Reutlinger Diskussionsbeiträge zu Finanz- und Rechnungswesen
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2019-1
Indicators of disruption potentials - analysis of the blockchain technology’s potential impact
(2019)
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 analysis, 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 disruption was assessed using an example for each of the three applications.
Additionally, the paper might serve as a basis for future research on the topic, once the technology develops further, since it is generally hard to tell whether the fourth and fifth characteristics are fulfilled by blockchain at this point. Therefore, the results of the paper also back criticism of Christensen’s theory regarding its usefulness for predictions.
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 disruptive pattern, despite the recent hype surrounding blockchain-based cryptocurrencies. However, 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.
2018-1
In this article we would like to link certain developments of the Cryptocurrency price movement to the five characteristic phases speculative bubbles undergo according to US economists Charles Kindleberger and Hyman Minsky, who developed the respective framework in "Manias, panics and crashes" (1978). Although every speculative bubble is somewhat different, they tend to follow five phases.In addition, we would like to answer the question how speculative bubbles develop and why they suddenly collapse.
2016-2
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.
2016-1
In a recent publication Novy-Marx (2013) finds evidence that the variable gross profitability 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 augments the three-factor model by the factor gross profitability and examines whether a profitability-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 factors 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.
2015-1
Oldtimer als Wertanlage
(2015)
Der Oldtimermarkt hat sich in den Jahren 2007-2013 äußerst positiv entwickelt. In diesem Markt mit zunehmender wirtschaftlicher Relevanz sind die Preise in den letzten Jahrzehnten kontinuierlich gestiegen. Der Markt ist sehr vielschichtig und setzt sich aus einer Vielzahl von Akteuren auf der Angebots- und Nachfrageseite zusammen. Das gehandelte Gut, der Oldtimer, kann in zahlreiche Kategorien unterteilt werden und dies macht den Markt sehr komplex und z.T. unübersichtlich. Im Oldtimermarkt herrschen keine normalen Marktpreise wie etwa bei börsengehandelten Papieren. Oldtimerpreise basieren auf Schätz- und Transaktionswerten, werden im Endeffekt aber von dem Oldtimer - „Liebhaber“ bestimmt. Außerdem führen diverse Faktoren zu unterschiedlichen Preisen für identische Fahrzeugmodelle. Dies ist auch durch die Intransparenz des Marktes bedingt, da die meisten Transaktionen privat geschehen und die Informationen nicht für die breite Öffentlichkeit zugänglich gemacht werden. Nur etwa ein Fünftel aller Transaktionen wird über Auktionshäuser und Händler abgewickelt. Weitere Probleme des Marktes sind eine geringe Liquidität und ein erschwerter Marktzugang. Die Datensammlung über den Oldtimermarkt hat sich in den letzten Jahren allerdings stetig verbessert. Es sind inzwischen einige Oldtimer-Indizes entstanden, welche die Wertentwicklung der Oldtimer abbilden. Diese Indizes weisen einen durchweg positiven Trend auf und schlagen Börsen-Indizes wie bspw. den DAX. Nichtdestotrotz können diese Oldtimer – Indizes täuschen, da in ihnen nur ausgewählte Fahrzeuge enthalten sind und Unterhaltskosten nicht berücksichtigt werden. Korrelationsberechnungen belegen, dass die Asset – Klasse “Oldtimer“ eine geringe bzw. negative Korrelation zu anderen Anlagen besitzt. Dies ist eine gute Voraussetzung für den Oldtimer als Diversifikationsobjekt. In der Berechnung eines optimalen Portfolios wird gezeigt, dass die Asset – Klasse “Oldtimer“ in einem Portfolio aus liquiden Anlagen das Portfolio optimieren kann. Die Arbeit zeigt, dass Oldtimer eine gute Wertanlage sein können, wenn die hohe Mindestanlagesumme für die Direktinvestition in Top-Oldtimer bewältigt werden kann. Die besten Wertanlagen sind Oldtimer mit einer erfolgreichen (Renn-)Historie, die in geringen Stückzahlen gefertigt wurden und einen gewissen Grad an Originalität in Technik und Design aufweisen. Wird der Oldtimer als Einzel-Investment betrachtet, sollte stets auch die „emotionale“ Rendite berücksichtigt werden.
