大户与散户在证券市场的博弈

通过对Laffon的模型进行了改进，将散户的效用函数改成了常系数绝对风险厌恶的负指数形式。Laffon的结论为：当θ1,θ2相距不远时，大户与散户都偏好混同均衡。而改进后的模型却找到了θ1,θ2的距离在一个具体的范围内，大户与散户才都偏好混同均衡。     

高校图书馆信息服务中的信息不对称现象及对策

信息不对称理论是微观信息经济学研究的一个核心内容，它普遍存在于社会生活的各个方面，图书馆同样存在着严重的信息不对称问题。本文揭示了图书馆信息服务中存在的几种信息不对称现象，并提出了抑制信息不对称的策略。     

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。     

业财融合背景下的信息系统审计研究

在企业业财融合的背景下,信息系统审计环境发生了巨大的变化。论文旨在指出企业业财融合背景下信息系统审计环境变化对审计的影响,分析现代信息审计的新发展和新趋势,进而剖析审计变化对审计工作者带来的挑战,提出应付这些挑战的解决方案。期望从理论方面拓展和创新理论思想,从实践方面为当代信息系统审计提供新的思考和思路,强化审计的增值作用,也有助于企业对信息系统的风险进行有效的监管。     

中小企业会计信息失真原因及对策

随着社会的发展,会计信息对投资者、企业,甚至是整个国家经济都有着举足轻重的影响。但由于多种原因,当前我国中小企业会计信息失真现象普遍存在,严重影响了中小企业经营决策的制定和我国经济发展。为此,在对中小企业会计信息现状和会计信息失真主要表现及原因分析的基础上,提出了针对该现状的治理对策。     

Monitoring recessions: A Bayesian sequential quickest detection method

Monitoring business cycles faces two potentially conflicting objectives: accuracy and timeliness. To strike a balance between these dual objectives, we propose a Bayesian sequential quickest detection method to identify turning points in real time with a sequential stopping time as a solution. Using four monthly indexes of real economic activity in the United States, we evaluated the method’s real-time ability to date the past five recessions. The proposed method identified similar turning-point dates as the National Bureau of Economic Research (NBER), with no false alarms, but on average, it dated peaks four months faster and troughs 10 months faster relative to the NBER announcement. The timeliness of our method is also notable compared to the dynamic factor Markov-switching model: the average lead time was about five months when dating peaks and two months when dating troughs.     

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.     

Carrot and stick: A role for benchmark-adjusted compensation in active fund management

Investors delegating their wealth to privately informed managers face not only an intrinsic asymmetric information problem but also a potential misalignment in risk preferences. In this setting, we show that by tying fees symmetrically to the appropriate benchmark investors can tilt a fund portfolio toward their optimal risk exposure and realize nearly all the value of managers’ information. They attain these benefits despite an inherent inefficiency in the choice of the benchmark, and at no extra cost of compensating managers for exposure to relative-performance risk. Under certain conditions, benchmark-adjusted performance fees are necessary to prevent passive alternatives from dominating active management. Our results shed light on a recent debate on the appropriate fee structure of active funds in contexts of high competition from passive funds.     

Pricing, learning, and strategic behavior in a single-sale model

Summary. We analyze an infinite horizon model where a seller who owns an indivisible unit of a good for sale has incomplete information about the state of the world that determines not only the demand she faces but also her own valuation for the good. Over time, she randomly meets potential buyers who may have incentives to manipulate her learning process strategically. We show that i) the seller's incentives to post a high price and to experiment are not necessarily monotonic in the information conveyed by a buyer's rejection; and ii) as the discount factors tend to one, there are equilibria where the seller always ends up selling the good at an ex-post individually rational price. Received: January 6, 1999; revised version: July 15, 2000     

Modeling Disinterest and Dislike: A Bounded Bayesian Mixed Logit Model of the UK Market for GM Food

Mixed logit models represent a powerful discrete choice analytical model but require assumptions about the functional form of the parameter distributions. The use of unbounded distributions, such as the normal distribution, may be regarded as unsuitable where theory indicates that all are negatively affected by increases in an attribute, such as price. Bounded distributions such as the triangular and log-normal are unable to model the case where a section of the population is indifferent towards an attribute, while the remainder are negatively disposed toward it. Train and Sonnier’s bounded mixed logit model accommodates these features and is employed in this paper. A censored normal and Johnson’s S_b distribution are used to model preferences in the UK for food attributes, including price and GM technology. Bi-modal distributions are identified regarding GM food: some are unlikely to ever consume it, some are close to indifference and willing to consume at relatively small discounts while the remainder are fairly unresponsive to further price reductions.