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This thesis examines Life Cycle Costing through a literature review and a fictional case study. It explores key challenges faced in implementing and utilizing Life Cycle Costing, proposes strategies for overcoming these challenges, and evaluates the potential impact of early integration of this technique on decision-making processes. Additionally, by use of the case study, the thesis exemplifies how Life Cycle Costing identifies trade-offs that would otherwise have remained unnoticed. The case study highlights how the implementation of the technique unveils that the option initially expected to be more costly turns out to be more economical. The findings underscore the superiority of the Life Cycle Costing methodology, questioning the narrow focus on immediate costs in traditional cost accounting, opening the door to a business model where long-term cost savings are recognized and valued.
Diese Bachelorarbeit beschäftigt sich mit der Forschungsfrage, wie die Materialwirtschaft die Kosten im Gastgewerbe beeinflusst und untersucht zudem, wie eine möglichst bessere Materialwirtschaft zu mehr Leistungsfähigkeit sowie Kostensenkung beitragen kann. Auf der Grundlage einer eingehenden Problemanalyse anhand eines Beispielrestaurants und einer gründlichen Untersuchung der theoretischen Herausforderungen im Gastgewerbe werden verschiedene Aspekte der Materialwirtschaft analysiert.
Die Forschungsmethode dieser Arbeit besteht aus einer empirischen Analyse und einem theoretischen Rahmen, wobei Daten aus dem Beispielrestaurant und aus relevanten Literaturquellen verwendet werden.
Die Ergebnisse der Analyse deuten darauf hin, dass saisonale Schwankungen, Wagniskosten sowie Abfallmengen und inflationsbedingte Kostensteigerungen erhebliche Herausforderungen für die Materialwirtschaft im Gaststättengewerbe darstellen.
Diese Untersuchung liefert bedeutende Erkenntnisse für die Gastronomen im Bereich der Materialwirtschaft und widmet sich als Grundlage für die Entwicklung neuer Strategien zur Kostenoptimierung und Leistungssteigerung im Gaststättengewerbe. Mit Hilfe dieser Erkenntnisse können Restaurantbetriebe ihre Rentabilität verbessern und zudem auf langfristiger Basis erfolgreich am Markt wirtschaften.
Die vorliegende Bachelorarbeit untersucht die aktuelle steuerliche Behandlung
von Kryptowährungen und Krypto-Assets im deutschen Steuerrecht von Privatpersonen
und aus gewerblicher Sicht und hat zum Ziel, deren steuerliche Besonderheiten
umfassend darzustellen. Dabei werden zunächst verschiedene Arten
und Transaktionen von Krypto-Assets erläutert und die rechtlichen Grundlagen
und steuerlichen Regelungen für den Umgang mit Krypto-Assets beleuchtet. Anschließend
werden verschiedene Steuerarten analysiert. Bei der Analyse wird die
Besteuerung von Gewinnen aus den verschiedenen Arten von Transaktionen mit
Krypto-Assets, wie dem Handel oder Einkünften aus Mining, Lending und Staking
in bestehende Steuerkategorien eingeordnet. Die Analyse trägt zu einem besseren
Verständnis der steuerlichen Herausforderungen im Zusammenhang mit
Krypto-Assets bei und bietet eine Orientierungshilfe für alle, die sich für Krypto-
Investitionen interessieren.
Unternehmenserfolg wird häufig durch die Subtraktion der Kosten vom Umsatz berechnet. Niedrigere Kosten tragen dabei maßgeblich zur Wirtschaftlichkeit von Unternehmen bei. Die Budgetierung ist ein beliebtes Werkzeug, Kosteneffizienz zu erzielen und die vorhandenen Mittel im Unternehmen optimal zu verteilen. In der Theorie werden dabei die verschiedensten Verfahren beschrieben, welche in der Unternehmenspraxis Anwendung finden. In dieser Arbeit wird die Umstellung von der traditionellen Budgetierung zu Zero-Base Budgeting für die Gemeinkosten im Privatkunden Geschäftsbereich bei Vodafone untersucht. Die Implementierung von Zero-Base Budgeting führte zu mehr Transparenz und Kostensensibilität in den Fachbereichen, war aber mit enormem Aufwand und Unklarheiten verbunden. Die Soll-Situation wurde durch die Anwendung von Optimierungspotentialen aus der Literatur formuliert und verspricht mehr Kosteneffizienz und weniger Unklarheiten durch die Einführung von Leistungsniveaus und einem Budgetschnitt. Mögliche Herausforderungen bei der Anwendung sind dabei die Annahme eines neuen Prozesses und die Durchführbarkeit von Leistungsniveaus und die Rangfolge der Entscheidungspakete.
