Hedge fund performance appraisal using data envelopment analysis

In this paper we apply data envelopment analysis (DEA) to evaluate the performance of hedge fund classifications. The purpose of alternative investment strategies such as hedge funds is to offer absolute returns, so using passive benchmarks to measure their performance could be ineffective. With the increasing number of hedge funds available, institutional investors, pension funds, and high net worth individuals urgently need a trustworthy efficiency appraisal method. DEA can achieve this. An important benefit of the DEA measure is that benchmarks are not required, thereby alleviating the problem of using traditional benchmarks to examine non-normal distribution of hedge fund returns. We suggest that DEA be used as a complimentary technique (or method) for the selection of efficient hedge funds and funds of hedge funds for investors. Using DEA can shed light and further validate hedge fund manager selection with other methodologies.     

Mutual funds performance appraisal using stochastic multicriteria acceptability analysis

Mutual fund investors are concerned with the selection of the best fund in terms of performance among the set of alternative funds. This paper proposes an innovative mutual funds performance evaluation measure in the context of multicriteria decision making. We implement a multicriteria methodology using stochastic multicriteria acceptability analysis, on Greek domestic equity funds for the period 2000-2009. Combining a unique dataset of risk-adjusted returns such as Carhart’s alpha with funds’ cost variables, we obtain a multicriteria performance evaluation and ranking of the mutual funds, by means of an additive value function model. The main conclusion is that among employed variables, the sophisticated Carhart’s alpha plays the most important role in determining fund rankings. On the other hand, funds’ rankings are affected only marginally by operational attributes. We believe that our results could have serious implications either in terms of a fund rating system or for constructing optimal combinations of portfolios.     

The Optimal Interaction between a Hedge Fund Manager and Investor

ABSTRACT

This study explores hedge funds from the perspective of investors and the motivation behind their investments. We model a typical hedge fund contract between an investor and a manager, which includes the manager’s special reward scheme, i.e., partial ownership, incentives and early closure conditions. We present a continuous stochastic control problem for the manager’s wealth on a hedge fund comprising one risky asset and one riskless bond as a basis to calculate the investors’ wealth. Then we derive partial differential equations (PDEs) for each agent and numerically obtain the unique viscosity solution for these problems. Our model shows that the manager’s incentives are very high and therefore investors are not receiving profit compared to a riskless investment. We investigate a new type of hedge fund contract where the investor has the option to deposit additional money to the fund at half maturity time. Results show that investors’ inflow increases proportionally with the expected rate of return of the risky asset, but even in low rates of return, investors inflow money to keep the fund open. Finally, comparing the contracts with and without the option, we spot that investors are sometimes better off without the option to inflow money, thus creating a negative value of the option.     

Multiple Fund Investment Situations and Related Games

This paper deals with interactive multiple fund investment situations, in which investors can invest their capital in a number of funds. The investors, however, face some restrictions. In particular, the investment opportunities of an investor depend on the behaviour of the other investors. Moreover, the individual investment returns may differ. We consider this situation from a cooperative game theory point of view. Based on different assumptions modelling the gains of joint investment, we consider three corresponding games and analyse their properties. We propose an allocation process for the maximal total investment revenues.Ruud Hendrickx acknowledges financial support from the Netherlands Organisation for Scientific Research (NWO).     

一直在努力?——基金管理者买卖行为的有效性分析

通过构建收益缺口-基金的净资产收益与投资组合收益之差,探讨了我国证券市场中开放式基金管理者的买卖行为及其对基金业绩的影响.研究结果表明,在2004至2007年中,基金月收益缺口的均值显著大于零,表明基金管理者的努力总体上能增加基金的价值;投资者若模拟基金的股票构成进行投资,在熊市中,其平均回报小于基金的收益,但在牛市中,却显著地大于基金的收益,这一差异对配置型基金更明显.同时,基金收益缺口的大小与基金的类型和规模显著相关.     

Optimal construction and rebalancing of index-tracking portfolios

Index funds aim to track the performance of a financial index, such as, e.g., the Standard?&?Poor’s?500 index. Index funds have become popular because they offer attractive risk-return profiles at low costs. The index-tracking problem considered in this paper consists of rebalancing the composition of the index fund’s tracking portfolio in response to new market information and cash deposits and withdrawals from investors such that the index fund’s tracking accuracy is maximized. In a frictionless market, maximum tracking accuracy is achieved by investing the index fund’s entire capital in a tracking portfolio that has the same normalized value development as the index. In the presence of transaction costs, which reduce the fund’s capital, one has to manage the trade-off between transaction costs and similarity in terms of normalized value developments. Existing mathematical programing formulations for the index-tracking problem do not optimize this trade-off explicitly, which may result in substantial transaction costs or tracking portfolios that differ considerably from the index in terms of normalized value development. In this paper, we present a mixed-integer linear programing formulation with a novel optimization criterion that directly considers the trade-off between transaction costs and similarity in terms of normalized value development. In an experiment based on a set of real-world problem instances, the proposed formulation achieves a considerably higher tracking accuracy than state-of-the-art formulations.     

