Corporate disclosure and investor sentiment

Investor decision-making relies on accurate, timely information, but market efficiency theories and information asymmetry challenge the ability to outperform the market. Disclosure practices, including the emerging importance of ESG information, play a key role in shaping investor sentiment and market dynamics. Digital platforms, especially social media, have transformed how information is disseminated, influencing corporate disclosure practices and investor reactions. Behavioral finance highlights how psychological factors can lead to deviations from fundamental valuations. The COVID-19 pandemic underscored the impact of external shocks on investor sentiment, with government interventions playing a critical role in market responses. Auditing, adapting to include non-financial information like ESG, remains essential in reducing information asymmetry, with modern data-analytic tools like Process Mining offering potential to enhance audit efficiency. This dissertation explores the interplay between financial reporting, news dissemination, auditing practices, and their collective impact on the capital market, highlighting the importance of active corporate communication, government response to crises, and the evolving role of auditing in maintaining market trust

Borrowing in Foreign Currency: Austrian Households as Carry Traders

Household borrowing in a foreign currency is a widespread phenomenon in Austria. Twelve percent of Austrian households report their housing loan to be denominated in either Swiss franc or Japanese yen for example. Yet, despite its importance, peculiar character, and immediate policy concerns, we know too little about the attitudes and characteristics of the households involved in this type of carry trade. We analyze a uniquely detailed financial wealth survey of 2,556 Austrian households to sketch a comprehensive profile of the attitudes and characteristics of the households involved. We employ both univariate tests and multivariate multinomial logit models. The survey data suggests that risk-loving, wealthy, and married households are more likely to take a housing loan in a foreign currency. High-income households are more likely to take a housing loan in general. These findings may partially assuage policy concerns about household default risk on foreign-currency housing loans.oreign currency borrowing, mortgages, banking sector, Austria, Swissfrancs

Efficient and realistic 3-D Boundary Element simulations of underground construction using isogeometric analysis

The paper outlines some recent developments of the boundary element method (BEM) that makes it more user friendly and suitable for a realistic simulation in geomechanics, especially for underground excavations and tunnelling. The innovations refer to the introduction of isogeometric concepts, elasto-plastic analysis and the simulation of ground support. The introduction of isogeometric concepts for the description of the excavation boundaries results in less user and analysis effort, since complex geometries can be modelled with few parameters and degrees of freedom. No mesh generation is necessary. In order to consider heterogeneous and inelastic ground conditions a domain discretisation is used but the use of isogeometric methods results in a minimum of user effort. Efficient methods are also presented for modelling rock bolts. A comparison of results of test examples with other numerical methods and analytical solutions confirm the efficiency and accuracy of the proposed implementation. A practical example with a complex geometry is presented.Comment: 33 pages, 25 figures. arXiv admin note: text overlap with arXiv:2003.1021

The Turn to Artificial Intelligence in Governing Communication Online

Presently, we are witnessing an intense debate about technological advancements in artificial intelligence (AI) research and its deployment in various societal domains and contexts. In this context, media and communications is one of the most prominent and contested fields. Bots, voice assistants, automated (fake) news generation, content moderation and filtering – all of these are examples of how AI and machine learning are transforming the dynamics and order of digital communication. On 20 March 2018 the Alexander von Humboldt Institute for Internet and Society together with the non-governmental organisation Access Now hosted the one-day expert workshop “The turn to AI in governing communication online”. International experts from academia, politics, civil society and business gathered in Berlin to discuss the complex socio-technical questions and issues concerning subjects such as artificial intelligence technologies, machine learning systems, the extent of their deployment in content moderation and the range of approaches to understanding the status and future impact of AI systems for governing social communication on the internet. This workshop report summarises and documents the authors’ main takeaways from the discussions. The discussions, comments and questions raised and responses from experts also fed into the report. The report has been distributed among workshop participants. It is intended to contribute current perspectives to the discourse on AI and the governance of communication

Coupling of boundary element regions with the boundary element tearing and interconnecting method (BETI)

