Stochastic dominance analysis of Asian hedge funds

We employ the stochastic dominance approach that utilizes the entire return distribution to rank the performance of Asian hedge funds as traditional mean-variance and CAPM approaches could be inappropriate given the nature of non-normal returns. We find both first-order and higher-order stochastic dominance relationships amongst the funds and conclude that investors would be better off by investing in the first-order dominant funds to maximize their expected wealth. By investing in higher-order dominant funds, risk-averse investors can maximize their expected utilities but not their wealth. In addition, we find the common characteristic for most pairs of funds is that one fund is preferred to another in the negative domain whereas the preference reverses in the positive domain. We conclude that the stochastic dominance approach is more appropriate compared with traditional approaches as a filter in hedge fund selection. Compared with traditional approaches, the SD approach, not only is assumption free, but also provides greater insights to the performance and risk inherent in a hedge fund's track record.     

Stochastic dominance and portfolio analysis

The principle of stochastic dominance is used to characterize the optimal efficient sets when the distributions of the random prospects belong to a family. Most of the well-known distributions are considered. In each case, the optimal efficient sets are characterized by easily verifiable conditions on the parameters of the distributions. These optimal efficient sets are then compared with the corresponding mean-variance (MV) efficient set. It is often found that the optimal efficient sets are proper subsets of the MV efficient set. Thus, the MV criterion is a proper efficiency criterion, but the MV efficient set can be excessively large compared to the optimal efficient set.     

A stochastic dominance analysis of the turnover related performance of mutual funds

Mutual fund performance relative to portfolio turnover is examined for funds in different investment categories using non-parametric, stochastic dominance criteria. We find that, in general, high-turnover funds are at least equally preferable to those with low turnover. This suggests that the costs of obtaining and exploiting information are, on average, compensated for by the subsequent return distribution. The exception is maximum capital gains funds. Here, high-turnover funds clearly dominate those with low turnover and the information gathering function is profitable.We gratefully acknowledge the contribution of an anonymous referee and the comments of Art Gudikunst of Bryant College.     

Calendar anomaly in the Greek stock market: Stochastic dominance analysis

Using stochastic dominance (SD) analysis, this paper examines calendar anomalies in the Athens Stock Exchange (ASE), an emerging market thrust into a path of rapid transition by the economic integration of Greece with the European Union. SD offers two essential analytical attributes: It requires no assumptions regarding the normality of return distributions, and it imposes few restrictions on investors' risk-return tradeoff preference. Between 1985 and 2004, we find temporal predictability of returns in the ASE — a strong “day” effect and rather weak “week” and “January” effects. Our findings on the week and January effects are far less robust as compared to those reported in earlier studies based on parametric tests.     

Stochastic dominance as an approach to uncertainty in cost accounting

Presently textbook treatment of the topic of uncertainty in cost accounting never goes beyond the notions of mean and variance and the maximization of expected utilities. Because the application of these models requires artificial assumptions about either loss functions or utility functions, students are often left wondering how practical probabilistic models are afterall. This paper suggests that stochastic dominance be used to supplement the current textual material on uncertainty. Since these models are easy to implement in a cost accounting context, the class can devote more time to accounting issues in the context of uncertainty rather than get lost in decision theory. Three models of stochastic dominance are discussed here: the first order, the second order, and the third order stochastic dominance. All the necessary assumptions about each model are stated, and each model is accompanied by a numerical example.     

Stochastic dominance statistics for risk averters and risk seekers: an analysis of stock preferences for USA and China

Recent research has found a number of scaling law relationships in foreign exchange data. These relationships, estimated using simple ordinary least squares, can be used to forecast losses in foreign exchange time series from as little as one month’s tick data. We compare the loss forecasts from a new scaling law against six parametric Value at Risk models. Compared to these models, the new scaling law is easier to fit, provides more stable forecasts and is very accurate.     

