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Smart(phone) investing? A within investor-time analysis of new technologies and trading behavior
(2021)
Using transaction-level data from two German banks, we study the effects of smartphones on investor behavior. Comparing trades by the same investor in the same month across different platforms, we find that smartphones increase purchasing of riskier and lottery-type assets and chasing past returns. After the adoption of smartphones, investors do not substitute trades across platforms and buy also riskier, lottery-type, and hot investments on other platforms. Using smartphones to trade specific assets or during specific hours contributes to explain our results. Digital nudges and the device screen size do not mechanically drive our results. Smartphone effects are not transitory.
The FOMC risk shift
(2021)
We identify a component of monetary policy news that is extracted from high-frequency changes in risky asset prices. These surprises, which we call “risk shifts”, are uncorrelated, and therefore complementary, to risk-free rate surprises. We show that (i) risk shifts capture the lion’s share of stock price movements around FOMC announcements; (ii) that they are accompanied by significant investor fund flows, suggesting that investors react heterogeneously to monetary policy news; and (iii) that price pressure amplifies the stock market response to monetary policy news. Our results imply that central bank information effects are overshadowed by short-term dynamics stemming from investor rebalancing activities and are likely to be more difficult to identify than previously thought.
Broad, long-term financial and economic datasets are a scarce resource, in particular in the European context. In this paper, we present an approach for an extensible, i.e. adaptable to future changes in technologies and sources, data model that may constitute a basis for digitized and structured long- term, historical datasets. The data model covers specific peculiarities of historical financial and economic data and is flexible enough to reach out for data of different types (quantitative as well as qualitative) from different historical sources, hence achieving extensibility. Furthermore, based on historical German company and stock market data, we discuss a relational implementation of this approach.
The so-called Troika, consisting of the EU-Commission, the European Central Bank (ECB) and the International Monetary Fund (IMF), was supposed to support the member states of the euro area which had been hit hard by a sovereign debt crisis. For that purpose, economic adjustment programs were drafted and monitored in order to prevent the break-up of the euro area and sovereign defaults. The cooperation of these institutions, which was born out of necessity, has been partly successful, but has also created persistent problems. With the further increase of public debt, especially in France and Italy, the danger of a renewed crisis in the euro area was growing. The European Stability Mechanism (ESM) together with the European Commission will replace the Troika in the future, following decisions of the EU Summit of December 2018. It shall play the role of a European Monetary Fund in the event of a crisis. The IMF, on the other side, will no longer play an active role in solving sovereign debt crises in the euro area. The current course is, however, inadequate to tackle the core problems of the euro zone and to avoid future crises, which are mainly structural in nature and due to escalating public debt and lack of international competitiveness of some member countries. The current Corona crisis will aggravate the institutional problems. It has led to a common European fiscal response ("Next Generation EU"). This rescue and recovery program will not be financed by ESM resources and will not be monitored by the ESM. One important novelty of this package is that it involves the issuance of substantial common European debt.
Der Einsatz von Künstliche Intelligenz (KI) – Technologien eröffnet viele Chancen, birgt aber auch viele Risiken – insbesondere in der Finanzbranche. Dieses Whitepaper gibt einen Überblick über den aktuellen Stand der Anwendung und Regulierung von KI-Technologien in der Finanzbranche, und diskutiert Chancen und Risiken von KI. KI findet in der Finanzbranche zahlreiche Anwendungsgebiete. Dazu gehören Chatbots, intelligente Assistenten für Kunden, automatischer Hochfrequenzhandel, automatisierte Betrugserkennung, Überwachung der Compliance, Gesichtserkennungssoftware zur Kundenidentifikation u. v. m. Auch Finanzaufsichtsbehörden setzen zunehmend KI-Anwendungen ein, um große und komplexe Datenmengen (Big Data) automatisiert und skalierbar auf Muster zu untersuchen und ihren Aufsichtspflichten nachzukommen.
Die Regulierung von KI in der Finanzbranche ist ein Balanceakt. Auf der einen Seite gibt es eine Notwendigkeit Flexibilität zu gewährleisten, um Innovationen nicht einzudämmen und im internationalen Wettbewerb nicht abgehängt zu werden. Strenge Auflagen können in diesem Zusammenhang als Barriere für die erfolgreiche Weiter-)Entwicklung von KI-Applikationen in der Finanzbranche wirken. Auf der anderen Seite müssen Persönlichkeitsrechte geschützt und Entscheidungsprozesse nachvollziehbar bleiben. Die fehlende Erklärbarkeit und Interpretierbarkeit von KI-Modellen entsteht in erster Linie durch Intransparenz bei einem Großteil heutiger KI-Anwendungen, bei welchen zwar die Natur der Ein- und Ausgaben beobachtbar und verständlich ist, nicht jedoch die genauen Verarbeitungsschritte dazwischen (Blackbox Prinzip).
