 Stefan Bigger, The crypto model – Application of the Fama-French Three-Factor model and its extension by Carhart to cryptocurrencies, University of Zurich, Faculty of Business, Economics and Informatics, 2022. (Bachelor's Thesis)
In this thesis, I introduce my crypto model, which is an application of the Fama-French Three-Factor model (FF3M) and its extension by Carhart for cryptocurrencies. We will find that the factors SMB (small minus big) and HML (high minus low) of the FF3M can be transferred to cryptocurrencies, whereby the SMB factor can be replaced by the market capitalization and the HML factor by the transaction-to-market ratio of a cryptocurrency. We will also discover that the PR1YR factor of Carhart’s model can be replaced by the momentum return on a cryptocurrency. I will conclude this thesis by providing evidence that small-size cryptocurrency portfolios do not have a significant higher return than big-size cryptocurrency portfolios and that high-value cryptocur- rency portfolios do not have a significant higher return than low-value cryptocurrency portfolios. This is not in line with the results of the Fama-French Three-Factor model. Another conclusion will be that high-momentum cryptocurrency portfolios do not have a significant higher return than low-momentum cryptocurrency portfolios, which is not in line with Carhart’s model. |
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Sina Krumhard, Toward Unpacking Trust in a Local Sharing Community in Switzerland, University of Zurich, Faculty of Business, Economics and Informatics, 2022. (Bachelor's Thesis)
Over the past decade, more and more business models have been established that rely on re-using and sharing resources within their user community. These sharing economies rely on technological mediation, such as online platforms, to enable access, distribution, and coordination of different types of shared resources. In such collaborative environments, trust was identified to play an important role within the community by prior research. However, obtaining trusting peers as well as trusting the supporting service poses a challenge to effective interactions in sharing economies. In our qualitative study, we employed surveys and follow-up interviews to conceptualize interpersonal and system trust in one Swiss sharing economy community, which recently introduced an impersonal sharing process over smart lockers. Further, we investigate how this new impersonal sharing option is perceived by the members when it comes to the trust relationships within the community. This thesis proposes, based on the gathered findings, a series of design considerations to improve interpersonal and system trust within online sharing economy communities. |
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Dominik Frauchiger, HealthPlanner – Entwicklung einer Softwareunterstützung für die ärztliche Konsultation von Patienten mit Adipositas, University of Zurich, Faculty of Business, Economics and Informatics, 2022. (Bachelor's Thesis)
Only 50% of patients adhere to a prescribed therapy plan in developed countries, in less developed ones the percentage is even smaller (World Health Organization, 2003). One key point for the low adherence rate is a suboptimal healthcare-professional-to-patient communication, which itself originates from medical terminology (Härter et al., 2005). Furthermore, patients have a hard time remembering all therapy steps, because the information from the healthcare professional overload the short-term memory of the patient (Sandberg et al., 2008). These problems also exist in the widely used model of the “shared decision-making”. Consequently, this work tries to answer following research question. How can we support the shared decision-making in consultations with patients with adiposities via an application? To answer this question a prototype has been made in three iterations. This prototype was evaluated via consultations with healthcare professionals and patients. In this work, five design principles have been identified, which support the understanding of the patient about the therapy decisions. It was also found, how one can guarantee the usability and embedding in the consultation. But some healthcare professionals noted that they will decide about the usage of the application individually for each new patient. These results can be used as a guideline to create applications, which support shared decision-making in health-related consultations. This support should then increase the adherence of the patient to the therapy. |
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Peng Yan, Combined-GAN: Utilizing GAN for Open-Set Recognition by Generating Effective Unknown Samples, University of Zurich, Faculty of Business, Economics and Informatics, 2022. (Master's Thesis)
Discovering the unknown world is a big challenge. Different from traditional classification, for Open-Set Recognition (OSR), the open-set model needs to classify known data as well as tackle unknown data. In this thesis, we utilize Generative Adversarial Network (GAN) to generate effective open-set samples (unknown data) to assist an open-set model to know more information about the open space (the space far from known/training data).
