Thesis (Ph. D.)--University of Missouri-Columbia, 2007. / The entire dissertation/thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file (which also appears in the research.pdf); a non-technical general description, or public abstract, appears in the public.pdf file. Title from title screen of research.pdf file (viewed on September 28, 2007) Vita. Includes bibliographical references.

The use of gamification has increased in companies in recent years and is used among other things to accelerate learning, increase motivation and engagement. Gamification is defined as the use of game elements in a non-game context. This study aims to investigate whether the use of gamification raises the financial value of a company. The purpose of the study is to expand the knowledge of gamification so that it can be used more efficiently and more frequently in businesses. The research was conducted with an event study on companies that are listed on Nasdaq Stockholm. With the theory of the efficient market hypothesis as a foundation, investors' willingness to buy shares in a company as a direct measure of news publishing on a company's gamification use was examined. The result, which is based on 91 articles from Swedish news sources, illustrates that news about companies' use of gamification does not have a significant impact on their share price. Therefore, in line with the efficient market hypothesis, the news about gamification does not increase the value of the companies, which is the conclusion of this study. The result also shows that the choice of gamification technology or industry that the company is active in does not have an impact on the significance of the results. The study concludes that a correlation between gamification and a company's financial value may exist, although the results of this study indicate the contrary. / Användningen av gamification har ökat hos företag de senaste åren och används bland annat för att skynda på inlärning, höja motivation och öka engagemang. Gamification definieras som användandet av spelelement utanför en spelkontext. Denna studie syftar till att utforska om användandet av gamification höjer det finansiella värdet hos ett bolag. Anledningen till studien är att expandera kunskapen om gamification, för att det ska kunna användas effektivare och mer frekvent i företagande. Undersökningen genomfördes med en eventstudie på företag som är noterade på Stockholmsbörsen Nasdaq. Med teorin om den effektiva marknadshypotesen i grunden granskades investerares vilja att köpa aktier i ett bolag som en direkt åtgärd av nyheters publicering om ett bolags användande av gamification. Resultatet, som är baserat på 91 artiklar från svenska nyhetskällor, åskådliggör att nyheter om företags användande av gamification inte har någon signifikant påverkan på företaget aktiekurs. I linje med den effektiva marknadsanalysen, så har därför inte nyheterna om gamification ökat värdet på företagen, vilket också är denna studies slutsats. Resultatet visar även att val av gamficationteknik eller marknad som företaget är aktivt i inte har en påverkan på signifikansen av resultaten. Studien konkluderar att en korrelation mellan gamification och ett företags finansiella värde kan existera, även om resultaten från denna studie tyder på motsatsen.

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This paper researches the effects of choice of payment (cash and stock) and M&A type (technological and non-technological) on bidders’ performance. We investigate 500 events in Swedish market between 2005 and 2015. Moreover, we also control the size of firms and the value of takeovers. In this paper, we conduct an event study in order to generate abnormal returns for the bidders at and around the M&A announcement. This research generates statistically significant and positive abnormal returns for the bidders especially when deals are financed by shares. Moreover, we also find that the technological M&A brings about lower abnormal returns than non-technological M&A. When we control for payment choice in technological M&A, the result shows that technological M&A paid for in shares generates higher abnormal returns than technological M&A paid for in cash.

The use of statistical analysis has been prevalent in the sports gambling industry for years. More recently, we have seen the emergence of "adjusted statistics", a more sophisticated way to examine each play and each result (further explanation below). And while adjusted statistics have become commonplace for professional and recreational bettors alike, little research has been done to justify their use. In this paper the effectiveness of this data is tested on the most heavily wagered sport in the world – the National Football League (NFL). The results are studied with two central questions in mind: Does the market account for the information provided by adjusted statistics? And, can this data be interpreted to create a profitable betting strategy? First, the Efficient Market Hypothesis is introduced and tested using these new variables. Then, a betting model is built and tested.

The empirical data indicates that Generation Y generally has a very high average financial literacy. The rationality they exhibit in the mastery of financial information and tools does not affect their savings and investments. Instead, the investment behavior is given in expression by their character, but also demographic basis.

