盈余分解,价值相关性和可预测性

S. Babaie
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引用次数: 0

摘要

与净收益相比,那些组成成分具有不同质量的持续性和波动性的公司的收益组成部分更能提供信息。我们研究净收益及其组成部分是否比仅净收益具有更多的信息内容的问题。我们构建了一个模型,通过拆分盈余价值相关性和可预测性来描述成分波动性及其持久性的影响。我们研究中的分析基于德黑兰证券交易所(TSE) 2005年至2019年期间600家公司的年度观察结果。数据来源于RAHAVARD NOVIN伊朗软件和公司的财务报表。数据分析的统计检验是均值差异检验(t检验)和回归分析。当前研究的结果表明,随着盈余组成部分(销售、员工费用、其他销售、一般和管理费用以及所得税)的持续和波动性增加,盈余分解可以提高盈余的可预测性。此外,当员工费用的波动性增加时,分解盈余可以提高盈余价值相关性。由于净盈余的价值相关性在过去几十年中有所下降,本研究的结果表明,盈余分解在提高盈余价值相关性及其可预测性方面发挥了重要作用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Earnings Decomposition, Value Relevance and Predictability
Compared with net earnings, the components of earnings are more informative in companies whose components have different qualities of persistence and volatility. We examine the issue of whether net earnings together with their components have more information content than only net earnings. We construct a model to describe the effect of components volatility and their persistence through disaggregation of earnings value relevance and predictability. The analyses in our study are based on 600 firm-year observations in Tehran Stock Exchange (TSE) for the period 20052019. Data are derived from RAHAVARD NOVIN Iranian software and firms' financial statements. The statistical tests for data analyses are the difference of means test (t-test) and regression analyses. The results of the current study indicate that as the persistence and volatility of selected components of earnings (sales, employee expenses, other selling, general and administrative expenses, and income taxes) increase, earnings disaggregation can improve earnings predictability. Furthermore, when the volatility of employee expenses increases, disaggregated earnings can improve earnings value relevance. As the value relevance of net earnings has been declined over the past decades, the results of the current study suggest that earnings disaggregation plays a major role in improving earnings value relevance and their predictability.
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