In our Combined-GAN model, we adopt encoder-decoder network architecture for the generative model. By combining the latent space from two different known classes, the generated samples can acquire features from the corresponding known classes. We assume the generated samples locate around the decision boundaries of known classes and can be represented as open-set samples. The generated samples are fed into an open-set model together with known samples for OSR. Compared with other OSR approaches in different open-set scenarios, the quantitative and qualitative results show our generative model can generate effective unknown samples for the open-set model to classify known classes and detect unknown classes at the same time. |
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Lutharsanen Kunam, High Level Semantic Video Understanding, University of Zurich, Faculty of Business, Economics and Informatics, 2022. (Master's Thesis)
High level semantic video understanding deals with the problem of analyzing basic insights from movies like interpersonal relationships, relationships to other entities or interpersonal interactions. The Deep Video Understanding Challenge has focused on this issue and organizes an annual competition in which a set of queries is created which should be answered by the participants. This thesis is written in the context of the Deep Video Understanding Challenge 2021 and describes a pipeline that is able to answer the set of queries on a movie- and scene-level. The pipeline consists of a scene segmentation engine which cuts the scenes into single keyframes and shots. After that, they are processed by two streams, which consists of several feature extraction models. One stream focuses on the visual component, while the other stream focuses on the audio component. After that, the features are combined and processed. Numerous classifiers are trained and used to predict the interpersonal relationships, relationships with other entities or
interpersonal interactions. At the movie-level, a knowledge graph is then created, reflecting all the relationships between all the entities of a movie. This is used to answer the queries at movie-level. There, 8% of all questions could be answered correctly. The queries from scene-level could be answered to 1.5% correctly. The other pipelines from the DVU Challenge 2021 achieves better results as the worst result on movie level is 17% of correctly answered queries and the worst result on scene-level is 27% of correctly answered queries. |
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Gian Waltert, Measuring the Effects of a Conversational Agent on Dyadic Interaction: A Study in Financial Advisory Sessions, University of Zurich, Faculty of Business, Economics and Informatics, 2022. (Master's Thesis)
Conversational agents or digital assistants have continued gaining traction as an integral part of our personal and professional interactions. However, there is still room for improvement, particularly in professional advisory sessions or meetings. If banks manage to integrate conversational agents effectively into advisory sessions, they can attain new clients with a unique service experience and increase the perceived quality of the interaction. The University of Zurich's Information Management Research Group, in cooperation with external partners, has developed a prototype called Heinzelmännli to explore opportunities in this emerging field. The contribution of this thesis is twofold. Firstly, the effects the integration of a conversational agent has on interaction and communication are assessed based on experiments conducted in two Swiss banks. Secondly, based on the insights gathered, ThinkLets were developed to promote effective behaviors and limit destructive habits. Finally, the results are discussed in the context of conversational rights and interaction structure, as well as the perceived quality of service encounters. Also, suggestions are made on further improvements and developments of the conversational agent to support the points raised. |
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Joshua Heubi, Erreichbarkeitstrainer 3.0: Weiterentwicklung des digitalen Trainers zum gesprächsführenden Sparringpartner für Mitarbeiter im Rahmen des Onboardings, University of Zurich, Faculty of Business, Economics and Informatics, 2022. (Master's Thesis)
This thesis deals with the further development of the Reachability Trainer into the Reachability Trainer 3.0. It will be transformed into a conversational pedagogical agent that supports new employees of a public administration in telephone-based citizen service training during the onboarding process. Integrated into a social blended learning concept, the Reachability Trainer 3.0 offers six exercises with which the employees can train limitless how to act in different situations. The conversations between the employees and the Reachability Trainer 3.0 during the exercises take place at different degrees of structuring. For testing, two public administrations provide four groups of four to six people each. The groups work on different training programmes. Separated testing people from the public administrations perform the exercises too. Feedback is collected from all to answer which possibilities current technologies offer to develop such an agent, in which ways it can support new employees during onboarding and how it can be prevented from causing a feeling of being monitored by the Reachability Trainer. |
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Marc Zeugin, Bankruptcy Prediction for European Companies, University of Zurich, Faculty of Business, Economics and Informatics, 2022. (Master's Thesis)
The effect of firms’ financial characteristics and macroeconomic conditions were examined.
Furthermore, the influence of dynamic variables on classification performance was investigated.
