Who Charges More: Hedge Funds or Mutual Funds?*

Explicit mutual fund fees are typically less than 1% of the assets under management. By comparison, the typical hedge fund charges a base fee of 2% plus a performance fee equal to 20% of net profits. Thus, hedge funds appear to charge far more for even comparable performance—unless one takes account of the following:

• ? For most mutual funds, a very high percentage of performance is driven by its passive exposure to the market, even though the fee is applied to the total fund.
• ? Many hedge funds are designed to provide returns that are completely independent of market performance.

Using these two assumptions, the author provides a simple example that shows that a representative mutual fund's performance can be replicated by combining an index fund, which represents the mutual fund's passive component, with a hedge fund, representing the mutual fund's active component. When analyzed in this way, the fee of the combined fund turns out to be remarkably close to the actual fee of the mutual fund. This in turn suggests that the implicit fee for the mutual fund's small active component is comparable to the fees of the hedge fund.     

Locked Up by a Lockup: Valuing Liquidity as a Real Option

Hedge funds often impose lockups and notice periods to limit the ability of investors to withdraw capital. We model the investor's decision to withdraw capital as a real option and treat lockups and notice periods as exercise restrictions. Our methodology incorporates time-varying probabilities of hedge fund failure and optimal early exercise. We estimate a two-year lockup with a three-month notice period costs approximately 1% of the initial investment for an investor with constant relative risk aversion utility and risk aversion of three. The cost of illiquidity can easily exceed 10% if the hedge fund manager can arbitrarily suspend withdrawals.     

Conditional Properties of Hedge Funds: Evidence from Daily Returns*

Using daily returns on a set of hedge fund indices, we study (i) the properties of the indices' conditional density functions and (ii) the presence of asymmetries in conditional correlations between hedge fund indices and other investments and between hedge fund indices themselves. We use the SNP approach to obtain estimates of conditional densities of hedge fund returns and then proceed to examine their properties. In general, a nonparametric GARCH(1,1) model appears to provide the best fit for all strategies. We find that the conditional third and fourth moments are significantly affected by changes in the current volatility of returns on hedge fund indices. We examine changes in the conditional probability of tail events and report significant changes in the probability of extreme events when the conditioning information changes. These results have important implications for models of hedge fund risk that rely on probability of tail events. We formally test for the presence of asymmetries in conditional correlations to determine if there is contagion between hedge funds and other investments and between various hedge fund indices in extreme down markets versus extreme up markets. We generally do not find strong evidence in support of asymmetric correlations.     

The Style Consistency of Hedge Funds

This study examines the style classification and the style consistency of hedge funds using a new proprietary database over the period May 1989 to April 1999. First, a hard clustering procedure is applied to classify hedge funds into homogeneous groups. It is shown that the methodology is robust and can be used to build stable hedge funds indexes. The method performs equally well as the principal component analysis in explaining in‐ and out‐of‐sample cross‐sectional hedge funds' returns. Second, we extend hard to fuzzy cluster memberships, relaxing the full assignment of the funds to individual clusters. We apply the fuzzy clustering methodology to estimate hedge funds' probabilistic exposure to various styles. We introduce three consistency indicators to quantify the hedge fund managers' style opportunism levels. We finally document that there is no evidence that style consistency leads to superior hedge funds' performance.     

Not only skill but also scale: Evidence from the hedge funds industry

This paper empirically tests a two-levels model of decreasing returns to scale using a sample of hedge funds. The two-levels model assumes that a fund's gross alpha is a decreasing function of both the fund scale and the style scale measured by the aggregate size of peers in the hedge fund style. We find that a fund-level model underestimates the impact of diseconomies of scale on the gross alpha by 55 basis points. The results indicate that managers should consider the constraints imposed by the style scale when optimizing their portfolio sizes. We also provide evidence that hedge funds did not invest at their optimal amount and confirm that skill and the ability to resist decreasing returns to scale are two important components of selecting hedge fund performers.     

