Alumni social networks and hedge fund performance: Evidence from China

Based on unique data of Chinese private hedge funds, we first construct the “strong alumni” (alumni of the same school and the same major) social networks of private hedge fund managers, and examine the impact of alumni social networks on the performance of hedge funds in China. We build a series of alumni networks using the educational background information of 4734 private hedge funds, and perform an empirical analysis on a sample of 1115 private hedge funds products from 2010 to 2019. Different from previous findings of mutual funds, we find that more central network positions of hedge fund managers are associated with better risk-adjusted fund performance. Hedge fund managers with more central positions conduct more active investment styles and receive lower fund flows.¹ The results supplement the evidence that information advantages brought by central position in social networks can influence managers' investment styles, thus improve hedge fund performance.     

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.     

Liquidity shocks,size and the relative performance of hedge fund strategies

We examine whether the increase in the flow of capital to hedge funds over the period 1994–2005 had a negative impact on performance. More specifically, we study the relative performance of small versus large funds for each of the hedge fund strategies. Our results indicate that on an absolute return basis, small funds outperform large funds. On a risk-adjusted return basis, however, we find that large funds outperform small funds, and that large funds are also shown to hold less liquid assets and take on less systematic and idiosyncratic risk than small funds. Further, funds that experience positive liquidity shocks generally outperform those that experience negative liquidity shocks. We also find evidence that hedge fund managers that are aggressive in dealing with liquidity shocks perform better than hedge fund managers that are conservative in dealing with liquidity shocks.     

Dissecting hedge funds' strategies

This paper dissects the dynamics of the hedge fund industry with four financial markets, including the equity market, commodities, currencies, and debt market by employing a large number of assets from these markets. We employ four main representative hedge fund strategy indices, and a cap-weighted global index to estimate an asymmetric dynamic conditional correlation (ADCC) GJR-GARCH model using daily data from April 2003 to May 2021. We break down the performance, riskiness, investing style, volatility, dynamic correlations, and shock transmissions of each hedge fund strategy thoroughly. Further, the impact of commodity futures basis on hedge funds' return is analyzed. Comparing the dynamic correlations during the 2008 global financial crisis (GFC) with COVID-19 pandemic reveals changing patterns in hedge funds' investing styles. There are strong and pervasive shock spillovers from hedge fund industry to other financial markets, especially to futures commodities. An increase in the futures basis of several commodities drives up hedge funds' performance. While hedge fund industry underperforms compared to equity market and commodities, the risk-reward measures show that hedge funds are superior to other markets, and safer than the bond market.     

Synthetic hedge funds

We provide evidence on the performance and the replication success of a broad sample of 72 synthetic hedge funds from January 2009 to December 2013. Thereby, we assign the term “synthetic hedge fund” to mutual funds and exchange-traded funds with hedge fund indices as their benchmarks. Replication success is measured through different perspectives from distributional characteristics to risk-adjusted performance. We find an overall significant underperformance of synthetic hedge funds compared to an appropriate benchmark index. Furthermore, mutual funds (associated with active portfolio management) can produce return characteristics closer to hedge fund benchmarks than exchange-traded funds (associated with passive management) can. From a single strategy perspective, we find a picture of heterogeneity. Regarding the market environment, we show larger return differences for unusual market conditions than for regular ones.     

Should hedge funds be cautious reporting high returns?

In a recent article, Schuster and Auer (2012) show that fund managers with a certain positive performance need to be aware of the fact that too high prospective excess returns can lower the empirical Sharpe ratio of their funds. In this note, we investigate the empirical relevance of this effect. We analyse whether hedge funds being evaluated on the basis of the Sharpe ratio negatively influence their performance by reporting too high returns. Our results show that a economically significant number of hedge funds listed in the CISDM hedge fund database has at least once reported a high return causing this effect.     

Optimal hedge fund portfolios under liquidation risk

We use an expected utility framework to integrate the liquidation risk of hedge funds into portfolio allocation problems. The introduction of realistic investment constraints complicates the determination of the optimal solution, which is solved using a genetic algorithm that mimics the mechanism of natural evolution. We analyse the impact of the liquidation risk, of the investment constraints and of the agent's degree of risk aversion on the optimal allocation and on the optimal certainty equivalent of hedge fund portfolios. We observe, in particular, that the portfolio weights and their performance are significantly affected by liquidation risk. Finally, tight portfolio constraints can only provide limited protection against liquidation risk. This approach is of special interest to fund of hedge fund managers who wish to include the hedge fund liquidation risk in their portfolio optimization scheme.     

