产业政策会影响上市公司盈余预告自愿披露吗？——基于政策信号传递效应视角

产业政策是政府资源配置的导向信号,对上市公司管理层信息披露行为具有重要影响。基于2006—2019年我国A股上市公司自愿性盈余预告数据,实证检验了产业政策引导管理层盈余预告自愿披露的作用路径。研究发现,产业政策信号传递具有引导管理层盈余预告自愿披露的积极作用;且在市场化程度较高的地区,以及分析师关注度较高的企业,该积极作用更显著。进一步研究发现,管理层顺应产业政策导向主动披露盈余预告能够引起更为正向的市场反应,获取超额收益。因此,政府应关注产业政策信号传递在信息市场中的正向作用,以及区域差异性和分析师行为对这一过程的影响,从而使得产业政策实施效果最优化。     

嵌入知识的综合集成预测方法及其在企业收益额预测中的应用

针对企业收益额预测，提出了一种嵌入知识的综合集成预测方法。首先，基于系统思想，提出了嵌入知识的人-机交互式综合集成预测方法框架；进而重点介绍了集成预测方法中的信息预处理、预测模型选择、效果检验等关键子模块；最后，以某公司的收益额预测为例，验证了其有效性。     

A Reality Check for Data Snooping

Data snooping occurs when a given set of data is used more than once for purposes of inference or model selection. When such data reuse occurs, there is always the possibility that any satisfactory results obtained may simply be due to chance rather than to any merit inherent in the method yielding the results. This problem is practically unavoidable in the analysis of time‐series data, as typically only a single history measuring a given phenomenon of interest is available for analysis. It is widely acknowledged by empirical researchers that data snooping is a dangerous practice to be avoided, but in fact it is endemic. The main problem has been a lack of sufficiently simple practical methods capable of assessing the potential dangers of data snooping in a given situation. Our purpose here is to provide such methods by specifying a straightforward procedure for testing the null hypothesis that the best model encountered in a specification search has no predictive superiority over a given benchmark model. This permits data snooping to be undertaken with some degree of confidence that one will not mistake results that could have been generated by chance for genuinely good results.     

汉英词典例证不足略观

词典是学习者学习外语、查阅资料中必不可少的工具，为读者提供充足的例证来理解并表达准确的含意。词典例证具有 很重要的功能，包括反映基本语义信息、反映概念信息、反映文化信息、规范英语、指导写作等方面，但是例证不足也会给读者 带来很大误导。以姚小平《汉英词典》第三版为例，从例证与释义的衔接不当、例证语体信息的不明确、例证不足及例证译文的 不准确四方面具体分析，重点结合百科知识，对比研究汉英词典中例证的不足之处，以期为汉英词典的例证准确性做出微薄贡 献。     

Accuracy of Numerical Solutions Using the Euler Equation Residuals

This paper is concerned with asymptotic properties on the accuracy of numerical solutions. It is shown that the approximation error of the policy function is of the same order of magnitude as the size of the Euler equation residuals. Moreover, for bounding this approximation error the most relevant parameters are the discount factor and the curvature of the return function. These findings provide theoretical foundations for the construction of tests to assess the performance of alternative computational methods.