The fragile capital structure of hedge funds and the limits to arbitrage

During a financial crisis, when investors are most in need of liquidity and accurate prices, hedge funds cut their arbitrage positions and hoard cash. The paper explains this phenomenon. We argue that the fragile nature of the capital structure of hedge funds, combined with low market liquidity, creates a risk of coordination in redemptions among hedge fund investors that severely limits hedge funds' arbitrage capabilities. We present a model of hedge funds' optimal asset allocation in the presence of coordination risk among investors. We show that hedge fund managers behave conservatively and even abstain from participating in the market once coordination risk is factored into their investment decisions. The model suggests a new source of limits to arbitrage.     

Hedge funds and optimal asset allocation: Bayesian expectations and spanning tests

This paper analyzes the contribution of hedge funds to optimal asset allocations between 1993 and 2010. The preferences of specific institutional investors are captured by implementing a Bayesian asset allocation framework that incorporates heterogeneous expectations regarding hedge fund alpha. Mean-variance spanning tests are used to infer the ability of hedge funds to significantly enhance the mean-variance efficient frontier. Further, a novel democratic variance decomposition procedure sheds light on the dynamics in the co-movement of hedge fund returns with a set of common benchmark assets. The empirical findings indicate that portfolio benefits of hedge funds are time-varying and strongly depend on investor optimism regarding hedge funds’ ability to generate alpha. In general, allocations to hedge funds improve the global minimum variance portfolio even after controlling for short-selling restrictions and minimum diversification constraints. However, due to dynamics underlying the composition of the aggregate hedge fund universe, the factor structure of hedge fund returns has become more similar to the benchmark assets over time.     

The risk in hedge fund strategies: Theory and evidence from long/short equity hedge funds

Theory suggests that long/short equity hedge funds' returns come from directional as well as spread bets on the stock market. Empirical analysis finds persistent net exposures to the spread between small vs large cap stocks in addition to the overall market. Together, these factors account for more than 80% of return variation. Additional factors are price momentum and market activity. Combining two major branches of hedge fund research, our model is the first that explicitly incorporates the effect of funding (stock loan) on alpha. Using a comprehensive dataset compiled from three major database sources, we find that among the three thousand plus hedge funds with similar style classification, less than 20% of long/short equity hedge funds delivered significant, persistent, stable positive non-factor related returns. Consistent with the predictions of the Berk and Green (2004) model we find alpha producing funds decays to “beta-only” over time. However, we do not find evidence of a negative effect of fund size on managers' ability to deliver alpha. Finally, we show that non-factor related returns, or alpha, are positively correlated to market activity and negatively correlated to aggregate short interest. In contrast, equity mutual funds and long-bias equity hedge funds have no significant, persistent, non-factor related return. Expressed differently, L/S equity hedge funds, as the name suggests, do benefit from shorting. Besides differences in risk taking behavior, this is a key feature distinguishing L/S funds from long-bias funds.     

Should Asset Managers Hedge Their “Fees at Risk”?

Although the recent financial crisis afflicted all asset managers, the problem of general market exposure was in some respects worse for the long-only funds that rely almost completely on asset-based fees than for the “absolute return” and other kinds of hedge funds that also receive performance-based fees. While the revenue generated by performance-based fees is expected to be volatile, asset-based fees tend to be viewed as an “annuity” stream that involves little or no earnings risk. But, especially in the case of long-only funds, large shortfalls in asset fees were caused by the combination of significant redemptions and sharp reductions in assets under management that accompanied the plunge in asset prices. In this article, the author attempts to quantify the expected effect of market fluctuations on the asset fees and profitability of long-only asset managers. Having done so, he then argues that traditional long-only asset managers—managers whose only reason for being is their ability to generate above-market returns (or “alpha”) on a fairly consistent basis—routinely retain too much beta risk in their primarily asset-based fee structures. The author offers two main reasons for long-only asset managers to hedge beta risk: (1) it would reduce the need for fund management firms to hold liquid capital to ensure solvency and fund important projects during market downturns; (2) it would provide the firm's current and prospective clients with a clearer signal of whether its managers are succeeding in the firm's mission of generating alpha, as well as the possibility of more equity-like and cost-effective incentive compensation systems for those managers.     