Data on firms from eight different European countries were collected and analyzed.
Six different statistical models were employed and optimally tuned, and they revealed that
prediction performance is significantly increased if macroeconomic conditions are included.
The dynamic component was shown to enhance model prediction for most classification methods. Classification models were compared with each other, and significant differences in classification power were observed. Overall, the results imply a significant improvement if macroeconomic conditions and dynamic variables are included. |
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Selina Ott, Third-Party Litigation Finance and its Impact, University of Zurich, Faculty of Business, Economics and Informatics, 2022. (Master's Thesis)
The aim of this master’s thesis is to highlight the highly debated asset class of third-party
litigation finance and its impact. Different authors have presented contradicting opinions
involving positive and negative arguments regarding the social impact of this asset class.
This master’s thesis investigates the quantitative investor impact of litigation finance. Recent
definition on investor impact assist to identify that an investment in third-party litigation
finance provides capital allocation to an undersupplied market and helps firms and
individuals to access justice. To quantify the impact generated each underlying position of
two European litigation finance funds are assessed. By means of a binary system each
position is evaluated according to its likelihood of being litigated in the absence of an
external funder. The realised claim value from cases which can only be funded with the
external capital represents the impact generated. With the investor funding of the two funds,
a total realized claim value of more than EUR 800 million was achieved, representing the
impact generated. Even if the data justifies impact return, the extent to which the funder is
altruistically motivated remains unclear. |
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Paride Iadonisi, Financing M&A: Leverage Dynamics and Performance, University of Zurich, Faculty of Business, Economics and Informatics, 2022. (Master's Thesis)
This thesis examines the effect of leverage on M&A operative performance and analyses post-acquisition leverage dynamics. The study is based on a sample of 1,719 firms and 1,181 acquisitions in the DACH region from 2000 to 2019. The results indicate that overleveraged firms pursue the most performance-increasing acquisitions, are less likely to make acquisitions, and generally decrease their leverage ratio in the acquisition year
and in the three following years. Additionally, managers of underleveraged firms, usually
increase their leverage ratio in the same period. The thesis confirms the current knowledge of leverage dynamics and performance also in the DACH market and it expands it by considering operative performance metrics instead of the usually implemented stock
performance.
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Ivo Popov, Who would bear an automated payment tax? An analysis of the relationship between income, wealth, and payments in Switzerland, University of Zurich, Faculty of Business, Economics and Informatics, 2022. (Bachelor's Thesis)
The goal of this paper is to determine how wealth, income and trading relate to the transac-tion values of individuals and how the employee count and the economic sector relate to the transaction values of small and medium-sized enterprises. Surveys were used to collect data on the transaction values of small and medium-sized enterprises and individuals in Switzer-land for 2020. The surveys gathered 58 observations for individuals and eight observations for small and medium-sized enterprises. For this reason, only the data on individuals were processed through regressions and mediation analysis. The findings show that income and wealth impact the transaction volume. Contrary to previous research, both income and wealth regressively affect the transaction volume of individuals rather than progressively. This paper indicates that wealth, but not income, affects the likelihood of an individual to trade; yet, trading itself does not correlate with the transaction volume of individuals. The data on small and medium-sized enterprises, however, was insufficient for any meaningful statistical analysis. Further data gathering and research efforts are needed. |
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Mingrui Zhang, Bank Profit and Leverage: Evidence from Covid-19, University of Zurich, Faculty of Business, Economics and Informatics, 2022. (Master's Thesis)
This article examines the impact of the leverage ratio on bank profits using quarterly data
from 2017 to 2021. As an external shock, the COVID-19 epidemic can test the ability of
banks to deal with risks. Using the OLS and GMM models, this paper concludes that bank
profits will increase as the leverage ratio increases, and this conclusion will not change as
the COVID-19 epidemic hits. In the short term after the shock arrives, the rate at which bank
profits increase with the leverage ratio will become smaller. |
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Fabiano Crivelli, Stock-market Appraisal to Emissions Reduction / Net-Zero Target Announcements: “The Climate Pledge” Case, University of Zurich, Faculty of Business, Economics and Informatics, 2022. (Bachelor's Thesis)
The scientific consensus argues that greenhouse gas emissions must be drastically curtailed by 2050 to mitigate the impact of climate change caused by humankind.
