Efficient fund of hedge funds construction under downside risk measures

We consider portfolio allocation in which the underlying investment instruments are hedge funds. We consider a family of utility functions involving the probability of outperforming a benchmark and expected regret relative to another benchmark. Non-normal return vectors with prescribed marginal distributions and correlation structure are modeled and simulated using the normal-to-anything method. A Monte Carlo procedure is used to obtain, and establish the quality of, a solution to the associated portfolio optimization model. Computational results are presented on a problem in which we construct a fund of 13 CSFB/Tremont hedge-fund indices.     

Dynamic preferences for popular investment strategies in pension funds

In this paper, we characterize dynamic investment strategies that are consistent with the expected utility setting and more generally with the forward utility setting. Two popular dynamic strategies in the pension funds industry are used to illustrate our results: a constant proportion portfolio insurance (CPPI) strategy and a life-cycle strategy. For the CPPI strategy, we are able to infer preferences of the pension fund’s manager from her investment strategy, and to exhibit the specific expected utility maximization that makes this strategy optimal at any given time horizon. In the Black–Scholes market with deterministic parameters, we are able to show that traditional life-cycle funds are not optimal to any expected utility maximizers. We also prove that a CPPI strategy is optimal for a fund manager with HARA utility function, while an investor with a SAHARA utility function will choose a time-decreasing allocation to risky assets in the same spirit as the life-cycle funds strategy. Finally, we suggest how to modify these strategies if the financial market follows a more general diffusion process than in the Black–Scholes market.     

Hedge fund return predictability; To combine forecasts or combine information?

While the majority of the predictability literature has been devoted to the predictability of traditional asset classes, the literature on the predictability of hedge fund returns is quite scanty. We focus on assessing the out-of-sample predictability of hedge fund strategies by employing an extensive list of predictors. Aiming at reducing uncertainty risk associated with a single predictor model, we first engage into combining the individual forecasts. We consider various combining methods ranging from simple averaging schemes to more sophisticated ones, such as discounting forecast errors, cluster combining and principal components combining. Our second approach combines information of the predictors and applies kitchen sink, bootstrap aggregating (bagging), lasso, ridge and elastic net specifications. Our statistical and economic evaluation findings point to the superiority of simple combination methods. We also provide evidence on the use of hedge fund return forecasts for hedge fund risk measurement and portfolio allocation. Dynamically constructing portfolios based on the combination forecasts of hedge funds returns leads to considerably improved portfolio performance.     

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.     

基金网络能够提高投资绩效吗？

基金网络在金融市场的信息流动中发挥着重要作用。本文利用基金共同持股关系构建了一个有效的基金网络数据集,以中国资本市场股票型基金2005-2018年季度数据为研究样本,考察基金网络是否以及如何影响投资绩效。结果表明,基金在基金网络中越处于网络中心地位,基金的投资绩效越高。使用基金家族网络作为工具变量缓解内生性偏误后,基金网络仍然对投资绩效具有显著的正向影响。进一步地,本文考察了基金网络影响投资绩效的渠道,结果表明,基金网络主要通过提高基金的选股技能、资产配置技能和管理技能影响投资绩效。最后,本文考察了基金网络对基金市场份额的影响,研究发现基金网络会显著提高基金的市场份额,对基金在市场上的占有率有积极的正向影响。     

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.     

Global equity fund performance, portfolio concentration, and the fundamental law of active management

This paper investigates the relation between portfolio concentration and the performance of global equity funds. Concentrated funds with higher levels of tracking error display better performance than their more broadly diversified counterparts. We show that the observed relation between portfolio concentration and performance is mostly driven by the breadth of the underlying fund strategies; not just by fund managers’ willingness to take big bets. Our results indicate that when investors strive to select the best-performing funds, they should not only consider fund managers’ tracking-error levels. More important is that they take into account the extent to which fund managers carefully allocate their risk budget across multiple investment strategies and have concentrated holdings in multiple market segments simultaneously.     

Asset Allocation and Selectivity of Asian Mutual Funds During Financial Crisis

This paper evaluates the ability of US-based Asian mutual fund managers in coping with the 1997 Asian financial crisis. We find that the actively managed mutual funds under-perform with respect to the market portfolio by 1.71% in average monthly return. Such poor performance is caused by fund managers' relative weakness in country selection as well as in stock picking. Fund managers are also found to be more skillful in picking the correct market when the market is going up than going down. Our results are consistent with the literature that asset allocation in Asian mutual funds is a dominating factor relative to selectivity in explaining fund returns during the financial crisis. In addition, there exists a negative relation between asset allocation ability and selectivity of fund managers.     