The Bachelor Thesis examines the effects of the integration of environmental, social and governmental (ESG) criteria in equity funds on performance compared to conventional equity funds. For this purpose, a quantitative analysis is carried out which includes a detailed examination of 769 equity funds. The equity funds are divided into two different groups - ESG equity funds and conventional equity funds - and are analyzed for various financial ratios. The goal of the study is to illustrate the financial performance differences between ESG-focused equity funds and conventional equity funds and thus provide a scientific contribution to the academic debate on sustainable investments. Initially, the thesis delves into the central concepts of ESG, the historical development of investment funds, theoretical frameworks, and existing studies. The following analysis provides an insight into the relationship between ESG criteria and the performance of equity funds. It not only draws on two different ESG rating systems, but also provides a geographical breakdown. Although the work as a whole helps to develop a deeper understanding of sustainable investment and highlights potential implications for investors and the financial sector, the results of the analysis show that more research is needed in this area.
Analysis of Fintech Markets
(2023)
The technological advancement in the business sector, in particular in the banking world, forces the financial sector to adapt its services. The Fintech companies aim to cope with these advancements and change the money management for clients. The question that arises is how the FinTech companies have developed and if they are profitable. That is the reason for the research of the development of the Fintech companies theoretically and practically, focusing on their financial performance. The methodology used in this paper is for the first chapter gathering existing knowledge of previous studies and including law directives to underline the development and in the second chapter using the information available from the companies itself. One can conclude the development of the acceptance of digitalized banks have increased after the economic crisis in 2008. Furthermore, the regulatory systems have problems coping with the velocity of change and the income of new products and services. The practical analysis of the FinTech companies show, that they do have certain advantages for clients, but are not immune against economic volatility. Having analyzed existing companies is beneficiary for the research field, as for now no practical analysis of the companies have been done. Nevertheless, the limitation of this research is due to the fact of probable biased information from the companies.
The financial markets are currently facing uncertain circumstances, which is increasing their tail risk. A recent study was conducted to measure the tail connectedness between North America, Latin America, Europe, Asia, and Oceania. The study looked at 18 stock market indices using a neural network quantile regression approach from January 4, 2012, to May 5, 2022. The study found that the North American, European, and Latin American stock markets had the highest exposure to tail risk, while Asia and Oceania showed no significant risk compared to the rest of the world indices and were independent. The study also identified the Global Financial Crisis and the COVID-19 pandemic as intense events that yielded high tail risk. The Systematic Fragility Index ranked the pre-COVID period stock market and the Nasdaq during the COVID sample as the most susceptible markets. On the other hand, the Systematic Hazard Index identified the S&P as the chief risk contributor in the system.
Artificial intelligence is a disruptive technology, offering increasingly more opportunities to companies. However, the low digital maturity of the private banking sector, makes it hard for private banks to take advantage of this opportunity. Simultaneously, customers are expecting more digital solutions, forcing companies to adapt their services.
The aim of this paper is to provide an overview, drawing conclusions about whether the implementation of AI technologies is profitable in the private banking sector.
This thesis is based on recent research about current possible applications and the respective benefits, risks and costs. Two use cases will be thoroughly analysed: the application of automated credit risk management systems and AI powered indexes. In the first case, the software NOLA 2.0 will be evaluated and used as a benchmark to highlight the positive and negative aspects deriving from AI credit risk management software. In the second case, the AI powered index AiPEXAR will be presented and compared to the most common ETF S&P 500, analysing the differences in their computation and their performance over time.
The analysis concluded that, even though the benefits substantially depend on the individual company, AI chatbots, customers' engagement, credit risk management software and banking apps are advantageous for private banks. Yet, the implementation of AI powered indexes may be precocious and therefore not yet profitable. It can also be concluded that for private banks, whose core competitive advantage lies in the expertise of the relationship managers, the digitalization of advisory may lead to unsatisfied customers.
This Thesis analyses the difference in the impact of the issuance of a green bond on the stock prices of the issuing entity by country, using an event study approach of 135 green bonds, by comparing the actual daily returns of the event window with the expected returns calculated from the estimation window. With only a slight influence of the country found, further factors effecting the impact are considered. While we conclude that German issuers tend to see a stronger impact than most issuers from other European countries, factors such as the risk of greenwashing, time of issuance, industry, and firm fundamentals appear to skew this impact so that it is not possible to make a definitive statement about the impact of the country of origin on the effectiveness of green bond issuances at providing excess stock returns.
This thesis examines the relationship between environmental, social and governance (ESG) scores and portfolio returns using ordinary least squares (OLS) regressions and statistical tests. ESG scores were collected from Refinitiv Datastream between January 2007 and February 2023 and consist primarily of companies listed in the Standard & Poor's 500 (S&P 500) Index. The risk factors were calculated using data from Kenneth R. French’s data library. OLS regressions are used to estimate abnormal returns. The portfolios are created by dividing stocks into five equal quantiles and allocating them to five portfolios according to their ESG scores. The portfolios were then reconstructed each year based on the company's ESG rating. This analysis concludes that there is no significant evidence of abnormal returns for high-rated ESG portfolios. Instead, it shows that the portfolio with the lowest 20% ESG ratings outperformed all other portfolios, including the sample market, over the indicated period.