激励制度创新与国有企业改革深化

深化国有企业改革既要建立对经理人员的激励机制,也需要建立对员工的激励机制。年薪制、股票期权制、管理层收购等激励制度已在我国国有企业改革中试行与实践,还应实施包括员工持股计划在内的股票期权计划和货币期权计划。     

我国股市中的过度反应和反应不足现象实证分析

随着证券市场中越来越多的异常现象的出现,传统的有效市场假说正不断受到质疑,其中又以股市中的过度反应和反应不足现象最为突出.该文从行为金融、统计、会计学等相关理论出发,对过度反应与反应不足的形成原因、表现、影响及应该采取的相应对策做些探讨与分析.     

透视市盈率

从三个不同层次分析了影响市盈率的因素 ,指出评价一只股票是否有投资价值 ,不仅要看它本身的市盈率 ,而且要与同行业其它公司的市盈率相比较 ,更要与企业的未来发展相联系。选择一个投资对象 ,不仅要看它现在能创造多少利润 ,而且要分析它将来的发展空间 ,更要重视其作为上市公司的“壳资源”的价值及人们的心理预期     

关于完善我国证券市场监管体系的思考

目前中国证券市场监管体系存在监管主体职能不强、监管效率低下水平不高、自律 管理有名无实、证券市场监管法律法规不健全及操作性差等问题,亟需借鉴美国等发达证券市场 的经验,从多方面加以完善,如建立多层次的证券监督体系、加强自律管理、健全配套规则和法 制、健全上市公司治理结构、建立完善的信息披露制度等。     

具有奖励机制与再保险安排的最优保险合约设计

在保险合约中引入奖励机制可以使投保人动态参与到保险合约中,赋予了投保人在面对索赔事件时是否执行索赔的可选择权,改变了传统保险合约中投保人执行索赔的单一权利,但却增加了保险人潜在的流动性风险。保险合约中再保险的安排则可以对冲由于奖励机制产生的潜在流动性风险,进一步分散保险人的风险,有助于保险人稳健经营。基于此,通过建立具有红利奖励机制与再保险安排的最优保险合约设计模型,最终求解得到最优保险合约是具有最优免赔额形式的保险合约。利用算例研究方法进行建模,研究结果显示,最优保险合约中的最优免赔额与奖励机制中的红利奖励之间具有正向关系,保费、自留额与最优免赔额之间则存在着显著的负向关系。     

资本市场开放与公司内部控制质量——基于“沪港通”的证据

以中国“沪港通”交易制度的实施为政策背景,采用多时点双重差分模型,考察资本市场开放对标的公司内部控制质量的影响,研究发现,“沪港通”交易制度的实施显著提升了公司的内部控制质量,在控制其他因素并经过安慰剂检验、去除A+H股影响、改变周期范围等稳健性检验后,结论依然成立。机制检验表明,“沪港通”主要通过内部和外部两种机制对公司内部控制质量产生影响,其中,内部机制是对股价波动性风险控制,外部机制是审计师声誉风险与政府部门监管。     

交易所年报问询能提升上市公司盈余质量吗？——基于深交所数据的实证分析

在上市公司公告年报后,交易所会组织专业人员对年报进行审核,并针对可能的疑问向上市公司发放年报问询函,要求公司回复并公开披露。基于这一制度背景,以深交所A股上市公司为研究对象,针对2014年至2017年间年报被问询的上市公司进行研究,发现在控制其他因素后,当年度年报被交易所问询的公司,其盈余管理程度更高、盈余质量更差,表明交易所在年报审核中是有的放矢的,关注到此类盈余质量更差的公司;同时发现,国有控股公司被问询的可能性低于非国有控股公司,表明交易所在年报问询中可能存在偏倚现象;进一步检验发现在年报被问询后,公司次年的盈余管理程度依然较高,盈余质量并未得到改善,年报问询这一非处罚性监管措施在改善盈余质量方面的监管效果有限。     

Multivariate volatility forecasts for stock market indices

Volatility forecasts aim to measure future risk and they are key inputs for financial analysis. In this study, we forecast the realized variance as an observable measure of volatility for several major international stock market indices and accounted for the different predictive information present in jump, continuous, and option-implied variance components. We allowed for volatility spillovers in different stock markets by using a multivariate modeling approach. We used heterogeneous autoregressive (HAR)-type models to obtain the forecasts. Based an out-of-sample forecast study, we show that: (i) including option-implied variances in the HAR model substantially improves the forecast accuracy, (ii) lasso-based lag selection methods do not outperform the parsimonious day-week-month lag structure of the HAR model, and (iii) cross-market spillover effects embedded in the multivariate HAR model have long-term forecasting power.     

How does news sentiment affect the states of Japanese stock return volatility?

This paper examines the impact of public news sentiment on the volatility states of firm-level returns on the Japanese Stock market. We firstly adopt a novel Markov Regime Switching Long Memory GARCH (MRS-LMGARCH), which is employed to estimate the latent volatility states of intraday stock return. By using the RavenPack Dow Jones News Analytics database, we fit discrete choice models to investigate the impact of news sentiment on changes of volatility states of the constituent stocks in the TOPIX Core 30 Index. Our findings suggest that news occurrence and sentiment, especially those of macro-economic news, are a key factor that significantly drives the volatility state of Japanese stock returns. This provides essential information for traders of the Japanese stock market to optimize their trading strategies and risk management plans to combat volatility.     

Do stock market returns predict changes to output? Evidence from a nonlinear panel data model

Recent empirical work suggests a predictive relationship between stock returns and output growth. We employ quarterly data from a panel of 27 countries to test whether stock returns as useful in predicting growth. Unlike previous research, our approach allows for the possible non-linear effect of recessions on the growth-return relationship. There is strong evidence to suggest that a linear model would be misspecified and provide potentially misleading inference. Using a switching regression approach, we find evidence that returns are most useful in predicting growth when the economy is in recession.First version received: November 2002/Final version received: April 2003This paper benefited greatly from discussions with Kalvinder Shields, Mark Harris, Pete Summers, and Vance Martin. Two anonymous referees provided useful comments on an earlier version of the paper for which we are grateful. The usual disclaimer applies to any errors and omissions. Funding from The University of Melbourne greatly assisted in the completion of this paper.