Contributions published at Department of Banking and Finance (Pablo Koch Medina)

The following paper examines the influence of ESG ratings on companies' share performance in times of crisis. The data basis and the delimitation criteria for this were created by Swiss companies that are traded on the SIX Exchange and, in addition to the COVID-19 and Ukraine crises, investigations were also carried out for normal market conditions and periods with less market volatility and global conflicts in order to be able to serve as a benchmark and to make a comparison. Thus, this paper joins and extends a growing body of literature examining ESG criteria's influence on stock performance. To investigate the impact of ESG criteria, their effect is observed using an OLS regression, with additional control variables included. The independent variable in the regression is the abnormal return, which was chosen to measure share performance. A positive influence of higher ESG ratings on share performance can be shown over the entire period, whereby the positive impact is higher in times of crisis than in the comparison periods with "normal" market conditions. These results speak in favour of investing in high-quality ESG stocks and confirm existing literature that has come to the same conclusions.

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With the aim of avoiding the worst effects of climate change, countries worldwide have committed to limiting global warming below 2.0 ◦C compared to pre-industrial levels. In response, achieving climate neutrality has become a critical objective, and Switzerland has committed to reaching this milestone by 2050. To achieve this goal, a combined effort from the government, organizations, firms and individuals is needed. Small and Medium-sized Enterprises (SMEs), which account for approximately 99% of all companies in Switzerland, play a crucial role in achieving this target. This study aims to investigate the barriers, motivations, and strategies of Swiss SMEs in their transition to a net-zero economy and to understand what is needed to accelerate the process. A mixed-method approach is employed, combining an extended literature research, two qualitative interviews and a quantitative survey with 99 participants. The analyses indicate that SMEs are lagging behind in the transition, with 74% of the companies still not having set a net-zero target and only 7% having reached net zero so far. Regulatory pressures, stakeholder demands and resource limitations are identified as main barriers. The results emphasize the importance of integrating sustainability into business strategies and the need for targeted support and incentives for SMEs. It is fundamental to prioritize climate impact and to consider the pathway to net-zero emissions.

Ziel – Das Ziel dieser Bachelorarbeit ist es, durch eine Aufarbeitung der Grundstrukturen und Aufgabenbereiche der Schweizerischen Nationalbank sowie des Federal Reserve Systems einen Vergleich zu ziehen, sowie deren Verhalten zwischen April 2018 und April 2023 zu analysieren. Zudem wird eine Zeitreihenanalyse durchgeführt, die jeweils in Bezug auf drei Einflussparameter erfolgt (Arbeitslosenquote, Ölpreis und Leitzins), um die Inflation in der Schweiz und den USA zu erklären. Der Beobachtungszeitraum erstreckt sich von April 2018 bis April 2023 auf monatlicher Basis. Ergebnisse – Es sind sowohl interessante Unterschiede als auch Gemeinsamkeiten zwischen den beiden Nationalbanken zu erkennen. Ein Beispiel für einen gewichtigen Unterschied ist die Definition der Preisstabilität, welche in der Schweiz mit einer Inflationsrate von 0 % – 2 % gleichgesetzt wird. In den USA hingegen wird eine durchschnittliche Inflation von 2 % angestrebt. Bei der Zeitreihenanalyse wurde festgestellt, dass alle drei untersuchten Einflussparameter statistisch signifikante Resultate liefern, jedoch unterscheiden sich diese im jeweiligen Land teilweise erheblich. Dabei liefert vor allem das Modell für die Schweiz gute Resultate. Wert – Diese Bachelorarbeit ermöglicht es dem Leser, einen Vergleich zwischen der Schweizerischen Nationalbank und dem Federal Reserve System zu ziehen. Zudem beinhaltet sie eine empirische Untersuchung der Inflation in der Schweiz und den USA.

Sustainability has been one of the most discussed topics in recent years and leading to a growing trend of Environmental, Social and Governance (ESG) disclosure initiatives. This thesis uses a benchmarking approach to examine the qualitative and quantitative assessment of the sustainability indicators of Europe’s 100 largest financial institutions. Ranked according to market capitalization, the sustainability of the individual banks is measured using critical figures from their annual- and sustainability reports1 and compared with each other. Using a regression, the most important findings can finally be drawn up. Since sustainability reporting for banks is not yet mandatory, this work aims to create a benchmark regarding specifically defined criteria. Therefore, all data has been collected, customized, reviewed, analysed and evaluated manually. This study developed a detailed set of key sustainability factors to allow a broad comparison between the financial institutions. As a result, analysing the process of this thesis, including difficulties in obtaining consistent and comparable data of the various banks, they should adopt a more aligned and transparent approach when publishing their sustainable data. Furthermore, this study aims to examine the relationship between the calculated score and a bank’s operational performance, Return on Assets (ROA). The generated score elects Cembra Money Bank AG as the best performing bank regarding sustainability disclosure in 2021. Moreover, the study's findings highlight the final regression’s significance and demonstrate that this work's hypothesis is applicable.

