Since the outbreak of the recent inancial crisis in 2007, central banks around the world have lowered interest rates while stock markets soared. On the example of North America, Europe, and Asia and in particular the United States, Germany, and China, the situation as of December 2015 is compared on the basis of economic theory and selected key performance indicators to the United States dot-com bubble in the nineties years of the twentieth century. Literature review ofers a complex general view on the issue of market bubbles with a historical review of the situation in 2007 and 2008. The only indication of a bubble can be found in the China Securities Index 300, more speciically in the technology sector. The further aim of the paper is related to analyse and compare returns of the explored indices among the regions and the sectors. On a broader level, the study inds that even though there are similarities, the current rise in indices does not qualify for an asset price bubble. Conclusion sums all the observed indings on both the levelsregional and national. Also, it ofers suggestions for discussion about the situation on the markets after the inancial crisis.
The economic crisis has forced managers of joint stock companies to look for short-term solutions for the sharp changes in stock prices of their companies. Even the companies of the V4 countries are not the exception. The authors have focused on those companies where have been used either reverse stock split or stock split. They analyzed the effects of the reverse stock split or stock splits on the abnormal returns of stocks. In this paper, the authors analyzed a dataset from 1993 until 2015 with 124 reverse stock splits and 184 stock splits in total focused on the stock market in V4. Based on their own research they conclude that when reverse stock splits were used stock returns significantly decreased one day around the announcement date. They conclude that managers of a company might use this instrument to move the stock price back to the optimal trading range outside of the penny stock area. In the case of stock splits, the authors concluded that the use of this tool results in a significant increase in the returns of a stock after the announcement date. However, the results are in contrast to some former studies which found no positive effect on the returns caused by stock splits. The authors conclude that managers of a company might use this instrument to transport information content of future (positive) performance of a company to the traders. Keywords: Vysegrad group countries, normal stock split, reverse stock split, abnormal returns. JEL Classification: G11, G23, G32
The intention of this paper is to provide new academic insights regarding an economically explainable valuation of transfer prices for European football players based on mathematical modeling. Football is the most popular sport in the world followed by approximately 3.5 billion people. The increasing commercialization and professionalization of the industry implies that every area of a football club is constantly put to the test for improvements. Especially after suffering financially under the consequences of the worldwide pandemic, clubs focus not only on sporting success but also on financial survival. Only financially stable clubs have the resources to be more successful. An expensive team does not have to be successful in terms of sports performance. However, a successful team in sports is expensive in the long run. Increasing digitalization offers new revenue potentials for football clubs that focus on selling merchandise in addition to gameday revenues and its media exploitation rights. However, player transfers have become increasingly important because these costs and revenues increased substantially in the relevance of a club’s financial situation. Regarding transfer costs, the question arises as to how transfer fees are determined and which factors have a major influence here. Clubs try to find new ways of evaluating the potential profit of player transfers to lower the risk of failed player investments. The aim of this article is to quantify the popularity of a football player in terms of his merchandising potential to amortize his transfer price. The mathematically formulated relationship calculates a reference value for a player, taking performance, age, number of customers purchasing merchandise, and player position into account. The information gained can be used by managers of European football clubs as a guide in transfer negotiations. For 6907 players of the European top leagues, we analyzed data in the period from 2003 to 2019. For 409 players in the season of 2018/2019 complete data sets were available, so that a model for calculating a theoretical transfer fee for a player during that season could be determined. The results of the study and the developed model suggest that, based on the available data, a football club should offer either one-year or three-year contracts to a transferred player, depending on the anticipated profit margin of merchandise sales and the quota of potential buyers of the products representing a percentage of the number of customers purchasing merchandise. This information gives football club’s management the chance to make better transfer decisions for the individual situation of the player and the club itself. Due to the increased importance of transfers on a football club’s financial performance, better transfer decision making leads to an improved financial stability of the respective clubs and eventually to sporting success.
Research background: Since the publication of Markowitz’ Portfolio Selection Theory, researchers and practitioners have been searching for the optimal structure of investment portfolios. An unlimited number of portfolio-based investment strategies have been created since 1952. However, none of these strategies seem to continuously generate overperformance over a long time period. This may also be due to the strong dynamics of economic development and other external factors. Purpose of the article: The aim of this article is to analyze which strategies are successful in generating winning portfolios in times of crisis. Three types of crises are considered: first, the bursting of the dot-com bubble in 2001, second, the financial crisis of 2008, and finally, the performance impact of the corona crisis. Methods: The data of the S&P 500 and STOXX Europe 600 companies are analyzed. The first step is the statistical review of the performance of companies in different periods with the focus on the analysis of the crisis years. Subsequently, the formation of portfolios is carried out according to known key figures such as high-low PE ratio, high-low market-to-book ratio, and others. In the form of a regression analysis, selected fundamental data are used to statistically check their relevance for performance. Findings & Value added: The results shows that all crises have similarities in certain factors. However, they also show that companies with a digital business model are able to manage crises better than those without a digital business model.
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