我国创业板企业内部人交易择时行为研究

利用深圳证券交易所2012年1月1日至2013年12月31日期间的创业板企业内部人的交易数据,从间接与直接两个角度考虑创业板企业的内部人交易与信息优势利用的关系.从间接角度来看,创业板企业的内部人卖出能够有效预测未来股票走势,来获取超额收益;而买入则不具有显著的择时能力,不能获取正的超额收益,这与主板企业具有相同特点;但其中创业板小额买入可取得长期收益,这与主板企业有所不同.从直接角度来看,创业板企业内部人在卖出中充分利用了估值判断优势,抓住高估值偏差的市场机会套现,这与主板企业的特点相同;而创业板企业的内部人买入交易决策与估值判断、业绩预测这两种信息优势利用的关系都不密切,这与主板企业的特点有所不同.     

股权分置改革试点G股的超常收益实证研究

本文采用事件研究法就股权分置试点改革过程中G股股票是否存在超常收益进行了实证分析。实证分析表明股改试点公司股票在试点公司完成股改后复牌当天确实存在着显著的正的超常收益,其中第一批试点公司G股股票的平均超常收益率高于第二批试点公司G股股票的平均超常收益率,深交所试点公司G股股票的平均超常收益率略高于上交所试点公司G股股票的平均超常收益率,中小企业板试点公司G股股票的平均超常收益率高于主板试点公司G股股票的平均超常收益率,高对价试点公司G股股票的平均超常收益率高于低对价试点公司G股股票的平均超常收益率。     

Nonparametric prediction of stock returns based on yearly data: The long-term view

One of the most studied questions in economics and finance is whether empirical models can be used to predict equity returns or premiums. In this paper, we take the actuarial long-term view and base our prediction on yearly data from 1872 through 2014. While many authors favor the historical mean or other parametric methods, this article focuses on nonlinear relationships between a set of covariates. A bootstrap test on the true functional form of the conditional expected returns confirms that yearly returns on the S&P500 are predictable. The inclusion of prior knowledge in our nonlinear model shows notable improvement in the prediction of excess stock returns compared to a fully nonparametric model. Statistically, a bias and dimension reduction method is proposed to import more structure in the estimation process as an adequate way to circumvent the curse of dimensionality.     

The impact of analyst recommendations on stock prices in Austria (2000–2014): evidence from a small and thinly traded market

Using a individually collected database for stock recommendations with more than 8,000 research reports issued over the period 2000–2014 on stocks listed in the Austrian Traded Index, we examine short-term market reactions. Besides traditional clustering of recommendation changes (upgrade, and downgrade) we take previous recommendations into account to get a very detailed subset of different event types. In order to consider Austrian market characteristics, we use an ARMA-market-GARCH model in addition to the market model to compare estimation results for abnormal returns. For the most extensive recommendation changes, from SELL to BUY, we document an abnormal return of 1.232 % and from BUY to SELL, \(-\)1.534 % compared to pure BUY or SELL recommendations with 0.436 and \(-\)0.672 %, respectively. Furthermore we are able to show that the magnitude of abnormal returns on the day of the event depends on the firm size and the delta between the target price of the recommendation and the actual price of the stock. Although we detect higher abnormal returns during the crisis, we do not find statistical evidence that investors tend to trust analysts’ opinions more during turbulent times. We conclude that the more sophisticated model does not improve the outcome and therefore a simple market model is sufficient to study events in the Austrian market.     

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。     

Additive efficiency decomposition in two-stage DEA

Kao and Hwang (2008) [Kao, C., Hwang, S.-N., 2008. Efficiency decomposition in two-stage data envelopment analysis: An application to non-life insurance companies in Taiwan. European Journal of Operational Research 185 (1), 418–429] develop a data envelopment analysis (DEA) approach for measuring efficiency of decision processes which can be divided into two stages. The first stage uses inputs to generate outputs which become the inputs to the second stage. The first stage outputs are referred to as intermediate measures. The second stage then uses these intermediate measures to produce outputs. Kao and Huang represent the efficiency of the overall process as the product of the efficiencies of the two stages. A major limitation of this model is its applicability to only constant returns to scale (CRS) situations. The current paper develops an additive efficiency decomposition approach wherein the overall efficiency is expressed as a (weighted) sum of the efficiencies of the individual stages. This approach can be applied under both CRS and variable returns to scale (VRS) assumptions. The case of Taiwanese non-life insurance companies is revisited using this newly developed approach.     

