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An application of two forecasting models for predicting price movements of a number of selected stocks in Hong Kong.January 1986 (has links)
by Lo Yat-keung & Ma Kwok-wa. / Bibliography: leaves 46-47 / Thesis (M.B.A.)--Chinese University of Hong Kong, 1986
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Discovering patterns on financial data streams. / CUHK electronic theses & dissertations collection / ProQuest dissertations and thesesJanuary 2010 (has links)
Then, we consider the patterns between news stream and time series indices stream. We first transform the news stream into a set of bursty feature (keywords) time series streams and propose three technique to study their relationship to time series index. First, we explore a Non-homogeneous Hidden Markov Model (NHMM) to predict the stock market process which takes both stock prices and news articles into consideration. Second, we propose a risk analytical model to predict the volatility of price indices by integrating news information. Finally, we devise an algorithm to detect the priming event from text and a time series index. The evaluation on real world dataset suggests the significant correlation exists between news stream and time series stream and our pattern discover algorithm can detect promising patterns from this relationship to support real world applications effectively. / We start from investigating the co-movement relationship of multiple time series. We propose techniques to study two aspects of this problem. First, we propose a co-movement model for constructing financial portfolio by analyzing and mining the co-movement patterns among two time series. Second, we presents an efficient streaming algorithm to discover leaders from multiple time series stream. Both of the algorithms are evaluated using real time series indices data and the result proves that co-movement patterns and detected leaders are promising and can support various applications including portfolio management, high frequency trading and risk management. / With the increasing amount of data in financial market, there are two types of data streams attracting a lot of research and studies, time series index stream and related news stream. In this thesis, we focus on discovering patterns from these data streams and try to answer the following challenging questions, (I) given two co-evolving time series indices, what is the co-movement dependency between them. (II) given a set of evolving time series, could we detect some leaders from them whose rise or fall impacts the behavior of many other time series? (III) could we integrate the news stream information into stock price prediction? (IV) could we integrate the news stream information into stock risk analysis? and (V) could we detect what are those events that trigger time series index movement. For each of the question, we design algorithms and address three technique issues (I) how to detect promising patterns from the noisy financial data; (II) how to update the old patterns when new data arrives in high frequency; (III) how to use the pattern to support the financial applications. / Wu, Di. / Adviser: Jeffrey Xu Pu. / Source: Dissertation Abstracts International, Volume: 73-01, Section: B, page: . / Thesis (Ph.D.)--Chinese University of Hong Kong, 2010. / Includes bibliographical references (leaves 124-131). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. [Ann Arbor, MI] : ProQuest Information and Learning, [201-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. Ann Arbor, MI : ProQuest dissertations and theses, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstract also in Chinese.
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Stock risk mining by news.January 2009 (has links)
Pan, Qi. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2009. / Includes bibliographical references (leaves 70-73). / Abstract also in Chinese. / Abstract --- p.i / Acknowledgement --- p.iii / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Main Contributions --- p.5 / Chapter 1.2 --- Structure of Thesis --- p.6 / Chapter 2 --- Related Works --- p.7 / Chapter 2.1 --- Literature Review --- p.7 / Chapter 2.1.1 --- Existing Works on Bursty Feature Idenfication --- p.9 / Chapter 2.2 --- Classification --- p.9 / Chapter 2.2.1 --- Support Vector Machine --- p.9 / Chapter 2.2.2 --- Decision Tree and C4.5 Algorithm --- p.10 / Chapter 2.3 --- PageRank and HITS Algorithm --- p.10 / Chapter 2.3.1 --- PageRank --- p.11 / Chapter 