The Impact of Loss Aversion and Market Sentiment on Implied Volatility Skews.

The thesis “The Impact of Loss Aversion and Investor Sentiment on Implied Volatility Skews” examines how market participants’ behaviour influences the pricing of equity options. Option Pricing has historically been a purely neoclassical topic, however, articles which link option pricing to behavioural finance are becoming increasingly popular. More specifically implied volatility skews, representing a pricing anomaly with regards to the theoretical, neoclassical assumptions of most option pricing models, are in the center of the research. A first relation to behavioural aspects can be concluded by the fact that implied volatility skews have been observed as a standard pattern since the 1987 US stock market crash. The standard argumentation to explain this anomaly is mainly based on shortfalls of the neoclassical assumptions within the standard option pricing models. Non-normal distribution functions, leverage effects and non-continuous trading markets which follow a jump diffusion process, can all result in distortions in the implied volatility surface. Furthermore, a limitation of arbitrage due to herding and the positioning of market participants also contribute to this inconsistency. The empirical study of the thesis is based on a deep knowledge of option pricing, option sensitivities and derivatives trading strategies. It applies behavioural finance theories to gather evidence on psychological impacts on options implied volatilities. The Prospect Theory, as one of the cornerstones of behavioural finance, lays the foundation for the argumentation about loss aversion and potential positioning of market participants in the option markets. Market Sentiment indicators are used as a proxy for potential loss apprehension. The present thesis focuses on the European option market, whilst the limited research already conducted in this field focused on the US market. It reveals evidence of a relationship between market sentiment and changes in implied volatility skews. It hence supports findings that have been made in previous studies on the US market. Changes in market sentiments can therefore help to understand the mechanism that leads to changes in the slope of implied volatility skews. However, compared to previous studies which mainly focussed on the correlation between skew and sentiment, the empirical study of this thesis analysed the relationship not only in a general way. Due to the 10 year dataset it was possible to also analyse different market environments and leading/delayed dependencies. The thesis therefore contributes to the theoretical understanding of derivatives markets but also adds a practical value in analysing the impacts of sentiment and market participants’ positioning.Administración y Dirección de Empresa

Die Subversion verletzender Worte: Grundlagen einer Politik des Performativen

Hate Speech wird hierzulande zunehmend als ernsthaftes gesellschaftliches Problem erkannt. Während in Debatten über Handlungsmöglichkeiten meistens Sanktionierungen durch staatliche Institutionen im Zentrum stehen, macht der Autor eine rhetorisch-künstlerische Form der Intervention stark, die der verletzenden Kraft nicht frontal entgegentritt, sondern sie umlenkt und zurückwirft. In Auseinandersetzung mit Hate Poetry, Kanak Sprak und Kanak Attak arbeitet der Autor Grundlagen zum Verständnis von Hate Speech und der Subversion verletzender Worte aus. Dabei knüpft er an Konzepte von Butler, Derrida, Austin und Bourdieu an und entwickelt sie weiter. Sein Buch stellt ein differenziertes theoretisches Instrumentarium für eine sprachpolitische Praxis gegen Hate Speech bereit

IFN-γ and TNF-α synergize to inhibit CTGF expression in human lung endothelial cells.

