This thesis consists of three parts: a genetic fuzzy trading model for stock trading, incremental intraday information for financial time series forecasting, and intraday effects in conditional variance estimation. Part A investigates a genetic fuzzy trading model for stock trading. This part contributes to use a fuzzy trading model to eliminate undesirable discontinuities, incorporate vague trading rules into the trading model and use genetic algorithm to select an optimal trading ruleset. Technical indicators are used to monitor the stock price movement and assist practitioners to set up trading rules to make buy-sell decision. Although some trading rules have a clear buy-sell signal, the signals are always detected with 'hard' logical. These trigger the undesirable discontinuities due to the jumps of the Boolean variables that may occur for small changes of the technical indicator. Some trading rules are vague and conflicting. They are difficult to incorporate into the trading system while they possess significant market information. Various performance comparisons such as total return, maximum drawdown and profit-loss ratios among different trading strategies were examined. Genetic fuzzy trading model always gave moderate performance. Part B studies and contributes to the literature that focuses on the forecasting of daily financial time series using intraday information. Conventional daily forecast always focuses on the use of lagged daily information up to the last market close while neglecting intraday information from the last market close to current time. Such intraday information are referred to incremental intraday information. They can improve prediction accuracy not only at a particular instant but also with the intraday time when an appropriate predictor is derived from such information. These are demonstrated in two forecasting examples, predictions of daily high and range-based volatility, using linear regression and Neural Network forecasters. Neural Network forecaster possesses a stronger causal effect of incremental intraday information on the predictand. Predictability can be estimated by a correlation without conducting any forecast. Part C explores intraday effects in conditional variance estimation. This contributes to the literature that focuses on conditional variance estimation with the intraday effects. Conventional GARCH volatility is formulated with an additive-error mean equation for daily return and an autoregressive moving-average specification for its conditional variance. However, the intra-daily information doesn't include in the conditional variance while it should has implication on the daily variance. Using Engle's multiplicative-error model formulation, range-based volatility is proposed as an intraday proxy for several GARCH frameworks. The impact of significant changes in intraday data is reflected in the MEM-GARCH variance. For some frameworks, it is possible to use lagged values of range-based volatility to delay the intraday effects in the conditional variance equation. / Ng, Hoi Shing Raymond. / Adviser: Kai-Pui Lam. / Source: Dissertation Abstracts International, Volume: 72-01, Section: B, page: . / Thesis (Ph.D.)--Chinese University of Hong Kong, 2010. / Includes bibliographical references (leaves 107-114). / 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 Company, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstract also in Chinese.

Almost two decades after the burst of the Dot-com bubble, investors are opinionated as to whether a new technology bubble has formed in the equities market. Similar to the late 1990's and early 2000's, many Internet firms today go through initial public offering without yet turning over a dollar of earnings, but boast certain revenue-associated performance metrics to investors promising of future success. However, investors are known to hold sentiments sensitive to earnings announcements (Seok, Cho & Ryu, 2019) and reward firms which meet or beat earnings with higher stock returns (Bartov, Givoly & Hayn, 2002). That raises a question on the content of earnings announcements: Besides earnings and cash flow, are there other factors that may influence investor decisions to trade some Internet stocks? My primary hypothesis is that the voluntary disclosure of specific non-financial key performance indicators (NFKPI) during earnings announcement by Internet firms influences the investors' investing/trading decisions. My motivation for this research is to understand better whether there is a strategic element in the voluntary disclosure of NFKPI in Internet companies and how it may impact investors' decisions. The results could be useful to firms in their evaluations of whether to release NFKPI or similar information and to equity research analysts as well as investors in measuring their expectations and valuations of the firms' stocks. The intention of the study is not to generalize the findings to the full market, as the number of companies with the practice of voluntary disclosure of NFKPI is comparatively few compared to those without the practice. Instead, this study examines the effects of NFKPI on the stock returns of those companies which choose to disclose it. I use event study methodology to test the statistical significance of disclosure of NFKPIs during earnings announcements. By controlling for earnings surprise and other meaningful financial ratios, I also examine how the signaling effect of NFKPI could be distinguished from the signaling effects of important information concurrently released during earnings announcements. I focus on two types of NFKPI within the Internet industry: Gross Bookings for online booking agency services and Daily Active Users for social media. As earnings reports and quarterly filings often do not necessarily come together on the same date, I hand-collected data to estimate the surprise effect of NFKPI per earnings announcement, by using available broker forecasts of the respective NFKPI as a proxy for the investor's NFKPI expectation. The results show that while revenue surprise remains consistently the most influential variable to investors, NFKPI Surprise has a positive, statistically significant relationship with the firm's abnormal returns. Additionally, despite being insignificant when expected earnings is beat or in line with consensus, NFKPI Surprise is found statistically significant with a positive relationship to abnormal returns when expected earnings is missed. In line with existing research on management's motivation to prevent negative earnings surprises (Matsumoto, 2002), these findings imply that if firms could employ the voluntary disclosure of NFKPI to manipulate investors' impression and to cushion their stock prices against potential negative market reactions when earnings is missed.