2.3.2 --- HITS --- p.11 / Chapter 2.4 --- Efficient Market Hypothesis --- p.12 / Chapter 3 --- Problem Statement --- p.14 / Chapter 3.1 --- Volatility --- p.14 / Chapter 3.2 --- Financial Model --- p.15 / Chapter 3.3 --- Problem Statement --- p.16 / Chapter 4 --- Volatility V.S. Trend Prediction --- p.18 / Chapter 5 --- Bursty Volatility Features --- p.22 / Chapter 5.1 --- ADFIDF Measure --- p.24 / Chapter 5.2 --- Bursty Volatility Features --- p.28 / Chapter 5.3 --- Bursty Volatility Features Selection --- p.29 / Chapter 6 --- Volatility Ranking --- p.32 / Chapter 6.1 --- Graph Construction --- p.32 / Chapter 6.2 --- Volatility Ranking By News --- p.35 / Chapter 7 --- Volatility Index for Stock Volatility --- p.37 / Chapter 8 --- Experiments --- p.41 / Chapter 8.1 --- Experiments for Volatility Index --- p.41 / Chapter 8.1.1 --- Effectiveness of Volatility Index --- p.42 / Chapter 8.1.2 --- Information from News --- p.42 / Chapter 8.1.3 --- Information from Market --- p.45 / Chapter 8.1.4 --- Correlation Value --- p.46 / Chapter 8.1.5 --- Bursty Feature selection --- p.47 / Chapter 8.2 --- Experiments for Ranking --- p.48 / Chapter 8.2.1 --- Ranking Quality Comparison --- p.49 / Chapter 8.2.2 --- Capturing Bursty Features --- p.51 / Chapter 8.2.3 --- The Effectiveness of Feature Rank --- p.52 / Chapter 8.2.4 --- The Effectiveness of Random Walk --- p.53 / Chapter 8.2.5 --- Combination of VbN and GARCH --- p.54 / Chapter 8.2.6 --- Ranking Result Sample --- p.56 / Chapter 9 --- Conclusion --- p.58 / Chapter A --- Most Important Features for Stocks --- p.60 / Chapter B --- Correlation Matrix of Stocks --- p.63 / Chapter C --- News Index Evaluation Result Table --- p.65 / Chapter D --- Stock Data in Experiments --- p.67 / Chapter E --- Constructed Graph --- p.68 / Bibliograph --- p.70
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Which version of the equity market timing affects capital structure, perceived mispricing or adverse selection?Chazi, Abdelaziz 08 1900 (has links)
Baker and Wurgler (2002) define a new theory of capital structure. In this theory capital structure evolves as the cumulative outcome of past attempts to time the equity market. Baker and Wurgler extend market timing theory to long-term capital structure, but their results do not clearly distinguish between the two versions of market timing: perceived mispricing and adverse selection. The main purpose of this dissertation is to empirically identify the relative importance of these two explanations. First, I retest Baker and Wurgler's theory by using insider trading as an alternative to market-to-book ratio to measure equity market timing. I also formally test the adverse selection model of the equity market timing: first by using post-issuance performance, and then by using three measures of adverse selection. The first two measures use estimates of adverse information costs based on the bid and ask prices, and the third measure is based on the close-to-offer returns. Based on received theory, a dynamic adverse selection model implies that higher adverse information costs lead to higher leverage. On the other hand, a naïve adverse selection model implies that negative inside information leads to lower leverage. The results are consistent with the equity market timing theory of capital structure. The results also indicate that a naïve, as opposed to a dynamic, adverse selection model seems to be the best explanation as to why managers time equity issues.
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The Relationship between Stock Prices and Exchange Rates in SwedenXu, Yue January 2011 (has links)
This paper empirically investigates the exchange rate effects of Swedish krona against euro (SEK/Euro) on stock prices in Sweden. The sample period for the study has been taken from March, 2001 to March, 2011 using monthly nominal exchange rate of SEK/Euro and monthly closing values of OMX Stockholm All Share (OMXPI) Index. The developed unit root test and cointegration technique have been applied for the research. It was found that both data series were nonstationary and integrated of order 1. The test result also showed there was no cointegrating relationship between stock prices and exchange rates. Further investigation into their contemporaneous relationship highlighted a statistically significant negative linear relationship between the said variables, suggesting that an appreciation of the Swedish krona against euro leads to a contemporaneous increase in the value of the Swedish stock market.
