创业板投资者情绪及其收益率相关性研究

本文采用向量自回归模型VAR方法分别研究了我国主板市场与创业板市场投资者情绪与收益率之间影响是系。研究发现我国主板市场中投资者情绪对收益率有显著影响,而收益率对投资者情绪无显著影响;而创业板市场表现不同,投资者情绪对收益率无显著相关影响。研究表明:出现上述现象的原因是由于两市场的投资者结构存在差异,创业板市场投资者更成熟、创业板政策及监管更为全面等原因。     

机构投资者参与公司治理的决策研究——基于绝对净收益的视角

为了改善我国上市公司治理,提高上市公司的绩效并促进股票市场的健康发展,政府监管部门出台了一系列促进机构投资发展政策和措施。机构投资者得到了巨大的发展。但是,机构投资者的发展对改善上市公司治理的作用受到质疑。本文通过构建理论模型,采用监督绝对净收益的标准分析机构投资者参与公司治理的决策情况。研究发现,机构投资者监督绝对净收益大于零,就会参与到公司治理中。     

中国农村人力资本收益率研究

本项研究依据的数据资料是“中国人力资本投资与城乡就业相关性研究”课题组在 2 0 0 2年 7月至 2 0 0 3年 1月对全国 1 5省市进行的问卷调查。在对数据进行分析的基础上 ,使用计量经济学的相关模型估计了中国农村不同形式人力资本收益率。     

浅谈项目评价指标--内含报酬率的修正

内含报酬率的经济涵义是在计算期内项目的收益率,它反映了项目的获利能力。但目前教科书中介绍的内含报酬率存在着某些缺陷与不合理,有必要对其不合理及缺陷之处作一些修正。     

Automatic variance ratio test under conditional heteroskedasticity

An extensive Monte Carlo experiment is conducted to evaluate small sample properties of the automatic variance ratio test under conditional heteroskedasticity. It is found that the test shows serious size distortion in small samples. For improved small sample performance, this paper proposes the use of wild bootstrap. When wild bootstrapped, the automatic variance ratio test shows no size distortion, and it has power substantially higher than its competitors such as the Chen–Deo test and wild bootstrap Chow–Denning test.     

对冲基金风险收益特征的实证分析

对冲基金是一种高风险的投资工具.本文采用马科维茨的资本资产定价理论及相关的投资组合风险收益分析工具,对对冲基金的收益和风险特征进行了分析,结果表明:(1)对冲基金全行业平均收益率高于标准普尔和全球债券指数收益率;(2)对冲基金收益率的时间序列不服从正态分布,其三维和四维的分布特征表明其历史收益率虽然出现异常波动的概率较低,但一旦出现,损失很大;(3)对冲基金收益率与代表传统投资工具的股票、债券收益率之间没有稳定的相关性,对冲基金在牛市和熊市都能获得绝对收益.因此,在不考虑数据偏差的条件下,投资对冲基金期望收益更高,但并不比传统投资工具"危险".     

Peer effect on dividends and return comovement

This study investigates the stock return comovement of dividend-paying and nonpaying firms induced by peer effects of dividend payout policies. We consider peer effect as a channel that links a firm’s dividend initiation to firms that did not change dividend status. Dividend initiation attracts investors to the industry and puts pressure on peer firms to change their dividend policy, which leads to return comovement between nonpaying peers and paying firms. Using matched peer firms that resemble dividend initiators, we find that return comovement can be induced through an indirect channel without changes in style or category. Excess return comovement for firms without dividends is observed with dividend payers of the market and their industries through peer influence.     

Belief-based momentum indicator and stock market return predictability

Li et al. (2022) propose a new momentum indicator that combines past returns and consistent belief information, and show that the indicator positively predicts cross-sectional stock returns. Based on the momentum indicator of Li et al. (2022), we further develop a conditional past return (CPR) indicator that additionally adds the direction information for the investors' consistent belief. We examine the effectiveness of CPR as a predictor for stock market returns. Our evidence shows that CPR significantly and positively predicts future one-month market returns. And CPR provides unique predictive information that is not related to the other popular predictors. The abundant out-of-sample evidence further supports CPR’s predictive ability. Additionally, we detect the asymmetric role of CPR in predicting market returns and find that much of the predictive ability of CPR is attributed to the interaction between the positive past returns and the positive consistent belief.     

When bad news is good news: Geopolitical risk and the cross-section of emerging market stock returns

Using a news-based gauge of geopolitical risk, we study its role in asset pricing in global emerging markets. We find that changes in risk positively predict future stock returns. The countries with the highest increase in geopolitical uncertainty outperform their counterparts with the lowest change by up to 1% per month. The anomaly is not explained by other established asset pricing effects and remains robust to many considerations. We link the observed phenomenon with investor overreaction to geopolitical news driven by the availability bias.