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1
Li, Rong-Jen. "Combined Leverage and the Volatility of Stock Prices". Thesis, North Texas State University, 1985. https://digital.library.unt.edu/ark:/67531/metadc331340/.
Testo completoAbstract (sommario):
Much has been written during the past decade to explain the relationship between financial and operating leverage and stock-price volatility. However, the relationship between combined leverage and stock-price volatility has yet to be fully explored. Mandelker and Rhee's (MR) recent study uses both operating and financial leverage in a regression (equivalent to the traditional total leverage—DTL) and shows that both types of leverage are positively associated with common stock betas. Huffman recently demonstrated that there are interactions between operating leverage and financial leverage. Therefore, MR's model could be oversimplified. This study examines the relationship between firms' combined leverage and their stock-price volatility. The study also examines industry and industry growth to see if the relationship is influenced by these factors. The question is whether DOCL is a better risk measure than DTL and whether there is an interaction between operating and financial leverage. The inferences that can be drawn from the study's results are as follows: (a) Stock risk is a function of combined leverage; (b) Industry significantly influences the relationship between stock risk and DOCL; (c) High growth increases the relationship between stock risk and DOCL; (d) Combined leverage (DOCL) is a better risk measure than total leverage (DTL). Further, the problem with the traditional total leverage measure is the omission of the interaction between DOL and DFL. This is consistent with Huffman's theory and suggests Mandelker and Rhee's model is oversimplified.
2
Wang, Hanfeng, e 王漢鋒. "Essays on stock trading volume, volatility and information". Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2007. http://hub.hku.hk/bib/B38826185.
Testo completo
3
Rahou, Amar A. M. "A generalised framework for modelling & forecasting share prices : a field study on modelling and forecasting the share prices from the banking sector". Thesis, University of South Wales, 2009. https://pure.southwales.ac.uk/en/studentthesis/a-generalised-framework-for-modelling--forecasting-share-prices(10fcca19-ff9a-4497-a0be-55f3e980cbed).html.
Testo completoAbstract (sommario):
Modelling and forecasting the stock market remains a challenge because of the high volatilities in individual stock prices and the market itself. Hence, this topic has received much attention in the literature since forecast errors represent the systematic risk faced by investors. Therefore, the ability to reliably forecast the future values of the shares would provide essential help in reducing that risk to those investors. The main aim of this research is to develop and calibrate a framework that can be used to model the daily share prices of the companies from the banking sector and hence produce informative and reliable one step-ahead forecasts using an adaptive BPNN. To this end, a novel forecasting algorithm is proposed. This algorithm proposes six steps that, when followed, possibly will lead to obtaining superior forecasting models for the share prices from the banking sector. In addition, novel technical indicators, and further information reflecting market knowledge were developed in this research so as to improve the modelling and forecasting share prices for the banking sector, alongside a novel application of the correctly identified turning points which provided an accurate assessment of the performance of the forecasting models. Furthermore, a selection of a set of inputs that are salient to financial data was identified. The research was to inform and improve share price forecasts of the banking sector. The historic open share prices for HSBC, Lloyds TSB, RBS and Barclays were used as case studies and the results give evidence to conclude that useable forecasting models can be obtained by employing the developed framework to the share prices from the banking sector in terms of the correctly identified turning points and the direction of the shares which are achieved more than 70% of the time. The empirical results show that using the market knowledge as input generally improved the modelling and forecasting of the share prices from the banking sector.
4
Ho, Yueh-Fang. "Three essays on seasoned equity offerings /". Philadelphia, Pa. : Drexel University, 2003. http://dspace.library.drexel.edu/handle/1860/251.
Testo completo
5
Parsa, Sahar. "Investors' horizon and stock prices". Thesis, Massachusetts Institute of Technology, 2011. http://hdl.handle.net/1721.1/65491.
Testo completoAbstract (sommario):
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Economics, 2011.Cataloged from PDF version of thesis.
Includes bibliographical references (p. 140-150).
This dissertation consists of three essays on the relation between investors' trading horizon and stock prices. The first chapter explores the theoretical relation between the horizon of traders and the negative externality generated by their activity on the information revealed by stock prices. The last two chapters focus on the empirical relation between institutional investors trading frequency and stock prices behaviour. The first chapter examines how short term trading impacts the aggregation of information in financial markets. I develop a model where short-term traders, in an attempt to learn about the average beliefs of future market participants, make the price relatively more noisy. This typically introduces a negative informational externality on long-term investors. I show that (i) as the horizon of the informed traders decreases, the price becomes relatively less precise; (ii) an inflow of informed traders in the market can decrease the informativeness of the price when the traders have a relatively short horizon or the market is expected to be thin in the future; (iii) finally, as rational informed short-term traders have access to an extra source of information about the future price, they end up creating more noise and a decrease in the informativeness of the price might result. Thus, paradoxically, more informed trading could lead to a less informative price. Among scholars, practitioners and policy makers, investor short-termism and high frequency trading have been associated with excess volatility in financial markets and with a disconnect between asset prices and fundamentals. Motivated by this observation, in Chapter 2 I construct a novel measure of the intrinsic frequency of trading for each of the large US institutional investors (13-F institutions) using Thomson-Reuters Institutional Holdings quarterly data for the period 1980-2005. This measure controls for the market and portfolio characteristics and identifies an investor-specific fixed effect in the frequency of trading. I then study how the composition of these fixed effects impacts stock price behavior through their forecasting role in explaining the return and the return on equity (cash flow of a company) in the short run as well as the long run. I show that (i) the securities in which investors exhibit higher intrinsic trading frequency exhibit higher volatility, but (ii) this volatility is mainly driven by the cashflow component of the security prices. Further, (iii) the prices of the securities held by investors with a higher intrinsic trading frequency do not forecast the long-run return as opposed to the securities held by investors with a lower intrinsic trading frequency. As such, the prices mainly respond to the long-run return on equity. Overall, the results challenge the view that higher frequency of trading-a commonly used proxy for investor short-termnism-causes a disconnect between asset prices and fundamentals. Finally, in Chapter 3 (co-auhtored with Fernando Duarte) we show a novel relation between the institutional investors' intrinsic trading frequency-a commonly used proxy for the investors's investment horizon- and the cross-section of stock returns. We show that the 20$ of stocks with the lowest trading frequency earn mean returns that are 6 percentage points per year higher than the 20% of stocks that have the highest trading frequency. The magnitude and predictability of these returns persist or even increase when risk-adjusted by common indicators of systematic risks such as the Fama-French, liquidity or momentum factors. Our results show that the characteristics of stockholders affect expected returns of the very securities they hold, supporting the view that heterogeneity among investors is an important dimension of asset prices.
by Sahar Parsa.
Ph.D.
6
Wong, Sau-shing Pierre, e 黃守誠. "A study of the correlation of share price movements of Taiwan listed companies with cross holdings". Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1997. http://hub.hku.hk/bib/B31268390.
Testo completo
7
Pu, Hansong. "An Analysis of Preferred Equity Redemption Cumulative Stock". Thesis, University of North Texas, 1994. https://digital.library.unt.edu/ark:/67531/metadc277588/.
