Constant and variable returns to scale DEA models for socially responsible investment funds

In order to evaluate the performance of socially responsible investment (SRI) funds, we propose some models which use data envelopment analysis (DEA) and can be computed in all phases of the business cycle. These models focus on the most crucial elements of an investment in mutual funds.     

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.     

Semi-Absolute Deviation Rule for Mutual Funds Portfolio Selection

Investors consider mutual funds as an interesting investment opportunity. This is the result of the impressive growth shown by these financial products in recent times. In this paper we propose a mixed integer linear programming model dealing with the portfolio selection problem on mutual funds in a single period investment strategy. We propose some heuristics and compare their performance. According to the results obtained on real instances, heuristics have proved to be effective and efficient.     

Analysis of hedge fund strategies using slack-based DEA models

Hedge funds have made a significant impact on the performance of world financial markets in recent times. Our objective in this paper is to develop a robust framework for the evaluation of hedge funds by incorporating a maximum number of performance measures through public data sources. We analyse the hedge fund strategies (styles) using a variety of classical risk-return measures with the help of slack-based Data Envelopment Analysis (DEA) models to determine a unique performance indicator. The main thrust is to investigate the risk return profile of 4730 hedge funds classified under 18 different strategies using multiple inputs and outputs. The originality of the work lies in applying Slack-Based DEA to decipher the risk-return profile of these strategies using advanced risk-return measures such as Value at Risk, drawdown, lower and higher partial moments and skewness. We find that the correlation between the ranking of hedge fund strategies based on Sharpe ratio and the DEA models is very low; at the same time, there is a significant correlation between rankings obtained by the application of DEA using different sets of input/output measures. We have also compared the DEA rankings with other traditional financial ratios such as modified Sharpe ratio, Sortino ratio and Calmar ratio. The paper also studies the impact of events such as the Asian financial crisis on the performance of hedge funds. The study around the event shows that only a relatively small number of strategies performed better during times of turmoil.     

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。     

Resampling DEA estimates of investment fund performance

Data envelopment analysis (DEA) is attractive for comparing investment funds because it handles different characteristics of fund distribution and gives a way to rank funds. There is substantial literature applying DEA to funds, based on the time series of funds’ returns. This article looks at the issue of uncertainty in the resulting DEA efficiency estimates, investigating consistency and bias. It uses the bootstrap to develop stochastic DEA models for funds, derive confidence intervals and develop techniques to compare and rank funds and represent the ranking. It investigates how to deal with autocorrelation in the time series and considers models that deal with correlation in the funds’ returns.     

Self-organizing maps could improve the classification of Spanish mutual funds

In this paper, we apply nonlinear techniques (Self-Organizing Maps, k-nearest neighbors and the k-means algorithm) to evaluate the official Spanish mutual funds classification. The methodology that we propose allows us to identify which mutual funds are misclassified in the sense that they have historical performances which do not conform to the investment objectives established in their official category. According to this, we conclude that, on average, over 40% of mutual funds could be misclassified. Then, we propose an alternative classification, based on a double-step methodology, and we find that it achieves a significantly lower rate of misclassifications. The portfolios obtained from this alternative classification also attain better performances in terms of return/risk and include a smaller number of assets.     

基金风险改变了投资者的业绩敏感程度吗？——基于基金业绩波动与资金净流量关系的实证研究

本文利用我国2005年至2011年期间开放式基金的面板数据,研究了基金业绩波动对投资者业绩敏感程度的影响。在验证了基金资金净流量与基金业绩的正相关关系后,实证研究发现:(1)基金业绩波动降低了投资者对基金业绩的敏感程度:基金业绩波动越大,相同业绩提升带来的资金净流量越少;(2)对于不同业绩类型的基金,业绩波动对基金“业绩—资金净流量”关系的反向影响程度也有所不同:这一影响主要体现在绩劣基金中,中等业绩基金次之,在明星基金中反而体现为正向影响。     

Socially Responsible Investment: A multicriteria approach to portfolio selection combining ethical and financial objectives

