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.     

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.     

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.     

Data envelopment analysis models of investment funds

This paper develops theory missing in the sizable literature that uses data envelopment analysis to construct return-risk ratios for investment funds. It explores the production possibility set of the investment funds to identify an appropriate form of returns to scale. It discusses what risk and return measures can justifiably be combined and how to deal with negative risks, and identifies suitable sets of measures. It identifies the problems of failing to deal with diversification and develops an iterative approximation procedure to deal with it. It identifies relationships between diversification, coherent measures of risk and stochastic dominance. It shows how the iterative procedure makes a practical difference using monthly returns of 30 hedge funds over the same time period. It discusses possible shortcomings of the procedure and offers directions for future research.     

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.     

Estimating fees for managed futures: a continuous-time model with a knockout feature

Past research regarding incentive fees based on high-water marks has developed models for the specific characteristics of hedge funds. These theoretical models have used either discrete time or a Black-Scholes type differential equation. However, for managed futures, high-water marks are measured more frequently than for hedge funds, so a continuous-time model for managed futures may be appropriate. A knockout feature is added to a continuous model, which is something unique to managed futures although it could also have some relevance to hedge funds. The procedures allow one to derive the distribution function for the fund's survival time, which has not been derived in past research. The distribution of the maximum until ruin is derived as well, and used to provide an estimate of expected incentive fees. An estimate of the expected fixed fee is also obtained. The model shows that the expected incentive fee would be maximized if all funds were invested in margins, but for total fees to be maximized in the presence of a knockout feature, less than half of the funds should be invested. This is precisely what fund managers do. This result suggests that designing a fund with incentive fees only may cause fund managers to adopt the highest leverage, and thus, highest risk possible.     

Fitting asset returns to skewed distributions: Are the skew-normal and skew-student good models?

Vernic (2006), Bolancé et al. (2008), and Eling (2012) identify the skew-normal and skew-student as promising models for describing actuarial loss data. In this paper, we change the focus from the liability to the asset side and ask whether these distributions are also useful for analyzing the investment returns of insurance companies. To answer this question, we fit various parametric distributions to capital market data which has been used to describe the investment set of insurance companies. Our results show that the skew-student is an especially promising distribution for modeling asset returns such as those of stocks, bonds, money market instruments, and hedge funds. Combining the results of Vernic (2006), Bolancé et al. (2008), Eling (2012), and this paper, it appears that the skew-student is a promising actuarial tool since it describes both sides of the insurer’s balance sheet reasonably well.     

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.     

风险规避和最优套期保值比率

在一般的期望效用框架下,研究投资者的风险厌恶态度对于其套期保值策略的影响.首先,给出了投资者采用不同套期保值策略时,效用函数应该满足的条件;其次,讨论了期望效用框架下,Rubinstein整体风险厌恶度量与经典的Arrow Pratt局部风险厌恶度量和更强的Ross的风险度量之间的关系,提出了一组条件,使得在该组条件下,风险厌恶的人际间比较可以用Rubinstein整体风险厌恶度量来刻画;最后,在现货和期货服从正态分布的假设下,使用之前提出的条件,研究投资者风险厌恶程度对于其持有的最优套期保值比率的影响.     

The role of index bonds in universal currency hedging

This study examines the demand for index bonds and their role in hedging risky asset returns against currency risks in a complete market where equity is not hedged against inflation risk. Avellaneda's uncertain volatility model with non-constant coefficients to describe equity price variation, forward price variation, index bond price variation and rate of inflation, together with Merton's intertemporal portfolio choice model, are utilized to enable an investor to choose an optimal portfolio consisting of equity, nominal bonds and index bonds when the rate of inflation is uncertain. A hedge ratio is universal if investors in different countries hedge against currency risk to the same extent. Three universal hedge ratios (UHRs) are defined with respect to the investor's total demand for index bonds, hedging risky asset returns (i.e. equity and nominal bonds) against currency risk, which are not held for hedging purposes. These UHRs are hedge positions in foreign index bond portfolios, stated as a fraction of the national market portfolio. At equilibrium all the three UHRs are comparable to Black's corrected equilibrium hedging ratio. The Cameron-Martin-Girsanov theorem is applied to show that the Radon-Nikodym derivative given under a P -martingale, the investor's exchange rate (product of the two currencies) is a martingale. Therefore the investors can agree on a common hedging strategy to trade exchange rate risk irrespective of investor nationality. This makes the choice of the measurement currency irrelevant and the hedge ratio universal without affecting their values.     

