Contributions in Merlin

Does the success of green political parties in parliament influence banks' lending behaviour? This thesis collects data on the relative green party size in 21 countries, defined as the number of seats the green party has in parliament over the total number of available seats and matches it with both firm-level and loan-level data. The data is then analysed using a regression that is based on panel data and industry-size-location-time fixed effects to control for endogeneity. The results show a significant positive correlation between green party presence in parliament and domestic bank loans. This master thesis contributes to the literature that analyses the effects of introducing more stringent climate policies and how banks react when firms experience environmental concerns

This paper analyses the effect of several macroeconomic variables on the returns of the Nikkei 225 (N225) Index. Monthly and daily data of the last 18 to 20 years are used. The applied method for the time series data analysis is the EGARCH model. I find that the one-month government bond yield and the earnings have a negative effect on the N225 Index, while the influence of the unemployment rate, industrial production, Yen/USD exchange rate, retail sales and gross domestic product is positive. Remarkably, the consumer price index and the money aggregate have a positive impact on the N225 Index.

In this study, I examine the validity of the small-cap premium (i.e., the size effect) from 2000 to 2021, using the Swiss Performance Index (SPI) to represent the Swiss stock market. I sort SPI stocks in terms of size (market capitalisation) and value (book-to-market ratio). Then, I construct six portfolios based on these categories to analyse the size effect in relation to performance, as well as statistically. I find that the small market capitalisation portfolio and low bookto-market ratio portfolio returns significantly outperform the benchmark (SPI) over the 21-year period, with this effect amplified during the COVID-19 pandemic. However, I find no significant statistical size effect across the six portfolios.

Central bank purchases under QE programs have the unintended consequence of making some collateral securities more scarce in the market. Such scarcity effects can usually be found in the bilateral repo market, where special repo rates are traded, but prolonged and excessive central bank asset purchases coupled with high a demand for safe assets can also cause a decrease in general collateral repo rates, which in turn reflects the scarcity of the whole class of government bonds. In this dissertation, I study scarcity effects of US Treasuries by investigating the Treasury GCF repo rate. Each $1 trillion purchase of Treasuries by the Fed is associated with a 40-46 basis point decline in the Treasury general collateral repo rate. This suggests moderate general Treasury collateral scarcity effects of quantitative easing in the US.

Multi-Asset Barrier Reverse Convertible (MBRC) are one of the most sold structured products in the world, especially in Switzerland where 200 billion CHF of assets are being sold per year. Some structured products can be evaluated with a close-end solution, which does not exist for MBRCs. There exist multiple methods to price MBRC and this thesis will focus on the implementation of the pricing algorithm of MBRC suggested by Lindauer and Seiz (2008). In this thesis also ceteris paribus effects of influencing parameters are measured and described. It is observed that volatility, maturity, type of the product and a barrier level have a big impact on the final price, whereas the dividend yield and risk-free rate are influencing each other in an unknown way.

The role structure of a top management team (TMT)—the roles of TMT members and the relationships among those roles—has important implications for how TMT members work together as a group in directing an organization and shaping its strategy. Although the importance of TMT role structure has long been noted, it has received scant attention until recently when upper-echelons scholars started examining its formation and influence. To stimulate a concerted effort in studying TMT role structure, we develop a framework elaborating its main themes, draw out key contributions from extant research (see the SMS Collection), and outline promising future directions. In particular, we highlight important dynamics of how formal and informal structures complement or compete with each other in the strategic leadership of an organization.

