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.     

中国股市收益率与异质波动性关系研究

本文研究了中国股票市场的异质波动性问题。主要从异质波动性的识别与分布,异质波动性与股票收益率之间的关系,以及异质波动性是否被充分定价等三方面进行探讨。研究的目的在于分析股票异质波动性问题在中国股票市场中的特殊地位,这其中也包括异质波动性对股票收益影响问题。结合中国股票市场的数据,采用广义矩估计(GMM)的数量方法,显著地得到了中国股票市场中异质波动性水平,并以此分析了异质波动性与股票收益之间的关系,证明股票异质波动性水平是投资者进行决策时需要考虑的重要因素之一。     

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。     

基金经理过度自信对基金收益与风险的影响研究

本文扩展了以前的研究范围，考察了基金经理过度自信对基金收益与风险的影响。与以前研究不同的是。我们在模型中引进了基金经理的能力这一参数，并假设基金经理从接收到的信号中提取信息的多少依赖于其能力的大小。我们发现。过度自信导致基金经理交易较多数量的风险资产。结果使得基金获得了较高的收益。但同时基金的风险也较高。从不同的角度。我们进一步证实了以前的研究结论。     

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。     

Moment condition failure in stock returns: UK evidence

We examine the issue of moments existence in the UK stock market. It is found that the second moment of stock returns is finite, and therefore, the infinite variance stable distribution is ruled out as a candidate for modelling stock returns. In contrast with the US evidence, we cannot rule out the possibility that the fourth moment is finite.     

基金投资行为与投资绩效实证研究

本文主要研究2000年末到2004年6月国内基金投资行为与投资绩效。我们将基金交易行为分为:新进入、完全退出和对仓位进行调整3类,并分别研究其投资行为。研究结果显示,我国基金交易频率很高,近90%的基金采用动量投资策略,基金新进入股票时动量效应最强。价值型基金更易采取动量投资策略,高动量组收益高于低动量组收益。     

媒体信息量异常或有害股票收益

本文借助一个独特的数据样本,运用媒体对股票的剩余关注度模型,实证研究异常媒体信息量与股票收益之间的关系,以期为投资者进行投资决策提供一定的参考和指导。研究发现:异常媒体信息量越大,该股票在下一个月的平均收益率越低,存在媒体效应;由此所构造的零投资组合经CAPM模型、FF三因素模型和Car-hart四因素模型调整后,均能获取显著的超额收益,结果具有稳健性。此外,实证结果还表明媒体效应所带来的超额收益源于媒体信息量异常大的股票组合的显著低收益,本文认为,这种不对称现象产生的原因可能更多的是由投资者情绪导致的股票价格对媒体报道的过度反应,并进而导致较低的期望收益。     

Portfolio selection of a closed-end mutual fund

A well-known regulation on the management of a closed-end mutual fund is that the managers’ account cannot invest in risky assets. This paper studies the impact of this regulation under a given management fee structure such that the cumulative management fee rate is described by a fixed RCLL deterministic increasing function. We conclude that the manager’s welfare is approximately the same whether the regulation exists or not. In the expected utility maximization framework, we explicitly find the optimal investment-consumption plan when it exists, and get a sequence of asymptotic near-optimal investment-consumption plans when an optimal one does not exist.     

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.     

Does stock return predictability affect ESO fair value?

Executive Stock Options (ESOs) are modified American options that cannot be valued using standard methods. With a few exceptions, the literature has discussed the ESO fair value by assuming unpredictable stock returns which are not supported by the available empirical evidence. In this paper we obtain the fair value of American ESOs when stock returns are predictable and, specifically, driven by the trending Ornstein–Uhlenbeck process of Lo and Wang (1995). We solve the executive’s portfolio allocation problem for a simple buy-and-hold strategy when his wealth can be distributed between a risk-free asset and a market portfolio. This problem is jointly solved with the executive’s optimal exercise policy. We find that executives tend to wait longer the higher the predictability, independently of the composition of executive’s asset menu. We have also analyzed the implications under the FAS123R proposals for the ESO fair value and found that, even for low autocorrelations, there is a meaningful mispricing when unpredictable returns are erroneously assumed.     

Take (smoothed) risks when you are young, not when you are old: How to get the best from your pension plan

Using stochastic modelling, we demonstrate that the best investmentstrategy for the accumulation phase of a defined contributionpension plan is one that limits the range of returns that arecredited to the plan member's account. In particular, we showthat with-profit accumulation programmes which make use of asmoothing fund to smooth out returns over time dominate unit-linkedaccumulation programmes. However, for the distribution phase,we show that it is hard in practice for an investment-linkeddistribution programme to beat the income and security providedby a standard annuity, although we again find that, by avoidingextremely poor outcomes, with-profit distribution programmesdominate unit-linked distribution programmes. Return smoothingby means of a smoothing fund is therefore a valuable featureof any long-term investment programme both during the accumulationand distribution phases.     

Maximum probability dominance and portfolio theory

The concept of probability dominance and some of its parametric and nonparametric aspects are explored here in comparing two or more competing portfolios of returns. These aspects deal with the theory of stochastic dominance and that of mean-variance efficiency, which have been applied frequently in portfolio literature. Some illustrative applications are also developed here for evaluating the performance of mutual fund portfolios.Grateful thanks are due to P. L. Yu and the anonymous referee for their many constructive suggestions.     

