Contributions in Merlin

The digitally enabled sharing economy, also called the “digital sharing economy” (DSE), has changed patterns of consumption by introducing new choices and channels for provision and receipt of services. The DSE encompasses sharing systems whose business models may vary distinctly from platform to platform. Although business models in the context of the sharing economy have been studied so far, we have observed that the current literature does not provide an approach that covers all the possible business models (in the broadest sense of the term) that (potentially) exist within the scope of the DSE. The present paper, therefore, aims to propose a typology of business models in the DSE that covers a wide space of models – even those which may not involve “business” in the commercial sense. This is achieved through an iterative inductive process based on a design science research approach. The typology can assist in positioning the current and future sharing systems in the DSE by systematically classifying their business models. It is intended to serve as a guiding tool for the sustainability assessment of platforms from both resource and socio-economic perspectives. The present study can also enable researchers and practitioners to capture and systematically analyse digital sharing business models based on a structured, actionable approach.

Statistical charts complement textual reports by visualizing overall patterns or relations in the data. However, layout algorithms may place charts far from their associated text. Such distant placement can cause reading difficulties, or worse, a misinterpretation. We conducted an eye-tracking experiment comparing reading behaviors in two proximity levels: Placing text and chart on the same page, versus placing them on two different pages. The results indicate that the proximity influences text-reading stronger than chart-reading behavior. We discuss design implications for text-chart layout algorithms and practices. This paper and all data and materials are freely available at https://osf.io/xunt9.

In this paper, we show how to use the framework of mod-Gaussian convergence in order to study the fluctuations of certain models of random graphs, of random permutations and of random integer partitions. We prove that, in these three frameworks, a generic homogeneous observable of a generic random model is mod-Gaussian under an appropriate renormalisation. This implies a central limit theorem with an extended zone of normality, a moderate deviation principle, an estimate of the speed of convergence, a local limit theorem and a concentration inequality. The universal asymptotic behavior of the observables of these models gives rise to a notion of mod-Gaussian moduli space.

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Data often contains sensitive information, which poses a major obstacle to publishing it. Some suggest to obfuscate the data or only releasing some data statistics. These approaches have, however, been shown to provide insufficient safeguards against de-anonymisation. Recently, differential privacy (DP), an approach that injects noise into the query answers to provide statistical privacy guarantees, has emerged as a solution to release sensitive data. This study investigates how to continuously release privacy-preserving histograms (or distributions) from online streams of sensitive data by combining DP and semantic web technologies. We focus on distributions, as they are the basis for many analytic applications. Specifically, we propose SihlQL, a query language that processes RDF streams in a privacy-preserving fashion. SihlQL builds on top of SPARQL and the w-event DP framework. We show how some peculiarities of w-event privacy constrain the expressiveness of SihlQL queries. Addressing these constraints, we propose an extension of w-event privacy that provides answers to a larger class of queries while preserving their privacy. To evaluate SihlQL, we implemented a prototype engine that compiles queries to Apache Flink topologies and studied its privacy properties using real-world data from an IPTV provider and an online e-commerce web site.

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This thesis investigates the market timing ability of the VSMI with two di↵erent strategies for the Swiss market using data from July 2011 until June 2019. The first strategy is based on size and di↵ering between small and big stock portfolios, whereas the second strategy consists of alternating between value and growth stock portfolios and therefore is constructed on the style of the stocks. For both strategies, the portfolios are for robustness formed in two ways according to Fama and French (1993), with the first setting being a 2-by-3 approach and the second a 5-by-5 approach. The empirical results of this thesis then suggest a profitable strategy based on size, where the big stocks outperform the small stocks on days following an increase in the VSMI. This superiority is especially profitable on days following a particularly high increase in the VSMI of over 30% and results in a significant payo↵ when implementing a zerocost portfolio. Overall the strategy based on size clearly outperforms the market portfolio. The reasoning for this is that the VSMI is a valid timing instrument for size investing and indicates a ”flight to quality” and ”flight to liquidity” movement. On the other hand, the empirical results show that the style investing strategy reacting to changes in the VSMI is not equally profitable and delivers mixed results that are not significant. According to the results, the value stocks outperform the growth stocks on days following minor positive increases in the VSMI, but on days following huge increases, the opposite is the case. This observation might be due to the popularity of style investing and the fact that these portfolios react faster to changes in the VSMI, and therefore, the VSMI loses its timing ability.

This paper explores the impact of information traders and noise traders on China stock market by applying the the information adjusted noise model (IAMN).The result of empirical test shows China stock market is completely inefficient and both the two types of the investors are contributing to the noise trader risk, which increase the volatility of the market. The Noise trader risk is higher in Bullish period than in Bearish market and the risk is increasing over time. The study of the interaction between information traders and noise traders shows that a part of the noise trader risk is attributed to information traders. They can be overreacting to the mispricing that caused by noise traders and in many cases even join them, which expand the noise trader risk in the market.

The credit rating of corporations aims to provide insights about their creditworthiness and model the bankruptcy probability. These ratings often consult financial key figures and neglect the macroeconomic perspective. This descriptive thesis investigates the contemporaneous effects of macroeconomic drivers on bankruptcies in Switzerland. Applying a first-difference lagged model I found that the effects of the variables included vary across industries and that these effects tend to rise when considering the seasonally not adjusted GDP.

This paper will provide an overview of how Robo-Advisors elicit investor ESG preferences in their suitability assessment regarding the forthcoming changes in the regulation in MiFID 2 concerning the amendment of the delegated regulation (EU) 2017/575 which stipulates the integration of environmental, social and governance (ESG) considerations and preferences into the investment advice and portfolio management. A sample of ten Robo-Advisor was studied to analyze the dierent approaches on how the Robo-Advisors elicited ESG preferences from their clients. This was achieved by completing the suitability assessments of the Robo-Advisors and comparing the surveys on pragmatic goals of how ESG preferences were requested with respect to other relevant topics such as time-component, nancial and risk measures versus ESG preferences. Subsequently, the strengths and weaknesses of the surveys were demonstrated. The ndings show the existence of a fragmented Robo-Advisor market which uses mainly four dierent implementations such as a) no ESG preferences are requested, b) check the box to invest in an ESG compliant portfolio, c) select ESG and non ESG preferences, and lastly d) select ESG preferences. Having analyzed the contemporary status of the suitability assessments with regards to ESG preferences, this paper proposes an optimized denition of ESG preference as well as key features for an online survey which is based on the strengths of the current questionnaires as well as the proposed denition. Thus, the suggested questionnaire's core features are the extent of the questionnaire itself, the balance between ESG preferences and other measures, requesting ESG as well as non ESG preferences, a clear denition of ESG preferences and the possibility of ranking ESG preferences. I