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This thesis examines returns around earnings announcements for companies with seasonality in earnings. Earnrank is used as a measure of seasonality where earnrank for a company is calculated quarterly by taking last five years of earnings data, ranking them and taking the average of the ranks for the respective quarter. For seasonal firms, we find robust evidence that abnormal returns are created when such firms announce their earnings for the highest seasonality quarter as measured by their earnrank. Additionally, the results were consistent for different time periods and abnormal returns were found to increase over time. We also performed the analysis industry-wise and found significant difference in returns for most and least seasonal firms in Manufacturing, Financial and Construction sectors. The results for Construction sector is in conflict to our hypothesis and require further exploration. We also study which kind of firms exhibit seasonality and found evidence for high seasonality in large firms, value firms, old firms, firms with lower turnover and firms with lower accruals. Lastly, we studied factors determining abnormal returns relative to the four-factor model and found size to be a significant explanatory variable. The long-short portfolio based on seasonality generated an alpha of 62 basis points per month. / Master of Science

The decisions of the federal government such as new legislation, bills and reforms can have serious implications for the financial markets, especially in terms of corporate profitability and shareholder value. As the overseers of federal agencies, U.S. Senators are arguably the most important participants in these decision making processes, in addition to being the most informed investors in the market. As such, Senators may be able to capitalize on their superior networks and information through stock trading. The portfolios traded on such insider information should generate abnormal returns against the market index. This study conducts an analysis of the abnormal returns on common stock purchases reported by U.S. Senators between 1995 and 2012. This paper recreates congressional buy portfolio using a consistent methodology throughout the entire sample period considered by earlier studies. While the sample size is reduced, the methodology used in this analysis relies on actual transactions dates to maximize accuracy. An analysis of the abnormal returns of the common stock investments of U.S. Senators during the period 1995 – 2012 shows that Senators are generally poor investors: purchases made by senators underperform the market index by approximately 3% a year.

One of the most controversial issues for long-term stock performance is whether the presence of anomalies is against the efficient market hypothesis. The methodologies to measure abnormal returns applied in the long-run event studies are questioned for their reliability and specification. This thesis compares three major methodologies via a simulation process based on the UK stock market over a period of 1982 to 2008 with investment horizons of one, three and five years. Specifically, the methodologies that are compared are the event-time methods based on models (Chapter 3), the event-time methods based on reference portfolios (Chapter 4), and the calendar-time methods (Chapter 5). Chapter 3 covers the event-time approach based on the following models which are used to estimate normal stock returns: the market-adjusted model, the market model, the capital asset pricing model, the Fama-French three-factor model and the Carhart four-factor model. The measurement of CARs yields misspecification with higher rejection rates of the null hypothesis of zero abnormal returns. Although the application of standard errors estimated from the test period improves the misspecification, CARs still yield misspecified test statistics. When using BHARs, well-specified results are achieved when applying the market-adjusted model, capital asset pricing model and Fama-French three-factor model over all investment horizons. It is important to note that the market model is severely misspecified with the highest rejection rates under both measurements. The empirical results from simulations of event-time methods based on reference portfolios in Chapter 4 indicate that the application of BHARs in conjunction with p-value from pseudoportfolios is appropriate for application in the context of long-run event studies. Furthermore, the control firm approach together with student t-test statistics is proved to yield well-specified test statistics in both random and non-random samples. Firms in reference portfolios and control firms are selected on the basis of size, BTM or both. However, in terms of power of test, these two approaches have the least power whereas the skewness-adjusted test and bootstrapped skewness-adjusted test have the highest power. It is worth noting that when the non-random samples are examined, the benchmark portfolio or control firm needs to share at least one characteristic with the event firm. The calendar-time approach is suggested in the literature to overcome potential issues with event-time approaches like overlapping returns and calendar month clustering. Chapter 5 suggests that both three-factor and four-factor models present significant overrejections of the null hypothesis of zero abnormal returns under an equally-weighted scheme. Even for stocks under a value-weighted scheme, the rejection rate for small firms shows overrejection. This indicates the small size effect is more prevalent in the UK stock market than in the US and the calendar-time approach cannot resolve this issue. Compared with the three-factor model, the four-factor model, despite its higher explanatory power, improves the results under a value-weighted scheme. The ordinary least squares technique in the regression produces the smallest rejection rates compared with weighted least squares, sandwich variance estimators and generalized weighted least squares. The mean monthly calendar time returns, combining the reference portfolios and calendar time, show similar results to the event-time approach based on reference portfolios. The weighting scheme plays an insignificant role in this approach. The empirical results suggest the following methods are appropriately applied to detect the long-term abnormal stock performance. When the event-time approach is applied based on models, although the measurement of BHARs together with the market-adjusted model, capital asset pricing model and Fama-French three-factor model generate well-specified results, the test statistics are not reliable because BHARs show severe positively skewed and leptokurtic distribution. Moreover, the reference portfolios in conjunction with p-value from pseudoportfolios and the control firm approach with student t test in the event-time approach are advocated although with lower power of test. When it comes to the calendar-time approach, the three-factor model under OLS together with sandwich variance estimators using the value-weighted scheme and the mean monthly calendar-time abnormal returns under equal weights are proved to be the most appropriate methods.