本研究的主旨在探討台灣證卷交易市場之上市公司辦理現金增資時採用不同承銷配售方式下各種資訊內涵差異，研究樣本包括民國八十四年至民國八十六年間，曾在台灣證卷交易市場宣告辦理現金增資之 278 家公司，其中又區分為 201 家採公開申購配售方式及 77 家採詢價圈購配售方式之現金增資公司樣本。本研究鑑於民國 84 年新版承銷配售制度施行以來，現金增資採行詢價圈購配售方式之公司股價出現特定人套利現象，甚至引發立法院於民國 86 年底，提出修正法案欲將詢價圈購提撥比率之但書規定廢除事件，故本研究目標將著重於探討公開申購配售與詢價圈購兩種不同承銷配售方式來現金增資之公司間其財務屬性及其對股價之影響是否有差異，以檢驗現行的詢價圈購制度是否有缺失。 實證結果顯示：採兩種不同承銷配售方式現金增資之公司，其財務變數並無顯著差異，顯示公司的財務特質並不影響其承銷配售方式的選擇。經由股價反應的驗證則發現採公開申購配售及詢價圈購承銷配售方式之現金增資之公司，其發行宣告首次見報時對股價異常報酬均有顯著正面的影響。但兩者對股價異常報酬之影響於統計上卻發現有顯著差異。至於在首日申購（圈購）日時之股價異常報酬反應，採公開申購配售者為顯著正股價異常報酬反應，採詢價圈購者股價異常報酬則為顯著負反應，因此兩者在首日申購日時對股價之反應有顯著差異，採公開申購配售公司之股價異常報酬反應明顯優於採詢價圈購配售公司。而於發行日時之價格異常報酬反應，採公開申購配售公司並不顯著，採詢價圈購配售方式公司卻有正向股價異常報酬反應，兩種承銷配售方式於發行日時顯示顯著的股價異常報酬反應差異。 兩種承銷配售方式為公司以現金增資向股東或投資大眾取得資金的途徑，其最終目的均相同，因此不同配售方式對股價異常報酬之影響應不會有太大差異，但本研究卻發現在首次宣告日、首日申購日及發行日時三種不同事件日下，兩種配售方式之股價異常報酬反應卻出現顯著差異的情形。由於此一差異與公司的財務特質無關，所以顯示詢價圈購配售方式可能存有缺失，造成特定人可藉由現行制度的漏洞來進行套利或取得比以往更多的新股，因此對於無法進行套利或取得新股的股東而言，現行的詢價圈購制度並不公平，確實有改善之必要。 / The study is based on a sample, consisting of 278firms, of the announcements of SEO(seasoned equity offerings) in Taiwan stock market during the period from Jan. 1996 to Dec. 1997, to detect whether the current circling system in TW is not proper. There are two major SEO underwriting procedures in TW: by offer=for-sales and by circling. The paper focuses on two types of firms which adapt different SEO underwriting. By comparing the both firms' financial characteristics and stock price responses, we know if the existing system is fair. The evidence shows that 89% financial ratios (in the research) of firms, adapting different underwriting procedures, don't have statistically significant positive abcdrmal returns for both underwriting procedures and the reaction levels for both are different. During the circling procedure, circling firms' stock price response is significantly negative but is significantly positive for offer-for- sales firms'. It's very clear that the latter firms have the better stock price performance than the former. During the days of offerings, circling firms' stock price response is significant positive but is not significant negative for offer-for sales firms'. In the research, we can be sure that these two SEO underwriting procedures are significantly different in all of three event days. Since the different market responses are not associated with firms' financial characteristics, we now can be sure that current circling system exist some problems. The system may provide some big stockholders having chances to arbitrage and to get more newissuing shares then they should have. To the other stockholders who can't engage in arbitraging and get new issuing shares, the existing circling system is unfair.