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Share price response to earnings announcements in the steel industryMartynyuk, Artem January 2012 (has links)
The purpose of the thesis is to study share price response to quarterly earnings per share (EPS) announcements in the world steel industry for the last five years (from 2007 to 2011), using the event study methodology. Moreover, the paper attempts to test share price reactions to earnings releases for yearly aggregation (pre-crisis, crisis and post-crisis periods) and countries aggregation (developed and developing countries) of sample steel companies. The research is conducted employing a sample of 30 listed companies, operating in the steel industry. The steel producers’ headquarters are situated in thirteen countries; they are traded on twelve stock markets as primary listing stock exchanges and are referred to thirteen respective indexes.The thesis uses the event study methodology in order to address the purpose of the research. This methodology provides an insight on how numerous corporate events (M&As and takeovers announcements, regulatory changings and earnings announcements) influence company’s stock prices. All the announcements were divided into two groups: “negative” announcements (Group I) and “positive” announcements (Group II). By “negative” announcements it is meant, that new actual earnings per share are smaller than earnings per share from the last quarter, and vice versa for “positive” announcements. The pattern for overall aggregation of sample companies showed the significant and expected share price response to earnings announcements for Group I only. The output for Group II was puzzling. This led to the assumption of negative market perception on the steel industry stock prices as a result of 2007-2008 financial crises. Indeed, for 2007, which was determined as a pre-crisis period for the steel industry, the share price reaction was significant for both groups of EPS announcements. However, within the two other periods (crisis period of 2008-2009 and post-crisis period of 2010-2011) significant and expected pattern was obtained only for Group I once again. The 2007 yearly aggregation comprised only twenty companies due to the data availability. This revealed the assumption, that this sample of twenty steel companies should be tested for the two other periods. However, the pattern remained the same as in the overall aggregation case. Furthermore, the sample steel companies were aggregated on countries basis. The obtained response was analogous to overall aggregation response, the only difference is that Group I reaction was more significant for developed countries than for developing counties sample.
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The Relations between News Management andStock Price-A Case Study of Soft-World GroupYu Lin, Hsin 25 August 2011 (has links)
Online game industry has not only been an emerging industry in the twentieth century, but also an industry with the largest economic scale within the digital content category. Soft-World International Corporation was the first gaming company to be listed in Taiwan in March 29th, 2001. By May 31th, 2011, more than 10 gaming companies have been listed on the GreTai Securities Market (GTSM) in Taiwan, making it one of the trading markets in the globe with the most number of gaming companies in it.
Moreover, as Korea created online games; Taiwan, Hong Kong and Macau prospered them, and China owns the largest online population, Asia has become the most active market for the online game industry in the world. Therefore, studies in online game markets have drawn the attention among local and foreign investors for the past 10 years.
In Asian markets, gaming stocks in Taiwan are being highly emphasized; meanwhile, GTSM also stresses the importance of corporate governance and investment environment. Hence, this study ¡§The Relations between News Management and Stock Price ¡V A Case Study of Soft-World Group¡¨ focuses on how gaming companies deal with news pieces. The management team will have a better understanding and control of how stock price is affected by spreading out press releases through the media and making public announcement on the Market Observation Post System. In terms of corporate governance, what are the management behaviors and ways to instantly deal with the media essential to investors who would further make comments about the company and eventually fluctuate the price?
This case study gathers and analyzes the historical news, public announcements and stock prices from the two listed companies in Taiwan¡¦s leading gaming enterprise, Soft-World Group ¡V the parent company, Soft-World and its subsidiary, Chinese Gamer .
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The Impact of Institutional Investors' Trading on Stock ReturnsChen, Yan-Hau 20 June 2002 (has links)
none
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Short selling when issuing Convertible Bonds and stock price before issuingChung, Chiao-Ling 12 June 2003 (has links)
none
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Margin Transaction,Wealth Effect and Misadjustment:An Analysis of Neutral Intervention PolicyTsai, Pual 11 July 2003 (has links)
none
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