The purpose of this paper is to investigate the long-term share price effects for Swedish companies that employed repurchases programs during 2000 - 2012. This paper applies a trading strategy where the investor invests in stocks of compa-nies that engage in repurchase of their own equity. We test buy-and-hold abnormal returns versus two different proxies for the control firm, using small sample t-statistics. Abnormal returns for one to five years are insignificant under sta-tistic tests, using the supersector indices. In contrast, they are significant using a proxy for the market index as control firm. Factors hypothesized to contribute to this result are incon-clusive using our method of comparison. As a whole, we suggest that investing in companies that repurchase stock is a solid strategy: It is on par or better than index.

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In this thesis we analyze the financial performance of Football clubs following an initial public offering (IPO). We conduct several analyses using time series stock data with a focus on finding evidence of long-run underperformance and IPO over/underpricing. To this end, we estimate cumulative abnormal returns (CAR) and Jensen’s Alpha. We also analyze coefficients such as beta to describe the volatility and the link football clubs’ stocks have to the general market. We look at historical events that may have affected the movement of stock prices and confirm this by benchmarking an index (STOXX index) compiled of a number of European football teams. Our results show that football clubs do in fact follow the clear pattern of other entities and sectors and previous research with regard to underperformance in the long run. We find that football clubs’ stocks are less volatile than the general market and have a low beta. With regards to over/underpricing, we only obtain data for a few football clubs. We find small signs of underpricing but are not able to confirm that this is statistical significant due to the size of our sample.

The primary objective of this thesis is to investigate the value implications of the mergers and acquisitions deals initiated by the firms from the CEE region. We examine the sample of the 203 M&A announcements made by the bidder firms from the two major economies in the region-Poland and Russia-over the period 2006-2016. We apply the event study methodology to investigate the effect of the M&A announcement on the wealth of the acquirers' shareholders. The results demonstrate that on average investors of the Polish acquirers receive positive short-term wealth effect, while the investors of the Russian firms lose in short-term value. Our empirical findings provide partial support for the positive wealth effect when acquirers target the strategically important asset. Our results hold after controlling for the number of firm and transaction-specific characteristics. JEL Classification G14, G32, G34 Keywords mergers and acquisitions, event study, bidder gains, shareholder wealth effects, Central and Eastern Europe Author's e-mail lukashova.a.v@gmail.com Supervisor's e-mail kocenda@fsv.cuni.cz

The effectiveness of the PEG ratio as a valuation tool has been a topical debate between market commentators ever since being popularised by Lynch (1989). This study examines the appropriateness of the fair value criteria of 1.0 (PEGL) in comparison with a time-series based share specific benchmarking model (PEGT). Furthermore, influencing factors of analyst forecasting accuracy, namely: the number of analyst contributions, forecast dispersion and forecast horizon, were tested and compared using sub-set portfolios for each category with the objective of identifying a possible optimal PEG trading rule strategy. The outcome showed a consistent outperformance of PEGT portfolios compared to PEGL portfolios and the market benchmark. Unexpected results were obtained for the impact of analyst forecasts on the performance of the PEG ratio with additional literature review providing possible reasons that analyst optimism may have a more influencing impact on the PEG ratio than forecasting accuracy. Finally, an optimised PEG trading rule strategy delivered annual abnormal returns of 5.4% (CAGR: 19.7%) for a PEGL portfolio, versus that of 13.7% (CAGR: 28.5%) for a PEGT portfolio. The ensuing methodology appeared to single out small cap firms with above market growth prospects. Copyright / Dissertation (MBA)--University of Pretoria, 2010. / Gordon Institute of Business Science (GIBS) / unrestricted