Testo completoAbstract (sommario):
This dissertation examines whether Percs, Preferred Equity Redemption Cumulative Stocks, are properly priced regarding to the relevant securities, such as the underlying common stock, the long-term call option of the stock, and so on. Test results indicate that Percs were overpriced with respect to the equivalent packages composed of the relevant securities. Further tests on arbitrage restrictions show that transaction costs would prevent arbitrage profits. This dissertation also examines the market reactions to Percs offerings. Test results reveal that the market reactions to the announcement of Percs offering and the actual issuance are both significantly negative. Compared to the market reaction on common stock offering announcement, the market reaction on Percs offering announcement is weaker. The overpricing of Percs and the weaker reaction of the market suggest that Percs may have advantages in transaction costs, taxes and some corporate finance issues.
8
Mullins, Mark Robert. "Stock market prices : determinants and consequences". Thesis, London School of Economics and Political Science (University of London), 1990. http://etheses.lse.ac.uk/1192/.
Testo completoAbstract (sommario):
This thesis concludes that aggregate stock market prices are significantly linked to the real economy. The thesis does, however, find a number of instances of non-efficient market behaviour, in terms of unexplained stock returns prior to financial crises, the predictability of the equity premium, and, possibly, the weak statistical relationship between stock market prices and corporate investment. Chapter I examines stock price behaviour prior to the stock market crash of 1987. Using data from 23 stock markets, there is little support for the view that the recent crash was caused by a bursting bubble. However, there is evidence that equity prices have recently moved in a non-random manner on some of these exchanges. Chapter II investigates the movements of stock prices in the United Kingdom from 1700 to 1987. A strong nominal interest rate effect on excess returns is found for the entire period, but it appears that inflation has a consistent, negative effect only after 1950. Chapter III analyzes major British financial crises since 1700. Using efficient and non-efficient market models, it is found that fluctuations in macroeconomic variables account for up to one half of equity price variation. As well, relatively few crises have been preceded by the excessive positive returns consistent with rational bubbles. Chapter IV finds that Tobin's Q in OECD countries is inappropriately modelled within a static framework but is improved markedly using a dynamic error correction model. The Q measures are also superior to real stock prices as predictors of investment. Chapter V compares the effects of equity prices on corporate investment and output in Japan, West Germany, the United Kingdom and the United States. It seems that the effect of the equity market is greater in the latter two countries for various institutional reasons associated with managerial autonomy.
9
Huang, Lin. "On excess volatility of stock prices". Thesis, University of Essex, 2007. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.442742.
Testo completo
10
Takahashi, Yutaka. "A study of Japanese stock prices". Thesis, Massachusetts Institute of Technology, 1991. http://hdl.handle.net/1721.1/13401.
Testo completo
11
Marques, Eliano Patrício Macedo. "Social media impact on stock prices". Master's thesis, Instituto Superior de Economia e Gestão, 2015. http://hdl.handle.net/10400.5/10642.
Testo completoAbstract (sommario):
Mestrado em Econometria Aplicada e PrevisãoEste documento explora o impacto do social media nos preços das ações. Para medir tal impacto, foi construído uma plataforma online na Cloud da Amazon (AWS) recorrendo a ferramentas como o R, web APIs do Twitter, Google News, Google Finance, Yahoo News, Yahoo Finance e Financial Times. O objetivo deste estudo passa por criar uma base de dados para modelação com uma granularidade de 15 minutos incluindo como possíveis variáveis explicativas todas as noticias publicadas das fontes acima referidas para o Tesco e SKY. Posteriormente, recorrendo a uma técnica de GARCH multiplicativos, diversos modelos econométricos foram desenvolvidos com o objetivo de efetuar previsões a um passo dos retornos dos preços das ações acima referidos. Se efetivamente a informação do social media for relevante, deverá ser observado uma melhoria nas previsões dos retornos das ações. No decorrer do documento, será apresentado a metodologia utilizada no estudo e a sua aplicação em dados com elevada frequência. No geral, podemos concluir que a informação do social media é residualmente relevante para modelar e prever os retornos dos preços das ações e, nos modelos sem informação do Twitter, o segundo melhor modelo para o Tesco e o melhor modelo para a SKY, inclui informação do social media. No que se refere às fontes utilizadas, pode-se concluir que o Google Finance e o Financial Times relevam maior importância nos movimentos dos retornos das ações do que o Yahoo Finance e/ou Twitter, apesar de tal relevância ser muito residual e próxima de zero.
This dissertation explores the impact of social media on stock prices. In order to measure such an impact, an end-to-end online platform was created leveraging the Amazon Web Services cloud, open source R, web APIs from Twitter, Google News, Google Finance, Yahoo News, Yahoo Finance and Financial Times. The end goal was to create an intraday dataset that tracks all the news related to two companies Tesco PLC, SKY PLC and then perform several econometric models using a Multiplicative GARCH model to understand if the social media news from multiple sources are statistically relevant to measure the stock prices returns and if the forecast accuracy improves by including such covariates in the predictive equations. For all of the approaches it will be presented the respective theory background and their applications to high-frequency data. Overall it can be concluded that news, past market information and tweets didn't improve that much the stocks returns models and forecasting accuracy but, for models without Twitter, Tesco's 2nd best model and SKY's best model included social media news as covariates. Google Finance and Financial Times presented better results when compared to Yahoo Finance and/or Twitter, however, overall, the impact was very residual and closer to zero.
12
Liu, Taisheng. "Stock market overreaction and underreaction : theoretical explanations and empirical evidences". HKBU Institutional Repository, 2006. http://repository.hkbu.edu.hk/etd_ra/693.
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13
Chen, Gang. "The Chinese stock market : an emperical analysis of market segmentation, inter-relationships and theoretical versus actual stock prices". Thesis, University of Aberdeen, 2011. http://digitool.abdn.ac.uk:80/webclient/DeliveryManager?pid=165872.
Testo completoAbstract (sommario):
This thesis contributes to our knowledge of the behaviour of the Chinese stock market by offering an empirical investigation into issues such as market segmentation, inter‐relationships between Chinese stock markets and inter‐relationships with foreign stock markets. Basic questions which have been typically analysed for developed stock markets are considered in this thesis. These include an analysis of core concepts such as volatility; causal links with economic variables and the reasons why the theoretical stock price may be different from the actual stock price. Methodological methods include; cointegration, generalised autoregressive heteroscedastic modelling (GARCH), vector autoregressive framework modelling (VAR) and panel data analysis. Both daily and monthly observations are used over a time period from 1996 to 2006. The results indicate that there is a rich set of reasons why we may observe phenomena such as a discount on B shares and a relationship between A shares and B shares. The findings also suggest that China is not isolated from the rest of the world and that there is evidence of inter‐relationships with foreign stock markets and that Chinese stock market prices are close to their fundamental value. This is not generally the finding for developed stock markets. Overall, it appears that the methodological approaches usually associated with developed stock markets can serve us well as useful tools in creating a deeper understanding of the underlying fundamentals describing the Chinese stock market.
14
Garg, Vivek, University of Western Sydney e School of Economics and Finance. "The Capital Asset Pricing Model : a test on the Stock Exchange of Singapore". THESIS_XXX_EFI_Garg_V.xml, 1999. http://handle.uws.edu.au:8081/1959.7/459.
