http://hdl.handle.net/10900/53328 Tue, 12 May 2026 09:16:22 GMT 2026-05-12T09:16:22Z http://hdl.handle.net/10900/96531 Indicators of Disruption Potentials - Analysis of the Blockchain Technology’s Potential Impact Daxhammer, Rolf J.; Freistedt, Paul The goal of this paper was to answer the question whether blockchain has the potential to become a disruption according to Clayton Christensen’s disruption theory. Therefore, the theory and the five characteristics that define the process of disruption were outlined in the first part of the paper. That and the following explanation of the blockchain technology served as the basis for the analysis and evaluation in chapters four to seven. For the analy-sis, three applications of the DLT, namely payment methods, intermediaries, as well as data storage and transfer, were considered. The fulfillment of the five characteristics of disrup-tion was assessed using an example for each of the three applications. While the results of the analysis provide a general idea about the indicators of disruption for three applications of blockchain, they are not fully representative. Hence, even if the example of microgrids suggests that blockchain will probably not be disruptive for inter-mediaries, there is a fair chance that it could be in fields other than electricity. Moreover, to answer the question concerning whether the DLT will be disruptive, only three major fields of application were considered. However, the technology also has other forms of applica-tion, which might or might not reveal indicators of disruption. Another possible source of error is the assumption that characteristics of disruption are not fulfilled, as it is not possible to ultimately prove that something does not exist. Moreover, there is a chance that some of the sources are biased towards or against blockchain. This paper suggests that, in the financial services industry, too, the impact of blockchain will be significant. However, given the manifoldness of the services that are part of the industry, it cannot generally be concluded whether the DLT will disrupt the industry. For example, in services related to payment methods, blockchain is unlikely to follow disrup-tive pattern, despite the recent hype surrounding blockchain-based cryptocurrencies. How-ever, regarding data storage and transfer, the technology might as well follow disruptive pattern in the financial services industry just as the application of blockchain solutions has been doing in the healthcare industry. Tue, 17 Dec 2019 00:00:00 GMT http://hdl.handle.net/10900/96531 2019-12-17T00:00:00Z http://hdl.handle.net/10900/85539 Stages of a speculative bubble in the asset class Cryptocurrencies Daxhammer, Rolf J.; Facsar, Máté At the beginning of 2017 the price of one Bitcoin, one of the most popular Cryptocurrencies, was at barely 1.000 USD. By mid-December 2017 the price not only surged 20x to an all-time high (ATH) but the number of other Cryptocurrencies offered to the public increased to more than 1.500 raising 6.5 billion USD via initial coin offerings alone in 2017. One year after the All-Time-Highs, the Bitcoin price not only tumbled about 80 percent from its highs but it also fell below the estimated break-even price needed to make the mining process aka validation of Cryptocurrency transactions profitable. The following paper will follow Cryptocurrencies in their stages of a typical speculative bubble. Wed, 09 Jan 2019 00:00:00 GMT http://hdl.handle.net/10900/85539 2019-01-09T00:00:00Z http://hdl.handle.net/10900/73445 Financial Nudging – Verhaltenswissenschaftliche Ansätze für bessere Finanzentscheidungen Daxhammer, Rolf J.; Hagenbuch, Raphael Die vorliegende Arbeit thematisiert die Identifizierung und Darstellung von Ansätzen, wie man Menschen zu einem besseren Entscheidungsverhalten bei Finanzprodukten und -dienstleistungen bewegen kann. Hierfür werden sogenannte Nudges bei Krediten, Kreditkarten, Hypotheken, der Altersvorsorge und Aktien/Anleihen erläutert. Die Arbeit beginnt mit einer knappen Einführung in die Entscheidungstheorie. Danach wird die seit Jahrzehnten dominierende neoklassische Kapitalmarktheorie kurz erläutert und der Bogen zur jungen Disziplin der Behavioral Finance gespannt. Im Anschluss daran werden Verzerrungen und Heuristiken entlang des Entscheidungsprozesses aufgezeigt und erklärt. Das nächste Kapitel, „Libertärer Paternalismus“, bildet den theoretischen Rahmen für Nudging. Im letzten Kapitel werden Nudgingansätze bei Krediten, Kreditkarten, Hypotheken, der Altersvorsorge und Aktien/Anleihen dargestellt. Thu, 01 Dec 2016 00:00:00 GMT http://hdl.handle.net/10900/73445 2016-12-01T00:00:00Z http://hdl.handle.net/10900/69133 The Examination of a Profitability-Based Four-Factor Model to Explain Stock Returns: Empirical Evidence from the German Stock Market Daxhammer, Rolf J.; Kappler, Jonathan In a recent publication Novy-Marx (2013) finds evidence that the variable gross profitabil-ity has a strong statistical influence on the common variation of stock returns. He also points out that there is common variation in stock returns related to firm profitability that is not captured by the three-factor model of Fama and French (1993). Thus, this thesis aug-ments the three-factor model by the factor gross profitability and examines whether a prof-itability-based four-factor model is able to better explain monthly portfolio excess returns on the German stock market compared to the three-factor model of Fama and French (1993) and the Capital Asset Pricing Model (CAPM). Based on monthly stock returns of the CDAX over the period July 2008 to June 2014 this thesis documents four main findings. First, a significant positive market risk premium and a significant positive value premium can be identified. No evidence is found for a size or a profitability effect. Second, all included fac-tors have a strong significant effect on monthly portfolio excess returns. Third, the four-factor model clearly outperforms both the three-factor model of Fama and French (1993) and the CAPM in capturing the common variation in monthly portfolio excess returns. The CAPM performs worst. Finally, the results indicate that the three-factor model of Fama and French (1993) is somewhat better in explaining the cross-section of portfolio excess returns than the four-factor model. Again, the CAPM performs worst. Nevertheless, the four-factor model is considered to be an improvement over the three-factor model of Fama and French (1993) and the CAPM in determining stock returns on the German stock market. Fri, 01 Jan 2016 00:00:00 GMT http://hdl.handle.net/10900/69133 2016-01-01T00:00:00Z