technology), while global managers can invest worldwide.

Dedicated short managers only use short positions. In a sense, they are the mirrors of traditional long-only managers. They suffered greatly during the bull market of the 1990s but put up a better overall performance during the bear market of the 2000s.

Emerging market funds invest in all types of securities in emerging countries, including equities, bonds and sovereign debt. While many investors avoid investing in regions where information is scant, accounting standards are weak, political and economic turmoil is prevalent and experienced management is scarce, others see these as opportunities that can result in undetected, undervalued and under-researched securities. Emerging market hedge funds typically tend to be more volatile than developed market long/short equity funds. Because many emerging markets neither allow short selling nor offer viable futures or other derivative products with which to hedge, these funds often employ a long-biased strategy.

Market timers vary their long/short exposure in response to market factors within a short period of time.

1.2.3 The event-driven style

Event-driven strategies focus on debt, equity or trade claims from companies that are in a particular stage of their life cycle, such as spin-offs, mergers and acquisitions, bankruptcy reorganizations, re-capitalization and share buybacks.


Excerpted from Hedge Funds by François-Serge Lhabitant Excerpted by permission.
All rights reserved. No part of this excerpt may be reproduced or reprinted without permission in writing from the publisher.
Excerpts are provided by Dial-A-Book Inc. solely for the personal use of visitors to this web site.

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Table of Contents

Foreword by Mark Anson.