2012-2
This study analyses the impact of Basel III on the fair pricing of bank guarantee facilities.Guarantees are an important risk mitigation instrument between exporters and importers in international trade and regularly a prerequisite for cross border sales contracts to be closed. Basel III – which shall be introduced from 2013 onwards - is a new regulation stipulating higher capital requirements for banks compared to the predecessor Basel II. It will therefore have an impact on the pricing of guarantee facilities which banks provide to exporting companies, making it also a crucial regulation for the cost of exportation overall. The study compares those contents of Basel III and Basel II which are particularly relevant for guarantees in order to identify and crystallize pricing-relevant changes in the regulations and their respective impact potential. The Basel frameworks are analyzed part by part and reviewed in terms of relevance for guarantees. In case of ambiguity the analysis is verified by complementary expert interviews. References and examples are mainly focusing on the German banking system but the basic conclusions can be generalized for those countries adopting Basel III.1 As the result, a case study expresses the quantitative outcomes of different scenarios and the impact of the different price determining factors on the overall fair pricing of bank guarantee facilities.
2012-1
The intention of this paper is to show that the statistical approach to risk is not enough to explain the behavior of investors. It furthermore proposes ideas and alternative approaches on how to deal with risk. Psychological findings are of particular interest as they might enhance our understanding of risk perception and assessment. The chapter “From the normal distribution to fat tails” starts with the rejection of the normal distribution as a simplifying basis for risk and return. This rejection is supported by several empirical observations like clustering of volatility and fat tails. This leads to a two-step approach for modeling risk and return based on the distinction of conditional and un-conditional changes. Conditional time series models (ARMA, ARCH, GARCH) and alternative distributions are presented (Stable Paretian, Student’s T, EVT) as a way to improve the art of risk and return modeling beyond the normal distribution assumption. The chapter ends with the conclusion that each model is only a statistical approximation and never encompasses the unpredictability of black swans and the nature of human behavior in the financial markets. After having discussed the limitations of the purely statistical approach to risk and return this paper goes beyond the standard theory of finance for two purposes. Firstly, behavioral finance provides some arguments for the limitation of statistics in assessing risk. Secondly, an alternative approach to risk perception is presented. This alternative is called Prospect Theory, a rather psychology-based approach using preferences to explain investors’ actions by human behavior in decision making processes. Starting point is the utility function and the value function followed by a description of the two phases: framing and evaluation. The value function is then clearly distinguished from the utility function by elaborating certain effects like reference points, loss aversion or the weighting function. In this section the paper enters the arena of human risk perception which is far from being monetarily rational in the sense of the homo oeconomicus. With Cumulative Prospect Theory there exists an extension to multiple outcome scenarios where risk does not necessarily have to be known. In such a situation, besides risk, there also exists immeasurable uncertainty. Current research confirms and rejects parts of (Cumulative) Prospect Theory which is not necessarily a bad sign as human behavior is rarely exactly replicable and the complexity does not really allow generalizations. Therefore, even if the theory is not completely correct it still enhances our understanding of risk perception and human decision making which can be a very valuable input for agent-based models. The next chapter analyses in more detail possible distortions from psychological biases in the assessment of risk. In this context the law of small numbers, overconfidence and feelings/experience are discussed. Knowing these biases complicates the idea of developing a risk model even further. However, this is again another step to better understand the underlying processes and motives of decision making in the context of financial markets. The last chapter is an attempt to link the different aspects to get a holistic view on risk behavior. Two possibilities are discussed: Hedonic psychology, with the distinction between blow up and bleeding strategy, and heuristic-based explanations for real observations like clustering of expectations and trust in experts. This leaves space for further research as we do not have a tool that is based on current findings and can actually help us in explaining and predicting behavior in financial markets. One possibility would be to link all these aspects in the approach of computational finance to develop agent-based models in which market observations, psychological findings and the situational context can be integrated.