Style analysis and Value-at-Risk of Asia-focused hedge funds

In this paper we identify risk factors for Asia-focused hedge funds through a modified style analysis technique. Using an Asian hedge fund index, we find that Asian hedge funds show significant positive exposures to emerging equity markets. For both a static and rolling period style analysis, our model provides a high explanatory power for returns of the considered hedge fund index. We further conduct a Value-at-Risk analysis using the results of a rolling window style analysis as inputs. Our findings suggest that the considered parametric models outperform a simple historical simulation that is purely based on past return observations.     

A stochastic dominance analysis of yen carry trades

Yen carry trades have made headline news for over a decade. We examine the profitability of such trades for the period 2001–2009. Yen carry trades generated high mean returns and Sharpe ratios prior to the recent financial crisis. They continued to outperform major stock markets for the full sample period. Given the non-normality of carry trade returns, we apply non-parametric tests based on stochastic dominance (SD) to evaluate whether the high returns of yen carry trades are compatible with risk as reflected in returns on US and global stock market indices. We apply a general test for SD developed recently by Linton, Maasoumi and Whang (2005) to six currencies as well as portfolios of these currencies. For a large class of risk-averse investors, profits from yen carry trades cannot be attributed to risks.     

An empirical analysis of marginal conditional stochastic dominance

Stochastic dominance is a more general approach to expected utility maximization than the widely accepted mean–variance analysis. However, when applied to portfolios of assets, stochastic dominance rules become too complicated for meaningful empirical analysis, and, thus, its practical relevance has been difficult to establish. This paper develops a framework based on the concept of Marginal Conditional Stochastic Dominance (MCSD), introduced by Shalit and Yitzhaki (1994), to test for the first time the relationship between second order stochastic dominance (SSD) and stock returns. We find evidence that MCSD is a significant determinant of stock returns. Our results are robust with respect to the most popular pricing models.     

Performance measurement of hedge funds using data envelopment analysis

Data envelopment analysis (DEA) is a nonparametric method from the area of operations research that measures the relationship of produced outputs to assigned inputs and determines an efficiency score. This efficiency score can be interpreted as a performance measure in investment analysis. Recent literature contains intensive discussion of using DEA to measure the performance of hedge funds, as this approach yields some advantages compared to classic performance measures. This paper extends the current discussion in three aspects. First, we present different DEA models and analyze their suitability for hedge fund performance measurement. Second, we systematize possible inputs and outputs for DEA and again examine their suitability for hedge fund performance measurement. Third, two rules are developed to select inputs and outputs in DEA of hedge funds. Using this framework, we find a completely new ranking of hedge funds compared to classic performance measures and compared to previously proposed DEA applications. Thus, we propose that classic performance measures should be supplemented with DEA based on the suggested rules to fully capture hedge fund risk and return characteristics.      

Optimal allocation to hedge funds: an empirical analysis

What percentage of their portfolio should investors allocate to hedge funds? The only available answers to the above question are set in a static mean-variance framework, with no explicit accounting for uncertainty on the active manager's ability to generate abnormal return, and usually generate unreasonably high allocations to hedge funds. In this paper, we apply the model introduced in Cvitanic et al (2002b Working Paper USC) for optimal investment strategies in the presence of uncertain abnormal returns to a database of hedge funds. We find that the presence of the model risk significantly decreases an investor's optimal allocation to hedge funds. Another finding of this paper is that low beta hedge funds may serve as natural substitutes for a significant portion of investor risk-free asset holdings.     