Testo completoAbstract (sommario):
Of the many analytical methods collectively referred to as Modern Portfolio Theory (MPT), the Capital Asset Pricing Model (CAPM) is the most familiar to today’s generation of students of finance. The popularity of the CAPM arises from its success in expressing a powerful theoretical insight in a simple, usable form. The primary use of the CAPM is to determine minimum required rates of return from investment in risky assets. The variable in the CAPM is called ‘beta’, a statistical measure of risk which has become familiar to all finance professionals. Over the past decade, beta has become the most widely recognised and applied measure of risk in the investment community. The model has been extensively tested in the developed capital markets, mainly in the United States of America. But the model has not been extensively tested in other developed and developing countries, often due to the size of the capital market and the lack of the data in these countries. This study attempts to fill this vacuum and tries to update the earlier tests done on the Stock Exchange of Singapore. On addition, a review of the validity of the CAPM over time, as proxied by the stationarity of the beta, is performed. Also, tests regarding heteroskedasticity and its implications have been undertaken.Master of Commerce (Hons)
15
Fodor, Bryan D. "The effect of macroeconomic variables on the pricing of common stock under trending market conditions". Thesis, Department of Business Administration, University of New Brunswick, 2003. http://hdl.handle.net/1882/49.
Testo completoAbstract (sommario):
Thesis (MBA) -- University of New Brunswick, Faculty of Administration, 2003.Typescript. Bibliography: leaves 83-84. Also available online through University of New Brunswick, UNB Electronic Theses & Dissertations.
16
Beyer, Scott B. "Recovering jump risk and diffusion parameters implied by market prices of short-dated options /". free to MU campus, to others for purchase, 2003. http://wwwlib.umi.com/cr/mo/fullcit?p3099610.
Testo completo
17
Kemerer, Kevin L. "Accounting variables, stock splits and when-issued trading". Diss., Virginia Tech, 1990. http://hdl.handle.net/10919/39702.
Testo completoAbstract (sommario):
When-issued trading, the contractual agreement for the sale and purchase of shares to be issued in the future (when-issued securities), typically occurs after stock split announcements. Curiously, when-issued trading does not always exist for a stock-splitting firm's shares even though the shares are eligible for when-issued trading.
Although stock splits have been the subject of a large number of studies, intriguing questions concerning these events remain unanswered. In particular, academia has yet to explain adequately the positive average abnormal returns associated with stock split announcements.
These two peculiar phenomena are examined. A major objective of this dissertation is to determine whether there are systematic differences between those stock-splitting firms whose shares are traded on a when-issued basis and those whose shares arc not.
A logistic regression model was constructed, using information with respect to nine accounting variables, to determine if there are systematic differences in accounting information that are useful in classifying stock-splitting firms as being associated with when-issued trading. The classification accuracy of the logistic regression model was significantly better than a random walk model, but was not better than the maximum chance model. The results of the final model indicate that size of the stock-splitting firm is the most significant factor affecting the probability that a stock-splitting firm's shares
are traded on a when-issued basis. The probability that a stock-splitting firm's shares will be traded on a when-issued basis increases with firm size.
The presence/absence of when-issued trading indicates that investors do not react to stock splits in a consistent manner. Therefore, the stock price behavior around the stock split announcements was examined and the difference in the reaction to announcements of when-issued traded and non-when-issued traded firms was tested for statistical significance. The results indicate that the market responds more favorably to the stock split announcements made by non-when-issued traded firms.
The variation in the stock price behavior over a two-day stock split announcement period was analyzed cross-sectionally to determine whether the market reaction displayed through stock prices is related to selected accounting variables. Again, size was the most significant factor. In this case, size was negatively related to the stock price behavior suggesting that stockholders of larger firms earn lower abnormal returns. Another interpretation would be that stock splits are viewed more favorably if authorized by smaller firms.
Overall, the results of this study suggest that all stock-splitting firms are not similar and that the market does not react consistently to the announcement of stock splits of all firms. It seems that the larger the firm, the more likely its shares will be traded on a when-issued basis after the stock split is announced. Furthermore, the market does not react as positively to stock split announcements of larger firms as it does to announcements of smaller firms. My conclusion is that larger firms are more efficiently valued and, accordingly, the announcements of stock splits by larger firms are less informative than for smaller ones.Ph. D.
18
Norlander, Olof. "Analysis of stock forum texts to examine correlation to stock prices". Thesis, Uppsala universitet, Avdelningen för datalogi, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-298484.
Testo completoAbstract (sommario):
In this thesis, four methods of classification from statistical learning have been used to examine correlations between stock forum discussions and stock prices. The classifiers Naive Bayes, support vector machine, AdaBoost and random forest, were used on text data from two different stock forums to see if the text had any predictive power for the stock price of five different companies. The volatility and the direction of the price - whether it would go up or down - over a day was measured. The highest accuracy obtained for predicting high or low volatility came from random forest and was 85.2 %. For price difference the highest accuracy was 69.2 %, using the support vector machine. The average accuracy for predicting the price difference was 58.6 % and the average accuracy for predicting the volatility was 73.4 %. This thesis was made in collaboration with the company Scila which works with stock market security.
19
Kukk, Kätriin. "Correlation between emotional tweets and stock prices". Thesis, Uppsala universitet, Institutionen för lingvistik och filologi, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-381101.
Testo completoAbstract (sommario):
Social media platforms such as Facebook and Twitter have enormous amounts of data that can be extracted and analyzed for various purposes. Stock market prediction is one of them. Previous research has shown that there is a correlation between Twitter sentiment – the proportion of positive, negative and neutral tweets – and the changes in companies’ stock prices. The present study investigates if categorizing tweets into a bigger number of categories – anger, disgust, joy, surprise, none - results in stronger correlations being found. In total, 5985 tweets in English about American Airlines, American Express, AstraZeneca and ExxonMobil were extracted and analyzed with the help of sentiment and emotion classifiers trained. Tweet sentiment showed stronger correlations with stock returns than emotion did, although the type of correlation found differed between the companies considered. It is suggested that dividing tweets into fewer categories results in semantically more distinct labels that are easier to distinguish between and that therefore show stronger correlations. Furthermore, the results indicate that the pairs of values showing the strongest correlations depend on the characteristics of each individual company.
20
Duarte, Fernando Manuel. "Essays on macroeconomic risks and stock prices". Thesis, Massachusetts Institute of Technology, 2011. http://hdl.handle.net/1721.1/65483.
Testo completoAbstract (sommario):
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Economics, 2011.Cataloged from PDF version of thesis.
Includes bibliographical references.
In this thesis, I study the relationship between macroeconomic risks and asset prices. In the first chapter, I establish that inflation risk is priced in the cross-section of stock returns: stocks that have low returns during inflationary times command a risk premium. I estimate a market price of inflation risk that is comparable in magnitude to the price of risk for the aggregate market. Inflation is therefore a key determinant of risk in the cross-section of stocks. The inflation premium cannot be explained by either the Fama-French factors or industry effects. Instead, I argue the premium arises because high inflation lowers expectations of future real consumption growth. To formalize and test this hypothesis, I develop a consumption-based general equilibrium model. The model generates a price of inflation risk consistent with my empirical estimates, while simultaneously matching the joint dynamics of consumption and inflation, the aggregate equity premium, and the level and slope of the yield curve. In the second chapter, with L. Kogan and Dmitry Livdan, we study the relation between returns on the aggregate stock market and aggregate real investment. While it is well known that aggregate investment rate is negatively correlated with subsequent excess stock market returns, we find that it is positively correlated with future stock market volatility. Thus, conditionally on past aggregate investment, the mean-variance tradeoff in aggregate stock returns is negative. We interpret these patterns within a general equilibrium production economy. In our model, investment is determined endogenously in response to two types of shocks: shocks to productivity and preference shocks affecting discount rates. Preference shocks affect expected stock returns, aggregate investment rate, and stock return volatility in equilibrium, helping model reproduce the empirical relations between these variables. Thus, our results emphasize that the time-varying price of aggregate risk plays and important role in shaping the aggregate investment dynamics. In the third chapter, with S. Parsa, we show a novel relation between the institutional investors' intrinsic trading frequency-a commonly used proxy for the investors's investment horizon- and the cross-section of stock returns. We show that the 20% of stocks with the lowest trading frequency earn mean returns that are 6 percentage points per year higher than the 20% of stocks that have the highest trading frequency. The magnitude and predictability of these returns persist or even increase when riskadjusted by common indicators of systematic risks such as the Fama-French, liquidity or momentum factors. Our results show that the characteristics of stockholders affect expected returns of the very securities they hold, supporting the view that heterogeneity among investors is an important dimension of asset prices. JEL classification: E31, E44, G12.
by Fernando Manuel Duarte.
