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Earnings warnings : market reaction and management motivationSupattarakul, Somchai 25 July 2011 (has links)
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The relationship between stock returns and the past performance of tourism industry firms in the United States: empirical evidence and implications.January 2003 (has links)
Zhang Minye. / Thesis submitted in: November 2002. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2003. / Includes bibliographical references (leaves 148-152). / Abstracts in English and Chinese. / Chapter CHAPTER 1: --- INTRODUCTION --- p.1 / Chapter 1.1 --- Overview --- p.1 / Chapter 1.2 --- Thesis Outline --- p.7 / Chapter CHAPTER2: --- TOURISM INDUSTRY AND TOURISM STOCKS --- p.9 / Chapter 2.1 --- Definitions --- p.9 / Chapter 2.2 --- Tourism Industry and Stocks in the U.S --- p.10 / Chapter 2.2.1 --- Introduction --- p.10 / Chapter 2.2.3 --- Financial Problems --- p.14 / Chapter 2.3 --- Mean-Variance Analysis and Fama-French Three- Factor Risk-adjusted Performance of Tourism Stocks in the U.S. (From 1990 to 2000) --- p.17 / Chapter 2.3.1 --- The Comparison between Tourism Stocks and Market Portfolio in the U.S --- p.18 / Chapter 2.3.2 --- Fama-French Three-factor Regression and Risk-adjusted Performance --- p.22 / Chapter 2.3.3 --- Explanations of High Systematic Risk and undervalued performance in Tourism Industry and Tourism Stocks --- p.27 / Chapter CHAPTER3: --- LITERATURE REVIEW --- p.31 / Chapter 3.1 --- Anomalies in average stock returns and Fama- French three-factor model --- p.31 / Chapter 3.2 --- Explanations for predictability of stock returnsin different horizons --- p.34 / Chapter 3.3 --- "Literature related to past trading volume, past earnings data, firm size, and industry effect" --- p.40 / Chapter CHAPTER 4: --- MOTIVATIONS AND RESEARCH QUESTIONS --- p.44 / Chapter 4.1 --- Motivations --- p.44 / Chapter 4.2 --- Research Questions --- p.48 / Chapter 4.3 --- Hypotheses --- p.51 / Chapter CHAPTER 5: --- RESEARCH METHODOLOGY AND RESULTS --- p.57 / Chapter 5.1 --- Research Methodology --- p.57 / Chapter 5.1.1 --- Samples and Data Selection --- p.57 / Chapter 5.1.2 --- Research Design --- p.58 / Chapter 5.1.3 --- Summary Statistics of Price and Earning Strategies --- p.62 / Chapter 5.2 --- Results for Short-term Price Contrarian Strategies --- p.65 / Chapter 5.2.1 --- Price Contrarian Strategies for Tourism Portfolio and Market Portfolio --- p.66 / Chapter 5.2.2 --- Volume-Based Price Contrarian Strategy for Tourism Portfolio and Market Portfolio --- p.68 / Chapter 5.2.3 --- Size-Based Price Contrarian Strategy for Tourism Portfolio and Market Portfolio --- p.72 / Chapter 5.2.5 --- Lead-lag Hypothesis --- p.78 / Chapter 5.2.6 --- Section Summary --- p.85 / Chapter 5.3 --- Results for Intermediate- and Long-term Price Momentum and Contrarian Strategies --- p.87 / Chapter 5.3.1 --- Basic Price and Earning Momentum Strategies for Tourism Portfolio and Market Portfolio --- p.89 / Chapter A. --- Price Momentum and Overreaction Hypothesis --- p.89 / Chapter B. --- Earning Momentum and underreaction hypothesis --- p.96 / Chapter C. --- Subsection summary --- p.100 / Chapter 5.3.2 --- Volume-Based Price and Earning Momentum Strategies for Tourism Portfolio and Market Portfolio --- p.105 / Chapter A. --- Volume-Based Price Momentum --- p.105 / Chapter B. --- Volume-Based Earning Momentum --- p.111 / Chapter C. --- Subsection summary --- p.115 / Chapter 5.3.3 --- Size-Based Price and Earning Momentum Strategy for Tourism Portfolio and Market Portfolio --- p.116 / Chapter A. --- Size-Based Price Momentum --- p.116 / Chapter B. --- Size-Based Earning Momentum --- p.121 / Chapter C. --- Subsection summary --- p.125 / Chapter 5.3.4 --- Returns of Risk-Adjusted Momentum Strategies for Tourism Portfolio --- p.127 / Chapter 5.3.5 --- Section Summary --- p.130 / Chapter CHAPTER 6: --- CONCLUSIONS --- p.133 / Chapter A. --- Main Results and Discussions --- p.133 / Chapter B. --- Contributions and Suggestions --- p.143 / Chapter C. --- Limitations and Future Research --- p.146 / REFERENCES --- p.148 / APPENDIX --- p.153 / Appendix 1: Tourism Industry SIC Code Description --- p.153 / Appendix 2: Tourism Stock Sample List --- p.156
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Estimating market values for non-publicly-traded U.S. life insurersZhao, Liyan 28 August 2008 (has links)
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Volume and Performance of Convertible Preferred Stocks Used in Mergers: 1968-1984Nijim, Monther M. 05 1900 (has links)
This study provides information about convertible preferreds generally and, in particular, those used in financing mergers during the period 1968-1984. Specifically, the following topics are examined: (1) traditional corporate motives for the use of convertible preferreds as a financing means in mergers and acquisitions, (2) annual data about convertible preferreds' issuance by volume and purpose for the period 1968-1984, (3) average annual returns of merger-related convertible preferreds and average annual returns of common stock of the same companies for the period 1968-1980, (4) performance of convertible preferreds in relation to the market in general, and (5) the future of convertible preferreds as a financing instrument in merger activity.
