将现金流量信息与损失风险信息分离

Bin Li
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引用次数: 2

摘要

先前的文献将会计损失的弱盈余反应系数(ERC)解释为损失缺乏前瞻性信息或市场对损失的错误定价的表现。根据收益分解理论,我预测损失不仅包含有关未来现金流量的信息(即现金流量新闻),还包含有关风险的信息(即预期收益和贴现率新闻)。然而,这些信息成分抵消了估值效应,导致ERC减弱。与预测一致,我表明,在控制了有关风险的信息(主要是预期回报)之后,损失的ERC在统计上显着,当每年或在收益公告前后测量回报时,损失越大,负回报越多。此外,亏损公司的未来收益和经营性现金流将继续低迷,亏损越大,分析师对亏损年度的预测修正就越负面。我还证明,当亏损不是因为研发费用、引发运营缩减、以及不太可能转为盈利时,亏损会提供更多的负现金流信息。进一步的测试证实了我的发现在考虑未来收益漂移/逆转、预期收益和贴现率新闻的替代代理、替代测试组合和替代模型规范时的稳健性。总的来说,我的论文对损失的信息内容提供了新的见解。这篇论文被会计Suraj Srinivasan接受。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Separating Information about Cash Flows from Information about Risk in Losses
Prior literature interprets the weak earnings response coefficient (ERC) of accounting losses as a manifestation either of lack of forward-looking information in losses or of market mispricing of losses. Based on return decomposition theory, I predict that losses contain information not only about future cash flows (i.e., cash flow news) but also, about risk (i.e., expected returns and discount rate news). However, these informational components have offsetting valuation effects, resulting in a muted ERC. Consistent with the prediction, I show that, after controlling for information about risk (mainly expected returns), the ERC of losses becomes statistically significant with more negative returns for larger losses when returns are measured either annually or around earnings announcements. Moreover, loss firms will continue to have poor future earnings and operating cash flows, and larger losses are associated with more negative analyst forecast revisions in the loss-reporting year. I also document that losses provide more negative cash flow information when they are not because of research and development expensing, when they trigger operational curtailments, and when they are less likely to reverse to profits. Further tests confirm the robustness of my findings to considering future return drifts/reversals, alternative proxies for expected returns and discount rate news, alternative test portfolios, and alternative model specifications. Overall, my paper provides new insights into the information content of losses. This paper was accepted by Suraj Srinivasan, accounting.
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