1,720,964 research outputs found
Proceedings of the 1st International Workshop on Grid Technology for Financial Modeling and Simulation (GRID 2006)
No full textDistribuzione a pagamento di musica sulla rete radiomobile via Internet: Aspetti tecnici ed economici
No full textMusica Digitale: significato, formati e trend di mercat
The Stability of Tax Elasticities over the Business Cycle in European Countries
No full textWe estimate short- and long-run tax elasticities that capture the relationship between changes in national income and tax revenue. We show that the short-run tax elasticity changes according to the business cycle. We estimate a two-state Markov-switching regression on a novel data set of tax policy reforms in 15 European countries from 1980 to 2013, showing that the elasticities during booms and recessions are statistically (and often economically) different. The elasticities of personal income taxes, corporate income taxes, indirect taxes and social contributions tend to be larger during recessions. Estimates of long-run elasticities are in line with existing literature
Machine learning-driven credit risk: a systemic review
Full text linkCredit risk assessment is at the core of modern economies. Traditionally, it is measured by statistical methods and manual auditing. Recent advances in financial artificial intelligence stemmed from a new wave of machine learning (ML)-driven credit risk models that gained tremendous attention from both industry and academia. In this paper, we systematically review a series of major research contributions (76 papers) over the past eight years using statistical, machine learning and deep learning techniques to address the problems of credit risk. Specifically, we propose a novel classification methodology for ML-driven credit risk algorithms and their performance ranking using public datasets. We further discuss the challenges including data imbalance, dataset inconsistency, model transparency, and inadequate utilization of deep learning models. The results of our review show that: 1) most deep learning models outperform classic machine learning and statistical algorithms in credit risk estimation, and 2) ensemble methods provide higher accuracy compared with single models. Finally, we present summary tables in terms of datasets and proposed models
The Determinants of Risk Premia on the Italian Stock Market: Empirical Evidence on Common Factors in Asset Pricing Models
No full textWe study the pricing factor structure of Italian equity returns using 25 years of data. A two‐step empirical analysis is provided where first we estimate an unrestricted multifactor model to test if there is any evidence of misspecification. Then, we estimate the restricted model through the
Generalized Methods of Moments. We find that the market premium and
the size premium are confirmed for a domestic Italian investor. On the
contrary, weak evidence is found for the value premium. Finally, we
highlight, that augmenting the model with a momentum factor may at least
partially improve its performance. As a robustness check we control if the
above results also hold for three shorter sub‐periods taking into account
the macroeconomic and financial conditions that characterized the Italian
economy. The results are generally confirmed in the case of the size and
value factors while the momentum effect shows an irregular trend playing
any role in the first sub‐period but becoming more important in the
subsequent two
External shocks, trade margins, and macroeconomic dynamics
Full text linkThis paper studies the role of the exchange rate regime for trade of new products. It first provides VAR evidence that a rise in external productivity shifts trade away from new products and more so in fixed regimes. Then, it presents a model with firm dynamics in line with this evidence. We argue that exchange rate policy can affect firms' entry decisions with consequences for the competitiveness of a country's exports well beyond the short run. In our setup, fixed exchange rates can foster the competitiveness of firms that trade new products, while flexible rates favor firms that produce mature products
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
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