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The Relationship Between an Industry Average Beta Coefficient and Price Elasticity of DemandJoslyn-Battaglia, Kari 12 1900 (has links)
The price elasticity of demand coefficient for a good or service is a measure of the sensitivity, or responsiveness, of the quantity demanded of a product to changes in the price of that product. The price elasticity of demand coefficients were generated for goods and services in nine different industries for the years 1972 to 1984. A simple linear demand function was employed, using the changes in the Consumer Price Index as a proxy for changes in price and Personal Consumption Expenditures, taken from the National Income and Product Accounts, as a proxy for quantity. Beta measures the sensitivity, or responsiveness, of a stock to the market. An industry average beta coefficient was generated for each of the nine industries over the time period, using the beta coefficients published by Value Line for firms which met certain criteria. In order to test the relationship between the price elasticity of demand and an industry average beta coefficient, a simple regression was performed using the beta coefficient as the dependent variable and the price elasticity of demand coefficient as the independent variable. The results broke down into 3 basic categories: those industries for which there seemed to be no relationship, those industries where there was a fairly strong probability that a relationship exists and the price elasticity of demand explains at least part of the variation in beta coefficients, and those industries where there was a very high probability that a relationship does exist and the variation in the price elasticity of demand coefficients substantially explained the variation in the industry average beta coefficients. The first category includes the food at home, tobacco, and shoe industries. The second category includes the men's clothing, the women's clothing, and the alcoholic beverages industries, and the third includes the automobile, airline, and fast-food restaurant industries.
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Intra-Industry Effects of the Ten Largest United States Bank Failures: Evidence from the Capital MarketsChoi, In Suk 12 1900 (has links)
This study examines the differential effect of each of the ten largest bank failures on shareholders' wealth of non-failed banks over the period from 1973 through 1984. It examines how contagion and information effects of major bank failures have changed over time.
FDIC policy for settling failures has important implications for system stability, and has changed over time. This study's purpose is to provide empirical evidence on the effects of FDIC policy. The FDIC's handling of the Penn Square failure signaled a policy shift and offers a unique opportunity to examine changes in market reactions to large bank failures.
The literature on the capital market effects of major bank failures provides limited evidence on the impact of bank failures and related FDIC policy. Most fail to discriminate between contagion and information effects, and conduct analysis on one (or a few) bank failure(s) in the mid-1970s using traditional event study methodology.
This study considers multivariate regression (MVRM) an appropriate methodology for bank failures which are likely to have simultaneous impact on non-failed banks. MVRM, which accounts for contemporaneous cross-sectional dependence of residuals, has three advantages over standard residual analysis: no "event clustering" problem, multiple hypotheses tests, and computational efficiency. This study uses daily stock-return data for fifty-one non-failed commercial banks. For each bank failure, the non-failed banksare grouped into three portfolios: "information-related," "large," and "small." The impact on each portfolio is tested for an average effect and joint hypotheses on excess return.
This study offers evidence on no contagion effects and lack of information effects before Penn Square, strong information effects since Penn Square, contagion effects in post-Penn Square failures, and capital market discipline on large banks since Penn Square. There has been a change in the nature of the impact of bank failures since Penn Square.
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Analyst forecast accuracy, dispersion, and stock returns before and during stock market crashes.January 2008 (has links)
Wang, Xiaolei. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2008. / Includes bibliographical references (leaves 34-39). / Abstracts in English and Chinese. / Chapter Chapter 1. --- Introduction --- p.1 / Chapter Chapter 2. --- Identification of Stock Market Crashes --- p.5 / Chapter 2.1 --- Identification Criteria --- p.7 / Chapter 2.2 --- Identification Results --- p.8 / Chapter Chapter 3. --- Data --- p.10 / Chapter 3.1 --- Data Issue for Chapter 4 --- p.10 / Chapter 3.2 --- Data Issue for Chapter 5 --- p.12 / Chapter 3.3 --- Data Issue for Chapter 6 --- p.12 / Chapter Chapter 4. --- Examination of AFE --- p.13 / Chapter 4.1 --- Definition of AFE and MAAFE --- p.13 / Chapter 4.2 --- Examination of MAAFE --- p.14 / Chapter 4.3 --- Examination of AFE by Grouping Duration --- p.15 / Chapter Chapter 5. --- Examination of AFD --- p.18 / Chapter Chapter 6. --- Examination of the Relationship between AFD and ESR --- p.22 / Chapter 6.1 --- Portfolio Strategy - Sorting by Size and Dispersion --- p.23 / Chapter 6.2 --- Portfolio Strategy - Sorting by Size and Book to Market Ratio --- p.26 / Chapter 6.3 --- Fama-French Time Series Regression Test (Three-Factor Model) --- p.28 / Chapter 6.4 --- Fama-French Time Series Regression Test (Three-Factor Model with Dispersion on the Right Hand Side) --- p.30 / Chapter 6.5 --- Introduction of a Nonlinear Form of AFD to the Fama-French Model --- p.31 / Chapter Chapter 7. --- Conclusions --- p.32 / References --- p.34 / Appendix Table I to Table XVI --- p.40-55 / Figure I to Figure VI --- p.56-61
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The potage of Chinese stocks: Strengths and weaknesses for United States investorsSrivastava, Shubhi 01 January 2007 (has links)
The thesis examined the differences between the Chinese market, a fast-growing emerging market, and that of the United States, a well-known developed market. In order to understand the overall performance of the Chinese stock market, the research compared the risk and returns characteristics of Chinese stock markets using the S & P 500 Index for the 2000-2005 period. Findings show that significant differences exist between the Chinese and the U.S. markets. The thesis also attempted to identify the characteristics of the Chinese markets that hinder their efficiency.
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