Selling put options can be lucrative; however, the returns tend to exhibit a strong negative skewness. Moreover, the seller may have liquidity issues during the holding period, especially when margin requirements become too large. Existing hedging techniques often overlook potential liquidity problems during the holding period, focusing solely on terminal losses. To address this limitation, we present a novel risk management approach by reformulating the closing time of the short position as an optimal stopping problem. To find the solutions, we decompose the holding period into a sequence of binary stopping decisions, which naturally fit into the reinforcement learning framework. Multiple deep reinforcement learning algorithms, namely Deep Q-Learning, Rainbow, and Synchronous Advantage Actor-Critic, are employed to identify the optimal times for closing the position. Our training framework introduces a new reward function that enables the agents to maximize each option’s profit and enhance its Sharpe ratio. In a simulated environment with nontrivial optimal stopping solutions, we demonstrate the e↵ectiveness of the algorithms and our training setup. Furthermore, we apply these algorithms to market data; specifically, SPY put option data from 2005 to 2022. During this analysis, we encounter a significant imbalance in the training data between paths with negative and positive returns, making it challenging for the algorithms to learn an optimal solution. Consequently, we propose several approaches to tackle this issue in future research. Overall, our work presents a promising approach to address liquidity concerns during option selling strategies, and our findings contribute to the advancement of reinforcement learning techniques in the financial domain.

We investigate the stock return predictive power at the high-frequency level after statistically significant overnight jumps conditioned on prevailing stock and market level news sentiment. We provide evidence that sentiment variables as well as the jump direction explain variation in intraday returns following a jump event and document the effect over the trading day. We identify overnight jumps through highfrequency based jump tests and calculate our sentiment variables from the Thomson Reuters News Analytics dataset. We document our findings for S&P 500 constituents from 2004 to 2021. In the case of positive jumps, we document a stronger overreaction behaviour to both, the direction of the jump and to the prevailing news sentiment, whilst for negative jumps, we can only document a reversal behaviour relating to the direction of the jump. In addition, the paper presents a trading strategy based on the observed phenomena. The strategy exhibits no correlation to the market portfolio, exhibits tail hedging characteristics, whilst maintaining a positive drift component. Key words: stock return predictability, statistical jumps, private information, news sentiment, nontrading hour information, market level sentiment, company-specific sentiment

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Ein gut funktionierender Elektrizitätsmarkt ist von essenzieller Bedeutung für unserer Gesellschaft. Um diesen besser zu verstehen, wurde er bereits umfassend erforscht. Die Coronapandemie und Ukrainekrise haben jedoch grosse Veränderungen mit sich gebracht, die bis jetzt kaum untersucht wurden. Vorliegende Arbeit erleuchtet diese Forschungslücke indem Strompreise und -verbräuche mittels Korrelationen und Regressionen analysiert werden. Die Ergebnisse zeigen, dass die Elektrizitätsmärkte während den Preisexplosionen in den Jahren 2021 und 2022 stärker voneinander abhängen und die Nachfrage nach Elektrizität die Preise nahezu nicht beeinflusst hat. In der Schweiz konnte im Jahr 2022 sogar eine leicht negative Korrelation zwischen Preis und Verbrauch festgestellt werden.

Criticism towards the “standard” Dividend Growth Model (Gordon Growth Model) and its exponential growth pattern have sprouted alternative models such as the “modified” Dividend Growth model, with a linear growth pattern, introduced by Balschun and Schindler (2015). Applying standard portfolio construction techniques, this thesis asses if the models can enhance the portfolio management process regarding risk-adjusted excess returns within the North American stock markets. The investment universe is given by the S&P500 from 2003 until 2022. Based on the “modified” Dividend Growth Model, value is provided with certain input parameters, whereas the “standard” Dividend Growth Model does not provide value.

In dieser Arbeit wird mit dem Fama-French-3-Factor- und Carhart-4-Factor-Model eine empirische Analyse im Schweizer Aktienmarkt durchgeführt. Im untersuchten Zeitraum von Juli 2012 bis Juni 2022 werden die Risk Premiums dieser Modelle berechnet. Unabhängig von den gewählten Modellannahmen können das durchschnittliche Market Risk und Momentum Premium signifikant ungleich null nachgewiesen werden. Das mittlere Size Premium wird Annahmen-unabhängig nicht signifikant ungleich null belegt. Die Schlussfolgerung zur Signifikanz des durchschnittlichen Value Premiums fällt aufgrund der Abhängigkeit zu den gewählten Modellannahmen nicht eindeutig aus. Der Modellvergleich mittels Regressionsanalyse zeigt, dass das Carhart-Model, auch unter adjustierten Bedingungen, durchgehend die höhere Modellgüte als das Fama-French-Model aufweist

This study implements momentum strategies on the Swiss Performance Index (SPI) and examines their profitability over an 18-year time horizon. The robustness of these strat-egies is analyzed by adjusting certain parameters including lags, transaction costs, size and weight of the winner portfolios and short selling. The results are consistent with the existing literature and confirm the validity of momentum strategies in the Swiss equity market. The results remain significant after risk adjustments, indicating that the momen-tum effect persists after controlling for risk. While the momentum phenomenon is par-tially explained, certain underlying factors remain unanswered, suggesting potential areas for future research.