Spontaneous private sector engagement is paramount to achieving this objective.
This research aims to assess, using an event-study design, the investors’ response following the public companies’ adherence to the Climate Pledge, a climate initiative co-founded by Amazon in 2019. Potential stock-market abnormal returns
are subsequently regressed on firms’ financial metrics and announcement modalities to evaluate the main factors affecting shareholders’ perception.
Consistent with prior literature, the empirical evidence does not consider corporate adhesion to the pledge as a market mover. Nonetheless, the principal finding of this research denotes that an excellent ESG rating increases companies’ reliability and translates their commitment into significant firms’ market value abnormal returns. |
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Xingzao Yang, Was the 2008 financial crisis responsible for life losses in the COVID-19 pandemic, with evidence from the USA, University of Zurich, Faculty of Business, Economics and Informatics, 2022. (Master's Thesis)
Could more severe economic loss in the 2008/09 financial crisis lead to higher COVID-19 case death
rates at the state level in the US? To empirically verify this question, this paper uses a COVID-19
data set of all states in the US from March to May in 2020, together with data from multiple sources
on financial crisis severity and other economic and demographic indicators. Main results can be
summarized into three aspects: First, in the initial stage of the pandemic, larger decline in GDP
growth and increase in debt growth during the 2008 financial crisis fostered higher COVID-19 case
fatality rates among US states. Second, this paper verifies that the 2008 economic crisis affected
COVID-19 case death rates through cutting expenditures in the public healthcare systems, especially
on the number of curative beds. Third, rising adult obesity rates in the US amplified negative effects
of the 2008 financial recession on COVID-19 case fatality rates. To conclude, findings in this paper
suggest that the impact of financial instability may be underestimated if its effect on the public health
sector in the long term is neglected. Coordinated efforts are needed to strengthen the financial system
while ensuring adequate funding to buffer the healthcare systems from unanticipated and exogenous
shocks in the future.
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Leo Ajdinovic, Benefits, risks and capital efficiency consideration of a reinsurer’s investment strategy with EUR liabilities and USD assets, University of Zurich, Faculty of Business, Economics and Informatics, 2022. (Master's Thesis)
Partner Reinsurance Europe SE (PRESE) is a European legal entity based in Dublin and a subsidiary of PartnerRe, a Bermuda-based composite reinsurer. PRESE holds an asset-liability portfolio with a net short-duration position where its long-duration liabilities are primarily in EUR and CHF while its shorter-duration invested assets are in USD. PRESE’s investment strategy reflects the view that USD assets yield higher returns than EUR or CHF assets and that the duration risk is not adequately compensated for in market pricing. The central question of the thesis is whether currency mismatch creates a substantial risk for which the entity is not sufficiently compensated. In other words, the thesis performs a formal validation of the current in- vestment strategy. In order to do so, the thesis constructs various investment portfolios by altering the currency composition of the existing investment portfolio and applies Group Capital Model (GCM), a stochastic model, to identify the investment portfolio with the best return-risk profile. Furthermore, the thesis explores the validity of res- ults by incorporating the cost of capital and examining the feasibility of hedging with forward agreements. In the last part, the thesis briefly discusses the limitations of the methodology used. The thesis concludes that the current investment strategy is close to optimal, and no significant gains can be obtained through currency reallocation.
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Timon Bodmer, Applying the inelastic market hypothesis to active and passive managed funds and predicting price movements, University of Zurich, Faculty of Business, Economics and Informatics, 2022. (Master's Thesis)
In this thesis I investigate the inelastic market hypothesis by Gabaix and Koijen (2021), henceforth
G&K. They hypothesize that, due to constrained market participants, price elasticity of demand of
stock prices is smaller than commonly assumed. The consequence is that inflow and outflow in and
out of the stock market have a massive price impact. Mainstream models assume asset demand to be
highly elastic. In this case small changes in prices lead to a large change in demand but changes in
demand would not change price by much. In those models the price is the direct result of discounted
future cash flows or dividends. Market movement would only impact the prices in a small way and
only short term. Arbitrageurs would instantly profit from these mispricings and thus rebalance the
market.