In a context of Socially Responsible Investment (SRI), this paper deals with portfolio selection for investors interested in ethical policies. In the opportunity set there are ethical assets and other assets which are not characterized as ethical. Two goals are considered, the traditional financial goal in the classical utility theory under uncertainty and an ethical goal in the same utility framework. A new financial-ethical bi-criteria model is proposed with absolute risk aversion coefficients and targets depending on the investor’s ethical profile. This approach is relevant as an increasing number of mutual funds are becoming interested in SRI strategies. From the proposed model, an actual case on green investment is developed. Concerning this case (without generalizing to other contexts), an analysis of the numerical results shows that efficient portfolios obtained by the traditional E-V model outperform the strong green portfolios in terms of expected return and risk, but this does not significantly occur with weak green investment.     

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.     

A Euclidean distance-based measure of efficiency in data envelopment analysis

Data envelopment analysis (DEA) has been proven as an excellent data-oriented performance evaluation method when multiple inputs and outputs are present in a set of peer decision-making units (DMUs). Several efficiency measures have been proposed in the DEA literature, see, for instances, radial efficiency measure of Charnes et al. (CCR)(A. Charnes. W.W. Cooper, and E. Rhodes, 1978. Measuring the efficiency of decision making units. Eur. J. Oper. Res. 2, 429–444), Russell graph measure (J.T. Russell, and R. Sirvant. 1999. An enhanced DEA Russell graph efficiency measure. Eur. J. Oper. Res. 115, pp. 596–607) and slack-based measure of Tone (K. Tone, 2001. A slack-based measure of efficiency in DEA. Eur. J. Oper. Res. 130, p. 498–509). In this article, we will propose an Euclidean distance-based measure of efficiency. Then, in order to discriminate the performance of efficient DMUs, an alternative super-efficiency DEA model is proposed. The applicability of the models developed is illustrated in the context of the analysis of gas companies performance.     

DEA Models for Identifying Critical Performance Measures

In performance evaluation, it is important to identify both the efficient frontier and the critical measures. Data envelopment analysis (DEA) has been proven an effective tool for estimating the efficient frontiers, and the optimized DEA weights may be used to identify the critical measures. However, due to multiple DEA optimal weights, a unique set of critical measures may not be obtained for each decision making unit (DMU). Based upon a set of modified DEA models, this paper develops an approach to identify the critical measures for each DMU. Using a set of four Fortune's standard performance measures, capital market value, profit, revenue and number of employees, we perform a performance comparison between the Fortune's e-corporations and 1000 traditional companies. Profit is identified as the critical measure to the performance of e-corporations while revenue the critical measure to the Fortune's 1000 companies. This finding confirms that high revenue does not necessarily mean profit for e-corporations while revenue means a stable proportion of profit for the Fortune's 1000 companies.     

基于VaR和ES调整的Sharpe比率及在基金评价中的实证研究

传统Sharpe比率将投资收益的标准差作为风险的度量,而实证研究中更关注基金的损失风险而非全部风险,这是收益标准差所无法准确刻画的。针对传统Sharpe比率的这一缺点,本文考虑了用于度量下方风险的指标风险价值VaR(Value at Risk)和预期不足ES(Expected Shortfall)来替代投资收益的标准差,从而对传统Sharpe比率进行了调整。这里对VaR和ES进行计算时,运用了经验非参数估计和非参数平滑核估计两种方法。此外,本文还考虑了基金收益随时间波动的动态性,用广义自回归异方差GARCH模型对收益波动进行模拟,考察动态的VaR和ES,在实践中以动态的VaR和ES评价风险收益更加灵活。在实证研究中,本文用传统的Sharpe比率、基于VaR和ES的Sharpe比率以及基于条件VaR和条件ES的条件Sharpe比率对国内证券市场上所有26只封闭式基金在2005-2009年间的业绩进行了实证分析,分析了基金在不同指标下所体现的风险控制能力和收益水平的差别,并基于不同指标对所有基金进行了排名。此外,本文还运用协整检验考察基金收益率与市场基准指数是否存在联动关系,检验证明两者并不存在长期的均衡关系。     

Data envelopment analysis of mutual funds based on second-order stochastic dominance