Face Recognition (FR) is increasingly influencing our lives: we use it to unlock our phones; police uses it to identify suspects. Two main concerns are associated with this increase in facial recognition: (1) the fact that these systems are typically less accurate for marginalized groups, which can be described as “bias”, and (2) the increased surveillance through these systems. Our paper is concerned with the first issue. Specifically, we explore an intuitive technique for reducing this bias, namely “blinding” models to sensitive features, such as gender or race, and show why this cannot be equated with reducing bias. Even when not designed for this task, facial recognition models can deduce sensitive features, such as gender or race, from pictures of faces—simply because they are trained to determine the “similarity” of pictures. This means that people with similar skin tones, similar hair length, etc. will be seen as similar by facial recognition models. When confronted with biased decision-making by humans, one approach taken in job application screening is to “blind” the human decision-makers to sensitive attributes such as gender and race by not showing pictures of the applicants. Based on a similar idea, one might think that if facial recognition models were less aware of these sensitive features, the difference in accuracy between groups would decrease. We evaluate this assumption—which has already penetrated into the scientific literature as a valid de-biasing method—by measuring how “aware” models are of sensitive features and correlating this with differences in accuracy. In particular, we blind pre-trained models to make them less aware of sensitive attributes. We find that awareness and accuracy do not positively correlate, i.e., that bias ≠ awareness. In fact, blinding barely affects accuracy in our experiments. The seemingly simple solution of decreasing bias in facial recognition rates by reducing awareness of sensitive features does thus not work in practice: trying to ignore sensitive attributes is not a viable concept for less biased FR.

Negative symptoms in the psychosis continuum are linked to impairments in reward processing and cognitive function. Processes at the interface of reward processing and cognition and their relation to negative symptoms remain little studied, despite evidence suggestive of integration in mechanisms and neural circuitry. Here, we investigated brain activation during reward-dependent modulation of working memory (WM) and their relationship to negative symptoms in subclinical and early stages of the psychosis continuum. We included 27 persons with high schizotypal personality traits and 23 patients with first episode psychosis as well as 27 healthy controls. Participants underwent functional magnetic resonance imaging while performing an established 2-back WM task with two reward levels (5 CHF vs. no reward), which allowed us to assess common reward-cognition regions through whole-brain conjunction analyses and to investigate relations with clinical scores of negative symptoms. As expected for behavior, reward facilitated performance while cognitive load diminished it. At the neural level, the conjunction of high reward and high cognitive load contrasts across the psychosis continuum showed increased hemodynamic activity in the thalamus and the cerebellar vermis. During high cognitive load, more severe apathy but not diminished expression in the psychosis continuum was associated with reduced activity in right lateral orbitofrontal cortex, midbrain, posterior vermal cerebellum, caudate and lateral parietal cortex. Our results suggest that hypoactivity in the cerebellar vermis and the cortical-striatal-midbrain-circuitry in the psychosis continuum relates to apathy possibly via impaired flexible cognitive resource allocation for effective goal pursuit.

In this paper, we use the methods of networks science to analyse the transaction networks of tokens running on the Ethereum blockchain. We start with a deep dive on four of them: Ampleforth (AMP), Basic Attention Token (BAT), Dai (DAI) and Uniswap (UNI). We study two types of blockchain addresses, smart contracts (SC), which run code, and externally owned accounts (EOA), run by human users, or off-chain code, with the corresponding private keys. We use preferential attachment and network dismantling strategies to evaluate their importance for the network structure. Subsequently, we expand our view to all ERC-20 tokens issued on the Ethereum network. We first study multilayered networks composed of Ether (ETH) and individual tokens using a dismantling approach to assess how the deconstruction starting from one network affects the other. Finally, we analyse the Ether network and Ethereum-based token networks to find similarities between sets of high-degree nodes. For this purpose, we use both the traditional Jaccard Index and a new metric that we introduce, the Ordered Jaccard Index (OJI), which considers the order of the elements in the two sets that are compared. Our findings suggest that smart contracts and exchange-related addresses play a structural role in transaction networks both in DeFi and Ethereum. The presence in the network of nodes associated to addresses of smart contracts and exchanges is positively correlated with the success of the token network measured in terms of network size and market capitalisation. These nodes play a fundamental role in the centralisation of the supposedly decentralised finance (DeFi) ecosystem: without them, their networks would quickly collapse.

For the fifth time since 2018, the Lifelog Search Challenge (LSC) facilitated a benchmarking exercise to compare interactive search systems designed for multimodal lifelogs. LSC'22 attracted nine participating research groups who developed interactive lifelog retrieval systems enabling fast and effective access to lifelogs. The systems competed in front of a hybrid audience at the LSC workshop at ACM ICMR'22. This paper presents an introduction to the LSC workshop, the new (larger) dataset used in the competition, and introduces the participating lifelog search systems.