<p>This study is based on three models, Markov model, Hidden Markov model and the Radial basis function neural network. A number of work has been done before about application of these three models to the stock market. Though, individual researchers have developed their own techniques to design and test the Radial basis function neural network. This paper aims to show the different ways and precision of applying these three models to predict price processes of the stock market. By comparing the same group of data, authors get different results. Based on Markov model, authors find a tendency of stock market in future and, the Hidden Markov model behaves better in the financial market. When the fluctuation of the stock price index is not drastic, the Radial basis function neural network has a nice prediction.</p>

<p>Marknadens reaktion när ett företag informerar och annonserar om en eventuell nyemission sägs vara oförutsägbar. Enligt tidigare forskning pressas aktiekursen i de flesta fallen nedåt vid en nyemission. Under det senaste året har en del nyemissioner utförts i synnerhet på grund av den globala lågkonjunkturen då många företag haft för lite kapitalbas. Vad gäller företag på Stockholmsbörsen som valt att nyemittera aktier har även här de flesta fått se sin aktiekurs rasa.<strong><em></em></strong></p><p>Författarna till denna uppsats avser att studera hur marknaden reagerar på ett offentligt tillkännagivande av en kommande nyemission. Det undersöks även om det förefaller någon skillnad mellan tillkännagivanden av nyemissioner genomförda innan eller under lågkonjunkturen och skillnader branscher emellan.<strong><em></em></strong></p><p>Då vi ville se hur denna händelse påverkar ett företags aktiekurser valde vi att göra en eventstudie. En eventstudie ger oss möjligheten att mäta effekten av en specifik händelse. Datainsamlingen har endast bestått av sekundärdata som vetenskapliga artiklar, litteratur, tidigare forskning samt elektroniska databaser så som Avanza och OMX. Vi valde att ta med alla de företag som under tidsperioden 2005-01-01 till 2009-04-01 annonserat om en nyemission och som i dagsläget fortfarande är noterade på OMX, Stockholmsbörsen.<strong><em></em></strong></p><p>I studien ingick 21 tillkännagivanden varav hela 13 stycken, ca 62 % av dem, resulterade i en negativ kursreaktion och avkastning. Fyra av åtta tillkännagivanden om nyemission som offentliggjordes innan lågkonjunkturen uppvisade en nedåtgående kursreaktion på annonseringsdagen och därmed en negativ abnormal avkastning. Denna trend fortsätter att hålla i sig då även nio av 13 tillkännagivanden under lågkonjunkturen, visade på en negativ abnormal avkastning.</p><p> </p><p> </p><p> </p> / <p>The market reaction when a company provides information about a possible equity issue is said to be unpredictable. According to previous research the stock price, in most cases, is pushed downward in case of an equity issue. Over the past year some equity issues has been implemented particular because of the global recession. This because many companies experience too small funds. As for companies on the Stockholm Stock Exchange that have chosen to do an equity issue most of them had also experienced a decline in the stock price.<strong><em></em></strong></p><p>The authors of this essay intend to study how the market reacts to a public announcement of an upcoming equity issue. They would also like to know if there is any differences between the announcements of an equity issue that's been done before or during the recession and if there is any differences between industries.<strong><em></em></strong></p><p>Thus we wanted to see how equity issues affect a company's stock price, we have chosen to do an event study. An event study enables us to measure the effect of a specific event. The data that we been using has only consisted of secondary data as scientific articles, literature, previous research and electronic databases such as Avanza and OMX. For our study we have chosen to include all of the companies that during the period 2005-01-01 to 2009-04-01 announced about an upcoming equity issue and are still listed at the OMX, on the Stockholm Stock Exchange.<strong><em></em></strong></p><p>The study included 21 public notices of which entirely 13 of them, about 62 %, resulted in a negative rate reaction and return. Four of the eight notices about an equity issue, which was announced before the recession, resulted in a declining rate reaction on the day of the announcement and also had a negative abnormal return. This trend continues thus nine of 13 notices, which announced an equity issue during the recession, also showed a negative abnormal return.</p><p> </p><p> </p><p> </p>

