Contributions in Merlin

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This thesis examines the initial analysis of the data set on financial inclusion obtained from Atlas in 2020. Potentially improving the data transparency in the sector for all stakeholders, the value and benefits of these data points are deliberated. By presenting the most relevant and informative variables via tabulated formats and eye-catching line and bar plots, this work provides a first visual illustration of what explanatory aspects the data set can offer. The focus is primarily laid on showing possibilities of how to graphically interpret key indicators or benchmark comparisons in fields such as financial performance, social performance, or credit risk.

This thesis investigates infrastructure project finance in Sub-Saharan Africa over a 30-year period. Realizing that a significant data and knowledge gap exists, the research analysis aims at reducing both gaps. A thorough descriptive analysis provides a holistic picture of the infrastructure project finance activity in the region over the period from 1990 to 2020. A multitude of current and historic trends are uncovered within it. A brief quantitative analysis meanwhile evaluates factors which could influence project finance and leads to speculate that there is a two-way relation between infrastructure project finance and economic output.

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This thesis examines the underlying reasoning behind the introduction of Basel III and the impact of the framework on the Swiss banking sector. The thesis provides a summary of the literature regarding the characteristics of banks and the associated market imperfections, as well as a descriptive analysis of the balance sheet of a set of Swiss banks. The main findings of this analysis are that the sample banks reacted in a similar way to the introduction of Basel III. Most sample banks reduced their lending in form of non-mortgage loans as a share of their total balance sheet assets, mainly by reducing the granting of non-mortgage loans to companies and retail customers. Moreover, within the scope of the thesis, it was shown that the sample banks change the focus of their granting of loans, non-mortgage loans were either reduced or grown at lower rate than the mortgage loans. Thus, the banks increasingly focused on lending in the form of mortgage loans rather than on non-mortgage loans.

Platforms are growing increasingly powerful, raising questions about whether their power might be exercised with bias. While bias is inherently difficult to measure, we identify a context within the music industry that is amenable to bias testing. Our approach requires ex ante platform assessments of commercial promise – such as the rank order in which products are presented – along with information on eventual product success. A platform is biased against a product type if the type attains greater success, conditional on ex ante assessment. Theoretical considerations and voiced industry concerns suggest the possibility of platform biases in favor of major record labels, and industry participants also point to bias against women. Using data on Spotify curators’ rank of songs on New Music Friday playlists in 2017, we find that Spotify’s New Music Friday rankings favor independent-label music, along with some evidence of bias in favor of music by women. Despite challenges that independent-label artists and women face in the music industry, Spotify’s New Music curation appears to favor them.

Die vorliegende Bachelorarbeit befasst sich mit dem Thema des Crowdlendings über Onlineplattformen für kleine und mittlere Unternehmen (KMU) in der Schweiz und seiner zukünftigen Entwicklung. Die Untersuchung wird anhand von Erkenntnissen aus bestehender Literatur und bereits erhobenen Daten durchgeführt. Im Theorieteil werden zunächst die relevanten Begriffe definiert. Danach wird genauer auf das globale sowie das Schweizer Crowdlending eingegangen. Auf Basis der gewonnenen Erkenntnisse wird daraufhin eine Prognose der Entwicklung des Crowdlendings für Schweizer Un-ternehmen erstellt. Dafür werden Expertenmeinungen und prognostizierte Daten zu-sammengeführt. Als Ergebnis zeigt diese Arbeit, dass die Zukunft viele Herausforde-rungen im Crowdlendingmarkt mit sich bringt. Neue Regulierungen, die coronavirus disease 2019 (COVID-19) und die Fähigkeit, funktionierende Kollaborationen einzuge-hen, werden die Entwicklung dieses Marktes in den nächsten Jahren entscheidend be-einflussen. Ob diese Art der Finanzierung die Kredite traditioneller Banken ersetzen oder doch nur supplementieren wird, kann nicht abschliessend beantwortet werden. Dies wird sich zeigen, wenn der Markt des Crowdlendings weiterhin wächst.

This work examines deep reinforcement learning for optimal asset allocation in the US stock market using a custom implementation of the proximal policy optimization algorithm (PPO). Two different policy distributions, namely the Gaussian and Dirichlet distribution are tested as well as two different network architectures, namely a feed-forward neural network and the latter combined with an additional LSTM module, with the aim to provide the agent with more information about the past. The portfolio rebalancing is done under consideration of constraints such as transaction costs, budget constraints, no short-selling constraints and no fractional shares trading. The state space is constructed including technical momentum indicators, past returns, volatility and the volatility index (VIX). The best-performing strategy is PPO using a Gaussian policy with a feed-forward neural network, while the Dirichlet policy is found to enforce equal weights under all circumstances. I

Introduction: Hospital quality rests on the morale and productivity of those who work in them. It is therefore important to try to understand the kinds of team leaders that create high morale within hospitals. Methods: This study collects and examines data on 3000 physicians in hospitals from Denmark, Australia and Switzerland. It estimates regression equations to study the statistical predictors of levels of doctors’ job satisfaction, their intentions to quit or stay in their current hospital and their assessment of the leadership quality of their immediate manager. A particular concern of this study is to probe the potential role played by clinical expertise among those in charge of other physicians. Results: When led by managers with high clinical expertise, hospital physicians are (1) more satisfied with their jobs, (2) more satisfied with their supervisors’ effectiveness and (3) less likely to wish to quit their current job. These findings are robust to adjustment for potential confounders, including age and job seniority, and pass a variety of statistical checks (including clustering of SEs and checking for omitted variable bias). They are replicated in each of the three nations. Conclusion: Physicians are happier with their jobs when led by outstanding clinical experts. It is not sufficient, it appears from this evidence, for leaders merely to be clinicians. This suggests that—though only an idealised and presumably infeasible randomised experiment could allow complete certainty—there is a natural case for managers within a hospital hierarchy to be drawn from the ranks of those who are themselves outstanding clinicians.

This paper studies the dynamic network connectedness between cryptocurrency returns and sentiments using the novel cryptocurrency-specific MarketPsych sentiment data for 13 cryptocurrencies with the highest market capitalization. The results indicate the dominance of cryptocurrencies with higher market capitalization and information transmission from cryptocurrency returns to sentiments. Our results also show that Bitcoin is losing its dominance to alt-coins in return spillovers while still dominant in sentiment spillovers.