Connective tissue growth factor (CTGF/CCN2) is an angiogenetic and profibrotic factor, acting downstream of TGF-β, involved in both airway- and vascular remodeling. While the T-helper 1 (Th1) cytokine interferon-gamma (IFN-γ) is well characterized as immune-modulatory and anti-fibrotic cytokine, the role of IFN-γ in lung endothelial cells (LEC) is less defined. Tumour necrosis factor alpha (TNF-α) is another mediator that drives vascular remodeling in inflammation by influencing CTGF expression. In the present study we investigated the influence of IFN-γ and TNF-α on CTGF expression in human LEC (HPMEC-ST1.6R) and the effect of CTGF knock down on human LEC. IFN-γ and TNF-α down-regulated CTGF in human LEC at the promoter-, transcriptional- and translational-level in a dose- and time-dependent manner. The inhibitory effect of IFN-γ on CTGF-expression could be almost completely compensated by the Jak inhibitor AG-490, showing the involvement of the Jak-Stat signaling pathway. Besides the inhibitory effect of IFN-γ and TNF-α alone on CTGF expression and LEC proliferation, these cytokines had an additive inhibitory effect on proliferation as well as on CTGF expression when administered together. To study the functional role of CTGF in LEC, endogenous CTGF expression was down-regulated by a lentiviral system. CTGF silencing in LEC by transduction of CTGF shRNA reduced cell proliferation, but did not influence the anti-proliferative effect of IFN-γ and TNF-α. In conclusion, our data demonstrated that CTGF was negatively regulated by IFN-γ in LEC in a Jak/Stat signaling pathway-dependent manner. In addition, an additive effect of IFN-γ and TNF-α on inhibition of CTGF expression and cell proliferation could be found. The inverse correlation between IFN-γ and CTGF expression in LEC could mean that screwing the Th2 response to a Th1 response with an additional IFN-γ production might be beneficial to avoid airway remodeling in asthma

Comparison of Transfer Learning and Established Calibration Transfer Methods for Metal Oxide Semiconductor Gas Sensors

Although metal oxide semiconductors are a promising candidate for accurate indoor air quality assessments, multiple drawbacks of the gas sensors prevent their widespread use. Examples include poor selectivity, instability over time, and sensor poisoning. Complex calibration methods and advanced operation modes can solve some of those drawbacks. However, this leads to long calibration times, which are unsuitable for mass production. In recent years, multiple attempts to solve calibration transfer have been made with the help of direct standardization, orthogonal signal correction, and many more methods. Besides those, a new promising approach is transfer learning from deep learning. This article will compare different calibration transfer methods, including direct standardization, piecewise direct standardization, transfer learning for deep learning models, and global model building. The machine learning methods to calibrate the initial models for calibration transfer are feature extraction, selection, and regression (established methods) and a custom convolutional neural network TCOCNN. It is shown that transfer learning can outperform the other calibration transfer methods regarding the root mean squared error, especially if the initial model is built with multiple sensors. It was possible to reduce the number of calibration samples by up to 99.3% (from 10 days to approximately 2 h) and still achieve an RMSE for acetone of around 18 ppb (15 ppb with extended individual calibration) if six different sensors were used for building the initial model. Furthermore, it was shown that the other calibration transfer methods (direct standardization and piecewise direct standardization) also work reasonably well for both machine learning approaches, primarily when multiple sensors are used for the initial model

Humans in XAI: increased reliance in decision-making under uncertainty by using explanation strategies

IntroductionAlthough decision support systems (DSS) that rely on artificial intelligence (AI) increasingly provide explanations to computer and data scientists about opaque features of the decision process, especially when it involves uncertainty, there is still only limited attention to making the process transparent to end users.MethodsThis paper compares four distinct explanation strategies employed by a DSS, represented by the social agent Floka, designed to assist end users in making decisions under uncertainty. Using an economic experiment with 742 participants who make lottery choices according to the Holt and Laury paradigm, we contrast two explanation strategies offering accurate information (transparent vs. guided) with two strategies prioritizing human-centered explanations (emotional vs. authoritarian) and a baseline (no explanation).Results and discussionOur findings indicate that a guided explanation strategy results in higher user reliance than a transparent strategy. Furthermore, our results suggest that user reliance is contingent on the chosen explanation strategy, and, in some instances, the absence of an explanation can also lead to increased user reliance

First implementation of a new cross-disciplinary observation strategy for heavy precipitation events from formation to flooding