This thesis investigates the association between ESG scores and future stock returns by using a large sample of more than 48,000 stock-month observations on total returns and ESG scores for STOXX 600 constituents from 2015 to 2022. Three different methodological approaches were employed: a portfolio-level analysis, cross-sectional time series (panel) regressions, and a difference-in-differences approach exploiting the COVID-19 crisis during the first quarter of 2020. The findings do not indicate a positive predictive relationship. Rather, there is some evidence that high-ESG-score stocks underperform stocks with low ESG scores.

This master’s thesis examines the impact on renewable energy stock returns of macroeconomic events in Europe. In particular the impact of the published REPowerEU-Plan and information regarding excess inflation on stock returns of European renewable energy infrastructure and non-infrastructure firms are analysed. In order to facilitate the analysis, a hand selected renewable energy stock portfolio is compared against the STOXX Europe 600. The underlying empirical design to enable the analysis is based on an Difference-in-Differences methodology. As a result, the mean returns around the treatment date are calculated and compared. In sub-analysis potential sources of biases are analysed.

In this thesis, a modular concept and a prototype for a course in the field of sustainable finance were developed. The University of Zurich offers a seminar called Advanced Portfolio Management Game, which serves as a basis. Financial and sustainability data of 244 companies were processed and integrated into different modules. The participants have to found a bank and set up a sustainable fund. They also have to make strategic decisions that include sustainability aspects. The aim of the game is to give the participants an overview of the broad topic of sustainable finance in a practical way.

Diese Bachelorarbeit misst die Diversifikation von Sektor-ETFs anhand von zwei Hauptkonzepten: der Diversifikation Ratio und der Risiko-Parit¨at. Sie untersucht unteranderem den Einfluss der spezifischen Eigenschaften eines Sektor-ETFs auf die Diversifikation. Die Ergebnisse zeigen, dass keine der Sektor-ETF ihr Diversifikationspotential vollst¨andig aussch¨opft und der Energiesektor die im Durchschnitt am schlechtesten diversifizierten Sektor-ETFs anbieten. Diese Ergebnisse sollen zu verbesserten Verst¨andnis der Diversifikation von Sektor-ETFs beitragen I

Diese Studie liefert eine umfassende Untersuchung der Prognoseeigenschaften des Buffett-Indikators im spezifischen Umfeld des Schweizer Aktienmarkts. Die Analyse ergänzt bestehende Forschungsarbeiten, indem sie die Anwendbarkeit und das Potenzial des Buffett-Indikators zur Vorhersage zukünftiger Bewegungen am Schweizer Aktienmarkt eingehend untersucht und damit einen Beitrag zur breiteren finanzwirtschaftlichen Literatur leistet. Der Buffett-Indikator, eine Kennzahl, welche die gesamte Marktkapitalisierung der börsenkotierten Aktien eines Landes mit dessen Bruttoinlandsprodukt vergleicht, nimmt in der Finanzanalyse eine Sonderstellung ein. Dieser Indikator, benannt nach dem amerikanischen Investor Warren Buffett, bietet wichtige Einblicke in die Marktbewertung und hilft Anlegern, über- oder unterbewertete Märkte zu erkennen.

This thesis uses the fundamental concept of merger arbitrage investing to derive rule-based investment strategies. The strategies are based on research findings regarding five deal-specific factors influencing deal success probabilities and aim to identify profitable merger arbitrage opportunities. A backtesting approach applied to a dataset of 160 M&A deals with targets that were, at the time of the transaction announcement, constituents of the S&P 500 index between 2010 and 2022 is used to test the proposed strategies. The results cannot confirm significant differences in returns between a long-only baseline strategy and the proposed strategies, disproving the effectiveness of the factors.

This paper conducts an analysis of a valuation at the initial public offerings (IPO), focusing on ON-Holding AG (ON). The study offers insights into valuation methods and the specialties for ON. The cost of capital and the growth rate is determined, and a valuation analysis is conducted. The methods used are the peer multiples and a sales to free cash flow estimation. Additionally, a case study is prepared for teaching purposes. Finally, the paper evaluates the results and identifies potential difficulties. The findings express, the share price was heavily influenced by growth opportunities and not purely based on the current financials.

This thesis studies social media’s valuation and recognition as an intangible asset under IFRS regulations. It determines whether a company’s social media channels qualify as an intangible asset and can be formally recognised as such. The work examines relevant IFRS regulations and social media theories in the theoretical section, followed by a practical analysis of the recognition criteria and valuation methods. Findings show that social media can be recognised as an intangible asset during a purchase price allocation if it is integral to the business model. The income approach, specifically the multi-period excess earnings method, is most suitable for estimating the fair value of social media.