Systematic risk and the cross section of hedge fund returns

This paper investigates the extent to which market risk, residual risk, and tail risk explain the cross-sectional dispersion in hedge fund returns. The paper introduces a comprehensive measure of systematic risk (SR) for individual hedge funds by breaking up total risk into systematic and fund-specific or residual risk components. Contrary to the popular understanding that hedge funds are market neutral, we find that systematic risk is a highly significant factor explaining the dispersion of cross-sectional returns while at the same time measures of residual risk and tail risk seem to have little explanatory power. Funds in the highest SR quintile generate 6% more average annual returns compared with funds in the lowest SR quintile. After controlling for a large set of fund characteristics and risk factors, systematic risk remains positive and highly significant, whereas the relation between residual risk and future fund returns continues to be insignificant. Hence, systematic risk is a powerful determinant of the cross-sectional differences in hedge fund returns.     

Large deviations estimation of the windfall and shortfall probabilities for optimal diversified portfolios

Many investors believe that they can effectively reduce risk by, among other ways, holding large combinations of investment assets. The purpose of this paper is to develop asymptotic approximations of the windfall and shortfall probabilities for an optimal portfolio of risky assets as the number of the assets becomes sufficiently large. We start by providing some heuristics to motivate our problem, then proceed to prove general large deviations theorems. We also present specific results with an application to the multivariate normal case. Both a theoretical analysis of the method and an empirical application justify the diversification tenet of the allocation strategies that many hedge funds and pension funds tend to adopt nowadays.     

Convertible Bond Arbitrage: Risk and Return

Abstract:  This paper specifies a simulated convertible bond arbitrage portfolio to characterise the risks in convertible bond arbitrage. For comparison the risk profile of convertible bond arbitrage hedge fund indices at both monthly and daily frequencies is also examined. Results indicate that convertible bond arbitrage is positively related to default and term structure risk factors. These risk factors are augmented with the simulated convertible bond arbitrage portfolio, mimicking a passive investment in convertible bond arbitrage, to assess the risk and return of individual hedge funds. We provide estimates of the performance of two hedge fund indices (an equally weighted and value weighted index) and a sample of convertible bond arbitrage hedge funds using a factor model methodology. Lagged and contemporaneous observations of the risk factors are specified, controlling for illiquidity in the securities held by funds. Our results cover two time periods. Initially we find evidence of abnormal risk adjusted returns in the individual hedge fund data and the equally weighted hedge fund index and no evidence of abnormal risk adjusted returns in the value weighted hedge fund index. When we examine performance during the credit crisis of 2007 and 2008 we find evidence of negative abnormal returns amongst individual hedge funds and the hedge fund indices.     

Hedge funds and their prime broker analysts

Are sell-side analysts reluctant to go against the investment views of their hedge funds when these hedge funds are their prime brokerage clients? We show that prime broker analysts tend to upgrade stocks recently bought by their clients. For stocks with upgraded recommendations, post-announcement cumulative abnormal returns are significantly lower for those purchased by the prime brokerage clients. Our results are stronger with high-dollar-turnover clients who generate more trading commissions. We also find that a hedge fund with a large bet on a stock has a stronger incentive to pressure the fund’s prime brokers to issue a favorable recommendation on the stock. Results are not driven by stocks of firms with low analyst coverage or small size.     

Passive Hedge Fund Replication – Beyond the Linear Case

In this paper we extend Hasanhodzic and Lo (2007) by assessing the out‐of‐sample performance of various non‐linear and conditional hedge fund replication models. We find that going beyond the linear case does not necessarily enhance the replication power. On the other hand, we find that selecting factors on the basis on an economic analysis allows for a substantial improvement in out‐of‐sample replication quality, whatever the underlying form of the factor model. Overall, we confirm the findings in Hasanhodzic and Lo (2007) that the performance of the replicating strategies is systematically inferior to that of the actual hedge funds.     

Which institutional investor types are the most informed?

We examine the informativeness of quarterly disclosed portfolio holdings across four institutional investor types: hedge funds, mutual funds, pension funds and private banking firms. Overweight positions outperform underweight positions only for hedge funds. By decomposing holdings and stock returns, we find that hedge funds are superior to other institutional investors both at picking industries and stocks and that they are better at forecasting long‐term as well as short‐term returns. Furthermore, our results show that hedge funds, mutual funds and pension funds are able to successfully time the market. The outperformance of hedge funds is not explained by a liquidity premium.     

