行业视角下中国上市公司外汇风险暴露研究——基于事件研究法的经验分析

文章基于事件研究法,通过选取2005年人民币"汇改"及2010年"汇改"重启两次关键事件,考察了其对我国深市13个行业指数外汇风险暴露的影响。结果表明:在"汇改"事件窗口中,13个行业中共11个行业表现出显著的外汇风险暴露,其中交通运输、房地产等行业收益率受到"汇改"事件的正向冲击,而制造业、金融及保险等行业收益率受到负向冲击;而在"汇改"重启事件中,由于汇率波动幅度相对较低、上市公司加强汇率避险等原因,13个行业中仅7个行业表现出外汇风险暴露。     

熊市中我国少数股票暴涨的原因探析--基于2010-2012年沪市涨幅前20名的股票实证分析

利用 Stata12、Excel 软件对2010-2012年熊市中的暴涨股票进行多元回归分析,结果显示：机构投资者在熊市中持股量越大,越有利于暴涨股票获取超额收益;个股换手率越高,流通股数越少,预期市盈率越低,暴涨股票越易于获取超额收益率,对此国家必须加强对股市的监管力度。     

对企业全面预算管理实施效果的经济评价——基于湘钢集团的研究

在全面预算管理方法迅速推广的背景下,对企业全面预算管理实施效果进行经济性评价很有必要。本文以湘钢集团实施的全面预算管理为例,详细介绍了预算管理经济性评价的基本思路和方法,以期对企业加强全面预算管理工作有所帮助,另外,警示企业,全面预算管理并非万能良方。     

中国经济转型期城镇少数民族教育收益率的实证研究

文章分别使用了OLS方法和分位回归技术,考察了1995—2007年间中国城镇少数民族教育收益率的总体水平及其长期变化趋势,并将之与汉族进行了比较,发现在经济转型期,中国城镇居民教育收益率总体上呈逐年上升趋势,少数民族与汉族之间的教育收益率没有显著差异。政策的力量与市场的力量有机结合、相互叠加,是转型时期中国城镇少数民族的地位并没有发生逆转的重要原因。与汉族相同,少数民族的教育收益率随着收入分位点提高而逐渐减小,即收入水平越高,教育收益率越低。     

在校工作经验对教育投资回报的影响——以哈尔滨市劳动力市场问卷调查为例

传统明瑟收入函数中收入取决于个人受教育程度、潜在市场工作经验和潜在市场工作经验平方项,其中受教育程度由受教育年限代表,不包含在校读书期间工作经验,然而,学生在毕业前往往能积累一定工作经验.因此,教育收益估计值包含了在校工作经验收益,导致教育收益估计值存在偏差.为了消除教育收益率估计偏差,使用哈尔滨市就业市场问卷调查数据,估算了两个收入方程——含在校工作经验变量的收入方程和不含有在校工作经验变量的收入方程.估算结果显示,后者较前者在教育投资回报系数上高出28%-44%(取决于对能力偏差的控制程度),这些结果表明传统明瑟收入函数过分夸大了个人受教育程度对收入的影响.     

光滑暧昧模型下的不透明交易和管制措施研究

本文假定透明交易者对额外投资机会回报率的标准差(方差,投资风险)存在暧昧,这种认知暧昧性抑制了透明交易者的投资行为,会导致风险资产溢价过高及社会福利损失.透明交易者是暧昧厌恶的投资者,其投资决策依据光滑暧昧厌恶模型,需求函数呈现连续且光滑的特征.而不透明交易者,通过支付一定的信息获取成本获得私有信息而具有信息优势,他们是标准的风险厌恶的投资者.通过构建理性预期均衡,本文的研究发现:初始资产严格为正的透明交易者将获得严格为正的超额收益;提高信息获取成本将减少不透明交易者的比例,从而增加风险资产溢价,降低福利水平,因而不是一项好的管制措施;而旨在提高市场透明度降低交易者暧昧性的举措总有利于提高福利水平.     

生产还是消费——中国股市生产资本资产定价模型实证检验

生产资本资产定价模型从企业利润最大化角度出发,推出资产的均衡价格.相较于消费资本资产定价模型,生产资本资产定价模型能更好的满足信息完全和决策者理性的假设条件.本文从生产资本资产定价模型出发,利用现值模型将生产的系统性风险因子,即生产的贝塔因子分解为现金流贝塔和折现率贝塔,并采用社会总投资和股市数据进行实证检验.本文发现生产-现金流贝塔是中国股市的重要定价因子,可较好地解释股权溢价的截面差异.相比之下,消费资本资产定价模型对不同资产之间风险溢价的解释能力较弱.     

Estimation of firm-specific technological bias,technical change and total factor productivity growth: a dual approach

This paper deals with modeling firm-specific technical change (TC), and technological biases (inputs and scale) in estimating total factor productivity (TFP) growth. Several dual parametric econometric models are used for this purpose. We examine robustness of TFP growth and TC among competing models. These models include the traditional time trend (TT) model and the general index (GI) model. The TT and the GI models are generalized to accommodate firm-specific TC and technological bias (in inputs and output). Both nested and non-nested tests are used to select the appropriate models. Firm-level panel data from the Japanese chemical industry during 1968- 1987 is used as an application.     

LOG-PERIODOGRAM ESTIMATION OF LONG MEMORY VOLATILITY DEPENDENCIES WITH CONDITIONALLY HEAVY TAILED RETURNS

ABSTRACT

Many recent papers have used semiparametric methods, especially the log-periodogram regression, to detect and estimate long memory in the volatility of asset returns. In these papers, the volatility is proxied by measures such as squared, log-squared, and absolute returns. While the evidence for the existence of long memory is strong using any of these measures, the actual long memory parameter estimates can be sensitive to which measure is used. In Monte-Carlo simulations, I find that if the data is conditionally leptokurtic, the log-periodogram regression estimator using squared returns has a large downward bias, which is avoided by using other volatility measures. In United States stock return data, I find that squared returns give much lower estimates of the long memory parameter than the alternative volatility measures, which is consistent with the simulation results. I conclude that researchers should avoid using the squared returns in the semiparametric estimation of long memory volatility dependencies.     

z Test for the significance of the mean of a stable probability distribution with 1<α≤2

The analysis of data using a stable probability distribution with tail parameter α<2 (sometimes called a Pareto–Levy distribution) seems to have been avoided in the past in part because of the lack of a significance test for the mean, even though it appears to be the correct distribution to use for describing returns in the financial markets. A z test for the significance of the mean of a stable distribution with tail parameter 1<α≤2 is defined. Tables are calculated and displayed for the 5% and 1% significance levels for a range of tail and skew parameters α and β. Through the use of maximum likelihood estimates, the test becomes a practical tool even when α and β are not that accurately determined. As an example, the z test is applied to the daily closing prices for the Dow Jones Industrial average from 2 January 1940 to 19 March 2010.