Company failure prediction with limited information: newly incorporated companies

Developing ‘Internal Rating Systems’ (IRB) for corporate risk management requires building risk (PD) models geared to the specific characteristics of corporate sub-populations (eg small and medium-sized enterprises (SMEs), private companies, listed companies, sector specific models), tuned to changes in the macro environment, and, of course, tailored to the available data. Tracking the risk of ‘newly incorporated companies’ provides a particular challenge since there is very limited publically available data in the time period from incorporation date until the submission of the first accounts. Yet a large number of these companies fail (via bankruptcy). We employ a substantial database to estimate discrete time hazard models (DHM) over the period 2000–2008 (4?427?896 firm-year observations and 34?903 incidences of insolvency), inclusive of macro and regional economic conditions, that capture early indicators of financial stress and measure aspects of the characteristics of board of directors in order to assess the utility of this type of non-financial information in failure prediction models.     

Analyzing return asymmetry and quantiles through stochastic volatility models using asymmetric Laplace error via uniform scale mixtures

This paper proposes a new approach to analyze stock return asymmetry and quantiles. We also present a new scale mixture of uniform (SMU) representation for the asymmetric Laplace distribution (ALD). The use of the SMU for a probability distribution is a data augmentation technique that simplifies the Gibbs sampler of the Bayesian Markov chain Monte Carlo algorithms. We consider a stochastic volatility (SV) model with an ALD error distribution. With the SMU representation, the full conditional distribution for some parameters is shown to have closed form. It is also known that the ALD can be used to obtain the coefficients of quantile regression models. This paper also considers a quantile SV model by fixing the skew parameter of the ALD at specific quantile level. Simulation study shows that the proposed methodology works well in both SV and quantile SV models using Bayesian approach. In the empirical study, we analyze index returns of the stock markets in Australia, Japan, Hong Kong, Thailand, and the UK and study the effect of S&P 500 on these returns. The results show the significant return asymmetry in some markets and the influence by S&P 500 in all markets at all quantile levels. Copyright © 2014 John Wiley & Sons, Ltd.     

基于区间变量RF算法的青海省电力公司员工离职预测

在电力体制改革全面深化的背景下,我国西部偏远地区的电力企业面临较为严重的人员流失问题。员工离职预测越来越受到电力企业关注,然而传统预测算法无法有效解决电力企业员工离职数据集的不平衡问题。基于此,本文提出一种基于区间变量的随机森林算法,采用青海省电力公司2009~2017年人力资源数据集进行实证分析,并与决策树、支持向量机、随机森林算法的预测效果进行对比。结果表明,该算法更适合解决数据不平衡问题,具有更高的预测精度;同时分析得到员工离职的重要特征,为相关电力企业人力资源管理提供决策依据。     

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.     

Measuring inefficiency for specific inputs using data envelopment analysis: evidence from construction industry in Spain and Portugal

This article contributes to the efficiency literature by defining, in the context of the data envelopment analysis framework, the directional distance function approach for measuring both technical and scale inefficiencies with regard to the use of individual inputs. The input-specific technical and scale inefficiencies are then aggregated in order to calculate the overall inefficiency measures. Empirical application focuses on a large dataset of Spanish and Portuguese construction companies between 2002 and 2010 and accounts for three inputs: materials, labor and fixed assets. The results show, first, that for both Spanish and Portuguese construction companies, fixed assets are the most technically inefficient input. Second, the most inefficient scale concerns the utilization of material input in both samples; the reason for this inefficiency is that firms tend to operate in the increasing returns to scale portion of technology set. Third, in both samples, large firms have the lowest input-specific technical inefficiencies, but the highest input-specific scale inefficiencies, compared to their small and medium-sized counterparts, and tend to suffer from decreasing returns to scale. Finally, in both samples, input-specific technical inefficiency under constant returns to scale increased during the period of the recent financial crisis, mainly due to the augmentation in scale inefficiency.

     

基于Lasso+SVM的制造业上市公司财务风险组合预警模型

根据组合预测思想构建了基于Lasso+SVM的制造业上市公司财务风险组合预警模型,包括串联型组合和信息融合型组合两种,并选取22个财务指标建立了财务预警指标体系,对我国86家制造业上市公司的财务状况进行了预测,还与单一风险预警模型预测效果进行了比较,结果发现:财务风险组合预警模型的预测效果明显高于单一预警模型,用第t-1年的财务数据进行预测的准确率达到了95%以上;串联型组合预警模型的预测效果最优,用第t-1和t-2年的财务数据进行预测的准确率分别达到了100%和90%.     