1 Characteristics of Hedge Funds.

1.1 What are hedge funds?

1.2 Investment styles.

1.2.1 The tactical trading investment style.

1.2.2 The equity long/short style.

1.2.3 The event-driven style.

1.2.4 The relative value arbitrage style.

1.2.5 Funds of funds and multi-strategy funds.

1.3 The current state of the hedge fund industry.

2 Measuring Return.

2.1 The difficulties of obtaining information.

2.2 Equalization, crystallization and multiple share classes.

2.2.1 The inequitable allocation of incentive fees.

2.2.2 The free ride syndrome.

2.2.3 Onshore versus offshore funds.

2.2.4 The multiple share approach.

2.2.5 The equalization factor/depreciation deposit approach.

2.2.6 Simple equalization.

2.2.7 Consequences for performance calculation.

2.3 Measuring returns.

2.3.1 The holding period return.

2.3.2 Annualizing.

2.3.3 Multiple hedge fund aggregation.

2.3.4 Continuous compounding.

3 Return and Risk Statistics.

3.1 Calculating return statistics.

3.1.1 Central tendency statistics.

3.1.2 Gains versus losses.

3.2 Measuring risk.

3.2.1 What is risk?

3.2.2 Range, quartiles and percentiles.

3.2.3 Variance and volatility (standard deviation).

3.2.4 Some technical remarks on measuring historical volatility/variance.

3.2.5 Back to histograms, return distributions and z-scores.

3.3 Downside risk measures.

3.3.1 From volatility to downside risk.

3.3.2 Semi-variance and semi-deviation.

3.3.3 The shortfall risk measures.

3.3.4 Value at risk.

3.3.5 Drawdown statistics.

3.4 Benchmark-related statistics.

3.4.1 Intuitive benchmark-related statistics.

3.4.2 Beta and market risk.

3.4.3 Tracking error.

4 Risk-Adjusted Performance Measures.

4.1 The Sharpe ratio.

4.1.1 Definition and interpretation.

4.1.2 The Sharpe ratio as a long/short position.

4.1.3 The statistics of Sharpe ratios.

4.2 The Treynor ratio and Jensen alpha.

4.2.1 The CAPM.

4.2.2 The market model.

4.2.3 The Jensen alpha.

4.2.4 The Treynor ratio.

4.2.5 Statistical significance.

4.2.6 Comparing Sharpe, Treynor and Jensen.

4.2.7 Generalizing the Jensen alpha and the Treynor ratio.

4.3 M2, M3 and Graham–Harvey.

4.3.1 The M2 performance measure.

4.3.2 GH1 and GH2.

4.4 Performance measures based on downside risk.

4.4.1 The Sortino ratio.

4.4.2 The upside potential ratio.

4.4.3 The Sterling and Burke ratios.

4.4.4 Return on VaR (RoVaR).

4.5 Conclusions.

5 Databases, Indices and Benchmarks.

5.1 Hedge fund databases.

5.2 The various biases in hedge fund databases.

5.2.1 Self-selection bias.

5.2.2 Database/sample selection bias.

5.2.3 Survivorship bias.

5.2.4 Backfill or instant history bias.

5.2.5 Infrequent pricing and illiquidity bias.

5.3 From databases to indices.

5.3.1 Index construction.

5.3.2 The various indices available and their differences.

5.3.3 Different indices–different returns.

5.3.4 Towards pure hedge fund indices.

5.4 From indices to benchmarks.

5.4.1 Absolute benchmarks and peer groups.

5.4.2 The need for true benchmarks.


6 Covariance and Correlation.

6.1 Scatter plots.

6.2 Covariance and correlation.

6.2.1 Definitions.

6.2.2 Another interpretation of correlation.

6.2.3 The Spearman rank correlation.

6.3 The geometry of correlation and diversification.

6.4 Why correlation may lead to wrong conclusions.

6.4.1 Correlation does not mean causation.

6.4.2 Correlation only measures linear relationships.

6.4.3 Correlations may be spurious.

6.4.4 Correlation is not resistant to outliers.

6.4.5 Correlation is limited to two variables.

6.5 The question of statistical significance.

6.5.1 Sample versus population.

6.5.2 Building the confidence interval for a correlation.

6.5.3 Correlation differences.

6.5.4 Correlation when heteroscedasticity is present.

7 Regression Analysis.

7.1 Simple linear regression.

7.1.1 Reality versus estimation.

7.1.2 The regression line in a perfect world.

7.1.3 Estimating the regression line.

7.1.4 Illustration of regression analysis: Andor Technology.

7.1.5 Measuring the quality of a regression: multiple R, R2, ANOVA and p-values.

7.1.6 Testing the regression coefficients.

7.1.7 Reconsidering Andor Technology.

7.1.8 Simple linear regression as a predictive model.

7.2 Multiple linear regression.

7.2.1 Multiple regression.

7.2.2 Illustration: analyzing the Grossman Currency Fund.

7.3 The dangers of model specification.

7.3.1 The omitted variable bias.

7.3.2 Extraneous variables.

7.3.3 Multi-collinearity.

7.3.4 Heteroscedasticity.

7.3.5 Serial correlation.

7.4 Alternative regression approaches.

7.4.1 Non-linear regression.

7.4.2 Transformations.

7.4.3 Stepwise regression and automatic selection procedures.

7.4.4 Non-parametric regression.

8 Asset Pricing Models.

8.1 Why do we need a factor model?

8.1.1 The dimension reduction.

8.2 Linear single-factor models.

8.2.1 Single-factor asset pricing models.

8.2.2 Example: the CAPM and the market model.

8.2.3 Application: the market model and hedge funds.

8.3 Linear multi-factor models.

8.3.1 Multi-factor models.

8.3.2 Principal component analysis.

8.3.3 Common factor analysis.

8.3.4 How useful are multi-factor models?

8.4 Accounting for non-linearity.

8.4.1 Introducing higher moments: co-skewness and co-kurtosis.

8.4.2 Conditional approaches.

8.5 Hedge funds as option portfolios.

8.5.1 The early theoretical models.

8.5.2 Modeling hedge funds as option portfolios.

8.6 Do hedge funds really produce alpha?

9 Styles, Clusters and Classification.

9.1 Defining investment styles.

9.2 Style analysis.

9.2.1 Fundamental style analysis.

9.2.2 Return-based style analysis.

9.2.3 The original model.

9.2.4 Application to hedge funds.

9.2.5 Rolling window analysis.

9.2.6 Statistical significance.

9.2.7 The dangers of misusing style analysis.

9.3 The Kalman filter.

9.4 Cluster analysis.

9.4.1 Understanding cluster analysis.

9.4.2 Clustering methods.

9.4.3 Applications of clustering techniques.


10 Revisiting the Benefits and Risks of Hedge Fund Investing.

10.1 The benefits of hedge funds.

10.1.1 Superior historical risk/reward trade-off.

10.1.2 Low correlation to traditional assets.

10.1.3 Negative versus positive market environments.

10.2 The benefits of individual hedge fund strategies.

10.3 Caveats of hedge fund investing.

11 Strategic Asset Allocation – From Portfolio Optimizing to Risk Budgeting.

11.1 Strategic asset allocation without hedge funds.

11.1.1 Identifying the investor’s financial profile: the concept of utility functions.

11.1.2 Establishing the strategic asset allocation.

11.2 Introducing hedge funds in the asset allocation.

11.2.1 Hedge funds as a separate asset class.

11.2.2 Hedge funds versus traditional asset classes.

11.2.3 Hedge funds as traditional asset class substitutes.

11.3 How much to allocate to hedge funds?

11.3.1 An informal approach.

11.3.2 The optimizers’ answer: 100% in hedge funds.

11.3.3 How exact is mean–variance?

11.3.4 Static versus dynamic allocations.

11.3.5 Dealing with valuation biases and autocorrelation.

11.3.6 Optimizer’s inputs and the GIGO syndrome.

11.3.7 Non-standard efficient frontiers.

11.3.8 How much to allocate to hedge funds?

11.4 Hedge funds as portable alpha overlays.

11.5 Hedge funds as sources of alternative risk exposure.

12 Risk Measurement and Management.

12.1 Value at risk.

12.1.1 Value at risk (VaR) is the answer.

12.1.2 Traditional VaR approaches.

12.1.3 The modified VaR approach.

12.1.4 Extreme values.

12.1.5 Approaches based on style analysis.

12.1.6 Extension for liquidity: L-VaR.

12.1.7 The limits of VaR and stress testing.

12.2 Monte Carlo simulation.

12.2.1 Monte Carlo for hedge funds.

12.2.2 Looking in the tails.

12.3 From measuring to managing risk.

12.3.1 The benefits of diversification.

13 Conclusions.

Online References.



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