Estimating the expected cost of equity capital using consensus forecasts

In this study, we develop a technique for estimating a firm’s expected cost of equity capital derived from analyst consensus forecasts and stock prices. Building on the work of Gebhardt/Lee/-Swaminathan (2001) and Easton/Taylor/Shroff/Sougiannis (2002), our approach allows daily estimation, using only publicly available information at that date. We then estimate the expected cost of equity capital at the market, industry and individual firm level using historical German data from 1989-2002 and examine firm characteristics which are systematically related to these estimates. Finally, we demonstrate the applicability of the concept in a contemporary case study for DaimlerChrysler and the European automobile industry

Robert Nye’s Falstaff: A Remarkable Case of Creative Reception

Among fictitious autobiographies as well as among historical novels, Robert Nye’s Falstaff (1976) is a special case in that it is not the autobiography of a historical personage, but of a dramatic character —who happens to be one of the most famous in Shakespeare, indeed in world drama, to be dictated by Falstaff to various amanuenses. After briefly discussing the sub-genre of fictitious autobiography, this paper will analyze the varied use of intertextuality, the tensions fabricated between the autobiographer and his helpers, and the critical thoughts and tendencies which Nye absorbed in preparing the work with particular emphasis on the clash between the Shakespearean intertexts and the diction surrounding it

The attack on Ukraine and the militarisation of Russian foreign and domestic policy: a stress test for military reform and regime legitimacy

Moscow's decision on 24 February 2022 to invade Ukraine constituted a culmination in the militarisation trajectory of Russian foreign policy since 2008. At the same time, the war has exposed the weaknesses of the military reform launched by Moscow in 2008. The high losses of the country's armed forces in Ukraine limit Russia's military power projection capabilities, for example in Syria and in other conflicts. Moreover, military setbacks and partial mobilisation have undermined an important pillar of the regime's legitimacy. (author's abstract

On the Non-Associativity of Analog Computations

The energy efficiency of analog forms of computing makes it one of the most promising candidates to deploy resource-hungry machine learning tasks on resource-constrained system such as mobile or embedded devices. However, it is well known that for analog computations the safety net of discretization is missing, thus all analog computations are exposed to a variety of imperfections of corresponding implementations. Examples include non-linearities, saturation effect and various forms of noise. In this work, we observe that the ordering of input operands of an analog operation also has an impact on the output result, which essentially makes analog computations non-associative, even though the underlying operation might be mathematically associative. We conduct a simple test by creating a model of a real analog processor which captures such ordering effects. With this model we assess the importance of ordering by comparing the test accuracy of a neural network for keyword spotting, which is trained based either on an ordered model, on a non-ordered variant, and on real hardware. The results prove the existence of ordering effects as well as their high impact, as neglecting ordering results in substantial accuracy drops.Comment: Published at the ECML PKDD Conference 2023, at the 4th Workshop on IoT, Edge, and Mobile for Embedded Machine Learnin

Fixed Point Analysis Workflow for efficient Design of Convolutional Neural Networks in Hearing Aids

Neural networks (NN) are a powerful tool to tackle complex problems in hearing aid research, but their use on hearing aid hardware is currently limited by memory and processing power. To enable the training with these constrains, a fixed point analysis and a memory friendly power of two quantization (replacing multiplications with shift operations) scheme has been implemented extending TensorFlow, a standard framework for training neural networks, and the Qkeras package [1, 2]. The implemented fixed point analysis detects quantization issues like overflows, underflows, precision problems and zero gradients. The analysis is done for each layer in every epoch for weights, biases and activations respectively. With this information the quantization can be optimized, e.g. by modifying the bit width, number of integer bits or the quantization scheme to a power of two quantization. To demonstrate the applicability of this method a case study has been conducted. Therefore a CNN has been trained to predict the Ideal Ratio Mask (IRM) for noise reduction in audio signals. The dataset consists of speech samples from the TIMIT dataset mixed with noise from the Urban Sound 8kand VAD-dataset at 0 dB SNR. The CNN was trained in floating point, fixed point and a power of two quantization. The CNN architecture consists of six convolutional layers followed by three dense layers. From initially 1.9 MB memory footprint for 468k float32 weights, the power of two quantized network is reduced to 236 kB, while the Short Term Objective Intelligibility (STOI) Improvement drops only from 0.074 to 0.067. Despite the quantization only a minimal drop in performance was observed, while saving up to 87.5 % of memory, thus being suited for employment in a hearing ai