Detecting structural breaks and identifying risk factors in hedge fund returns: A Bayesian approach

Extending previous work on asset-based style factor models, this paper proposes a model that allows for the presence of structural breaks in hedge fund return series. We consider a Bayesian approach to detecting structural breaks occurring at unknown times and identifying relevant risk factors to explain the monthly return variation. Exact and efficient Bayesian inference for the unknown number and positions of the breaks is performed by using filtering recursions similar to those of the forward–backward algorithm. Existing methods of testing for structural breaks are also used for comparison. We investigate the presence of structural breaks in several hedge fund indices; our results are consistent with market events and episodes that caused substantial volatility in hedge fund returns during the last decade.     

Changing investment styles: style creep and style gaming in the hedge fund industry

Notwithstanding their common features, hedge funds remain an extremely diverse asset class. Information on fund styles is important for numerous purposes, such as portfolio construction, performance attribution and risk management. With fund self‐declaration being prone to (strategic) misclassification, return‐based taxonomies grouping funds along similarities in realized returns provide a useful alternative. We provide a consistent classification system of homogeneous groups of hedge funds based on self‐organizing maps. Whereas some fund categories such as managed futures are largely consistent in their self‐declared strategies, others, especially so‐called ‘equity hedge’ funds, display no or very limited return similarities. Furthermore, we also find evidence of fund managers performing undisclosed changes of their trading style over time. Those funds that misclassified themselves once are particularly likely to change their trading style again. Although style self‐declaration can, therefore, be quite misleading, our results indicate that hedge funds do not misdeclare their style strategically to improve their relative performance. Copyright © 2006 John Wiley & Sons, Ltd.     

A tale of feedback trading by hedge funds

This paper studies the extent of feedback trading at the factor level by hedge fund managers. We show that fund managers continuously adjust their exposure to different risk factors conditional on the recent performance of these factors. The majority of managers apply a positive feedback strategy, whereas the remaining managers use a negative feedback strategy. In addition, we find some evidence for factor timing ability, although managers appear to be more backward looking than forward looking. We show that positive feedback trading can be beneficial to fund performance in our setup. If managers applied the positive feedback strategy more aggressively, however, they could benefit more from it. As such, the “smart switching benchmark” can be used to assess the risk-adjusted performance of hedge funds.     

Connected Stocks

We connect stocks through their common active mutual fund owners. We show that the degree of shared ownership forecasts cross‐sectional variation in return correlation, controlling for exposure to systematic return factors, style and sector similarity, and many other pair characteristics. We argue that shared ownership causes this excess comovement based on evidence from a natural experiment—the 2003 mutual fund trading scandal. These results motivate a novel cross‐stock‐reversal trading strategy exploiting information contained in ownership connections. We show that long‐short hedge fund index returns covary negatively with this strategy, suggesting these funds may exacerbate this excess comovement.     

Polynomial goal programming and the implicit higher moment preferences of US institutional investors in hedge funds

Polynomial goal programming (PGP) is a flexible method that allows investor preferences for different moments of the return distribution of financial assets to be included in the portfolio optimization. The method is intuitive and particularly suitable for incorporating investor preferences in higher moments of the return distribution. However, until now, PGP has not been able to meet its full potential because it requires quantification of “real” preference parameters towards those moments. To date, the chosen preference parameters have been selected somewhat “arbitrarily”. Our goal is to calculate implied sets of preference parameters using investors’ choices of and the importance they attribute to risk and performance measures. We use three groups of institutional investors—pension funds, insurance companies, and endowments—and derive implied sets of preference parameters in the context of a hedge fund portfolio optimization. To determine “real” preferences for the higher moments of the portfolio return distribution, we first fit implied preference parameters so that the PGP optimal portfolio is identical to the desired hedge fund portfolio. With the obtained economically justified sets of preference parameters, the well-established PGP framework can be employed more efficiently to derive allocations that satisfy institutional investor expectations for hedge fund investments. Furthermore, the implied preference parameters enable fund of hedge fund managers and other investment managers to derive optimal portfolio allocations based on specific investor expectations. Moreover, the importance of individual moments, as well as their marginal rates of substitution, can be assessed.     

Does concurrent management of mutual and hedge funds create conflicts of interest?

This paper shows that conflicts of interest may exist in cases where a hedge fund manager starts a mutual fund but not in the opposite case. We compare performance, asset flows, and risk incentives to establish several key differences between these two scenarios: First, prior to concurrent management, hedge fund managers experience worse performance while mutual fund managers achieve better performance relative to their full-time peers. Second, hedge fund managers who choose concurrent management are disproportionately the ones with less experience. Their hedge funds tend to suffer a decline in performance after the event. By contrast, mutual fund managers who choose concurrent management tend to outperform their full-time peers. Based on our findings, we make important recommendations for policy makers and companies. The relevance of our recommendations extends beyond the small share of companies presently engaged in concurrent management.     