Bootstrapping a distance test for stochastic dominance analysis

A major impediment to measuring portfolio performance under stochastic dominance has been the lack of test statistics for orders of stochastic dominance above first degree. In this article, the Bootstrap method, introduced by Efron (1979), is used to estimate critical values for distance statistics in order to test the null hypothesis of no dominance, under second- and third-degree stochastic dominance, for several samples of stock returns. These test statistics, suggested by Whitmore (1978), are analogous to the Kolmogorov-Smirnov distance statistics that can be used to test for first-degree stochastic dominance. Stochastic dominance is shown to accurately assess portfolio performance of sample distributions when the population distributions are controlled and Bootstrap statistics are employed in the analysis. In addition, second- and third-degree stochastic dominance analysis of the smallfirm January anomaly indicates that, over the 23-year time period 1964 to 1986, small firms statistically dominate a diversified market index in only one calendar year.     

Master funds in portfolio analysis with general deviation measures

Generalized measures of deviation are considered as substitutes for standard deviation in a framework like that of classical portfolio theory for coping with the uncertainty inherent in achieving rates of return beyond the risk-free rate. Such measures, derived for example from conditional value-at-risk and its variants, can reflect the different attitudes of different classes of investors. They lead nonetheless to generalized one-fund theorems in which a more customized version of portfolio optimization is the aim, rather than the idea that a single “master fund” might arise from market equilibrium and serve the interests of all investors.The results that are obtained cover discrete distributions along with continuous distributions. They are applicable therefore to portfolios involving derivatives, which create jumps in distribution functions at specific gain or loss values, well as to financial models involving finitely many scenarios. Furthermore, they deal rigorously with issues that come up at that level of generality, but have not received adequate attention, including possible lack of differentiability of the deviation expression with respect to the portfolio weights, and the potential nonuniqueness of optimal weights.The results also address in detail the phenomenon that if the risk-free rate lies above a certain threshold, the usually envisioned master fund must be replaced by one of alternative type, representing a “net short position” instead of a “net long position” in the risky instruments. For nonsymmetric deviation measures, the second type need not just be the reverse of the first type, and there can sometimes even be an interval for the risk-free rate in which no master fund of either type exists. A notion of basic fund, in place of master fund, is brought in to get around this difficulty and serve as a single guide to optimality regardless of such circumstances.     

The performance of enhanced-return index funds: evidence from bootstrap analysis

We apply the bootstrap technique proposed by Kosowski et al. [J. Finance, 2006, 61, 2551–2595] in conjunction with Carhart's [J. Finance, 1997, 52, 57–82] unconditional and Ferson and Schadt's [J. Finance, 1996, 51, 425–461] conditional four-factor models of performance to examine whether the performances of enhanced-return index funds over the 1996 to 2007 period are based on luck or superior ‘enhancing’ skills. The advantages of using the bootstrap to rank fund performance are many. It eliminates the need to specify the exact shape of the distribution from which returns are drawn and does not require estimating correlations between portfolio returns. It also eliminates the need to explicitly control for potential ‘data snooping’ biases that arise from an ex-post sort. Our results show evidence of enhanced-return index funds with positive and significant alphas after controlling for luck and sampling variability. The results are robust to both stock-only and derivative-enhanced index funds, although the spread of cross-sectional alphas for derivative-enhanced funds is slightly more pronounced. The study also examines various sub-periods within the sample horizon.     

Tournament behavior in Australian superannuation funds: A non-parametric analysis

Taylor's [Taylor, J. (2003). Risk-taking behavior in mutual fund tournaments, Journal of Economic Behavior and Organisation 50, 373–383] extension of the tournament model of Brown et al. [Brown, K. C., Harlow, W. V., Starks, L. T. (1996). Of tournaments and temptations: An analysis of managerial incentives in the mutual fund industry, Journal of Finance 15, 85–110] proposes that using an exogenous (endogenous) benchmark, will induce losing (winning) managers to gamble. This presents two competing testable hypotheses that are investigated in the current study. We use a sample period covering 1989 to 2001 of Australian multi-sector growth funds. We apply the non-parametric Cross-Product Ratio methodology. Generally, we find evidence in support of Taylor's model.     

