The London Business School’s Centre for HF Research and Education

A summary by Professor Narayan Naik of recent educational and research activities

Professor Narayan Naik

It has been a busy couple of months at the Centre. We have just run another successful two-day course on hedge funds, of which more later, as well as publishing two more research papers.

Risk and Portfolio Decisions involving Hedge Funds

The first of the research documents, "Risk and Portfolio Decisions involving Hedge Funds" (working paper no. HF-009) argues that hedge funds, while compared with mutual funds, can follow more dynamic trading strategies, can take long as well as short positions and therefore can bet on spreads like the small-cap large-cap spread or the value-growth spread. As a result, hedge funds can offer exposure to risk factors that traditional "long-only" strategies cannot.

The key issue is to understand the kinds and nature of the risk factors associated with different hedge fund strategies. It shows that a wide range of equity-oriented hedge fund strategies exhibit a non-linear payoff structure resembling a short position in the put option on the equity market. They also show a significant exposure to the small-cap large-cap spread. Having documented the presence of non-linearities, the paper assesses its implications for portfolio construction. It argues that the traditional mean-variance framework ignores the presence of nonlinearities and shows how an alternative framework- Conditional Value-at-risk (CVaR) – can be applied to construct hedge fund portfolios.

Finally, the paper also investigates how the limitations of the short history of hedge fund returns can be overcome by working with underlying risk factors estimated using a multi factor model. Since the underlying assets have a longer history, this approach provides insights into the long-term risk-return trade-offs of hedge funds.

The paper starts by developing the theoretical framework for modelling non-linear payoffs in assets pricing and assigning a value to the skill of the manager generating non-linear payoffs. It illustrates the applicability of this approach by implementing it for equity-oriented hedge fund strategies. It uses hedge fund returns data from HFR and CSFB/Tremont databases. The paper estimates systematic risk factors of different hedge fund strategies and demonstrates its applicability using out of sample analysis. Next, the paper analyses portfolio decisions with hedge funds. After building the theoretical framework for Conditional Value at risk (CVaR), it compares the tail-risk of mean-variance and mean-CvaR efficient portfolios. Finally, using the systematic risk factor model, it compares the long run performance of hedge funds with the recent performance.

The paper reaches three main findings. Firstly, the option-like payoffs are not limited to "trend followers" and "risk arbitragers", but an integral feature of the payoffs on a wide range of hedge fund strategies. In particular, the payoffs on a large number of equity-oriented hedge fund strategies resemble those from writing a put option on the equity index.

Secondly, the analysis shows that the expected tail losses of mean-variance optimal portfolios could be underestimated by as high as 54% compared to mean-CVaR portfolios. This suggests that ignoring tail risk can result in significantly higher losses during large market downturns.

Finally, the extrapolation of hedge fund returns using underlying risk factors suggests that the hedge funds performance during the last decade is not representative of their long-term performance. In particular, the mean returns during the 1927-1989 period are significantly lower and their standard deviations are significantly higher compared to those of their recent performance.

The results of this paper demonstrate the importance of allowing non-linear risk return relation while analysing hedge funds. The findings are useful to investors and regulators as they can now better understand the risk-return characteristics of hedge funds. In addition, the analysis presents tools that can be used to measure the net and gross risk exposures of hedge funds and also to assist with hedge funds portfolio construction.

Of flows, performance, and managerial incentives

Our second paper, "Flows, Performance, and Managerial Incentives in Hedge Funds" (working paper no. HF-016), discovers that hedge funds differ from mutual funds in a variety of aspects. They are less regulated, less transparent, charge performance-based compensation, and offer limited liquidity (lock-up, notice, and redemption periods) when compared to mutual funds. These differences have important implications for the incentives hedge fund managers have to deliver superior performance, as well as for the investment behaviour of investors. Using these issues as its basis, this paper investigates the complex relationship between flows, performance and managerial incentives in hedge funds.

The paper has two key objectives. Its first thrust is to analyse the determinants of money flows into hedge funds. In particular, its focus is on the relationship between money flows and past performance, managerial incentives, impediments to capital withdrawals, and past money flows. Its second objective is to analyse the relationship between fund size, past flows, managerial incentives, impediments to withdrawals and future performance.

The paper models the incentive-fee contract as a call option written by investors on assets under management. The net asset value (at which the money flows enter the fund), hurdle rate and high-water mark provisions determine the strike price of the call option. Since capital invested at different times are subjected to different high-water marks, the incentive-fee-contract amounts to the manager holding a portfolio of call options with different strike prices.