On the predictive ability of narrative disclosures in annual reports

We investigate whether narrative disclosures in 10-K and 10K-405 filings contain value-relevant information for predicting market performance. We apply text classification techniques from computer science to machine code text disclosures in a sample of 4280 filings by 1236 firms over five years. Our methodology develops a model using documents and actual performance for a training sample. This model, when applied to documents from a test set, leads to performance prediction. We find that a portfolio based on model predictions earns significantly positive size-adjusted returns, indicating that narrative disclosures contain value-relevant information. Supplementary analyses show that the text classification model captures information not contained in document-level features of clarity, tone and risk sentiment considered in prior research. However, we find that the narrative score is not providing information incremental to traditional predictors such as size, market-to-book and momentum, but rather affects investors’ use of price momentum as a factor that predicts excess returns.     

中国股票市场有效性的复合评价

本文以2000年1月4日至2011年4月1日的上证综指(000001)和深圳综指(399106)的日收盘价和日收益率为研究对象,根据随机游走假设,采用对数动态自回归模型、游程检验和单位根检验,对上海股票交易所和深圳股票交易所的市场有效性分别进行检验,结果表明沪深两市都基本达到弱式有效。由于上述检验无法证明两股市之间是否存在影响,价格水平是否互相包含,因此有必要验证沪深两市是否为联合有效。本文采用Johansen协整检验和Granger因果关系检验,结果表明上证综指的日收益率对深圳综指的日收益率有一定的预测作用,但沪深两市的价格不存在长期均衡关系,因此可判断沪深股市基本达到联合的弱式有效。     

Modelling dynamic portfolio risk using risk drivers of elliptical processes

The situation of a limited availability of historical data is frequently encountered in portfolio risk estimation, especially in credit risk estimation. This makes it difficult, for example, to find statistically significant temporal structures in the data on the single asset level. By contrast, there is often a broader availability of cross-sectional data, i.e. a large number of assets in the portfolio. This paper proposes a stochastic dynamic model which takes this situation into account. The modelling framework is based on multivariate elliptical processes which model portfolio risk via sub-portfolio specific volatility indices called portfolio risk drivers. The dynamics of the risk drivers are modelled by multiplicative error models (MEMs)-as introduced by Engle [Engle, R.F., 2002. New frontiers for ARCH models. J. Appl. Econom. 17, 425-446]-or by traditional ARMA models. The model is calibrated to Moody’s KMV Credit Monitor asset returns (also known as firm-value returns) given on a monthly basis for 756 listed European companies at 115 time points from 1996 to 2005. This database is used by financial institutions to assess the credit quality of firms. The proposed risk drivers capture the volatility structure of asset returns in different industry sectors. A characteristic cyclical as well as a seasonal temporal structure of the risk drivers is found across all industry sectors. In addition, each risk driver exhibits idiosyncratic developments. We also identify correlations between the risk drivers and selected macroeconomic variables. These findings may improve the estimation of risk measures such as the (portfolio) Value at Risk. The proposed methods are general and can be applied to any series of multivariate asset or equity returns in finance and insurance.     

Momentum Effect Differs Across Stock Performances:Chinese Evidence

Prior empirical studies find positive and negative momentum effect across the global nations, but few focus on explaining the mixed results. In order to address this issue, we apply the quantile regression approach to analyze the momentum effect in the context of Chinese stock market in this paper. The evidence suggests that the momentum effect in Chinese stock is not stable across firms with different levels of performance. We find that negative momentum effect in the short and medium horizon （3 months and 9 months） increases with the quantile of stock returns. And the positive momentum effect is observed in the long horizon （12 months）, which also intensifies for the high performing stocks. According to our study, momentum effect needs to be examined on the basis of stock returns. OLS estimation, which gives an exclusive and biased result, provides misguiding intuitions for momentum effect across the global nations. Based on the empirical results of quantile regression, effective risk control strategies can also be inspired by adjusting the proportion of assets with past performances.     

Simulation and evaluation of the distribution of interest rate risk

We study methods to simulate term structures in order to measure interest rate risk more accurately. We use principal component analysis of term structure innovations to identify risk factors and we model their univariate distribution using GARCH-models with Student’s t-distributions in order to handle heteroscedasticity and fat tails. We find that the Student’s t-copula is most suitable to model co-dependence of these univariate risk factors. We aim to develop a model that provides low ex-ante risk measures, while having accurate representations of the ex-post realized risk. By utilizing a more accurate term structure estimation method, our proposed model is less sensitive to measurement noise compared to traditional models. We perform an out-of-sample test for the U.S. market between 2002 and 2017 by valuing a portfolio consisting of interest rate derivatives. We find that ex-ante Value at Risk measurements can be substantially reduced for all confidence levels above 95%, compared to the traditional models. We find that that the realized portfolio tail losses accurately conform to the ex-ante measurement for daily returns, while traditional methods overestimate, or in some cases even underestimate the risk ex-post. Due to noise inherent in the term structure measurements, we find that all models overestimate the risk for 10-day and quarterly returns, but that our proposed model provides the by far lowest Value at Risk measures.