A stochastic Nash equilibrium portfolio game between two DC pension funds

In this paper, we study the stochastic Nash equilibrium portfolio game between two pension funds under inflation risks. The financial market consists of cash, bond and two stocks. It is assumed that the price index is derived through a generalized Fisher equation while the bond is related to the price index to hedge the risk of inflation. Besides, these two pension managers can invest in their familiar stocks. The goal of the pension managers is to maximize the utility of the weighted terminal wealth and relative wealth. Dynamic programming method is employed to derive the Nash equilibrium strategies. In the end, a numerical analysis is presented to reveal the economic behaviors of the two DC pension funds.     

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.     

Hedging effectiveness of stock index futures

The paper is concerned with the efficiency of hedging stock portfolios using futures stock indices covering the period January 1995–December 2001. The hedged portfolios consisted of the assets of seventeen investment companies quoted on the London Stock Exchange and two portfolios, which were assumed to match exactly the corresponding cash index. Two futures indices were used to hedge the funds namely FTSE100 and FTSE250 futures indices which are quoted on LIFFE. Weekly observations were used providing 365 observations for each variable.The total sample was split into two sections. The first 261 observations were used to estimate the optimal hedge ratio (i.e. the in-sample period) providing 260 returns for each variable and the remaining 104 (i.e. the post-sample period) observations utilised to check the efficiency of the estimated hedge ratio. In addition a second estimation window was tried using the last 30 observations of the in-sample period. A variety of methods were tried to estimate the optimal hedge ratio including ordinary least squares (OLS), methods allowing for the existence of Autoregressive Conditional Heteroskedasticity, and an Exponential Weighted Moving Average (EWMA).The general conclusions reached were that for the portfolios within the data set (i) that the EWMA method of estimation provided the best estimate of the optimal hedge (ii) the shorter estimation window was no more efficient than the longer window and (ii) the FTESE250 futures index was the best hedging vehicle for these portfolios.     

突发公共卫生事件对系统性金融风险的冲击及传染效应研究

首先基于面板向量自回归模型考察了突发公共卫生事件对系统性金融风险的冲击影响,接着综合考虑突发公共卫生事件的影响及其所导致的收益率的非对称性构建单指标非对称CoVaR模型,最后借助LASSO惩罚函数与局部估计法进行求解,以此构建有向网络分析金融机构间的传染效应.研究发现:(1)突发公共卫生事件冲击会使系统性金融风险水平短...     

Hedging mortality/longevity risks of insurance portfolios for life insurer/annuity provider and financial intermediary

In this paper, we propose two risk hedge schemes in which a life insurer (an annuity provider) can transfer mortality (longevity) risk of a portfolio of life (annuity) exposures to a financial intermediary by paying the hedging premium of a mortality-linked security. The optimal units of the mortality-linked security which maximize hedge effectiveness for a life insurer (an annuity provider) can be derived as closed-form formulas under the risk hedge schemes. Numerical illustrations show that the risk hedge schemes can significantly hedge the downside risk of loss due to mortality (longevity) risk for the life insurer (annuity provider) under some stochastic mortality models. Besides, finding an optimal weight of a portfolio of life and annuity business, the financial intermediary can reduce the sensitivity to mortality rates but the model risk; a security loading may be imposed on the hedge premium for a higher probability of gain to compensate the financial intermediary for the inevitable model risk.     

