Contributions in Merlin

Diese Arbeit untersucht Branchen-Momentum-Strategien im Euro STOXX 600. Dabei werden die vergangenen Gewinner- und Verlierer-Branchen gekauft bzw. verkauft. Mithilfe eines Backtesting-Verfahrens wird der Zeitraum von 2003 bis Ende 2022 analysiert, um mögliche Überrenditen zu untersuchen. Es konnte festgestellt werden, dass eine (12/1) Gewinner-Strategie eine jährliche Überrendite von bis zu 1.1920% erzielen kann, ohne überproportionale Risiken einzugehen. Gewinner-Verlierer-Strategien konnten keine Überrenditen erzielen. Obwohl alle Gewinner-Portfolios eine Überrendite aufweisen, sind diese jedoch nicht annähernd so groß wie bei vergleichbaren Strategien in anderen Studien.

In order to evaluate the social dimension of the ESG domain in Sustainable Finance, this thesis focuses on using deep learning models, specifically the use of a new BERT adaptation model called SocialBERT. By creating a model that is responsive to socially relevant texts, it addresses a significant research gap and makes it more effective at comprehending and assessing these elements. Social aspects are now playing a major part in determining the sustainability of financial investments, revolutionizing the financial industry with the rise of ESG investing. However, because of the richness and diversity of texts that are socially relevant, it is often difficult to quantify these social variables. Therefore, it is noticeable that we require sophisticated technologies to interpret and comprehend these texts. The SocialBERT model has been created to better understand the nuances and context of social aspects than conventional models because it has been pre-trained on a huge corpus of texts with a social focus. The model is assessed for its capabilities and performance, and the results show that it is more effective than conventional models at understanding social texts. Additionally, the thesis emphasizes the shortage of study in this field and the necessity of larger-scale investigations to promote a better understanding and integration of social factors into sustainable finance. This research builds on the development of deep learning techniques, the success of big language models like BERT and GPT, and growing trends in the application of Natural Language Processing (NLP) in finance. In conclusion, the SocialBERT model has the potential to improve sustainable finance decisionmaking by facilitating a more sophisticated understanding of social aspects. The results of this thesis not only to expand the pool of knowledge in the area but also open up fresh possibilities for investigation and advancement in the use of cutting-edge NLP technologies for ESG analysis. II

This study aims to determine whether it is possible for corporate insiders to generate abnormal returns and to test if the Efficient Market Hypothesis is valid for the Swiss Stock market and to which degree it can be applied. For this purpose, an event study for insider trades between January 2020 and January 2023 was conducted. The results suggest that corporate insiders can generate statistically significant abnormal returns and therefore reject the strong form of the Efficient Market Hypothesis in the Swiss stock market.

Based on the data of S&P 500 index from 2008-04-01 to 2022-12-30, four different models, namely Black-Scholes, Variance-Gamma (VG), GARCH, and COMFORT-GARCH models are employed to make options pricing, and the pricing quality of these models are compared. The results show that the COMFORT-GARCH model combines GARCH-type dynamics with an SV structure, it can better capture the volatility characteristics of S&P 500 index, yields a more stable price change with a smaller magnitude. The research confirms the applicability of COMFORT-GARCH model in the multivariate setting for potentially large numbers of assets.

Diese Arbeit untersucht den Einfluss des Faktors Volatilität auf die Aktienpreisbildung. In einem ersten Teil wird auf etablierte Finanzmarkttheorien und ihre Modelle eingegangen. Der zweite Teil behandelt die dazugehörige Empirie und die aktuellen Untersuchungsergebnisse zum Volatilitätsfaktor. Die Analyse des Volatilitätsfaktors stellt sechs Regressionsmodelle mit unterschiedlicher Parameterzusammenstellung im Kontext des FamaFrench-Dreifaktormodells (Fama und French (1993)) einander gegenüber, wobei die durchschnittlichen adjustierten R2 als Vergleichsmass genutzt werden. Die Ergebnisse zeigen, dass der Einfluss des Volatilitätsfaktors signifikant ist, da das Bestimmtheitsmass des FamaFrench-Dreifaktormodells kleiner ausfällt als dasjenige des Modells mit dem zusätzlichen Volatilitäts-Faktor. Die Untersuchung zeigte zudem eine grössere Relevanz des Faktors Volatilität gegenüber dem Value-Faktor auf. Nichtsdestotrotz ist der Faktor Volatilität kein geeigneter Ersatz weder für das Marktrisikopremium noch den Size-Faktor.