基于行为金融视角的基金申赎行为实证研究

以开放式证券投资基金申购、赎回行为背后的行为金融机理为研究对象,通过分析相关变量作用于基金投资者心理的方式和路径,探讨其对基金申购、赎回所产生的影响。在理论分析的基础上,提出基金业绩、规模、存续时间、价位、分红等变量能够各自基于信号传递、心理账户、预期框定偏差、预期惯性、处置效应等多元化路径影响投资者心理,并作用于基金申购、赎回和基金流量,并据此提出了相关假设。进一步地,通过建立结构方程模型,以我国327只股票型开放式证券投资基金为样本,对2011至2013年三组年度截面数据进行了检验。实证结果表明信号传递、预期框定偏差路径始终稳定存在,预期惯性路径仅在2011、2013年实证检验中存在,处置效应路径只在2012年检验中存在、且呈现非对称性特征,而心理账户路径则无法得到证实,据此得出结论认为基金业绩对基金申赎影响最为显著但不具稳定性。最后,从投资者行为模式和基金市场发展环境等角度对实证结果进行了分析。     

基于期权思想的封闭式基金管理费率的设计研究

针对目前我国证券投资基金单一的管理费率结构,以封闭式基金为研究对象,根据基金投资者的需求不同提出了在不同收益率目标下的管理费率结构,并借用B-S期权定价模型,计算出封闭式基金的管理费率.     

开放式基金流动性赎回风险实证分析与评价

本基于Vikram Nanda，M．P．Narayanan(2000)的基金管理能力与流动性需求、流动性赎回风险关系模型的修正，研究结果表明，基金管理所预期的利润与其管理能力正相关，而与流动性成本和流动性需求的风险呈负相关；负担基金管理的边际能力相对于低流动性需求投资的数量和高流动性需求投资的风险而言是递减的；最低赎回费用与高流动性需求投资的风险和低流动性需求投资的相对稀缺性正相关。在此基础上对我国开放式基金的流动性赎回风险进行实证分析评价，并提出了几点政策建议。     

我国封闭式投资基金业绩评价实证研究

随着我国基金行业超常发展,恰当的分析和评价基金业绩已越来越重要。本文根据CAPM的基本原理,利用国外先进的基金业绩评价方法对我国封闭式基金的综合业绩进行实证研究。研究结果表明:总体来看,基金获得的市场超额收益显著为负。基金经理不具有证券选择能力,但具有一定的市场择时能力,但这两种能力均不显著。同时,我们还发现不同投资风格的基金经理具有不同的证券选择能力和市场择时能力。     

Optimal consumption and portfolio choice for pooled annuity funds

This paper presents the optimal continuous time dynamic consumption and portfolio choice for pooled annuity funds. A pooled annuity fund constitutes an alternative way to protect against mortality risk compared to purchasing a life annuity. The crucial difference between the pooled annuity fund and purchase of a life annuity offered by an insurance company is that participants of a pooled annuity fund still have to bear some mortality risk while insured annuitants bear no mortality risk at all. The population of the pool is modelled by employing a Poisson process with time-dependent hazard-rate. It follows that the pool member’s optimization problem has to account for the stochastic investment horizon and for jumps in wealth which occur if another pool member dies. In case the number of pool members goes to infinity analytical solutions are provided. For finite pool sizes the solution of the optimization problem is reduced to the numerical solution of a set of ODEs. A simulation and welfare analysis show that pooled annuity funds insure very effectively against longevity risk even if their pool size is rather small. Only very risk averse investors or those without access to small pools are more inclined to pay a risk premium to access private life annuity markets in order to lay off mortality risk completely. As even families constitute such small pools the model provides theoretical justification for the low empirical annuity demand.     

货币市场基金申购赎回的实证研究

本文采用O’Neal分离现金流量方法研究影响货币市场基金投资者申购和赎回行为的具体因素。实证结果表明,基金业绩增长是决定货币市场基金申购和赎回的主要变量,基金当期净值增长率与基金份额净变动率、申购率和赎回率呈正相关关系,影响程度呈非对称性;货币市场基金投资者的申购决策主要考虑基金收益情况,赎回决策兼顾基金收益和风险分布。因此,提高基金收益及其稳定性,降低基金收益波动是货币市场基金加强流动性风险管理的基础。     

关于证券投资基金业绩评价方法及其应的探讨

本文从多个角度介绍了证券投资基金评价的各种方法,并结合我国实际情况,对各种方法的优点与不足进行了分析,为投资者评价基金及做出投资选择提供了有效方法。     

Tri-criterion inverse portfolio optimization with application to socially responsible mutual funds

