Please use this identifier to cite or link to this item: https://ah.lib.nccu.edu.tw/handle/140.119/114769
題名: Disaggregated Earnings Components as Explanatory Variables for Returns: The Case of Long Return Intervals
作者: Ohlson, James A.
Peng, Huoshu
關鍵詞: Aggregated earnings ; Earnings components ; Returns ; Operating cash flows ; Accruals
日期: May-2007
上傳時間: 15-Nov-2017
摘要: This study provides the evidence in Taiwan that the association between earnings and returns increases as the return interval expands, indicating that the ”measurement errors” in earnings could be minimized or even eliminated over long periods of time. Further decomposition of the ”bottom line” earnings into different components enhances the explanatory power of the model, implying that the analysis looking into the components of earnings is worthwhile. When earnings are decomposed into operating cash flows and accounting accruals, all their coefficients are significant, no matter short-term or long-term intervals. It shows that investors pay significant attention to cash flow information as well as accounting accrual information. When the accounting accruals are further divided into nondiscretionary accruals and discretionary accruals, the coefficients of discretionary accruals stand still as positive even in the long return intervals (e.g., ten-year return intervals), revealing that the discretionary accruals are not transitory in nature. The findings are robust to different assumptions of interest rates, different measures of cash flows and discretionary accruals, and dropping of outliers. Similar tests could be done for other stock markets to check the robustness of the model. And the traditional ”association studies” could be reworked using long-term intervals to see if the short-term association studies` findings still hold.
關聯: 會計評論, 45_s, 1-24
資料類型: article
DOI: http://dx.doi.org/10.6552/JOAR.2007.45.s.1
Appears in Collections:期刊論文

Files in This Item:
File Description SizeFormat
45_s-1.pdf831.68 kBAdobe PDF2View/Open
Show full item record

Google ScholarTM

Check

Altmetric

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.