Heavy Precipitation Events (HPE) are the result of enormous quantities of water vapor being transported to a limited area. HPE rainfall rates and volumes cannot be fully stored on and below the land surface, often leading to floods with short forecast lead times that may cause damage to humans, properties, and infrastructure. Toward an improved scientific understanding of the entire process chain from HPE formation to flooding at the catchment scale, we propose an elaborated event-triggered observation concept. It combines flexible mobile observing systems out of the fields of meteorology, hydrology and geophysics with stationary networks to capture atmospheric transport processes, heterogeneous precipitation patterns, land surface and subsurface storage processes, and runoff dynamics. As part of the Helmholtz Research Infrastructure MOSES (Modular Observation Solutions for Earth Systems), the effectiveness of our observation strategy is illustrated by its initial implementation in the Mueglitz river basin (210 km$^2$), a headwater catchment of the Elbe in the Eastern Ore Mountains with historical and recent extreme flood events. Punctual radiosonde observations combined with continuous microwave radiometer measurements and back trajectory calculations deliver information about the moisture sources, and initiation and development of HPE. X-band radar observations calibrated by ground-based disdrometers and rain gauges deliver precipitation information with high spatial resolution. Runoff measurements in small sub-catchments complement the discharge time series of the operational network of gauging stations. Closing the catchment water balance at the HPE scale, however, is still challenging. While evapotranspiration is of less importance when studying short-term convective HPE, information on the spatial distribution and on temporal variations of soil moisture and total water storage by stationary and roving cosmic ray measurements and by hybrid terrestrial gravimetry offer prospects for improved quantification of the storage term of the water balance equation. Overall, the cross-disciplinary observation strategy presented here opens up new ways toward an integrative and scale-bridging understanding of event dynamics

A calibrated diversity assay for nucleic acid libraries using DiStRO—a Diversity Standard of Random Oligonucleotides

We have determined diversities exceeding 1012 different sequences in an annealing and melting assay using synthetic randomized oligonucleotides as a standard. For such high diversities, the annealing kinetics differ from those observed for low diversities, favouring the remelting curve after annealing as the best indicator of complexity. Direct comparisons of nucleic acid pools obtained from an aptamer selection demonstrate that even highly complex populations can be evaluated by using DiStRO, without the need of complicated calculations

Developing a Monolithic Silicon Sensor in a 65 nm CMOS Imaging Technology for Future Lepton Collider Vertex Detectors

Monolithic CMOS sensors in a 65 nm imaging technology are being investigated by the CERN EP Strategic R&D Programme on Technologies for Future Experiments for an application in particle physics. The appeal of monolithic detectors lies in the fact that both sensor volume and readout electronics are integrated in the same silicon wafer, providing a reduction in production effort, costs and scattering material. The Tangerine Project WP1 at DESY participates in the Strategic R&D Programme and is focused on the development of a monolithic active pixel sensor with a time and spatial resolution compatible with the requirements for a future lepton collider vertex detector. By fulfilling these requirements, the Tangerine detector is suitable as well to be used as telescope planes for the DESY-II Test Beam facility. The project comprises all aspects of sensor development, from the electronics engineering and the sensor design using simulations, to laboratory and test beam investigations of prototypes. Generic TCAD Device and Monte-Carlo simulations are used to establish an understanding of the technology and provide important insight into performance parameters of the sensor. Testing prototypes in laboratory and test beam facilities allows for the characterization of their response to different conditions. By combining results from all these studies it is possible to optimize the sensor layout. This contribution presents results from generic TCAD and Monte-Carlo simulations, and measurements performed with test chips of the first sensor submission.Comment: 7 pages, 8 figures, submitted to IEEE Xplore as conference record for 2022 IEEE NSS/MIC/RTS

Growth and yield of mixed versus pure stands of Scots pine (Pinus sylvestris L. ) and European beech (Fagus sylvatica L.) analysed along a productivity gradient through Europe

