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An empirical analysis of press monitoring in China's publicly traded companies.January 2008 (has links)
Yin, Xiani. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2008. / Includes bibliographical references (leaves 58-59). / Abstracts in English and Chinese. / ABSTRACT --- p.ii / 摘要 --- p.iii / ACKNOWLEDGEMENTS --- p.iv / ABSTRACT --- p.ii / Chapter Chapter 1. --- Introduction --- p.8 / Chapter Chapter 2. --- Literature Review --- p.14 / Chapter Chapter 3. --- Institutional Background of the Political Control of Chinese Media --- p.19 / Chapter Chapter 4. --- Data and Sample Selection --- p.24 / Chapter 4.1 --- Data source --- p.24 / Chapter 4.2 --- Sample selection --- p.25 / Chapter 4.3 --- News collection --- p.28 / Chapter Chapter 5. --- Summary Statistics --- p.29 / Chapter Chapter 6. --- Methodology --- p.33 / Chapter 6.1 --- Event study --- p.33 / Chapter 6.2 --- Using CAR to calculate the overall market response after earnings announcement --- p.36 / Chapter 6.3 --- Measuring announcement date effects on stock performances --- p.36 / Chapter 6.4 --- Measuring news effect using CAR and Statistical Inference --- p.37 / Chapter Chapter 7. --- Empirical Results --- p.39 / Chapter 7.2 --- Overall market response after the earnings announcement --- p.42 / Chapter 7.3 --- Market reaction to official earnings announcements --- p.43 / Chapter 7.4 --- Market reaction to news report ´ؤ event study --- p.44 / Chapter 7.5 --- Differentiate higher circulation news effects on the market from lower circulation news --- p.47 / Chapter 7.6 --- Differentiate regional publications news effects on the market from national publications news --- p.48 / Chapter 7.7 --- Relationship between the number of news items and Cumulative Abnormal Return --- p.49 / Chapter 7.8 --- Relationship between “news influence coefficient´ح and Cumulative Abnormal Return: --- p.51 / Chapter 7.9 --- "Relationship between “news influence coefficient´ح, CAR, and number of restructuring activities in the second year" --- p.53 / Chapter 7.10 --- "Relationship between the number of restructuring activities, CAR, different news influence coefficient, and the third year ROE change" --- p.55 / Chapter Chapter 8. --- Conclusion --- p.57 / Tables --- p.61 / Table 1 Summary Statistics on Basic Information of the Sample --- p.61 / Table 2 Summary Statistics on ROE Change --- p.61 / Table 3 Two-sample Mean Comparison Test of the Earnings Performance Between the Subgroup with Negative News and the Subgroup Without Negative News --- p.62 / Table 4 Statistics about the number of restructuring activities of the companies with negative news --- p.63 / Table 5 Daily Average CAR over Different Periods --- p.64 / Table 6 Two-sample Mean Comparison Test --- p.65 / Table 7 Average Abnormal Returns From 3 Days Before Announcement to 10 Days After Announcement --- p.66 / Table 8 Abnormal Returns on the First Headline News Date and First Negative News Date --- p.67 / Table 9 Cumulative Abnormal Returns 10 Days After the First Headline News and First Negative News in a Clean Comparison --- p.68 / Table 10 Cumulative Abnormal Returns 10 Days After the First Headline News and First Negative News --- p.69 / Table 11 Comparisons of the CAR Between Higher and Lower Circulation News --- p.71 / Table 12 Comparisons of CAR Between Regional and National First Headline News --- p.72 / Table 13 Linear Regression Results With Dummy Variables --- p.73 / Table 14 Linear Regression Results with Number of News Items --- p.77 / Table 15 Linear Regression Results With “news influence coefficient´ح --- p.80 / Table 16 Poisson Regression Results with Number of News --- p.84 / Table 17 Linear Regression Results with Number of News --- p.86 / Table 18 Final Event Study Results --- p.88 / "Figure 1: Average CAR across Sample over (-3, 90) Days" --- p.92 / Appendix 1: Sample Companies --- p.93 / Appendix 2: Record of News Reports for Each Firm --- p.96 / Appendix 3: Number of Restructuring Activities During the Second Year --- p.99
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