Marknadens reaktion när ett företag informerar och annonserar om en eventuell nyemission sägs vara oförutsägbar. Enligt tidigare forskning pressas aktiekursen i de flesta fallen nedåt vid en nyemission. Under det senaste året har en del nyemissioner utförts i synnerhet på grund av den globala lågkonjunkturen då många företag haft för lite kapitalbas. Vad gäller företag på Stockholmsbörsen som valt att nyemittera aktier har även här de flesta fått se sin aktiekurs rasa. Författarna till denna uppsats avser att studera hur marknaden reagerar på ett offentligt tillkännagivande av en kommande nyemission. Det undersöks även om det förefaller någon skillnad mellan tillkännagivanden av nyemissioner genomförda innan eller under lågkonjunkturen och skillnader branscher emellan. Då vi ville se hur denna händelse påverkar ett företags aktiekurser valde vi att göra en eventstudie. En eventstudie ger oss möjligheten att mäta effekten av en specifik händelse. Datainsamlingen har endast bestått av sekundärdata som vetenskapliga artiklar, litteratur, tidigare forskning samt elektroniska databaser så som Avanza och OMX. Vi valde att ta med alla de företag som under tidsperioden 2005-01-01 till 2009-04-01 annonserat om en nyemission och som i dagsläget fortfarande är noterade på OMX, Stockholmsbörsen. I studien ingick 21 tillkännagivanden varav hela 13 stycken, ca 62 % av dem, resulterade i en negativ kursreaktion och avkastning. Fyra av åtta tillkännagivanden om nyemission som offentliggjordes innan lågkonjunkturen uppvisade en nedåtgående kursreaktion på annonseringsdagen och därmed en negativ abnormal avkastning. Denna trend fortsätter att hålla i sig då även nio av 13 tillkännagivanden under lågkonjunkturen, visade på en negativ abnormal avkastning. / The market reaction when a company provides information about a possible equity issue is said to be unpredictable. According to previous research the stock price, in most cases, is pushed downward in case of an equity issue. Over the past year some equity issues has been implemented particular because of the global recession. This because many companies experience too small funds. As for companies on the Stockholm Stock Exchange that have chosen to do an equity issue most of them had also experienced a decline in the stock price. The authors of this essay intend to study how the market reacts to a public announcement of an upcoming equity issue. They would also like to know if there is any differences between the announcements of an equity issue that's been done before or during the recession and if there is any differences between industries. Thus we wanted to see how equity issues affect a company's stock price, we have chosen to do an event study. An event study enables us to measure the effect of a specific event. The data that we been using has only consisted of secondary data as scientific articles, literature, previous research and electronic databases such as Avanza and OMX. For our study we have chosen to include all of the companies that during the period 2005-01-01 to 2009-04-01 announced about an upcoming equity issue and are still listed at the OMX, on the Stockholm Stock Exchange. The study included 21 public notices of which entirely 13 of them, about 62 %, resulted in a negative rate reaction and return. Four of the eight notices about an equity issue, which was announced before the recession, resulted in a declining rate reaction on the day of the announcement and also had a negative abnormal return. This trend continues thus nine of 13 notices, which announced an equity issue during the recession, also showed a negative abnormal return.