Morality scandals emphasise the necessity to establish ethical catalysts to diminish immoral behaviour. This thesis uncovers possible impacts of mirror and publicity contemplation ques-tions on multiple awareness types to enhance self-regulation and mitigate cognitive motiva-tional biases. Leveraging self-regulation and self-theories, this thesis argues that contemplative questions enhance accessibility to discrepancies, raise emotional discomfort and motivate self-alignment. Mirror questions are suggested to foster objective and private self-awareness, acting as amplifying tools for individuals to examine their private self-image, while publicity questions stimulate impression management and positive self-presentation by increasing public self-awareness. Future research approaches involve empirical validation of these theoretical in-sights.

Diese Arbeit untersucht zwei der meistverbreiteten Aktienmarkt-Anomalien, Value und Momen-tum, im Schweizer Aktienmarkt über den Zeitraum von 1990 bis 2022. Weiter wird untersucht, wie die beiden Strategien miteinander korrelieren. Sowohl Value- wie auch Momentum-Effekt sind in der Schweiz vorhanden. Der Momentum-Effekt ist dabei mit Renditen von jährlich 13.76% deutlich stärker ausgeprägt als der Value-Effekt mit jährlich 2.06%. Value-Strategien scheinen ausserdem von 1990 bis 2010 hervorragend funktioniert zu haben, danach aber nicht mehr. Werden jedoch Faktorrenditen berechnet, die anderen Variablen gegenüber neutral sind, ist nur noch Momentum signifikant. Die Korrelation der beiden Effekte ist mit -0.1 zwar negativ, aber nicht stark.

We adapt the design of four experimental studies on retirement decision-making and conduct replications with a larger online sample from the broader population. We replicate most of the main effects of the original studies. In particular, we confirm that consumption decisions are less efficient when subjects need to borrow from the future than when they need to save from the present. When subjects collect retirement benefits as lump sum instead of annuities, they choose to retire later, as suggested by the original study. We also confirm that savings are higher when they are incentivized with matching contributions than when incentivized with tax rebates. However, when faced with varying survival risks, subjects in our replication make only partial adjustments to spending paths when ambiguity is reduced. We also propose a further experimental research agenda in related topics and discuss practical issues on subject recruitment, attrition, and redesign of complex tasks.

Social entrepreneurship has emerged as an important means of addressing grand challenges. Although research on the topic has accelerated, scholars have yet to articulate an overarching framework that links the different pathways taken by social entrepreneurs with the positive effects of these efforts. To address this shortcoming, we conducted a systematic literature review which enabled us to conceptually differentiate between social value and social change as distinct outcomes of social entrepreneurship and identify seven pathways for achieving these outcomes. Building on our analysis, we outline a research agenda for questions pertaining to: the dynamics between social value and social change; how contextual factors and social entrepreneurs influence various pathways; design principles of business models and innovations that facilitate social value and social change; and defining, measuring, and ensuring accountability for social value and social change.

This paper examines the role of lifelong learning in counteracting skill depreciation and obsolescence. We differentiate between occupations with more hard skills versus more soft skills and draw on representative job advertisement data that contain machine-learning categorized skill requirements and cover the Swiss job market in great detail across occupations (from 1950 to 2019). We examine lifelong learning effects for “harder” versus “softer” occupations, thereby analyzing the role of training in counteracting skill depreciation in occupations that are differently affected by skill depreciation. Our results reveal novel empirical patterns regarding the benefits of lifelong learning, which are consistent with theoretical explanations based on structurally different skill depreciation rates: In harder occupations, with large shares of fast-depreciating hard skills, the role of lifelong learning is primarily as a hedge against unemployment risks rather than a boost to wages. By contrast, in softer occupations, in which workers build on more value-stable soft-skill foundations, the role of lifelong learning instead lies mostly in acting as a boost for upward career mobility and leads to larger wage gains.