On the High‐Frequency Dynamics of Hedge Fund Risk Exposures

We propose a new method to model hedge fund risk exposures using relatively high‐frequency conditioning variables. In a large sample of funds, we find substantial evidence that hedge fund risk exposures vary across and within months, and that capturing within‐month variation is more important for hedge funds than for mutual funds. We consider different within‐month functional forms, and uncover patterns such as day‐of‐the‐month variation in risk exposures. We also find that changes in portfolio allocations, rather than in the risk exposures of the underlying assets, are the main drivers of hedge funds' risk exposure variation.     

Management sub-advising in the mutual fund industry

This is a study of how contractual mechanisms can mitigate agency conflicts in sub-advised mutual funds. Sub-advising contracts allow fund families to expand their product offerings to include new investment styles and thereby gain market share. We show that costly contractual arrangements, such as co-branding, multi-advising, and performance-based compensation, can mitigate agency conflicts in outsourcing and protect investors from potential underperformance. Fund families will find it cost-effective to implement such incentive mechanisms only when investors are sophisticated in assessing manager skill. The findings help to explain why a large percentage of fund families outsource their funds to advisory firms.     

Picking funds with confidence

We present a new approach to selecting actively managed mutual funds that uses both portfolio holdings and fund return information to eliminate funds with predicted inferior performance through a sequence of pairwise fund comparisons. Our methodology determines both the number of skilled funds and their identities, and locates funds with substantially higher risk-adjusted returns than those identified by conventional alpha-ranking methods. We find strong evidence of time-series variation in both the number of funds identified as superior using our approach, as well as in their performance across different economic states.     

Portfolio manager ownership and fund performance

This paper documents the range of portfolio manager ownership in the funds they manage and examines whether higher ownership is associated with improved future performance. Almost half of all managers have ownership stakes in their funds, though the absolute investment is modest. Future risk-adjusted performance is positively related to managerial ownership, with performance improving by about 3 basis points for each basis point of managerial ownership. These findings persist after controlling for various measures of fund board effectiveness. Fund manager ownership is higher in funds with better past performance, lower front-end loads, smaller size, longer managerial tenure, and funds affiliated with smaller families. It is also higher in funds with higher board member compensation and in equity funds relative to bond funds. Future performance is positively related to the component of ownership that can be predicted by other variables, as well as the unpredictable component. Our findings support the notion that managerial ownership has desirable incentive alignment attributes for mutual fund investors and indicate that the disclosure of this information is useful in making portfolio allocation decisions.     

Commonalities in investment strategy and the determinants of performance in mutual fund mergers

This paper examines the determinants of cross-sectional variation in post-merger mutual fund performance. Mergers between funds with similar management objectives, as reflected by average portfolio book-to-market ratio, price–earnings ratio, beta and market capitalization values, outperform mergers between funds with dissimilar strategies. This superior performance transcends lower portfolio rebalancing costs which might be realized between merging funds which hold more assets in common. These results suggest that mutual fund mergers create collaborative benefits between funds with similar strategies. We also examine if fund governance structures influence the fund pairing process, testing if stronger fund oversight mitigates pairing mismatches. We find that less independent boards of trustees and boards with higher compensation are related to greater strategic mismatches between funds. These results suggest that more entrenched boards are more tolerant of fund mismatches which benefit the investment company, yet are not in investor’s best interests.     

Allocation of decision rights and the investment strategy of mutual funds

The literature suggests that while decentralized decision making can allow for greater specialization in an organization, it heightens the cost of coordinating decisions. The mutual fund industry—in particular, sole- and team-managed balanced funds—provides an ideal setting to test the specialization versus coordination trade-off, as information on decision structures and fund actions is easily obtained. We show that sole-managed balanced funds, with centralized decision rights, exhibit significant market timing that requires reallocation across asset classes. However, consistent with coordination difficulties between managers specializing in particular asset classes, no market timing is evident in team-managed balanced funds. Team-managed funds exhibit greater returns from specialization, in the form of better security selection performance than sole-managed funds. These results hold cross-sectionally and for funds that switch management structures. The overall returns across different management structures are similar, indicating a market equilibrium. Investor flows reward market-timing performance for sole- but not team-managed funds.     