Ph.D.
21
Xue, Qifeng. "Grey diffenrential equation modeling on stock prices". Master's thesis, University of Cape Town, 2005. http://hdl.handle.net/11427/4947.
Testo completo
22
Chen, YenHsiao. "Stock prices : fundamentals, bubbles and investor behaviour". Thesis, University of Aberdeen, 2008. http://digitool.abdn.ac.uk/R?func=search-advanced-go&find_code1=WSN&request1=AAIU500768.
Testo completoAbstract (sommario):
This thesis investigates ten markets: U.S., U.K., Hong Kong, Japan Singapore, Malaysia, South Korea, Thailand, Taiwan, and Indonesia over a sample period covering roughly from the 1970s to 2006, in order to investigate whether bubble behaviour is a major source of financial instability. Price movements have fundamental components and bubble components. An attempt to explain price behaviour therefore prompts two major questions: What are the fundamental drivers of stocks? What behaviour causes actual prices to deviate from their fundamental values? This thesis constructs fundamental movements in stock prices by utilising the present value model, which, in turn, involves two further issues. First, do investors expect the required rate of return to be time-varying? Second, which fundamental driver, dividends or earnings, is more efficient in tracing investor perceptions of expected cash flows? I address the former issue by building and testing two models which assume constant discount rate and time-varying discount rate respectively. The second issue we address by using dividends and earnings data as the fundamental factor. Revealed deviations from fundamental value are investigated by considering three types of bubble behaviour discussed in the extant literature: rational explosive bubbles; rational intrinsic bubbles; and irrational price dynamics. Such bubble processes are then compared with actual price movements to gauge which type of behaviour is more likely to track actual prices in the sample markets. With respect to whether the required rate of return is time-varying, two variants of the present value model are used to construct the fundamental values of the relevant market indices. Results demonstrate that the dynamic version of the present value model has superiority in tracking actual price movements when compared to a static version of the present value model. With regard to which series is more effective in tracing investor expected cash flows, the more broadly defined expected earnings, rather than cash dividends, drive stock prices in the developed markets of the U.S., U.K. and Japan, as well as the developing markets of Korea and Malaysia. Dividends have relatively more influence on the markets of Thailand, Taiwan and Indonesia, but neither the dividend discount nor earnings discount model can explain the time path of stock prices in Hong Kong and Singapore. In terms of the drivers of bubble phenomena, results suggest no rational explosive bubble exists in any of the markets in the sample.
23
關惠貞 e Wai-ching Josephine Kwan. "Trend models for price movements in financial markets". Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1994. http://hub.hku.hk/bib/B31211513.
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Stevenson, Alan J. "Price relationships between resource based stock prices and commodity prices". 2004. http://hdl.handle.net/1993/15768.
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"An application of two forecasting models for predicting price movements of a number of selected stocks in Hong Kong". Chinese University of Hong Kong, 1986. http://library.cuhk.edu.hk/record=b5885605.
Testo completo
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CHIA-LIN, HSU, e 徐嘉臨. "The Dynamic Relationships among Crude Oil Prices,Petroleum stock Prices,and Solar Stock Prices". Thesis, 2006. http://ndltd.ncl.edu.tw/handle/28709142495575343846.
Testo completoAbstract (sommario):
碩士開南管理學院
企業管理學系碩士班
94
The world crude oil price keeps rising constantly. Therefore the fluctuation of the world crude oil price is definitely an important issue to the macro-teconomy and industries in Taiwan. the purpose of this study is to examine The Dynamic Relationship among the price shocks of Crude Oil Prices Oil Price Shocks、Petroleum Industry、Solar Industry .The research methodologies of this paper are Unit root、cointegration、Granger Causality Test、vector autoregression model. The investigation period spans from 2000 to 2006. The empirical findings are summarized as follows：There are long equilibrium relationships within oil Price、stock price of solar industry and petroleum industry. Granger causality test indicated that solar industry dominant role in Oil Price、Petroleum Industry .The result of Impulse Response Analysis finds that the relation of the inter-actions of stock markets in solar Industry than Petroleum Industry；the result of Variance Decomposition suggests that solar industry are changed easily by oil price and Petroleum Industry.
27
"Movement of stock price and trading volume--: a comparison of Shanghai and Shenzhen stock market". 2000. http://library.cuhk.edu.hk/record=b5890180.
Testo completoAbstract (sommario):
by Kei Man Keung, Tong Suk Yi.Thesis (M.B.A.)--Chinese University of Hong Kong, 2000.
Includes bibliographical references (leaves 35-39).
ABSTRACT --- p.iii
TABLE OF CONTENTS --- p.iv
LIST OF TABLES --- p.v
Chapter
Chapter I. --- INTRODUCTION --- p.1
Chapter II. --- THE CHINESE CAPITAL MARKET --- p.6
Chapter III. --- DATA AND METHODOLOGY --- p.10
Cases Description --- p.10
Event 1: Hong Kong Handover (1 July 1997) --- p.11
Event 2: Zhu Rongji Elected the Prime Minister (March 1998) --- p.11
Event 3: U.S.- China Summit (25 June 1998) --- p.12
Event 4: The Chinese Embassy Bombingin Yugoslavia (8 May 1999) --- p.13
Event 5: China's WTO Entry (15 November 1999) --- p.13
Event 6: Macau Handover (20 December 1999) --- p.14
Three Models --- p.15
Chapter IV. --- EMPIRICAL RESULTS --- p.20
Chapter V. --- CONCLUSION --- p.26
APPENDIX --- p.28
BILIOGRAPHY --- p.35
28
cheng, chia-hui, e 鄭嘉慧. "The Impact of Stock Market Disturbances on Agricultural Prices and Stock Prices". Thesis, 2005. http://ndltd.ncl.edu.tw/handle/52413196026382201057.
Testo completo
29
Chen, Chia-Hui, e 陳嘉惠. "The Impact of Agricultural Price Target Zone on Agricultural Prices and Stock Prices". Thesis, 2005. http://ndltd.ncl.edu.tw/handle/73013050140597583252.
Testo completo
30
Ramsumar, Shaun. "Evaluating efficiency of ensemble classifiers in predicting the JSE all-share index attitude". Thesis, 2017. http://hdl.handle.net/10539/23366.
Testo completoAbstract (sommario):
A research report submitted to the Faculty of Commerce, Law and Management, University
of the Witwatersrand, Johannesburg, in partial fulfillment of the requirements for the degree
of Master of Management in Finance and Investment.