We present a framework for inverse optimization in a Markowitz portfolio model that is extended to include a third criterion. The third criterion causes the traditional nondominated frontier to become a surface. Until recently, it had not been possible to compute such a surface. But by using a new method that is able to generate the nondominated surfaces of tri-criterion portfolio selection problems, we are able to compute via inverse optimization the implied risk tolerances of given funds that pursue an additional objective beyond risk and return. In applying this capability to a broad sample of conventional and socially responsible (SR) mutual funds, we find that there appears to be no significant evidence that social responsibility issues, after the screening stage, are further taken into account in the asset allocation process, which is a result that is likely to be different from what many SR investors would expect.     

On a Local-Search Heuristic for a Class of Tracking Error Minimization Problems in Portfolio Management

In this paper we describe a 2-phase simulated annealing heuristic approach for a special class of portfolio management problems: the problem of optimizing a stock fund with respect to tracking error and transaction costs over time subject to a set of complex constraints with a linear factor return model “feeding” the objective function with data. Our results on managing two real-world funds of a major German capital investment company have shown that this meta-heuristic provides proposals for the fund manager which are feasible with respect to the investment guidelines and excellent in quality in acceptable time. Thus the approach is ideally suited to be used routinely and interactively within a decision support system to assist the fund manager in his complex task of portfolio control and optimization.     

Mean-chance model for portfolio selection based on uncertain measure

This paper discusses a portfolio selection problem in which security returns are given by experts’ evaluations instead of historical data. A factor method for evaluating security returns based on experts’ judgment is proposed and a mean-chance model for optimal portfolio selection is developed taking transaction costs and investors’ preference on diversification and investment limitations on certain securities into account. The factor method of evaluation can make good use of experts’ knowledge on the effects of economic environment and the companies’ unique characteristics on security returns and incorporate the contemporary relationship of security returns in the portfolio. The use of chance of portfolio return failing to reach the threshold can help investors easily tell their tolerance toward risk and thus facilitate a decision making. To solve the proposed nonlinear programming problem, a genetic algorithm is provided. To illustrate the application of the proposed method, a numerical example is also presented.     

Multiple criteria linear programming model for portfolio selection

The portfolio selection problem is usually considered as a bicriteria optimization problem where a reasonable trade-off between expected rate of return and risk is sought. In the classical Markowitz model the risk is measured with variance, thus generating a quadratic programming model. The Markowitz model is frequently criticized as not consistent with axiomatic models of preferences for choice under risk. Models consistent with the preference axioms are based on the relation of stochastic dominance or on expected utility theory. The former is quite easy to implement for pairwise comparisons of given portfolios whereas it does not offer any computational tool to analyze the portfolio selection problem. The latter, when used for the portfolio selection problem, is restrictive in modeling preferences of investors. In this paper, a multiple criteria linear programming model of the portfolio selection problem is developed. The model is based on the preference axioms for choice under risk. Nevertheless, it allows one to employ the standard multiple criteria procedures to analyze the portfolio selection problem. It is shown that the classical mean-risk approaches resulting in linear programming models correspond to specific solution techniques applied to our multiple criteria model. This revised version was published online in June 2006 with corrections to the Cover Date.     

扫描统计量--检测基金业绩持续性的新方法

基金业绩持续性检测的一般方法是横截面回归与列联表分析，都是从基金行业层面整体检测持续性，不能有效的检测单只基金的业绩持续性。为此本文引入一种新的检测方法——扫描统计量，可以创新性地对单只基金进行有效分析。利用扫描统计量方法对我国基金业绩持续性进行了实证分析，发现部分基金存在持续性，给出了持续性强度的上限，为投资者买卖基金、基金业绩考核、风险监控提供了决策参考依据。     

Optimal pension fund management under multi-period risk minimization

In this paper, a multi-period stochastic optimization model for solving a problem of optimal selection of a pension fund by a pension plan member is presented. In our model, members of the pension plan are given a possibility to switch periodically between J types of funds with different risk profiles and so actively manage their risk exposure and expected return. Minimization of a multi-period average value-at-risk deviation measure under expected return constraint leads to a large-scale linear program. A theoretical framework and a solution for the case of the pension system of Slovak Republic are presented.     

封闭式债券基金风格模糊聚类分析

封闭式债券基金能够在降低风险的同时获取投资收益,并且有着较长的久期,是稳健型投资者实现配置型投资收益较常选择的一个投资品种.利用模糊聚类分析,对封闭式债券基金主要的评价参数进行量化分析,从风险控制、收益水平、选时能力等方面将市场上现有的封闭式债券基金进了投资风格上的划分,为投资者如何选择封闭式债券基金提供了一个较为直观的方法.