Capacity Constraints and Hedge Fund Strategy Returns

Hedge funds have generated significant absolute returns (alpha) in the decade between 1995 and 2004. However, the level of alpha has declined substantially over this period. We investigate whether capacity constraints at the level of hedge fund strategies have been responsible for this decline. For four out of eight hedge fund strategies, capital inflows have statistically preceded negative movements in alpha, consistent with this hypothesis. We also find evidence that hedge fund fees have increased over the same period. Our results provide support for the Berk and Green (2004) rational model of active portfolio management.     

Hedge fund networks,information dissemination,and stock price comovement: Evidence from China

We define a hedge fund network as consisting of weak ties based on common holdings. By creating a filtered dataset of stocks held by hedge funds in China from 2010 to 2019, we examine the effect of the network on stock return comovement and further test the incentive-compatible conditions for honest communication between competitors (Stein, 2008). First, we find that the weak ties in a social network affect the behaviour of hedge fund managers, when formal institutions are imperfect. Second, we find that listed firms held by hedge funds are exposed to an information network that is composed of hedge funds. The higher the hedge fund network density is, the more likely information dissemination is, and the weaker the stock price comovement is. Third, our results support Stein's (2008) two major conclusions: a network effect exists only within stable relationships, and the more central a stock is in the network, the stronger the network effect is. After controlling for various external factors that might influence the hedge fund network's information diffusion mechanism, all the results meet our theoretical expectations. Overall, we contribute to the literature by determining the role of the hedge fund network as an information transmitter in weak ties and by providing empirical evidence on the theory of honest communication among competitors.     

Recent advances in hedge funds' performance attribution: Performance persistence and fundamental factors

We survey articles on hedge funds' performance persistence and fundamental factors from the mid-1990s to the present. For performance persistence, we present some pioneering studies that contradict previous findings that hedge funds' performance is a short term matter. We discuss recent innovative studies that examine the size, age, performance fees and other factors to give a 360° view of hedge funds' performance attribution. Small funds, younger funds and funds with high performance fees all outperform the opposite. Long lockup period funds tend to outperform short lockups and domiciled funds tend to outperform offshore funds. This is the first survey of recent innovative and challenging studies into hedge funds' performance attribution, and it should be particularly useful to investors trying to choose between hedge funds.     

Exploring the relationship between cryptocurrencies and hedge funds during COVID-19 crisis

In this paper, we investigated the relationship between cryptocurrency market and hedge funds in two different ways. First, we focus on the dependence between Cryptocurrency hedge funds and conventional hedge funds strategies using VAR and VECM models, while analyzing the impact of COVID-19 on the hedge funds' values. Secondly, we choose between ARDL and ARDL-ECM models to study the effects of cryptocurrency price changes on Crypto- Currency hedge funds' values during COVID-19 crisis. Our empirical findings demonstrate that there is substantial interactions between Crypto-Currency and conventional hedge funds. The COVID-19 pandemic has significant negative impact on the performance of the following hedge funds: Event Driven, Relative Value and Distressed Debt fund strategies, this has reflected in a significant drop in their values during this critical period. However, we demonstrate that COVID-19 pandemic did not affect the relationship between crypto-currency hedge funds and both bitcoin and Ethereum. These findings hold profound implications for hedge funds managers, cryptocurrency market main players and policy makers. Our study is crucial in forecasting the performance of these markets especially during global pandemics.     

Capturing hedge fund risk factor exposures: Hedge fund return replication with ETFs

We develop a new factor selection methodology of spanning the space of hedge fund risk factors with all available exchange traded funds (ETFs). We demonstrate the efficacy of the methodology with out-of-sample individual hedge fund return replication by ETF clone portfolios. This is consistent with our interpretation of ETF returns as proxies to risk factors driving hedge fund returns. We further consider portfolios of “cloneable” and “noncloneable” hedge funds, defined as top and bottom in-sample R² matches, and demonstrate that our ETF clone portfolios slightly outperform cloneable hedge funds out of sample.