A thesis submitted to the School of Economic and Business Sciences, Faculty of Commerce, Law and Management, University of the Witwatersrand in fulfilment of the requirements for the degree of Doctor of Philosophy (Ph/D). Johannesburg, South Africa June 2016 / In recent years, the debate on market efficiency has shifted to providing alternate forms of the hypothesis, some of which are testable and can be proven false. This thesis examines one such alternative, the Adaptive Market Hypothesis (AMH), with a focus on providing a framework for testing the dynamic (cyclical) notion of market efficiency using South African equity data (44 shares and six indices) over the period 1997 to 2014. By application of this framework, stylised facts emerged. First, the examination of market efficiency is dependent on the frequency of data. If one were to only use a single frequency of data, one might obtain conflicting conclusions. Second, by binning data into smaller sub-samples, one can obtain a pattern of whether the equity market is efficient or not. In other words, one might get a conclusion of, say, randomess, over the entire sample period of daily data, but there may be pockets of non-randomness with the daily data. Third, by running a variety of tests, one provides robustness to the results. This is a somewhat debateable issue as one could either run a variety of tests (each being an improvement over the other) or argue the theoretical merits of each test befoe selecting the more appropriate one. Fourth, analysis according to industries also adds to the result of efficiency, if markets have high concentration sectors (such as the JSE), one might be tempted to conclude that the entire JSE exhibits, say, randomness, where it could be driven by the resources sector as opposed to any other sector. Last, the use of neural networks as approximators is of benefit when examining data with less than ideal sample sizes. Examining five frequencies of data, 86% of the shares and indices exhibited a random walk under daily data, 78% under weekly data, 56% under monthly data, 22% under quarterly data and 24% under semi-annual data. The results over the entire sample period and non-overlapping sub-samples showed that this model's accuracy varied over time. Coupled with the results of the trading strategies, one can conclude that the nature of market efficiency in South Africa can be seen as time dependent, in line with the implication of the AMH. / MT2017

A research report submitted to the School of Economic and Business Sciences, Faculty of Commerce, Law and Management, University of the Witwatersrand, in partial fulfilment (50%) of the requirements for degree of Master of Commerce in Finance. March 2016 / This study attempts to determine the possible effects of individualism on industry volatility. The implications of this for behavioural finance are extensive, showing firstly that different industries react differently to behavioural biases and secondly that overconfidence is a possible driver of the positive effect of individualism on industry volatility. The country selection process was relatively objective, taking two countries with high individualism indexes and two with low indexes and including one with a medium index value. The result was a sample of the United States of America, the United Kingdom, South Africa, China and Taiwan. The industry selection process was more subjective. Industries were selected which should have a higher propensity to behavioural biases with lower book to market ratios (software and computer services industry and pharmaceutical and biotechnology industry) and other industries which should not be as strongly affected by behavioural biases (banks, mining, oil and gas producers, and mobile telecommunications industries). In order to correct for ARCH effects the series’ were modelled using a GARCH (1, 1) model. The resulting residuals, which showed no autocorrelation, were then used to conduct panel data regressions on each of the industries. The results confirmed that individualism had a positive effect on volatility in the industries which were expected (software and computer services and pharmaceuticals and biotechnology industries). However, it was also determined that the banks industry was significantly affected by individualism, an effect which it was hypothesised, was due to the individualism of employees as opposed to investors. / MT2017

Value and momentum strategies have been heavenly researched in financial academic literature. In this essay, different portfolios based on value and momentum strategies have been constructed to examine if it is possible to exploit market anomalies to outperform market returns. Both value and momentum is seen as two market anomalies according to earlier literature. The test were made on the Swedish market, and all data were collected from the Nasdaq OMX Stockholm Large Cap list. The findings includes a significant outperformance of market returns in nearly all portfolio tested, as well as lower standard deviations for some. However, an empirical asset pricing model, based on four factors from the Swedish market were constructed to seek explanation for the results. Overall the factor variables were rejected on their statistical significances, except for the market factor which were statistical significant for all portfolios except one.