中国股票市场横截面收益率的可预测性研究——兼与美国对比

本文旨在检验中国股票市场横截面收益的可预测性。我们选取了15个公司层面的特征指标作为变量,现有文献已经发现这些指标在美国股票市场上具有预测横截面股票收益的能力。我们检验这些变量在中国股票市场是否可以用来预测股票收益,样本的时间区间为1996~2015年。我们发现这些变量在中国股票市场对股票横截面收益的预测能力是相对较弱的。我们对中国股票市场的弱可预测性提出了两种可能的解释:其一,可能是收益预测因子在中国股票市场中的同质性比在美国股票市场中更强;其二,在中国股票市场中股票价格的无效率程度比较高。两种解释我们都找到了实证依据来支撑。     

基于ARMA模型的股价分析与预测的实证研究

利用ARMA模型对招商银行(600036)的股票日开盘价(2010/10/13-2011/4/8)数据进行分析,并预测出未来3天(2011/4/11-2011/4/13)的股票开盘价数据.与实际数据相对照,模型预测误差小,说明ARMA模型非常适合于短期预测.     

A semiparametric Bayesian approach to the analysis of financial time series with applications to value at risk estimation

GARCH models are commonly used for describing, estimating and predicting the dynamics of financial returns. Here, we relax the usual parametric distributional assumptions of GARCH models and develop a Bayesian semiparametric approach based on modeling the innovations using the class of scale mixtures of Gaussian distributions with a Dirichlet process prior on the mixing distribution. The proposed specification allows for greater flexibility in capturing the usual patterns observed in financial returns. It is also shown how to undertake Bayesian prediction of the Value at Risk (VaR). The performance of the proposed semiparametric method is illustrated using simulated and real data from the Hang Seng Index (HSI) and Bombay Stock Exchange index (BSE30).     

On interval portfolio selection problem

The future returns of each securities cannot be correctly reflected by the data in the past, therefore the expert’s judgements and experiences should be considered to estimate the security returns for the future. In this paper, we propose an interval portfolio selection model in which both the returns and the risks of assets are defined as intervals. By using interval and convex analysis, we solve this model and get the noninferior solution. Finally, an example is given to illustrate our results. The interval portfolio selection model improves and generalizes the Markowitz’s mean-variance model and the results of Deng et al. (Eur J Oper Res 166(1):278–292, 2005).     

省域审计供求关系与审计质量——基于审计投入的中介效应视角

文章基于我国上市公司年度样本,利用审计工时数据研究探索审计市场供需不平衡对审计质量的影响作用机制。结果表明,审计投入在事务所“异常”供给与审计质量间起中介作用,具体而言,审计投入在Big4事务所“异常”供给对审计质量的影响中发挥了完全中介效应,在Next6和Small事务所“异常”供给对审计质量的影响中发挥了部分中介效应。文章丰富了审计质量相关研究,并为深入分析审计质量影响因素的路径机制提供了一些经验证据。     

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.     

中国股市大公司股票与小公司股票收益关系的实证研究

对中国股市的大公司股票与小公司股票的价格与收益关系进行了实证研究,结果表明大公司股票与小公司股票的收益无论在牛市阶段还是熊市阶段都存在较高的相关性;熊市阶段大公司股票收益的自相关程度最高,存在一定趋势性.大公司股票与小公司股票的价格序列是单位根的,但不是协整的,二者的收益序列是稳定的,在牛市阶段和熊市阶段大公司股票与小公司股票收益之间存在双向的领先—滞后后关系.     

投资者情绪和市场利率对证券市场指数收益影响特点的动态刻画

本文基于2006年10月到2015年6月市场层面的投资者情绪和上证综指收益率,刻画了投资者情绪和市场利率对证券市场指数收益率的影响。首先,本文通过误差修正模型研究了短期层面投资者情绪对证券市场收益的影响特点,补充了以往在长期层面和整体收益水平上投资者情绪对市场收益影响的研究。由于市场层面的投资者情绪会受到宏观政策影响,之后本文将市场利率作为政策因素,通过分位数回归分析了不同市场收益水平下,市场利率和剔除了宏观政策因素的投资者情绪对市场收益的影响。研究结果表明:投资者情绪和证券市场收益之间的关系在短期层面上更为显著;当我国的证券市场环境处于“牛市”时,市场利率和投资者情绪均会对证券市场指数收益产生显著的影响,且随着市场收益水平的逐步上升,市场利率的反向作用和投资者情绪的正向作用均会逐渐加强。