Johannesburg, 2016The prediction of stock price and index level in a financial market is an interesting but highly complex and intricate topic. Advancements in prediction models leading to even a slight increase in performance can be very profitable. The number of studies investigating models in predicting actual levels of stocks and indices however, far exceed those predicting the direction of stocks and indices. This study evaluates the performance of ensemble prediction models in predicting the daily direction of the JSE All-Share index. The ensemble prediction models are benchmarked against three common prediction models in the domain of financial data prediction namely, support vector machines, logistic regression and k-nearest neighbour. The results indicate that the Boosted algorithm of the ensemble prediction model is able to predict the index direction the best, followed by k-nearest neighbour, logistic regression and support vector machines respectively. The study suggests that ensemble models be considered in all stock price and index prediction applications.
MT2017
31
CHIU, POH-LIM, e 邱柏霖. "Forecasting Taiwan stock prices". Thesis, 1998. http://ndltd.ncl.edu.tw/handle/63500112352295597390.
Testo completoAbstract (sommario):
碩士淡江大學
財務金融學系
86
Many economists believe that the overall performance of a country''s economy is strongly related to the performance of its stock market. Some empirical studies, however, show that this relationship does not necessarily hold. In the sense that stock market performance is highly unpredictable, the movement of stock prices has sometimes been expressed as a random walk process. Shiller (1989) and DeBond (1991) have also shown that stock price are both unpredictable and volatile in the short run. Other empirical studies show that overall economic performance has an influence on the performance of stock prices. Studies by Umstead (1977) and Fama (1981) show that a positive correlation exists between real economic growth and stock prices. Spiro (1990) and Cochrane (1991) find that economic fluctuations influence stock prices and that macroeconomic variables such as real output and the interest rate can explain stock market movement significantly. In this study, macroeconomic variables, which closely relation with stockprices proven by theories and previous empirical studies are used as the independent variables. A broad, real stock-market index is used as the dependent variable. Four econometric models including the Vector Autoregressive Model (VAR), the Seemingly Unrelated Regression (SUR), the Error Correction Model (ECM), and the Kalman Filter Model (KFM) are used to forecast Taiwan stock prices. Four econometric models, which have same basic functional form are used as the tool of the fundamental analysis. Further, this studies also compares four such models and determines which makes the most accurate out of sample and in of sample forecast. The contribution of the empirical results can provide a valuable suggestion for the investors and the analyst of stock market.(1)In-of-sample prediction performance The forecasting performance of the SUR is consistently better than the ECM,the VAR and the KFM.(2)Out-of-sample prediction performance The ECM perform much well than the KFM, the SUR and the VAR.
32
"The intertemporal relation among the G7 stock markets". 2004. http://library.cuhk.edu.hk/record=b5892214.
Testo completoAbstract (sommario):
Wong Ying Chiu.Thesis (M.Phil.)--Chinese University of Hong Kong, 2004.
Includes bibliographical references (leaves 62-69).
Abstracts in English and Chinese.
Chapter 1. --- Introduction and Literature Review --- p.1
Chapter 2. --- Methodology --- p.9
Chapter A. --- OLS Regression and Correlation
Chapter B. --- Simulation Trade
Chapter 3. --- Data --- p.15
Chapter 4. --- Empirical Findings --- p.21
Chapter A. --- OLS Regression and Correlation
Chapter B. --- Simulation Trade
Chapter 5. --- Conclusion --- p.32
Chapter 6. --- Figures and Tables --- p.34
Chapter 7. --- Bibliography --- p.62
Chapter 8. --- Appendix --- p.70
33
Zheng, Jing-Sian, e 鄭靖諴. "Empirical Analysis for Electricity Prices and Stock Prices". Thesis, 2011. http://ndltd.ncl.edu.tw/handle/84888383056140628811.
Testo completoAbstract (sommario):
碩士國立中央大學
統計研究所
99
Over the past two decades, many electricity markets around the world have decided to take the path of market liberalization. Since then, both consumers as producers are exposed to significantly higher risk. And some stylized facts of electricity spot prices have been found, especially the price spike which is a behavior that the prices increase or decrease significantly and return afterwards in short time intervals. This fact enhances the difficulty for modeling. For the purpose of comparison, we also apply the historical stock closing prices which have the similar behavior, but the return rate is not as high as the stock prices. In this paper, we use two models which include mean-reverting jump diffusion model and Markov regime-switching model to assess their ability to explain the electricity prices from the European Energy Exchange (EEX) and the stock prices from the Apple Inc. Before fitting the models, electricity prices need to be deseasonalized. After parameter estimating and simulating, we use three ways to measure the errors between the simulated values and the true values. We conclude that mean-reverting jump diffusion model is better modeling the stock prices and Markov regime-switching model has better ability to explain the electricity prices. However, if the result is the same for other market data, it suggests to further investigation.
34
Golding, John. "Stock prices as a leading indicator of economic activity". Thesis, 2011. http://hdl.handle.net/10539/10673.
Testo completoAbstract (sommario):
Most asset pricing theories suggest that asset prices are forward looking and reflect market expectations of future earnings. By aggregating across companies, aggregate market prices may then be used as leading indicators of future Real GDP, Real Industrial Production and the level of Inflation. A Hodrick & Prescott (1981) filter is used to detrend the data, which is compiled on an annual and quarterly basis from the JSE, to test whether stock returns are in fact useful for indicating economic activity. An autoregressive model is constructed, yielding strong evidence of significance, in the first four quarters on a quarterly basis, and two years on an annual basis, for Real Stock Prices. Therefore, in terms of a South African context, the Cycle of Real Stock Prices are a leading indicator on the JSE.
35
"On the performance of oscillators on G7 stock market indices". 2003. http://library.cuhk.edu.hk/record=b5891652.
Testo completoAbstract (sommario):
Ng Wing-kam.Thesis (M.Phil.)--Chinese University of Hong Kong, 2003.
Includes bibliographical references (leaves 54-55).
Abstracts in English and Chinese.
Chapter ONE --- INTRODUCTION --- p.1
Chapter TWO --- DATA AND TECHNICAL TRADING RULES --- p.4
Data
Technical Trading Rules
RSI
MACD
Chapter THREE --- EMPIRICAL RESULTS --- p.10
Sample Statistics
Technical Trading Rules (Without Transaction Cost)
MACD
RSI
Technical Trading Rules (With Transaction Cost)
MACD
RSI
Chapter FOUR --- CONCLUSION --- p.37
TABLES --- p.40
BIBLOGRAPHY --- p.54
36
"Event studies: stock price effect on the announcement of stock placement". Chinese University of Hong Kong, 1993. http://library.cuhk.edu.hk/record=b5887558.
Testo completoAbstract (sommario):
by Ng Tak-ming.Thesis (M.B.A.)--Chinese University of Hong Kong, 1993.
Includes bibliographical references (leaves 28-29).
ABSTRACT --- p.ii
TABLE OF CONTENTS --- p.iii
LIST OF TABLES --- p.iv
LIST OF FIGURES --- p.v
Chapter
Chapter I. --- INTRODUCTION AND LITERATURE REVIEW --- p.1
Chapter II. --- SAMPLE DESCRIPTION --- p.8
Chapter III. --- METHODOLOGY --- p.10
Chapter IV. --- RESULTS --- p.12
Chapter V. --- IMPLICATIONS --- p.19
Chapter VI. --- CONCLUSIONS --- p.21
REFERENCES --- p.28
37
"The Hong Kong stock market: characteristics and pricing of securities". Chinese University of Hong Kong, 1993. http://library.cuhk.edu.hk/record=b5887536.
