1,721,251 research outputs found
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
deep generative Models für die Erzeugung synthetischer Zeitreihen und Deep-Hedging-Anwendung
Full text linkMit der zunehmenden Bedeutung von maschinellem Lernen im Finanzbereich gewinnt auch die Erzeugung realistischer Zeitreihendaten für zahlreiche Anwendungen im Finanzsektor an Relevanz. Klassische stochastische Modelle sind zwar nützlich, müssen jedoch stets richtig kalibriert und an die jeweiligen Marktverhältnisse angepasst werden. Das kann sehr aufwendig sein, besonders wenn sich Marktgegebenheiten verändern. Deep Generative Models bieten eine rein datenbasierte Alternative. Frühere Untersuchungen zeigen, dass das Time-GAN-Modell zeitliche Dynamiken gut erfasst, aber im Vergleich zum CEGEN-Modell Schwierigkeiten hat, Abhängigkeiten zwischen den Vermögenswerten zu modellieren. In dieser Arbeit implementieren wir beide Modelle und entwickeln ein hybrides Modell, das die Struktur des CEGEN-Modells in den Trainingsprozess des Time-GAN-Modells integriert, um dessen Qualität zu verbessern. Wir evaluieren die Modelle anhand eines Datensatzes, der aus vier amerikanischen Technologieaktien besteht, und messen die Performance mit verschiedenen Benchmarks und Deep-Hedging-Anwendungen, für die wir das pfhedge-Paket adaptieren und einsetzen. Das CEGEN-Modell erzielt in unseren Untersuchungen die besten Ergebnisse. Als Kombination von CEGEN und Time-GAN schneidet das hybride Modell zwar in mehreren Metriken besser als das Time-GAN-Modell ab, jedoch bleibt es insgesamt hinter dem CEGEN-Modell zurück. Im Vergleich der verschiedenen Deep-Hedging-Modelle, die mit den synthetischen Daten unserer generativen Modelle trainiert wurden, mit klassischen Absicherungsstrategien auf der Grundlage des Black-Scholes-Merton-Modells oder anderen Deep-Hedging-Modellen, die mit Pfaden einer angepassten geometrischen brownschen Bewegung trainiert wurden, können wir keine klare Verbesserung feststellen. Das deutet darauf hin, dass weitere Forschung notwendig ist, bevor solche Modelle vollständig in praktischen Anwendungen eingesetzt werden können.With machine learning becoming increasingly important in finance, generating realistic time series data has become crucial for various financial applications. Traditional stochastic models are useful but often require extensive calibration and may become inadequate in changing market conditions. Deep generative models provide a purely data-driven alternative. Past research has shown that Time-GAN effectively captures temporal dynamics but, compared to CEGEN, struggles to model interdependencies between assets. In this thesis, we implement both generative models and develop a hybrid model that integrates CEGEN’s structure into Time-GAN’s training process to enhance its performance. We evaluate the models using a dataset of four American technology stocks and assess their performance based on multiple benchmarks and deep hedging applications using the pfhedge package. In our experiments, CEGEN outperforms the other generative models. The combined model improves Time-GAN’s results in several metrics, but, reflecting its hybrid nature, still lags behind CEGEN. When comparing deep hedgers trained on synthetic samples from our models, we find no clear outperformance relative to traditional hedging strategies based on the Black-Scholes-Merton model or deep hedgers trained on paths generated by a fitted geometric Brownian motion. This suggests that further research is necessary before fully relying on such models in practical applications
Utility based asset pricing under high risk aversion
Full text linkThis work aims to present three methods of pricing an asset.A price of a derivative is the amount of money a buyer agrees to pay to the seller at time 0 in order to receive the derivative at maturity time T. If the market is complete, this price is uniquely given by the initial wealth of the portfolio in stocks and bonds that recreates the terminal payoff (replication). But in reality transaction costs or non-traded assets cause that the financial market is not complete. Then different prices consistent with the No Arbitrage Condition exist as each corresponds to a different martingale measure. The superreplication price is defined as the supremum of these martingale measures and therefore unrealistically high, but all risks and uncertainty is removed. Hence we want to find another way of pricing in an incomplete market but remain risk averse.For these purposes we introduce the utility indifference price after explaining the concept of utility maximization and giving a short definition on risk aversion. This price considers the risk aversion and can also depend on the agent s initial wealth. Unlike the superreplication price the utility indifference price is not linear in the number of units of the claim, but converges to the superreplication price if the risk aversion tends to infinity. This statement is also proved. The utility indifference price can be considered as an interpolation between the totally risk averse superreplication price and the marginal utility price, which we introduce as the third price. By means of two examples all these properties will be verified
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