Variability of the ice nuclei concentration over Central Europe

Die kumulative Dissertation beschäftigt sich mit der atmosphärischen Konzentration von Eiskeimen, einer Unterklasse des atmosphärischen Aerosols, die bei der Eisbildung in Wolken eine zentrale Bedeutung besitzt. Messungen der Eiskeimkonzentration am Taunusobservatorium (Kleiner Feldberg) (nahe Frankfurt am Main) wurden mit dem Verfahren einer Vakuum-Diffusionskammer durchgeführt. Die Arbeit umfasst die Darstellung des angewandten Messverfahrens und die Analyse und Bewertung der Messergebnisse für den Raum Zentraleuropa, anhand von u.a. Rückwärtstrajektorien und Korrelationen zu aerosolphysikalischen Parametern. Ein signifikanter Einfluss von Mineralstaub-Ferntransport aus Wüstengebieten auf die Eiskeimkonzentration in Zentral-Europa wurde ermittelt.The topic of this cumulative thesis is the variability of the concentration of atmospheric ice nuclei (IN), a sub-group of the atmospheric aerosol, that plays a central role in the process of ice-formation in clouds. The measurements of the IN number concentration at a mountain station (Kleiner Feldberg, near Frankfurt am Main) with a static vacuum-diffusion chamber are discussed. The measuring system is described in detail. In addition the thesis includes an analysis and an appraisal of the results for Central Europe, using amongst others backward-trajectories and correlation-analysis with aerosol-physical parameters. A significant influence of long range transport of desert dust to Europe on the ice nuclei concentration is being detected

Shakespeare in French literary historiography

La réception de Shakespeare en France a déjà longtemps fourni un sujet d’études se concentrant sur maints auteurs, aspects et périodes. Cette communication étudie quelques aspects d’un champs qui ne semble pas encore avoir été exploré : les histoires de la littérature française. L’espace accordé à Shakespeare dans ces livres, probablement écrits pour la plupart par des spécialistes non pas de littérature anglaise, mais française, et s’adressant à un public qui s’intéresse à ce sujet-là est considérable. Les dictionnaires littéraires forment un premier objet d’analyse. Dans ce genre de livre, il y a eu, ces cinquante dernières années, des articles assez profonds sur Shakespeare. La même approche comparatiste, voire cosmopolite, déjà assez commune au dix-huitième siècle, caractérise (aux côtés d’une emphase sur l’identité et et sur la particularité françaises) un nombre étonnant de ces panoramas historiques de la littérature française de large envergure. L’accent reste par dessus tout sur les oeuvres dramatiques de Shakespeare, et dans ce genre sur les tragédies. Les discussions de la part des historiens de Voltaire, Ducis et Hardy sont étudiées de plus près comme des cas particulièrement révélateurs. Depuis le milieu du dix-neuvième siècle, Shakespeare a été reconnu dans l’historiographie littéraire française comme un des plus grands dramaturges de tous les temps, et beaucoup de comparaisons et de réflexions sur ses oeuvres démontrent à quel point il fait maintenant partie de la conscience culturelle française.The reception of Shakespeare in France has been studied for a long time and with regard to many different authors, aspects, and periods. The present paper takes a look at some parts of an area that does not appear to have been explored so far : histories of French literature. The places given to Shakespeare in such books, presumably written for the most part by specialists not in English, but in French literature and addressing readers interested in that subject, is very considerable. A first focus are literary dictionaries. In this kind of book there have been quite thorough entries for Shakespeare over the last fifty years. This comparative, indeed cosmopolitan approach, which was already widespread in the eighteenth century, also marks (alongside some strong assertions of French identity and particularity) an amazing number of large-scale historical surveys of French literature. The emphasis is constantly on Shakespeare’s dramatic works, and within that genre on the tragedies. The discussions by the historians of Voltaire, Ducis and Hardy are treated in some detail as particularly interesting sample cases. Since the middle of the nineteenth century the recognition of Shakespeare as one of the greatest dramatists of all time has become commonplace in French literary historiography, and many spontaneous comparisons as well as reflections on his work show to what extent he has become part of the cultural consciousness of France

A Riemannian Take on Human Motion Analysis and Retargeting

Dynamic motions of humans and robots are widely driven by posture-dependent nonlinear interactions between their degrees of freedom. However, these dynamical effects remain mostly overlooked when studying the mechanisms of human movement generation. Inspired by recent works, we hypothesize that human motions are planned as sequences of geodesic synergies, and thus correspond to coordinated joint movements achieved with piecewise minimum energy. The underlying computational model is built on Riemannian geometry to account for the inertial characteristics of the body. Through the analysis of various human arm motions, we find that our model segments motions into geodesic synergies, and successfully predicts observed arm postures, hand trajectories, as well as their respective velocity profiles. Moreover, we show that our analysis can further be exploited to transfer arm motions to robots by reproducing individual human synergies as geodesic paths in the robot configuration space.Comment: Accepted for publication in IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 202