G&K propose a fundamentally di↵erent approach. They argue that the market is inelastic. The main
driving force behind this are the constraints laid upon a large share of market participants. Those
institution are subject to a multitude of regulations, most importantly their fixed equity share. This
mandate on equity share creates additional market forces that result in this extreme price reaction.
G&K make the key distinction between micro and macroeconomic elasticity. They specifically focus
on the macroeconomic price elasticity that concerns the inflow of money into the stock market
from outside the stock market. This is in contrast to microeconomic elasticity that is concerned
with the price elasticity stemming from movements within the stock market. They find the price
impact multiplier M to be around 5. This implies that a 1$ inflow into the stock market increases
the aggregated value of the stock market by around 5$. This result is remarkable and would have
severe impact into the fundamentals of asset pricing and the whole financial sector. It would help
explain the pseudo-random behaviour of asset prices. It would also allow governments to adapt their
quantitative easing approach and influence the markets more directly through stock purchase rather
than through bonds.
I critically discuss all the theoretical reasons given by G&K and combine it with existing literature on
this topic. I especially focus on non-linear and asymmetric extensions as well as the micro foundation
of these market forces.
In my empirical part I use proprietary Swiss and US mutual funds data provided by Morningstar. |
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Sina Rafati Niya, Raphael Beckmann, Claudio Brasser, Michael Bucher, Nicolas Spielmann, Burkhard Stiller, DeTi: A Decentralized Ticketing Management Platform, Journal of Network and Systems Management, Vol. 30 (2), 2022. (Journal Article)
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Steven Ongena, Tanseli Savaser, Elif Sisli Ciamarra, CEO Incentives and Bank Risk over the Business Cycle, Journal of Banking and Finance, Vol. 138, 2022. (Journal Article)
We examine whether the relationship between managerial risk-taking incentives and bank risk is sensitive to the underlying macroeconomic conditions. We find that risk-taking incentives provided to bank executives are associated with higher bank riskiness during economic downturns. We attribute this finding to the increase in moral hazard during macroeconomic downturns when the perceived probability of future bailouts and government guarantees rises. This association is particularly strong for larger banks, banks that maintain lower capital ratios and banks that are managed by more powerful Chief Executive Officers (CEOs). Our findings highlight the importance of the interaction between managerial incentives and the macroeconomic environment. Boards and regulators may find it useful to consider the countercyclical nature of the relationship between risk-taking incentives and bank riskiness when designing managerial compensation. |
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Matúš Medo, Manuel Mariani, Linyuan Lü, The simple regularities in the dynamics of online news impact, Journal of Computational Social Science, Vol. 5 (1), 2022. (Journal Article)
Online news can quickly reach and affect millions of people, yet we do not know yet whether there exist potential dynamical regularities that govern their impact on the public. We use data from two major news outlets, BBC and New York Times, where the number of user comments can be used as a proxy of news impact. We find that the impact dynamics of online news articles does not exhibit popularity patterns found in many other social and information systems. In particular, we find that a simple exponential distribution yields a better fit to the empirical news impact distributions than a power-law distribution. This observation is explained by the lack or limited influence of the otherwise omnipresent rich-get-richer mechanism in the analyzed data. The temporal dynamics of the news impact exhibits a universal exponential decay which allows us to collapse individual news trajectories into an elementary single curve. We also show how daily variations of user activity directly influence the dynamics of the article impact. Our findings challenge the universal applicability of popularity dynamics patterns found in other social contexts. |
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Linda Isabella Hain, Julian Kölbel, Markus Leippold, Let’s Get Physical: Comparing Metrics of Physical Climate Risk, Finance Research Letters, Vol. 46, 2022. (Journal Article)
Investors and regulators require reliable estimates of physical climate risks for decision-making. While assessing these risks is challenging, several commercial data providers and academics have started to develop firm-level physical risk scores. We compare six physical risk scores. We find a substantial divergence between these scores, also among those based on similar methodologies. We show how this divergence could cause problems when testing whether financial markets are pricing physical risks. Hence, financial markets may not adequately account for the physical risk exposure of corporations using available risk scores. Finally, we identify key sources of uncertainty for further investigation. |
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