The paper uses a comprehensive hedge funds database created by merging three large databases (namely HFR, TASS and ZCM/MAR). The database includes net returns, monthly assets under management, and other fund characteristics such as lock up and restriction periods, management and incentives fees, inception data and fund strategy. Using a multivariate set up, it examines the relation between money flows, and fund characteristics and past performance. For estimating the determinants of future performance, it regresses hedge fund returns against fund size, past flows, managerial incentives, and impediments to capital withdrawal (lock up and restriction periods).

The paper has four main findings relating to flows, past performance and managerial incentives. First, that money-flows chase returns and the relation between performance-flow is convex. Second, that money flows are significantly higher for consistent winners (and lower for consistent losers). Thirdly, there is a positive relationship between flows and managerial incentives. Finally, investors do not prefer impediments to capital withdrawals.

In addition, the paper revealed new findings regarding a fund's future performance and its relationship to its size, past flows, managerial incentives, and lock up and restriction periods. It discovered that both the larger funds and the funds experiencing greater flows are associated with worse future performance, consistent with the presence of capacity constraint and decreasing returns to scale. It also documents a positive relationship between managerial incentives and future returns suggesting better incentives are associated with better future performance. Finally, the funds with greater impediments to withdrawal are often associated with better performance in the future, and this is consistent with investors earning a liquidity risk premium.

This work is currently being examined at a more macro level, which investigates whether money flows chase total returns or value added by the manager (the alpha). Preliminary analysis suggests that hedge fund investors do not distinguish between the alpha and beta-related components of total return. This has interesting implications for hedge fund managers' response to the money flowing into hedge funds.

Inside the Black Box

Last month the Centre successfully ran its popular two-day hedge fund course "Hedge Funds: Inside the Black-Box" for the sixth time in a row. As is frequently now the case, the participants on this course came from a wide range of backgrounds such as institutional and private investors, investment consultants, accountants, IFAs, trustees of pension funds and endowments, private bankers, managers of family offices and funds of hedge funds, hedge fund managers, risk managers, quantitative analysts, actuaries, regulators, lawyers, compliance officers and others.

This intensive course provides the knowledge and frameworks needed to address the key issues concerning hedge funds. Drawing on real-life cases, the course equips the participants with the practical tools and insights necessary to avoid common pitfalls. The enhanced understanding of the "what, why and how" of hedge funds and the economic intuition underlying various market practices is intended to transform the way graduates from the course deal with or manage hedge funds.

Amongst the questions the course tackles are:
 

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  • Why have hedge funds proved so attractive to some investors, while others remain wary?
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  • What is their performance record?
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  • How do hedge funds generate their returns?
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  • What kinds of risks do they take and how do these differ from traditional funds?
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  • How does capacity constraint affect hedge fund risks and returns?
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  • How important is qualitative analysis in fund selection and how useful is the past record?
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  • How does one think of a fund's "alpha" and life cycle going forward, and when constructing a fund of hedge funds?
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  • Can "star" fund managers or prop-desk traders become successful hedge fund managers?
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  • What should investors look out for?
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  • How do regulators view hedge funds?
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  • Do hedge funds pose a systemic risk to the stability of financial markets?
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The course starts with the basics of what the data does and doesn't tell as well as the problems presented by hedge fund indices, but quickly moves on to models of investment returns – the traditional version versus the hedge funds, for example. It also highlights how hedge fund alphas differ from traditional fund alphas. One cannot examine alpha without first looking at the betas. The search of alpha really begins with the search for betas. It provides a unifying theory of hedge funds, a framework that can be consistently applied across a wide range of strategies. It analyses the investment behaviour of hedge fund investors and discusses the implications of chasing return winners in the presence of capacity constraints. Our course applies the insights obtained in the process of strategic asset allocation, portfolio construction and implementation, risk management, and performance evaluation of hedge funds.

In spite of having considerable prior knowledge of hedge funds and their investment styles, trading strategies, structures, and compensation methods, the participants frequently find the analysis compelling, thought-provoking and indispensable. There is simply no other course like this. Susan Cross from GAM told us: "This was a well-delivered programme – a good mix of case studies and analysis has helped identify gaps in my own knowledge and has raised my awareness of current thinking. I would strongly recommend the Hedge Funds Programme to others."

And Man's Alison Carnwath said: "The Hedge Funds Programme was both educational and thought-provoking. My knowledge has been extended and the programme has left me contemplating alternative ways of approaching the industry."

For more information about the Centre and its educational and research activities, please visit www.london.edu/hedgefunds