Dieses Spannungsfeld zeigt sich auch im aktuellen regulatorischen Ansatz verschiedener Behörden. So werden einerseits die positiven Seiten von KI betont, wie Effizienz- und Effektivitätsgewinne sowie Rentabilitäts- und Qualitätssteigerungen (Bundesregierung, 2019) oder neue Methoden der Gefahrenanalyse in der Finanzmarktregulierung (BaFin, 2018a). Andererseits, wird darauf verwiesen, dass durch KI getroffene Entscheidungen immer von Menschen verantwortet werden müssen (EU Art. 22 DSGVO) und demokratische Rahmenbedingungen des Rechtsstaats zu wahren seien (FinTechRat, 2017).
Für die Zukunft sehen wir die Notwendigkeit internationale Regularien prinzipienbasiert, vereinheitlicht und technologieneutral weiterzuentwickeln, ohne dabei die Entwicklung neuer KIbasierter Geschäftsmodelle zu bremsen. Im globalen Wettstreit sollte Europa bei der Regulierung des KI-Einsatzes eine Vorreiterrolle einnehmen und damit seine demokratischen Werte der digitalen Freiheit, Selbstbestimmung und das Recht auf Information weltweit exportieren. Förderprogramme sollten einen stärkeren Fokus auf die Entwicklung nachhaltiger und verantwortungsvoller KI in Banken legen. Dazu zählt insbesondere die (Weiter-)Entwicklung breit einsetzbarer Methoden, die es erlauben, menschen-interpretierbare Erklärungen für erzeugte Ausgaben bereitzustellen und Problemen wie dem Blackbox Prinzip entgegenzuwirken.
Aus Sicht der Unternehmen in der Finanzbranche könnte eine Kooperation mit BigTech-Unternehmen sinnvoll sein, um gemeinsam das Potential der Technologie bestmöglich ausschöpfen zu können. Nützlich wäre auch ein gemeinsames semantisches Metadatenmodell zur Beschreibung der in der Finanzbranche anfallenden Daten. In Zukunft könnten künstliche Intelligenzen Daten aus sozialen Netzwerken berücksichtigen oder Smart Contracts aushandeln. Eine der größten Herausforderungen der Zukunft wird das Anwerben geeigneten Personals darstellen.
In the past decades, the use and production of chemicals has been on the rise globally due to increasing industrialization and intensive agriculture; resulting in the occurrence and ecotoxicological risks of chemicals of emerging concern (CECs) in the aquatic compartments. Risks include changes in community structure resulting in the dominance of one species and ecosystem imbalance. When dominant disease-causing organisms are in the environment, the disease transmission is increased. For example, host snails for the schistosomiasis, a human trematode disease, are known to be tolerant to pesticide
exposure compared to the predators. This would therefore result in an increased abundance of snails which consequently increase the disease transmission in the human population.
Kenya, being a low income country faces a lot of challenges with provision of clean water, diseases and sanitation facilities, and increasing population which results in intensive agriculture coupled with pesticide use. Although a lot of research has been carried out on the environmental occurrence and risk of CECs (Chapter 1), most of these studies have been done in developed countries with limited information from Africa. Additionally, research in Africa focused on urban areas with limited number of compounds analyzed and mostly in the water phase, and inadequate information on the effects of CECs on the aquatic organisms. In order to reduce this knowledge gap, this dissertation focused on identification and quantification of CECs present in water, sediment and snails from western Kenya, and the contribution of pesticides to the transmission of schistosomiasis.
Chapter 2 gives a summary of the results and discussion of the dissertation. In Chapter 3, a comprehensive chemical analysis was carried out on 48 water samples to identify compounds, spatial patterns and associated risks for fish, crustacean and algae using toxic unit (TU) approach. A total of 78 compounds were detected with pesticides and biocides being the compounds most frequently detected. Spatial pattern analysis revealed limited compound grouping based on land use. Acute risk for crustaceans and algae were driven by one to three individual compounds. These compounds responsible for toxicity were prioritized as candidate compounds for monitoring and regulation in Kenya.