Performance analysis of a collateralized fund obligation (CFO) equity tranche

This article examines the performance of the junior tranche of a collateralized fund obligation (CFO), i.e. the residual claim (equity) on a securitized portfolio of hedge funds. We use a polynomial goal programming model to create optimal portfolios of hedge funds, conditional to investor preferences and diversification constraints (maximum allocation per strategy). For each portfolio, we build CFO structures that have different levels of leverage, and analyze both the stand-alone performance as well as potential diversification benefits (low systematic risk exposures) of investing in the equity tranche of these structures. We find that the unconstrained mean-variance portfolio yields a high performance, but greater exposure to systematic risk. We observe the exact opposite picture in the case of unconstrained optimization, where a skewness bias is added, thus proving the existence of a trade-off between stand-alone performance and low exposure to systematic risk factors. We provide evidence that leveraged exposure to these hedge fund portfolios through the structuring of CFOs creates value for the equity tranche investor, even during the recent financial crisis.     

Do Female Mutual Fund Managers Manage Differently?

We examine the performance and investment behavior of female fixed‐income mutual fund managers compared with male fixed‐income mutual fund managers. We find that male‐ and female‐managed funds do not differ significantly in terms of performance, risk, and other fund characteristics. Our results suggest that differences in investment behavior often attributed to gender may be related to investment knowledge and wealth constraints. Despite the similarities between male and female managers, we find evidence that gender influences the decision making of mutual fund investors. We find that the net asset flows into funds managed by females are lower than for males, especially for the manager's initial year managing the fund.     

Optimal and Simple,Nearly Optimal Rules for Minimizing the Probability Of Financial Ruin in Retirement

Abstract

The increasing risk of poverty in retirement has been well documented; it is projected that current and future retirees’ living expenses will significantly exceed their savings and income. In this paper, we consider a retiree who does not have sufficient wealth and income to fund her future expenses, and we seek the asset allocation that minimizes the probability of financial ruin during her lifetime. Building on the work of Young (2004) and Milevsky, Moore, and Young (2006), under general mortality assumptions, we derive a variational inequality that governs the ruin probability and optimal asset allocation. We explore the qualitative properties of the ruin robability and optimal strategy, present a numerical method for their estimation, and examine their sensitivity to changes in model parameters for specific examples. We then present an easy-to-implement allocation rule and demonstrate via simulation that it yields nearly optimal ruin probability, even under discrete portfolio rebalancing.     

The performance of female hedge fund managers

Using data for the period 1994–2013, we examine the return and risk-taking behavior of hedge funds having at least one female portfolio manager and funds that have all female portfolio managers. Funds with all female managers perform no differently than all male-managed funds and have similar risk profiles. For single-style funds, those with mixed teams of both genders underperform male-only funds on both a raw and risk-adjusted basis, although mixed funds incur less risk and their Sharpe ratios do not differ. For funds of funds, both all-female and mixed funds have similar performance to male-managed funds. We then consider the failure rate across all fund styles. Funds with at least one female manager fail at higher rates, driven by difficulty in raising capital—these funds are smaller and are less likely to be closed to new investment. Surviving funds with at least one female manager have better performance than male-managed surviving funds, consistent with the idea that female managers need to perform better for their funds to survive. Yet, female-managed surviving funds have fewer assets under management than surviving male-managed funds. Using media mentions as a proxy for investor interest, female-managed funds receive proportionately less attention. Our results suggest that there are no inherent differences in skill between female and male managers, but that only the best performing female managers manage to survive.     

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.     

Hedge fund allocation: Evaluating parametric and nonparametric forecasts using alternative portfolio construction techniques

We propose a model for constructing Asian funds of hedge funds. We compare the accuracy of forecasts of hedge fund returns using an ordinary least squares (OLS) regression model, a nonparametric regression model, and a nonlinear nonparametric model. We backtest to assess these forecasts using three different portfolio construction processes: an “optimized” portfolio, an equally-weighted portfolio, and the Kelly criterion-based portfolio. We find that the Kelly criterion is a reasonable method for constructing a fund of hedge funds, producing better results than a basic optimization or an equally-weighted portfolio construction method. Our backtests also indicate that the nonparametric forecasts and the OLS forecasts produce similar performance at the hedge fund index level. At the individual fund level, our analysis indicates that the OLS forecasts produce higher directional accuracy than the nonparametric methods but the nonparametric methods produce more accurate forecasts than OLS. In backtests, the highest information ratio to predict hedge fund returns is obtained from a combination of the OLS regression with the Fung–Hsieh eight-factor variables as predictors using the Kelly criterion portfolio construction method. Similarly, the highest information ratio using forecasts generated from a combination of the nonparametric regression using the Fung–Hsieh eight-factor model variables is achieved using the Kelly criterion portfolio construction method. Simulations using risk-adjusted total returns indicate that the nonparametric regression model generates superior information ratios than the analogous backtest results using the OLS. However, the benefits of diversification plateau with portfolios of more than 20 hedge funds. These results generally hold with portfolio implementation lags up to 12 months.