This study is based on three models, Markov model, Hidden Markov model and the Radial basis function neural network. A number of work has been done before about application of these three models to the stock market. Though, individual researchers have developed their own techniques to design and test the Radial basis function neural network. This paper aims to show the different ways and precision of applying these three models to predict price processes of the stock market. By comparing the same group of data, authors get different results. Based on Markov model, authors find a tendency of stock market in future and, the Hidden Markov model behaves better in the financial market. When the fluctuation of the stock price index is not drastic, the Radial basis function neural network has a nice prediction.

This study discusses about the relationships between the qualities of collateralized shares by the broad of directors and the bank performance. In this study, we focus on the quantitative indicators of collateralized shares. Base on individual collateralization data, we build up the sets of the loans permitted by banks. In additon, this study is based on the multiple regression model to find out the relationships between the qualities of the collateral loans and the bank performance. By the conclusion, this study tries to give some advice to the banks about measuring the loans with collateralized shares. There are few conclusion of this study: 1. The stocks with higher price volatility are not good collaterals. The banks which have the loan with the collaterals with higher price volatility usually have bad proformance. The banks should pay attension to this indicator. 2. The collaterals are better with high ¡¥market price-to-book value¡¦. 3. By literature review, the higher proportion of collateralized shares by the broad of directors, the shares seem to be the worse collaterals for the banks. However, in this study, we find out some trade-off relationship between the profit and the risk in measuring this indicator.

In security markets, the stock price movements are closely linked to the market information. For example, the subprime mortgage triggered a global financial crisis in 2007. Drops occurred in virtually every stock market in the world. After the Federal Reserve took several steps to address the crisis, the stock markets have been gradually stable. Reaction of the traders to the arrival information results in different patterns of the stock price movements. Thus pattern matching is an important subject in future movement prediction, rule discovery and computer aided diagnosis. In this research, we propose a pattern matching procedure to seize the similar stock price movements of two listed companies during one day. First, the algorithm of searching the longest common subsequence is introduced to sieve out the time intervals where the two listed companies have the same integrated volatility levels and price rise/drop trends. Next we transform the raw price data in the found matching time periods to the Bollinger Band Percent data, then use the power spectrum to extract low frequency components. Adjusted Pearson chi-squared tests are performed to analyze the similarity of the price movement patterns in these periods. We perform the study by simulation investigation first, then apply the procedure to empirical analysis of high frequency transaction data of NYSE.

Financial Derivatives are one of the most popular and emerging innovations in the field of financial engineering. Since their inception, there has been a phenomenal growth in the volumes of derivatives traded all over the world. Financial markets are known to be extremely volatile and derivatives provide a way of eliminating or reducing the risks involved in these markets. Since these instruments derive their value from some underlying asset, trading in these instruments is bound to affect the underlying assets. Thus it becomes important to examine what these effects are and whether they have been favourable or detrimental to the underlying stock markets specially when there has been an explosive growth of these financial derivatives all over the world. This issue gains more importance in the case of emerging markets like India as they try to be more competitive and efficient as the developed Western markets. This thesis mainly deals with looking at this impact on the Indian stock markets. The Indian markets still being very new in this area, not many studies have been reported here related to this issue. The main focus of this thesis is to provide some more evidence on the impact of one kind of derivative instrument, namely options on different characteristics of underlying stocks in the Indian stock market. The thesis has the following objectives: • To examine the impact of option introduction on the price of underlying stocks in National Stock Exchange (NSE). • To examine the impact of option introduction on the volatility of underlying stocks in NSE • To examine the impact of option introduction on liquidity of underlying stocks in NSE NSE introduced derivatives beginning with index futures on June 12, 2000, followed by index options on June 4, 2001, options on individual securities on July 2, 2001 and finally futures on individual securities