Although data envelopment analysis (DEA) has been extensively used to assess the performance of mutual funds (MF), most of the approaches overestimate the risk associated to the endogenous benchmark portfolio. This is because in the conventional DEA technology the risk of the target portfolio is computed as a linear combination of the risk of the assessed MF. This neglects the important effects of portfolio diversification. Other approaches based on mean–variance or mean–variance–skewness are non-linear. We propose to combine DEA with stochastic dominance criteria. Thus, in this paper, six distinct DEA-like linear programming (LP) models are proposed for computing relative efficiency scores consistent (in the sense of necessity) with second-order stochastic dominance (SSD). The aim is that, being SSD efficient, the obtained target portfolio should be an optimal benchmark for any rational risk-averse investor. The proposed models are compared with several related approaches from the literature.     

Benchmark optimization and attribute identification for improvement of container terminals

The aim of this paper is to optimize the benchmarks and prioritize the variables of decision-making units (DMUs) in data envelopment analysis (DEA) model. In DEA, there is no scope to differentiate and identify threats for efficient DMUs from the inefficient set. Although benchmarks in DEA allow for identification of targets for improvement, it does not prioritize targets or prescribe level-wise improvement path for inefficient units. This paper presents a decision tree based DEA model to enhance the capability and flexibility of classical DEA. The approach is illustrated through its application to container port industry. The method proceeds by construction of multiple efficient frontiers to identify threats for efficient/inefficient DMUs, provide level-wise reference set for inefficient terminals and diagnose the factors that differentiate the performance of inefficient DMUs. It is followed by identification of significant attributes crucial for improvement in different performance levels. The application of this approach will enable decision makers to identify threats and opportunities facing their business and to improve inefficient units relative to their maximum capacity. In addition, it will help them to make intelligent investment on target factors that can improve their firms’ productivity.     

On the construction of mutual fund portfolios: A multicriteria methodology and an application to the Greek market of equity mutual funds

The evaluation of the performance of mutual funds (MFs) has been a very interesting research topic not only for researchers, but also for managers of financial, banking and investment institutions. In this paper, an integrated methodological framework for the evaluation of MF performance is proposed. The proposed methodology is based on the combination of discrete and continuous multicriteria decision aid (MCDA) methods for MFs selection and composition. In the first stage of the analysis the UTADIS MCDA method is employed in order to develop mutual fund's performance models supporting the selection of a small set of MFs, which will compose the final portfolios. In the second stage, a goal programming model is employed to determine the proportion of the selected MFs in the final portfolios. The methodology is applied on data of Greek MFs over the period 1999–2001 with encouraging results.     

Data envelopment analysis vs. principal component analysis: An illustrative study of economic performance of Chinese cities

This article compares two approaches in aggregating multiple inputs and multiple outputs in the evaluation of decision making units (DMUs), data envelopment analysis (DEA) and principal component analysis (PCA). DEA, a non-statistical efficiency technique, employs linear programming to weight the inputs/outputs and rank the performance of DMUs. PCA, a multivariate statistical method, combines new multiple measures defined by the inputs/outputs. Both methods are applied to three real world data sets that characterize the economic performance of Chinese cities and yield consistent and mutually complementary results. Nonparametric statistical tests are employed to validate the consistency between the rankings obtained from DEA and PCA.     

共同基金和无风险资产投资的最优策略

利用均值-方差模型,分析了非线性交易成本下的共同基金与无风险资产投资组合的有效边界和在一般的效用函数下讨论了投资者的最优投资策略.     

Seasonality and idiosyncratic risk in mutual fund performance

This paper examines the relationship between seasonality, idiosyncratic risk and mutual fund returns using multifactor models. We use a large sample containing the return histories of 728 UK mutual funds over a 23-year period to measure fund performance. We present evidence that idiosyncratic risk cannot be eliminated, we also find evidence of seasonality in all fund categories. Specifically, we find a close relation between the seasonality and the end of the tax-year. We document that the idiosyncratic risk puzzle cannot explain seasonality in fund performance in the UK. Although, we do find that idiosyncratic risk can account for the seasonality in the month of April. Thus, the results show a link between the tax-loss selling hypothesis in April and idiosyncratic risk in that month. Finally, we report evidence that idiosyncratic risk is negatively related to expected returns for most fund classes.