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|Title:||Earnings quality, analysts, institutional investors and stock price synchronicity||Authors:||Zhou, Jing||Degree:||Ph.D.||Issue Date:||2008||Abstract:||Stock price signals information to the financial market, the informativeness of stock price is always a keen topic in finance and accounting literature. Recently, attention has been directed to stock price synchronicity as a measure of stock price informativeness. The objective of this study is to examine the relationship between earnings quality (measured by a set of seven attributes: accrual quality, persistence, predictability, smoothness, value relevance, timeliness and conservatism) and stock price synchronicity. In addition, I examine with the presence of financial analysts and institutional investors, whether the relation between earnings quality and stock price synchronicity is stronger or weaker. Using 7,422 firm-year observations from 1996-2004 in the US market, I conduct the tests using the methods outlined in Fama-MacBeth (1983). The results support the hypothesis that the higher (lower) the earnings quality the lower (higher) the stock price synchronicity. The results are generally consistent with the information perspective of stock price synchronicity. I partition the full sample into analyst following/non-analyst following subsamples and high/low institutional ownership subsamples. The regression results reveal that the relation between stock price synchronicity and earnings quality is stronger for analyst following subsample (AF) and high institutional ownership (HIO) subsample, indicating that financial analysts and institutional investors reinforce the relation between earnings quality and stock price synchronicity. Overall, I find evidence that the higher (lower) earnings quality is associated with lower (higher) stock price synchronicity. This evidence suggests that earnings quality matters in the information incorporation process. I further provide evidence that two market participants, financial analysts and institutional investors reinforce the above relation.||Subjects:||Hong Kong Polytechnic University -- Dissertations.
Stock price forecasting.
|Pages:||iv, 173 leaves ; 30 cm.|
|Appears in Collections:||Thesis|
View full-text via https://theses.lib.polyu.edu.hk/handle/200/2576
Citations as of May 22, 2022
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