The boundary integral equation for elasticity is valid for a single domain consisting of homogeneous material properties. In the case of heterogeneity the consideration of different material properties is possible with a coupling of boundary element regions. Of course each region is again homogeneous. Another simulation application of multiple regions is the simulation of an industrial process, where different subdomains of a homogenous domain are treated differently due to a mechanical process. For instance, this is the case in tunnelling, where excavation is performed in a staged procedure. In the simulation of such an excavation process regions are deactivated step by step. As the material behaviour can be nonlinear an accurate simulation of such a staged process is a necessary requirement. Thus, the domain is decomposed into subregions which are coupled to neighbouring regions. There are different coupling strategies existing. In some of them stiffness matrices of subdomains are worked out which are the basis for the coupling and solution of the problem. A traditional method is the coupling of interface surfaces only [1]. In this method the stiffness matrix of a region is computed on the basis of the coupling surfaces (interfaces), whereas the coupling surface may be not identical to the complete surface of a subdomain and the size of the stiffness matrix is determined by the degrees of freedom of the coupling surface. In an application where the boundary conditions change (e.g. from interface to Neumann condition) from one calculation step to the other, the stiffness matrix has to be calculated new. A modern coupling technique is the Boundary Element Tearing and Interconnecting (BETI) method [2], similar to the method of Finite Element Tearing and Interconnecting (FETI) [3]. In this method the region stiffness matrix is worked out for the entire boundary of the region. The stiffness matrices of all regions remain the same during the whole analysis, even if the boundary conditions change during the simulation process. In setting up the equation system each subdomain is treated completely separated and independent from the others. Thus, a parallelisation of the computational work is ideally suited and implemented in the present computer code. In this work the theory of both mentioned coupling techniques are introduced briefly. The differences of both methods are worked out and advantages/disadvantages are shown and will be demonstrated. The accuracy of the results as well as the computational performance will be shown and compared based on a realistic simulation example

COVID-19 pandemic and capital markets: the role of government responses

This paper analyzes the moderation effect of government responses on the impact of the COVID-19 pandemic, proxied by the daily growth in COVID-19 cases and deaths, on the capital market, i.e., the S&P 500 firm’s daily returns. Using the Oxford COVID-19 Government Response Tracker, we monitor 16 daily indicators for government actions across the fields of containment and closure, economic support, and health for 180 countries in the period from January 1, 2020 to March 15, 2021. We find that government responses mitigate the negative stock market impact and that investors’ sentiment is sensitive to a firm’s country-specific revenue exposure to COVID-19. Our findings indicate that the mitigation effect is stronger for firms that are highly exposed to COVID-19 on the sales side. In more detail, containment and closure policies and economic support mitigate negative stock market impacts, while health system policies support further declines. For firms with high revenue exposure to COVID-19, the mitigation effect is stronger for government economic support and health system initiatives. Containment and closure policies do not mitigate stock price declines due to growing COVID-19 case numbers. Our results hold even after estimating the spread of the pandemic with an epidemiological standard model, namely, the susceptible-infectious-recovered model

Effects of short-term variability of meteorological variables on soil temperature in permafrost regions

Effects of the short-term temporal variability of meteorological variables on soil temperature in northern high-latitude regions have been investigated. For this, a process-oriented land surface model has been driven using an artificially manipulated climate dataset. Short-term climate variability mainly impacts snow depth, and the thermal diffusivity of lichens and bryophytes. These impacts of climate variability on insulating surface layers together substantially alter the heat exchange between atmosphere and soil. As a result, soil temperature is 0.1 to 0.8 ∘C higher when climate variability is reduced. Earth system models project warming of the Arctic region but also increasing variability of meteorological variables and more often extreme meteorological events. Therefore, our results show that projected future increases in permafrost temperature and active-layer thickness in response to climate change will be lower (i) when taking into account future changes in short-term variability of meteorological variables and (ii) when representing dynamic snow and lichen and bryophyte functions in land surface models

Distinction of subtype-specific antibodies against European porcine influenza viruses by indirect ELISA based on recombinant hemagglutinin protein fragment-1

BACKGROUND: Serological investigations of swine influenza virus infections and epidemiological conclusions thereof are challenging due to the complex and regionally variable pattern of co-circulating viral subtypes and lineages and varying vaccination regimes. Detection of subtype-specific antibodies currently depends on hemagglutination inhibition (HI) assays which are difficult to standardize and unsuitable for large scale investigations. METHODS: The nucleocapsid protein (NP) and HA1 fragments of the hemagglutinin protein (HA) of five different lineages (H1N1av, H1N1pdm, H1pdmN2, H1N2, H3N2) of swine influenza viruses were bacterially expressed and used as diagnostic antigens in indirect ELISA. RESULTS: Proteins were co-translationally mono-biotinylated and refolded in vitro into an antigenically authentic conformation. Western blotting and indirect ELISA revealed highly subtype-specific antigenic characteristics of the recombinant HA1 proteins although some cross reactivity especially among antigens of the H1 subtype were evident. Discrimination of antibodies directed against four swine influenza virus subtypes co-circulating in Germany was feasible using the indirect ELISA format. CONCLUSIONS: Bacterially expressed recombinant NP and HA1 swine influenza virus proteins served as antigens in indirect ELISAs and provided an alternative to commercial blocking NP ELISA and HI assays concerning generic (NP-specific) and HA subtype-specific sero-diagnostics, respectively, on a herd basis