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INTRA-INDUSTRY INFORMATION TRANSFERS ASSOCIATED WITH MANAGEMENT EARNINGS FORECASTS.

机译:与管理收入预测相关的行业内信息转移。

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摘要

This research provides a theoretical basis for expecting a stock price impact of a firm's disclosure of changes in expected earnings on other non-disclosing firms in its industry (an information transfer) and proposes tests of the proposition that management forecasts of earnings generate such transfers. Cluster analysis procedures are used to construct homogeneous industries for which the transfer effect is hypothesized. Parametric tests are proposed that mitigate the effects of cross-sectional correlation of market model residuals within the industry. In addition, a model is formulated that seeks to explain cross-sectional differences in the magnitude of observed information transfers by economic relationships between the disclosing firm and non-disclosing industry co-members. The magnitude of the information transfer is expressed as a function of the magnitude of changes in earnings expectations of the disclosing firm, the market share variability of the reporter, and a measure of the relative diversification (homogeneity) of industry co-members. The results of empirical tests of these models fail to reject the null hypotheses for information transfer existence and relationship to the sign and magnitude of changes in earnings expectations conveyed by management forecasts (for homogenous industries as defined by cluster analysis). At the 4-digit SIC code level, the results support the hypothesis that the magnitude of information transfers is positively related to the sign and magnitude of changes in earnings expectations conveyed by management forecasts. In addition, the results support the hypothesis that the magnitude of information transfer is inversely related to the relative diversification of industry co-members. The results do not support market share variability as a determinant of the magnitude of information transfers.
机译:这项研究为预期公司披露预期收益变化对行业中其他未披露公司的股价影响(信息转移)提供了理论基础,并提出了对管理层的盈余预测产生此类转移的命题的检验。聚类分析程序用于构造假设转移效应的同质产业。建议使用参数测试来减轻行业内市场模型残差的横截面相关性的影响。此外,制定了一个模型,试图通过披露公司成员与不披露行业成员之间的经济关系来解释所观察到的信息传递幅度的横截面差异。信息传递的幅度表示为披露公司的盈利预期变化幅度,报告者的市场份额可变性以及行业成员相对多元化(同质性)的量度。这些模型的经验检验结果不能拒绝信息传递存在的零假设以及与管理预测(对于聚类分析所定义的同质行业)所传达的盈利预期变化的符号和大小的关系。在4位数的SIC代码级别,结果支持以下假设:信息传递的幅度与管理层预测传达的预期收益变化的符号和幅度成正相关。此外,结果支持以下假设:信息传递的规模与行业共同成员的相对多元化程度呈反比关系。结果不支持市场份额的可变性来决定信息传输的规模。

著录项

  • 作者

    BAGINSKI, STEPHEN PAUL.;

  • 作者单位

    University of Illinois at Urbana-Champaign.;

  • 授予单位 University of Illinois at Urbana-Champaign.;
  • 学科 Accounting.
  • 学位 Ph.D.
  • 年度 1986
  • 页码 127 p.
  • 总页数 127
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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