on November 9, 2001. Due to the temporal proximity of the introduction of index options and individual options, there exists a possibility of an interaction of these two effects. This problem is solved by a judiciously chosen sampling design. In particular, three groups of stocks are considered. The first group consists of stocks on which options were first introduced on 2nd July 2001 and thus would exhibit a combined effect of the two events if any. The second group consists of stocks on which options were introduced much later and therefore would show effects of individual option introduction if any. The third group comprises of nonoptioned stocks whose returns are considered around the date of index option introduction and thus would show effects of index option alone if any. To separate the two effects an ANOVA/ Logistic Regression model is used. An objective selection of the event and estimation windows is done using a Bayesian Change Point Analysis. The first part of the thesis looks at the effect of option introduction on the price of underlying stocks. A standard event study methodology as has been used in the literature is employed for this purpose. The study does not find any significant effect of option introduction on the prices. The second part of the thesis deals with the effect on volatility. Volatility is measured as the risk of a stock and as is done in the literature, three kinds of risk are looked at: total risk, systematic risk and the unsystematic risk. In case of the total risk, an F-test and an Ansari Bradley test is used to check for changes in the variance and scale parameters of market-adjusted continuously compounded returns of the stocks before and after option introduction. The results of these tests are recorded as a categorical variable taking on the value 0 for no change and 1 for a change and a Binomial Logistic Regression is used to separate the effects of the two events. Furthermore, after recording the results of the above mentioned tests as a categorical variable with three categories (0, 1, -1), a Multinomial Logistic Regression is also used in order to estimate the direction of the change (increase, decrease or no change). The ratios of after to before total risks are also analyzed using an ANOVA model. The systematic risk is measured using three kinds of betas – OLS betas, Scholes-Williams betas and Fowler-Rorke betas. The differences in the before and after betas of every stock are modelled using an ANOVA model in order to separate the two effects as well as the interaction effect. The unsystematic risk is estimated by the conditional variances and the unconditional variances of ARMA and ARMA-GARCH models fitted to market model excess returns. The ANOVA model is used here as well. In addition to this, the before and after ARCH and GARCH coefficients of GARCH (1, 1) models fitted to the excess returns are also compared using the ANOVA model. The results indicate that individual options are leading to a decline in total risk however index options are causing an increase in total risk. The interaction effect is significant in this case thereby causing an increase in total risk in the Group I stocks. The OLS betas indicate that individual option introduction seems to have increased the systematic risk. The Scholes-Williams betas indicate that index option introduction seems to have increased the systematic risk. The Fowler Rorke betas on the other hand, do not show any significant impact of individual option or index option introduction. For all the three betas index options introduction seems to have no effect on the systematic risk. Though the interaction effect seems to be significant in all the three cases, it however does not significantly affect the systematic risk in Group I stocks. As regards the unsystematic risk, both the conditional and unconditional variances of ARMA models show a significant reduction for individual option introduction but index options do not have any significant impact on either one of these measures. In case of unconditional variances of ARMA-GARCH models, none of the effects come out as significant. While comparing the news and persistence coefficients of GARCH (1, 1) models, the news coefficients indicate that the due to index option introduction, stocks are becoming more efficient in terms of absorbing the news more rapidly. No significant effect of either event is found on the persistence coefficients. The last part of the thesis deals with the liquidity issue. Liquidity has been measured using two measures – relative volume (based on daily data) and implicit bid-ask spread given by Roll (1984) (calculated from intra-day data). In case of the liquidity measures, the Logistic Regression models are used i.e. a categorical variable with two or three categories obtained from the results of a Wilcoxon Rank Sum test for comparing the median volume and spread before and after option introduction, is used. It is found that for the relative volume, individual option introduction has led to a favourable effect in terms of increasing the volume post introduction of options; however index options seem to have had a negative effect. As for the spread, index options seem to have had a stabilizing influence on the underlying stocks than the individual options.