In Chapter 4, an extension of Chapter 3 was done to cover the CECs present in snails and sediment from the 48 sites. A total of 30 compounds were found in snails and 78 in sediments with 68 additional compounds being found which were not previously detected in water. Higher contaminant concentrations were found in agricultural sites than in areas without anthropogenic activities. The highest acute toxicity (TU 0.99) was determined for crustaceans based on compounds in sediment samples. The risk was driven by diazinon and pirimiphos-methyl. Acute and chronic risks to algae were driven by diuron whereas fish were found to be at low to no acute risk.
In Chapter 5, the effect of pesticide contamination on schistosomiasis transmission was evaluated by applying complimentary laboratory and field studies. In the field studies, the ecological mechanisms through which pesticides and physical chemical parameters affect host snails, predators and competitors were investigated. Pesticide data was obtained from the results in chapter 3. The overall distribution of grazers and predators was not affected by pesticide pollution. However, within the grazers, pesticide pollution increased dominance of host snails. On the contrary, the host-snail competitors were highly sensitive to pesticide exposure. For the laboratory studies, macroinvertebrates including Schistosoma-host snails, competitors and predators were exposed to 6 concentrations levels of imidacloprid and diazinon. Snails showed higher insecticide tolerance compared to competitors and predators. Finally, Chapter 6 summarizes the conclusions of this dissertation, placing it in a broader
context. In this dissertation, a comprehensive chemical characterization and risk assessment of CECs has been carried out in freshwater systems; together with the effects of pesticides on schistosomiasis transmission in rural western Kenya. Results of this dissertation showed that rural areas are contaminated posing a risk to aquatic organisms which contribute to schistosomiasis transmission. This shows the need for regular monitoring and policy formulation to reduce pollutant emissions which contributes negatively to both ecological and human health effects.
Background: Extracorporeal life support (ECLS) has become an integral part of modern intensive therapy. The choice of support mode depends largely on the indication. Patients with respiratory failure are predominantly treated with a venovenous (VV) approach. We hypothesized that mortality in Germany in ECLS therapy did not differ from previously reported literature
Methods: Inpatient data from Germany from 2007 to 2018 provided by the Federal Statistical Office of Germany were analysed. The international statistical classification of diseases and related health problems codes (ICD) and process keys (OPS) for extracorporeal membrane oxygenation (ECMO) types, acute respiratory distress syndrome (ARDS) and hospital mortality were used.
Results: In total, 45,647 hospitalized patients treated with ECLS were analysed. In Germany, 231 hospitals provided ECLS therapy, with a median of 4 VV-ECMO and 9 VA-ECMO in 2018. Overall hospital mortality remained higher than predicted in comparison to the values reported in the literature. The number of VV-ECMO cases increased by 236% from 825 in 2007 to 2768 in 2018. ARDS was the main indication for VV-ECMO in only 33% of the patients in the past, but that proportion increased to 60% in 2018. VA-ECMO support is of minor importance in the treatment of ARDS in Germany. The age distribution of patients undergoing ECLS has shifted towards an older population. In 2018, the hospital mortality decreased in VV-ECMO patients and VV-ECMO patients with ARDS to 53.9% (n = 1493) and 54.4% (n = 926), respectively.
Conclusions: ARDS is a severe disease with a high mortality rate despite ECLS therapy. Although endpoints and timing of the evaluations differed from those of the CESAR and EOLIA studies and the Extracorporeal Life Support Organization (ELSO) Registry, the reported mortality in these studies was lower than in the present analysis. Further prospective analyses are necessary to evaluate outcomes in ECMO therapy at the centre volume level.
Objective: The COVID-19 pandemic made it necessary to convert a course on history taking, in theory and practice, to an online format over a very short time. A key question was whether, and if so to what extent, basic theory and, in particular, the practical skills required to conduct medical interviews can be learned online.
Methodology/project description: The teaching program in basic theory was didactically redesigned and asynchronously placed on a learning platform, while the practical program, which consisted of training in conducting history-taking interviews, took place with the help of video conferencing software during synchronous sessions. For the practical sessions, the lecturers received organizational and technical support.
Results: Based on initial evaluation results, a positive picture of the conversion has emerged since the course was completed. The need to restructure the course and use new teaching methods because of the COVID-19 pandemic was well accepted by lecturers and students, and the course content was successfully adapted to an online format.
Conclusion: Overall, the online format enabled the learning objectives of the course to be successfully achieved. For topics such as non-verbal communication, the evaluation results indicated that a classroom format is preferable. Asynchronous theory teaching was generally very well received. Blended learning formats thus represent an appropriate means of teaching how to conduct medical interviews. Overall, online courses on conducting medical interviews provide students with the opportunity to become acquainted with the use of digital formats to conduct doctor-patient interviews, and to develop the relevant skills.