Testo completoAbstract (sommario):
by Chan Chi-man, Simon.Thesis (M.B.A.)--Chinese University of Hong Kong, 1993.
Includes bibliographical references (leaves [5]-[8] (2nd group)).
ACKNOWLEDGMENTS --- p.i
ABSTRACT --- p.ii
TABLE OF CONTENTS --- p.iv
LIST OF FIGURES --- p.vii
LIST OF TABLES --- p.viii
Chapter CHAPTER I. --- INTRODUCTION --- p.1
Background --- p.1
Objectives --- p.3
Scope --- p.5
Organization of the Paper --- p.6
Chapter CHAPTER II. --- THE HONG KONG STOCK MARKET - QUANTIFYING ITS CHARACTERISTICS --- p.7
Introduction --- p.7
Choice of Proxy for the Market --- p.9
Hong Kong in the Asian Pacific Region --- p.11
Choice of Benchmarks for Comparisons --- p.12
Comparative Returns and Standard Deviations --- p.13
Correlations Amongst Different Markets --- p.16
Comparative Price to Earnings (P/E) Ratios --- p.18
Market Liquidity --- p.19
Market Concentration --- p.20
Summary --- p.21
Chapter CHAPTER III. --- PRICING OF RISKY ASSETS IN HONG KONG --- p.23
Introduction --- p.23
Applicability of Pricing Models in the Hong Kong Stock Market --- p.23
Literature Review --- p.23
CAPM --- p.28
The model --- p.28
Hypotheses to be tested --- p.29
Data --- p.30
Methodology --- p.30
Portfolio construction --- p.30
Variable estimation --- p.31
Cross-sectional regressions --- p.31
Results and discussions --- p.32
Stability of Beta --- p.34
APT --- p.37
Introduction --- p.37
Analysis --- p.38
Chapter CHAPTER IV. --- THE EFFICIENCY AND ANOMALIES OF THE HONG KONG STOCK
MARKET --- p.51
Market Efficiency --- p.51
Introduction --- p.51
Informational Efficiency --- p.51
Forms of market efficiency --- p.52
Empirical evidence in Hong Kong --- p.53
Historical prices --- p.53
Investment advisory --- p.54
Government budget speeches --- p.55
Takeover --- p.55
Conclusions --- p.55
Anomalies --- p.56
Introduction --- p.56
An Exercise on PBV --- p.57
Summary --- p.58
Chapter CHAPTER V. --- POLITICAL INFLUENCE AND THE STOCK MARKET --- p.59
Introduction --- p.59
Literature Review --- p.60
Political Risk in Hong Kong --- p.61
Conclusion --- p.64
Chapter CHAPTER VI. --- DIVERSIFICATION --- p.65
Introduction --- p.65
Literature Review --- p.65
Does International Diversification Work --- p.67
Conclusion --- p.72
Chapter CHAPTER VII. --- CONCLUSIONS --- p.73
What Moves Stock Prices? --- p.74
Is the Stock Market Overreacting? --- p.75
Some Suggestions --- p.76
APPENDICES
BIBLIOGRAPHY
38
Xie, Chen. "Asset Pricing Implications of the Volatility Term Structure". Thesis, 2015. https://doi.org/10.7916/D8D79B6D.
Testo completoAbstract (sommario):
This dissertation aims to investigate the asset pricing implications of the stock option's implied volatility term structure. We mainly focus on two directions: the volatility term structure of the market and the volatility term structure of individual stocks.
The market volatility term structure, which is calculated from prices of index options with different expirations, reflects the market's expectation of future volatility of different horizons. So the market volatility term structure incorporates information that is not captured by the market volatility itself. In particular, the slope of the volatility term structure captures the expected volatility trend. In the first part of the thesis, we investigate whether the market volatility term structure slope is a priced source of risk or not. We find that stocks with high sensitivities to the proxies of the VIX term structure slope exhibit high returns on average. We further estimate the premium for bearing the VIX slope risk to be approximately 2.5% annually and statistically significant. The effect cannot be explained by other common risk factors, such as the market excess return, size, book-to-market, momentum, liquidity and market volatility. We extensively investigate the robustness of our empirical results and find that the effect of the VIX term structure risk is robust. Within the context of ICAPM, the positive price of VIX term structure risk indicates that it is a state variable which positively affects the future investment opportunity set.
In the second part of the thesis, we provide a stylized model that explains our empirical results. We build a regime-switching rare disaster model that allows disasters to have short and long durations. Our model indicates that a downward sloping VIX term structure corresponds to a potential long disaster and an upward sloping VIX term structure corresponds to a potential short disaster. It further implies that stocks with high sensitivities to the VIX slope have high loadings on the disaster duration risk, thus earn higher risk premium. These implications are consistent with our empirical results.
In the last part, we study the relationship between individual stock's volatility term structure and the stock's future return. We use a measure of stock's implied volatility term structure slope, defined as the difference between 3-month and 1-month implied volatility from at-the-money options, to demonstrate that option prices contain important information for the underlying equities. We show that option volatility term structure slopes are significant in explaining future equity returns in the cross-section. And we further find evidence that the implied volatility term structure is a measure of event risk: firms with the most negative volatility term structure are those for which the market anticipates news that may affect stock price within one month. Relevant events include, but are not limited to, earnings announcements.
39
Chen, Shih-Chang, e 陳世章. "Fundamental Analysis And Stock Prices". Thesis, 1998. http://ndltd.ncl.edu.tw/handle/31199700428820179809.
Testo completoAbstract (sommario):
碩士國立臺灣大學
會計學系
86
THESIS ABSTRACT GRADUATE INSTITUTE OF ACCOUNTING NATIONAL TAIWAN UNIVERSITY TITLE ： Fundamental Analysis And Stock Prices NAME ： Shih-Chang Chen ADVISOR ： Shu Yeh, Ph.D. Month/Year ： June, 1998 Investment analysts frequently use a set of financial variables to predict security prices and estimate the value of corporations. We want to research which financial variable would offer analysts useful information. Our findings also may help general investors to make accurate investment decisions. The research period is from 1987 to 1996. We select 9 financial variables which are used in the researches presented by Lev and Thiagarajan(1993) ,and Abarbanell and Bushee(1997).Our purpose is to investigate the information content of these financial variables, and whether investors would use it to estimate securities prices. We regress CAR, the cumulative abnormal return, on a set of financial variables and test the estimated parameters by Wilcoxon Signed-ranks Test to investigate the final results. Our findings are that three of those financial variables have information content. Among the three variables, inventory and gross margin can offer investors useful information to estimate security prices and get satisfied returns. As to the other variable, capital expenditure, it has unexpected explanations to our hypothesis and reserves to be investigated in the future.
40
Beckworth, David. "Monetary policy and stock prices". 2003. http://purl.galileo.usg.edu/uga%5Fetd/beckworth%5Fdavid%5Fm%5F200308%5Fphd.
Testo completo
41
yue-ren, Hung, e 黃鉞荏. "Study on Correlation among Oil Prices, Brass Prices and Taiwan Industry Group Stock Price Index". Thesis, 2007. http://ndltd.ncl.edu.tw/handle/12869892861585598372.
