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.     

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.     

Evaluation of Commodity Trading Advisors using fixed and variable and benchmark models

This paper examines the performance of Commodity Trading Advisors (CTAs) using fixed and variable benchmarking models. In order to avoid the troublesome passive and active commodity and managed futures benchmarks (indices) when examining the performance of CTAs, we innovate by using data envelopment analysis (DEA). Because this alternative class has non-linear returns due to long/short positions, and derivatives (i.e., dynamic trading strategies), DEA can alleviate the problems usually associated with these indices. The effectiveness of using benchmarking models in a DEA setting will provide investors with an alternative technique in assessing the performance and identifying efficient CTAs.     

基于DEA的基金绩效评价研究

用数据包络分析(DEA)方法对天天基金网中最新银河评级一年期表现优秀的三大类共39只基金绩效进行了进一步的评价研究,选取能充分体现基金风险与收益的统计指标,均值与方差,运用DEA有效性原理比较并分析了39只基金的技术有效性与规模有效性,给出了无效基金仿效的标杆.     

A note on statistical models for individual hedge fund returns

In recent years, a large number of research papers and monographs on the analysis of hedge fund returns have been published. Typically, the authors of these studies implicitly or explicitly treat monthly returns of hedge funds as independent and identically distributed observations. The Hedge Fund Index might be able to serve that role. But the returns of an individual hedge fund are not like that. They behave autoregressively depending on the time periods. This stochastic behavior should be modeled as a combined/regime switching stochastic process of two processes: i.i.d. process and autoregressive process. This paper first depicts the autoregressiveness of hedge fund returns. Then we introduce our statistical model for returns of an individual hedge fund and then, with our retrospective view, we perform several data analyses for individual hedge funds’ return data.     

Portfolio optimization with serially correlated, skewed and fat tailed index returns

This paper finds that mean-variance portfolio optimization of stocks, bonds, hedge funds, real estate investment trusts and commodities is sufficiently exact to optimize the investor’s utility. We approximate the expected utility using a Taylor series expansion including terms involving third and fourth order moments. The empirical findings for monthly data from August 1994–August 2009 suggest that the incorporation of skewness and kurtosis cause no noticeable change in the optimal portfolio allocation. However, the serial correlations of smoothed returns of hedge funds and real estate investment trusts indeed cause major changes in optimal portfolio allocation. Consequently, attention needs to be drawn to significant serial correlation and not to potential deviations from normality due to skewed and fat-tailed return distributions. The out-of-sample analysis using a moving window gives evidence that the optimal portfolio weight differ significantly considering serial correlation. The optimization using smoothed returns leads to the highest terminal wealth after 10 years. The highest utility is reached with smoothed as well as shrinked returns, while using unsmoothed as well as shrinked returns leads to an out-of-sample disaster. These findings have practical implications for investors who are willing to diversify their portfolios with hedge funds and real estate investment trusts.     

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.     

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.     

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.     

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.     

Fuzzy risk adjusted performance measures: Application to hedge funds

In this paper, following the notion of probabilistic risk adjusted performance measures, we introduce that of fuzzy risk adjusted performance measures (FRAPM). In order to deal efficiently with the closing-based returns bias induced by market microstructure noise, as well as to handle their uncertain variability, we combine fuzzy set theory and probability theory. The returns are first represented as fuzzy random variables and then used in defining fuzzy versions of some adjusted performance measures. Using a recent ordering method for fuzzy numbers, we propose a ranking of funds based on these fuzzy performance measures. Finally, empirical studies carried out on fifty French hedge funds confirm the effectiveness and give the benefits of our approach over the classical performance ratios.     