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.     

Style chasing by hedge fund investors

This paper examines whether investors chase hedge fund investment styles. We find that better-performing and more popular styles are rewarded with higher inflows in subsequent periods. This indicates that investors compare hedge fund styles in terms of recent performance and popularity, and they subsequently reallocate funds from less successful to more successful styles. Furthermore, we find evidence of competition between individual hedge funds of the same style. Funds outperforming the other funds in their styles and funds whose inflows exceed the average flows in their styles experience higher inflows in subsequent periods. One of the reasons for competition among same-style funds is investors’ search for the best managers. The high minimum investment required to invest in a hedge fund limits investors’ diversification opportunities and makes this search particularly important. Finally, we show that hedge fund investors’ implementation of style chasing in combination with intra-style fund selection represents a smart strategy.     

The alpha and omega of fund of hedge fund added value

In spite of a somewhat disappointing performance throughout the crisis, investors are showing interest in hedge funds. Still, funds of hedge funds keep on experiencing outflows. Can this phenomenon be explained by the failure of fund of hedge fund managers to deliver on their promise to add value through active management, or is it symptomatic of a move toward greater disintermediation in the hedge fund industry? We introduce a return-based attribution model allowing for a full decomposition of fund of hedge fund performance. The results of our empirical study suggest that funds of hedge funds are funds of funds like others. Strategic allocation turns out to be a crucial step in the investment process, in that it not only adds value over the long-term, but most importantly, it brings resilience precisely when investors need it the most. Fund picking, on the other hand, turns out to be a double-edged sword.     

Quantile regression analysis of hedge fund strategies

Extending previous work on hedge fund pricing, this paper introduces the idea of modelling the conditional quantiles of hedge fund returns using a set of risk factors. Quantile regression analysis provides a way of understanding how the relationship between hedge fund returns and risk factors changes across the distribution of conditional returns. We propose a Bayesian approach to model comparison which provides posterior probabilities for different risk factor models that can be used for model averaging. The most relevant risk factors are identified for different quantiles and compared with those obtained for the conditional expectation model. We find differences in factor effects across quantiles of returns, which suggest that the standard conditional mean regression method may not be adequate for uncovering the risk-return characteristics of hedge funds. We explore potential economic impacts of our approach by analysing hedge fund single strategy return series and by constructing style portfolios.     

Are hedge funds active market liquidity timers?

This paper investigates liquidity timing behaviour of hedge funds that invest globally in foreign investment assets. We expect these hedge funds to manage currencies exposure differently, depending on the extent they treat them as an asset class. In this paper, we investigate if actively timing foreign exchange (FX) liquidity adds value to hedge funds' investments. Unlike the existing studies where fund managers are assumed to either time or not time the market over the entire study period, we argue that fund managers may strategically choose to be active market liquidity timers based on the market condition at the time. To test this hypothesis, we develop a state-dependent liquidity timing model embedded with a Markov regime switching process and identify changes in the FX liquidity timing behaviour among the Global Derivatives hedge funds over an eighteen-year period. Our findings reveal that such regime changes in timing behaviour are driven by the underlying FX liquidity condition. A further analysis to compare the changes in the timing behaviour over time shows that hedge funds that are active market liquidity timers outperform those that engage in liquidity timing less frequently in all strategies categories.     

The financial crisis and hedge fund returns

The financial crisis has focused the lens of politicians and regulators on hedge funds as a source of systemic and operational risk in asset markets. We examine the extent to which available data can provide useful information regarding the impact of hedge funds on the financial system. Using data from January 1994 through September 2008, we find dramatic changes in the exposures of hedge funds to risk factors, accompanied by a significant and widespread increase in correlation between hedge fund and factor returns. Lastly, the discontinuity at zero in the cross-sectional distribution of hedge fund returns persists throughout the sample.     

Incentives and risk taking in hedge funds

We study how incentive fees and manager’s own investment in the fund affect the investment strategy of hedge fund managers. We find that loss averse managers increase the risk of the fund’s investment strategy with higher incentive fees. However, risk taking is greatly reduced if a substantial amount of the manager’s own money (at least 30%) is in the fund. Using the Zurich hedge fund universe, we test the relation between risk taking and incentive fees empirically. Hedge funds with incentive fees have significantly lower mean returns (net of fees), while downside risk is positively related to the incentive fee level. Fund of funds charging large incentive fees achieve relatively high mean returns, but with significantly higher risk as well.