Testo completoAbstract (sommario):
碩士樹德科技大學
金融保險研究所
95
Energy has been one of the major resources that human beings depend on for survival. It is also one of the main forces that drive economic development of a country. Among all energy supplies, crude oil plays a very significant role. The price increase due to demand is extremely different from the increase in the past three times of global oil crisis due to supply. Earlier issues on oil prices are on correlation with macroeconomicvariables. The author extends the issue on oil prices and common metal (brass) prices analysis across all industries. With the different characteristics of industries in Taiwan, the author further understands the results of different factors. The author adopts Garch model that better captures the data fluctuation of time array to explore the correlation among oil prices, brass prices and Taiwan industry group stock prices in order to understand which group stock prices will be affected by the fluctuation of oil and brass prices. From the evidence results, it is found that the return in one period behind of oil prices is in negative correlation with stock prices of electric machinery, transportation and department stores, meaning that the return in the precedent period of oil prices affects the stock price of electric machinery, transportation and department stores and the fluctuation is very ob-vious as well, causing fluctuation clustering. The return of current and one period behind of brass price is in apparent positive correlation with stock prices of foods, plastics, electric appliances, paper making and steel, etc showing that the stock prices are affected by the return of current and one period behind of brass price and the fluctuation is very obvious as well, causing fluctuation clustering.
42
"Rights issue and stock price movement in Hong Kong". Chinese University of Hong Kong, 1993. http://library.cuhk.edu.hk/record=b5887534.
Testo completoAbstract (sommario):
by Li Shu Kan Tony.Thesis (M.B.A.)--Chinese University of Hong Kong, 1993.
Includes bibliographical references (leaf 50).
ABSTRACT --- p.i
TABLE OF CONTENTS --- p.1
LIST OF FIGURES AND TABLES --- p.2
CHAPTER
Chapter I. --- INTRODUCTION --- p.3
Definition of Rights Issue --- p.6
Chapter II. --- PREVIOUS STUDIES --- p.9
Chapter III. --- DATA COLLECTION --- p.13
Chapter IV. --- METHODOLOGY --- p.16
Sutdy Period --- p.20
Chapter V. --- FINDINGS --- p.23
Post-announcement Parameters --- p.24
Discount to Net Asset Value --- p.26
Amount raised from Right Issues --- p.30
Right Issue Terms --- p.31
Further test on Price Press Hypothesis --- p.33
Chapter VI. --- CONCLUSION --- p.35
Chapter VII. --- FIGURES AND TABLES --- p.37
Chapter VIII. --- BIBLIOGRAPHY --- p.50
43
"The cross-sectional relationship between the fundamental variables and returns of Hang Seng Index constituent stocks of Hong Kong stock market". Chinese University of Hong Kong, 1996. http://library.cuhk.edu.hk/record=b5888684.
Testo completoAbstract (sommario):
by Ho Man Shing, William.Thesis (M.B.A.)--Chinese University of Hong Kong, 1996.
Includes bibliographical references (leaves 41-42).
ABSTRACT --- p.i
TABLE OF CONTENTS --- p.iii
LIST OF FIGURE --- p.v
LIST OF TABLES --- p.v
Chapter
Chapter I. --- INTRODUCTION --- p.1
Objectives of Research Project --- p.2
Chapter II. --- LITERATURE REVIEW --- p.4
Research work in the U. S --- p.4
Research work in Japan and H. K --- p.5
Chapter III. --- METHODOLOGY --- p.7
Research design --- p.9
Formation of portfolios --- p.10
Univariate Analysis --- p.11
Regression Analysis --- p.11
Data collection --- p.12
Chapter IV. --- RESULTS --- p.13
Univariate analysis of returns and fundamental variables --- p.13
Regression analysis of returns and fimdamental variables --- p.17
Security level regression analysis of returns and fimdamental variables --- p.17
Portfolio level regression analysis of returns and fundamental variables (ranked by different fundamental variables) --- p.21
Portfolio level regression analysis of returns and fundamental variables (ranked by two different fundamental variables) --- p.27
Effects of order of agglomeration and different combinations --- p.30
Chapter V. --- SUMMARY AND CONCLUDING REMARKS --- p.37
BIBLIOGRAPHY --- p.41
APPENDICES
Chapter A --- List of Hang Seng Index Constituent Stocks during 1989 to1994
Chapter B --- Print-out of the Regression Results at Security Level
Chapter C --- Print-out of the Regression Results at Portfolio Level (E/P then LS)
Chapter D --- Print-out of the Regression Results at Portfolio Level (LS then E/P)
44
Naidoo, Justin Rovian. "Index/sector seasonality in the South African stock market". Thesis, 2016. http://hdl.handle.net/10539/20938.
Testo completoAbstract (sommario):
This paper aims to investigate the apparent existence of two anomalies in the South African stock market based on regular strike action, namely the month of the year effect and seasonality across specific sectors of the Johannesburg Stock Exchange.
45
"Market efficiency research on Shanghai stock market". 2002. http://library.cuhk.edu.hk/record=b5890949.
Testo completoAbstract (sommario):
by Mi Jia, Wang Xueyu.Thesis (M.B.A.)--Chinese University of Hong Kong, 2002.
Includes bibliographical references (leaves 77-78).
ABSTRACT --- p.III
TABLE OF CONTENTS --- p.iv
LIST OF TABLES AND FIGURES --- p.vi
Chapters
INTRODUCTION --- p.1
DATA AND RESEARCH METHODOLOGY --- p.6
EFFICIENCY TESTS --- p.12
Time Serial Correlation Analysis --- p.12
Seasonal Fluctuation --- p.16
General Index's analysis and comparison --- p.17
Holiday Effect --- p.20
Test of Predictability in Stock Market Returns --- p.35
Larger Stock in June effect --- p.37
Passive Vs Active portfolio (with technical analysis) --- p.39
Technical analysis --- p.40
Filter Rules Approach Testing --- p.43
Returns over Short and Long Horizons --- p.49
Holding Period Return over Short and Long Horizons --- p.50
Accumulative Abnormal Return over Short and Long Horizons --- p.51
Mutual Fund Performance --- p.52
Mutual Fund vs. Index --- p.53
Relative Performance among Mutual Funds --- p.54
"B/M, Size, and P/E Effect" --- p.55
"Correlation among B/M, Assets, Market Value of A Share, P/E and Beta" --- p.56
B/M and Annual Return --- p.57
P/E and Annual Return --- p.59
Assets and annual return --- p.60
Market Value of A Share and Annual Return --- p.61
Beta and Annual Return --- p.53
Multiple Regressions --- p.64
CONCLUSION --- p.66
Limitation of Research --- p.66
Summary --- p.67
APPENDIX 1 --- p.69
APPENDIX 2 --- p.70
APPENDIX 3 --- p.71
APPENDIX 4 --- p.72
APPENDIX 5 --- p.73
BIBLIOGRAPHY --- p.77
46
"Earnings announcements and common stock price behaviour in Hong Kong". Chinese University of Hong Kong, 1988. http://library.cuhk.edu.hk/record=b5885854.
Testo completo
47
"Empirical test of arbitrate pricing theory in Hong Kong stock market". Chinese University of Hong Kong, 1991. http://library.cuhk.edu.hk/record=b5886855.
Testo completoAbstract (sommario):
by Chan Chun-hung Benjamin.Thesis (M.B.A.)--Chinese University of Hong Kong, 1991.
Bibliography: leaves 103-105.