Mixing of complementary tree species may increase stand productivity, mitigate the effects of drought and other risks, and pave the way to forest production systems which may be more resource-use efficient and stable in the face of climate change. However, systematic empirical studies on mixing effects are still missing for many commercially important and widespread species combinations. Here we studied the growth of Scots pine (Pinus sylvestris L.) and European beech (Fagus sylvatica L.) in mixed versus pure stands on 32 triplets located along a productivity gradient through Europe, reaching from Sweden to Bulgaria and from Spain to the Ukraine. Stand inventory and taking increment cores on the mainly 60-80 year-old trees and 0.02-1.55 ha sized, fully stocked plots provided insight how species mixing modifies the structure, dynamics and productivity compared with neighbouring pure stands. In mixture standing volume (+12 %), stand density (+20 %), basal area growth (+12 %), and stand volume growth (+8 %) were higher than the weighted mean of the neighbouring pure stands. Scots pine and European beech contributed rather equally to the overyielding and overdensity. In mixed stands mean diameter (+20 %) and height (+6 %) of Scots pine was ahead, while both diameter and height growth of European beech were behind (−8 %). The overyielding and overdensity were independent of the site index, the stand growth and yield, and climatic variables despite the wide variation in precipitation (520-1175 mm year−1), mean annual temperature (6-10.5 °C), and the drought index by de Martonne (28-61 mm °C−1) on the sites. Therefore, this species combination is potentially useful for increasing productivity across a wide range of site and climatic conditions. Given the significant overyielding of stand basal area growth but the absence of any relationship with site index and climatic variables, we hypothesize that the overyielding and overdensity results from several different types of interactions (light-, water-, and nutrient-related) that are all important in different circumstances. We discuss the relevance of the results for ecological theory and for the ongoing silvicultural transition from pure to mixed stands and their adaptation to climate change.The networking in this study has been sup-ported by COST Action FP1206 EuMIXFOR. All contributors thanktheir national funding institutions to establish, measure, and analysedata from the triplets. The first author also thanks the BayerischenStaatsforsten (BaySF) for supporting the establishment of the plots,the Bavarian State Ministry for Nutrition, Agriculture, and Forestryfor permanent support of the project W 07 ‘‘Long-term experimentalplots for forest growth and yield research’’ (# 7831-22209-2013) andthe German Science Foundation for providing the funds for the pro-jects PR 292/12-1 ‘‘Tree and stand-level growth reactions on droughtin mixed versus pure forests of Norway spruce and European beech’’.Thanks are also due to Ulrich Kern for the graphical artwork, and totwo anonymous reviewers for their constructive criticism

Swabian MOSES 2021: An interdisciplinary field campaign for investigating convective storms and their event chains

The Neckar Valley and the Swabian Jura in southwest Germany comprise a hotspot for severe convective storms, causing tens of millions of euros in damage each year. Possible reasons for the high frequency of thunderstorms and the associated event chain across compartments were investigated in detail during the hydro-meteorological field campaign Swabian MOSES carried out between May and September 2021. Researchers from various disciplines established more than 25 temporary ground-based stations equipped with state-of-the-art in situ and remote sensing observation systems, such as lidars, dual-polarization X- and C-band Doppler weather radars, radiosondes including stratospheric balloons, an aerosol cloud chamber, masts to measure vertical fluxes, autosamplers for water probes in rivers, and networks of disdrometers, soil moisture, and hail sensors. These fixed-site observations were supplemented by mobile observation systems, such as a research aircraft with scanning Doppler lidar, a cosmic ray neutron sensing rover, and a storm chasing team launching swarmsondes in the vicinity of hailstorms. Seven Intensive Observation Periods (IOPs) were conducted on a total of 21 operating days. An exceptionally high number of convective events, including both unorganized and organized thunderstorms such as multicells or supercells, occurred during the study period. This paper gives an overview of the Swabian MOSES (Modular Observation Solutions for Earth Systems) field campaign, briefly describes the observation strategy, and presents observational highlights for two IOPs