基于最小凸输入需求集方法的基金业绩评价

本文首先回顾了传统基金业绩评价方法，然后运用Chang（1999）的最小凸输入需求集（MCIRS）方法对我国2000年前上市的20只封闭式证券投资基金在2000年的业绩进行综合评价。实证研究表明：同益、景博、汉盛、金鑫、兴和、泰和、天元、普丰共8只基金相对有效，而其余12只基金则相对无效。并将结果与数据包络分析（DEA）的结果进行了比较。     

投资组合模型的改进研究:基于企业社会责任视角的实证分析

在尊重和借鉴前人对企业社会责任研究,尤其是在企业社会责任评价研究基础之上,本文从投资者的角度在投资组合过程中研究企业社会责任。在Markowitz(均值—方差)理论模型上添加企业社会责任的三个一级指标期望作为目标函数,由此将传统的投资组合模型扩展为五个目标函数的投资组合选择模型,而且我们根据经济学中经典的效用函数理论证明了此模型的正确性。本文引入主流的企业社会责任评价标准,并对一些典型公司进行打分量化。在此基础之上建立了以期望回报率、回报率的方差、核心利益相关者期望、蛰伏利益相关者期望和边缘利益相关者期望为目标函数的投资组合选择模型,在最小方差曲面上选取10个点构造投资组合,并以样本外的数据验证了模型的有效性。研究发现:根据此模型计算出来的部分投资组合回报率显著高于同期的市场指数。研究结果表明,这种关注企业社会责任的多目标投资组合选择模型,不仅让投资者可以直接控制企业社会责任,而且实际数据证明了此模型的优势之处,从而为关注企业社会责任的投资者提供一种投资的方法和思路。     

Portfolio selection for individual passive investing

This paper considers passive fund selection from an individual investor's perspective. The growth of the passive fund market over the past decade is staggering. Individual investors who wish to buy these funds for their retirement and brokerage accounts have many options and are faced with a difficult selection problem. Which funds do they invest in, and in what proportions? We develop a novel statistical methodology to address this problem by adapting recent advances in posterior summarization. A Bayesian decision‐theoretic approach is presented to construct optimal sparse portfolios for individual investors over time.     

Measuring the performance of nations at the Summer Olympics using data envelopment analysis

In this paper a well known tool for relative efficiency assessment, namely Data Envelopment Analysis (DEA), is used to measure the performance of the nations participating at the last five Summer Olympic games. The proposed approach considers two inputs (GNP and population) and three outputs (number of gold, silver and bronze medals won). To increase the consistency of the results, weight restrictions are included, guaranteeing a higher valuation for gold medals than for silver medals and higher for the latter than for bronze medals. Variable returns to scale are assumed. The results for the last five Summer Olympics are analysed. For each of them, a performance index as well as benchmarks are computed for each country. In addition, plotting the performance of a specific country for the different games can help identify trends as well as objective successes and disappointments.     

跳扩散条件下波动率风险溢价及影响因素研究——基于上证50 ETF期权市场的实证

本文采用上证50 ETF及其期权交易数据,运用SVCJ模型、MCMC及傅里叶变换等方法,从P测度及Q测度中提取波动率风险溢价,并分析了其时变特征及影响因素。实证研究表明:SVCJ模型相较于SV模型及SVJ模型具有更好的市场拟合优度;傅里叶变换法能提高波动率风险溢价的估计效率;波动率风险溢价具有时变特征,在市场急剧动荡时期,波动率风险溢价基本为负,投资者厌恶波动风险,购买期权对冲波动风险的意愿较高;在市场非急剧动荡时期,波动率风险溢价基本为正,投资者偏好波动风险,购买期权对冲波动风险的意愿较低;市场收益率、波动率、换手率及投资者情绪对波动率风险溢价具有显著的影响。     

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).     

Efficiency,size, benchmarks and targets for bank branches: an application of data envelopment analysis

This paper describes an application of data envelopment analysis (DEA) to the performance assessment of Portuguese bank branches. The analysis shows how DEA can complement the profitability measure currently used at the bank. The use of an efficiency-profitability matrix enabled the characterisation of the branches' performance profile. Consistent with the bank's development objectives, the analysis focused on the relation between branch size and performance. Two alternative target setting strategies were explored. One eliminates pure technical inefficiencies by focusing on the selection of appropriate benchmarks. The other attains the branches' most productive scale size through the elimination of scale inefficiencies, with minimal changes to branches' scale size.