ACKNOWLEDGMENT --- p.i
ABSTRACT --- p.ii
TABLE OF CONTENT --- p.iv
LIST OF TABLE --- p.vii
CHAPTER
Chapter I --- INTRODUCTION --- p.1
Chapter II --- "THE THEORETICAL FOUNDATION OF THE CAPITAL ASSET PRICING MODEL, CAPM" --- p.3
Chapter III --- THE THEORETICAL FOUNDATION OF THE ARBITRAGE PRICING THEORY --- p.5
Chapter IV --- REVIEWS ON THE PREVIOUS STUDIES ON THE ARBITRAGE PRICING THEORY --- p.9
Tests for Identification of the Number of Factors --- p.10
Studies Supporting the APT --- p.10
Roll and Ross [1980] --- p.10
Chen [1983] --- p.12
Pari and Chen [1984] --- p.13
Chang and Lewellen [1985] --- p.15
Studies Opposing the APT --- p.17
Shanken [1982] --- p.17
"Dhrymes, Friend and Gultekins [1985]" --- p.17
The Gultekins [1987] --- p.18
Test for Identification of Economic Factors --- p.20
"Chen, Roll and Ross [1986]" --- p.20
Burmeister and Wall [1986] --- p.26
Sweeney and Warga [1986] --- p.27
Beenstock and Chan [1988] --- p.28
Chapter V --- THE FOUNDATION AND OBJECTIVE OF THE STUDY --- p.30
Chapter VI --- THE PROPOSITION OF POTENTIAL FACTORS --- p.35
The Rationale and Criteria of the Proposition --- p.35
Descriptions of the Proposed Factors --- p.38
Industrial Production (PI) --- p.38
Industrial Production of Major Trading Partners --- p.39
Exchange Rate (EERI) --- p.39
Confidence Level of the Investors in Hong Kong --- p.41
The Inflation Rate (CPI) --- p.42
Interest Rate and Term Structure --- p.43
Foreign Stock Market Performance --- p.44
Chapter VII --- STATISTICAL CHARACTERISTICS OF THE POTENTIAL FACTORS --- p.45
Intercorrelations of the Factors --- p.45
Autocorrelations of the Factors --- p.47
Chapter VIII --- METHODOLOGY --- p.50
Phrase One: The Test on the CAPM Model --- p.50
Phrase Two: The Test on the APT model with the Identification of Relevant Factors --- p.52
Phrase Three: Test of the CAPM Residual --- p.55
Chapter IX --- BASIC RESULTS AND INTERPRETATIONS --- p.57
Phrase One: The Test on the CAPM Model --- p.57
Beta Coefficient --- p.58
"Statistical Significance, R2" --- p.60
The Intercept Constant --- p.62
Phrase Two: The Test on the APT Model --- p.64
The Relevant Factors and the Betas --- p.64
Financial Sector --- p.65
Utilities Index --- p.65
Properties Index --- p.67
Hotels Index --- p.68
Industrials Index --- p.69
"Improvement in the Significance, R2" --- p.70
The Intercept Constant --- p.72
Phrase Three : Test of the Residuals of CAPM --- p.74
Chapter X --- CONCLUSION --- p.76
Chapter XI --- LIMITATIONS AND FURTHER IMPROVEMENTS --- p.79
APPENDICES
Chapter I --- The Constituent Stocks of the Hong Kong Index As of April1990 --- p.83
Chapter II --- Autocorrelations of the Sectorial Indices and Potential Factors --- p.85
Chapter III --- Output of Regression on Sectorial Returns with Returns on Market Portfolio (HKI) as Independent Variable --- p.96
Chapter IV --- Output of Regression (Stepwise) on Sectorial Returns with Factors as Independent Variables --- p.98
Chapter V --- Output of Regression (Stepwise) on Residual Variances of Sectorial Indices (CAPM) with Factors as Independent Variables --- p.101
BIBLIOGRAPHY --- p.103
48
簡志偉. "Developing a stock recommendation system by stock prices correlation". Thesis, 2007. http://ndltd.ncl.edu.tw/handle/08199024686939231574.
Testo completoAbstract (sommario):
碩士國立政治大學
資訊科學學系
95
The method to accumulate wealth changes during different times. Making the investment is a method that can accumulate the wealth quickly in 21st century. The improvement of the national income makes today's stock market of Taiwan activate recently. From the statistical data of Taiwan Stock Exchange Corporation (TSEC), the stock market has already become important financing channel of investor. People attempting to earn profits in stock market must pay attention to the change of the stock price. However, many factors widely influence the price of the stock and make the investors hard to predict. In recent years, the fast development of computer science makes the technology of data mining applied to the stock market. The advantage of data mining is that we can find out useful information in a large amount of information. The purpose of this research is to use the technology of data mining to look for buying time and selling time of the stocks. This research investigates the correlation between a single stock and other stocks. By using the historical data of the stocks to find out the correlation between stocks, and developing the rules to calculate a prediction value, the recommendation of the buying or selling time of a stock can be done. The training analysis in this paper is collected from March, 2004 to March, 2006 and the prediction time is from March, 2006 to March, 2007. The empirical result shows that: from the distribution analysis of the profit rate, the trade number of the times analysis, the buy-and-hold policy comparative analysis, and the positive profit rate analysis: in the four models discussed the index with the rule of vote performs better than the buy-and-hold policy.
49
"Underpricing of new stock issues in Hong Kong: phenomenon and underlying causes". Chinese University of Hong Kong, 1989. http://library.cuhk.edu.hk/record=b5886201.
Testo completo
50
Piyackis, Alessandra. "The effect of analysts' stock recommendations on shares' performance on the JSE securities exchange in South Africa". Thesis, 2016. http://hdl.handle.net/10539/20984.
Testo completoAbstract (sommario):
A research report submitted to the Faculty of Commerce, Law and Management at the University of the Witwatersrand in partial fulfilment of the requirements for the degree of MM in Finance and Investment
March 2015Individual investors often do not have access to share trading information and even if they do, they may not be able to understand or accurately interpret this information. Investors rely on financial analysts’ forecasts and stock recommendations in order to make profitable investment decisions. The role of the financial analyst is an important one with two key objectives: earnings forecasts and stock recommendations (Loh and Mian 2006). These financial analysts play a significant role in the efficient functioning of global stock markets. The aim of the financial analyst is to evaluate shares trading on the stock market and their future price appreciation or depreciation to develop new buy, hold or sell recommendations to maximize shareholder wealth. The extant literature recognizes that new buy, hold and sell recommendations made by financial analysts have a substantial impact on the market (Womack, 1996). Research on financial analysts has become prevalent in financial literature with the promotion of financial analysts to the level of integral economic proxies worthy of individual examination (Bradshaw, 2011). The aim of this research report is to investigate whether financial analysts’ stock recommendations enhance or destruct shareholder wealth. The extant literature on financial analysts’ stock recommendations and forecasts suggests that the analysts’ recommendations have both a significant and an insignificant effect on stock prices in the market following the months after the change in recommendation is made. The accuracy of the financial analysts’ stock recommendations are measured in the months following the change in recommendation through determining if the recommendation outperforms the market benchmark. This report examines the effects of analysts’ recommendations on the performance of stocks on the Johannesburg Stock Exchange and concludes through determining if the share underperforms or outperforms the market benchmark surmising that to a varying degree there is value to be found in financial analysts’ stock recommendations for the individual investor.