Delta–Gamma hedging of mortality and interest rate risk

One of the major concerns of life insurers and pension funds is the increasing longevity of their beneficiaries. This paper studies the hedging problem of annuity cash flows when mortality and interest rates are stochastic. We first propose a Delta–Gamma hedging technique for mortality risk. The risk factor against which to hedge is the difference between the actual mortality intensity in the future and its “forecast” today, the forward intensity. We specialize the hedging technique first to the case in which mortality intensities are affine, then to Ornstein–Uhlenbeck and Feller processes, providing actuarial justifications for this selection. We show that, without imposing no arbitrage, we can get equivalent probability measures under which the HJM condition for no arbitrage is satisfied. Last, we extend our results to the presence of both interest rate and mortality risk. We provide a UK calibrated example of Delta–Gamma hedging of both mortality and interest rate risk.     

Financial contagion: extending the exposures network of the Mexican financial system

Direct contagion has been widely studied in recent years and little evidence has been found to be relevant to the study of systemic risk. However, we argue that this limited contagion effect might be associated with a lack of relevant data. A common assumption for the estimation of the matrices of exposures is to apply the maximum entropy principle to deal with data gaps; such an assumption might lead to an underestimation of contagion risk. In this paper, there are no data gaps and the information set is extended from interbank exposures alone to exposures among most of the financial intermediaries in the Mexican financial system (we even include exposures to some international foreign banks). Naturally, the contagion risk of an extended network of exposures changes with respect to the interbank exposures network, as there are many more institutions which can be the source of contagion and there are more institutions which can fail due to contagion. The most important contribution of this paper is that it provides evidence on financial contagion with an extended exposures network under stressful conditions. The results presented here support the international efforts by the Bank for International Settlements, the International Monetary Fund and the Financial Stability Board to increase the amount of information available which can be used to assess systemic risk and contagion based on exposures and funding data.     

中国股市二级市场交易基金收益与交易成本的关系研究

本文以中国二级市场上交易的封闭式基金、交易所开放式指数基金(ETF)、和上市型开放式基金(LOF)为例,借助微观市场结构的模型,分析基金自身的交易成本和收益之间的关系。本文证明2006年7月的基金改制事件提高了基金市场有效性。具体表现在这些基金的交易成本与相应时段内代表公司经营能力的累积净值和市场回报间存在显著的正相关关系。但与经典金融理论不同的是,我国二级市场交易基金(主要是封闭式基金)的交易成本和业绩波动率呈负相关的关系。本文认为这说明在我国封闭式基金市场存在"炒作"现象。最后,本文基于实证结果给出了一些政策上的建议。     

组合投资β调整与效用最大化的套期比的选择

为了针对市场风险对风险资产的组合投资进行套期保值，一般认为要选择将组合投资多头和期货合同空头结合起来的头寸方差最小化的套期保值比率，也就是要选择使某一特定函数的期望效用最大化的套期保值比率。但是本认为，由于种种原因，人们更倾向于选择对简单风险最小头寸的套期保值比率。     

What is the impact of stock market contagion on an investor’s portfolio choice?

Stocks are exposed to the risk of sudden downward jumps. Additionally, a crash in one stock (or index) can increase the risk of crashes in other stocks (or indices). Our paper explicitly takes this contagion risk into account and studies its impact on the portfolio decision of a CRRA investor both in complete and in incomplete market settings. We find that the investor significantly adjusts his portfolio when contagion is more likely to occur. Capturing the time dimension of contagion, i.e. the time span between jumps in two stocks or stock indices, is thus of first-order importance when analyzing portfolio decisions. Investors ignoring contagion completely or accounting for contagion while ignoring its time dimension suffer large and economically significant utility losses. These losses are larger in complete than in incomplete markets, and the investor might be better off if he does not trade derivatives. Furthermore, we emphasize that the risk of contagion has a crucial impact on investors’ security demands, since it reduces their ability to diversify their portfolios.