The performance and diversification benefits of funds of hedge funds

We examine the performance and diversification potential of 332 funds of hedge funds (FOHFs) for the period from January 1990 to May 2003. Consistent with prior studies, we find that FOHFs appear to underperform the hedge fund index on a risk-adjusted basis. However, FOHFs have characteristics that offset their apparent underperformance. Their returns do not suffer from negative skewness that is a feature of many hedge fund strategies. Relative to the hedge fund index, we find that FOHFs have lower correlations with stock indices in both bull and bear markets, making them a better diversification tool in equity portfolios. For bond portfolios, however, FOHFs have no diversification advantage over hedge fund indexing.     

Performance comparison between exchange-traded funds and closed-end country funds

The objective of this study is to compare the risk and return performance of exchange-traded funds (ETFs) available for foreign markets and closed-end country funds. We utilize 29 closed-end country funds (CEFs) for 14 countries over the sample period from April 1996 to December 2001. The performance proxies are mean returns and risk-adjusted returns. Results indicate that ETFs exhibit higher mean returns and higher Sharpe ratios than foreign closed-end funds, while CEFs exhibit negative alphas. This indicates that a passive investment strategy utilizing ETFs may be superior to an active investment strategy using CEFs. The findings reported here offer some insight on the relative advantages of each type of investment. Specifically, there may be some potential for additional types of ETFs that offer higher risk-adjusted returns than closed-end funds. Such ETFs may be able to offer higher risk-adjusted returns as part of an internationally diversified portfolio.     

Empirical test of the efficiency of the UK covered warrants market: Stochastic dominance and likelihood ratio test approach

This paper represents the first attempt to apply a stochastic dominance (SD) approach to examine the efficiency of the UK covered warrants market. Our empirical analyses reveal that neither covered warrants nor their underlying shares stochastically dominate the other, indicating the nonexistence of potential arbitrage gains in either wealth or utility, which implies market efficiency. To complement the SD results, we also employ a likelihood ratio (LR) test to examine information efficiency. A bootstrap methodology is developed to correct the size distortion of the LR test. Our findings show that UK covered warrant returns efficiently reflect the return information of the underlying shares.     

Large scale analysis of Islamic equity funds using a meta-frontier approach with data envelopment analysis

The paper aims to analyze the efficiency of Islamic equity funds (IEF) during crisis and growth periods and across six investment regions. To our best knowledge, our study uses for the first time the meta-frontier approach with data envelopment analysis (DEA) to compare the relative efficiency of Islamic equity funds. The paper uses a large scale set of data with a sample of 301 IEF for the period of 1993–2013 which enables us to reach conclusions across different investment regions and across different periods which cannot be made with a small size set of data. The paper provides empirical evidence about the improvement of the efficiency levels between 2002 and 2007. It shows that the average efficiency scores during recession periods are higher than the corresponding scores during growth periods. The paper also reveals that the Asia Pacific and Middle East/Africa investment regions exhibit the best technology for IEF. While North America, Europe, Emerging Markets and funds investing worldwide operate with almost the same scores and remain below the average showing a technology gap from “the best practice” for IEF. For funds investing worldwide and in North America, the meta-technology ratio is steadily increasing since 2009, indicating an improvement in their technologies. Our results suggest that although Islamic funds do not seem to be impacted by the financial crisis, they do need to improve their efficiency since the levels are far below the frontier.     

Do hedge funds deliver alpha? A Bayesian and bootstrap analysis

Using a robust bootstrap procedure, we find that top hedge fund performance cannot be explained by luck, and hedge fund performance persists at annual horizons. Moreover, we show that Bayesian measures, which help overcome the short-sample problem inherent in hedge fund returns, lead to superior performance predictability. Sorting on Bayesian alphas, relative to OLS alphas, yields a 5.5% per year increase in the alpha of the spread between the top and bottom hedge fund deciles. Our results are robust and relevant to investors as they are neither confined to small funds, nor driven by incubation bias, backfill bias, or serial correlation.