1,721,033 research outputs found
Financial markets as disordered interacting systems: information, risk and illiquidity
Full text linkTaming financial systemic risk: models, instruments and early warning indicators
No full textIn recent decades, most advanced and developing economies have suffered—or are still suffering—from profound and repeated crises. The literature has reflected on the determinants of these perturbations by placing particular emphasis on the malfunctioning of either the real or financial sphere of the economy. The main research question has been to understand whether it was the real economy that perturbed finance sectors or, alternatively, the financial/credit market that depressed real production. Whatever the direction of the causality nexus and, consequently the origin of the attack, with some studies identifying the direction from real markets to financial sectors (see Bernanke and Gertler 1989; Greenwald and Stiglitz 1993; Delli Gatti et al. 2012) and others reversing it (see Christiano and Ikeda 2011; Brunnermeier et al. 2012), what is certainly undoubted is the self-reinforcing interaction between the two sectors, which translates into booms followed by busts. In light of this, part of the literature has not focused as much on the origin of crises, but rather on the mechanisms of shock propagation. In this regard, many studies have shown that a combination of forces is needed to generate shock transmission. Specifically, the literature on contagion has shown that agents’ interaction and the emerging network topology are key ingredients for the spread of systemic risk (see, for instance, Lux 2016; Lux and Montagna 2017)
Taming financial systemic risk: models, instruments and early warning indicators
Full text linkIn recent decades, most advanced and developing economies have suffered—or are still suffering—from profound and repeated crises. The literature has reflected on the determinants of these perturbations by placing particular emphasis on the malfunctioning of either the real or financial sphere of the economy. The main research question has been to understand whether it was the real economy that perturbed finance sectors or, alternatively, the financial/credit market that depressed real production. Whatever the direction of the causality nexus and, consequently the origin of the attack, with some studies identifying the direction from real markets to financial sectors (see Bernanke and Gertler 1989; Greenwald and Stiglitz 1993; Delli Gatti et al. 2012) and others reversing it (see Christiano and Ikeda 2011; Brunnermeier et al. 2012), what is certainly undoubted is the self-reinforcing interaction between the two sectors, which translates into booms followed by busts. In light of this, part of the literature has not focused as much on the origin of crises, but rather on the mechanisms of shock propagation. In this regard, many studies have shown that a combination of forces is needed to generate shock transmission. Specifically, the literature on contagion has shown that agents’ interaction and the emerging network topology are key ingredients for the spread of systemic risk (see, for instance, Lux 2016; Lux and Montagna 2017). The interaction has in fact been recognized as generating two opposing effects: risk sharing, which decreases with connectivity, and systemic risk, which in contrast, increases with linkages (see, for instance, Allen and Gale 2000; Battiston et al. 2007, 2012a, b; Grilli et al. 2014; Iori et al. 2006; Mazzarisi et al. 2020; Tedeschi et al. 2012). Many other studies have confirmed the nonlinearity of this relationship. This body of work has also shown that other factors must be added to generate the catastrophic effects that characterized the 2007 financial collapse, namely the agents’ heterogeneity and financial fragility (see Aymanns et al. 2016; Bardoscia et al. 2017; Caccioli et al. 2011, 2014, 2015; Lenzu and Tedeschi 2012). In fact, as reported by Berardi and Tedeschi (2017) “on the one hand, the possible emergence of contagion depends crucially on the degree of heterogeneity. Indeed, when the agents’ balance sheets are heterogeneous, banks are not uniformly exposed to their counter-party. Therefore, if contagion is triggered by the failure of a big bank, which represents the highest source of exposure for its creditors, the situation is certainly worse than when agents are homogeneous [...]. On the other hand, the probability of default in credit markets is strictly linked to the presence of highly leveraged agents [...]. Indeed, when variations in the level of financial robustness of institutions tend to persist in time or to get amplified, financial linkages among financially fragile banks represent a propagation channel for contagion and a source of systemic risk.” Interestingly enough, this second element is very close in spirit to the Minskyan financial instability hypothesis, where endogenous shifts in the degree of financial fragility of agents generate business fluctuations and, possibly, the materialization of bankruptcy cascades (see Minsky 1964; Ferri and Minsky 1992)
Excess reciprocity distorts reputation in online social networks
Full text linkThe peer-to-peer (P2P) economy relies on establishing trust in distributed networked systems, where the reliability of a user is assessed through digital peer-review processes that aggregate ratings into reputation scores. Here we present evidence of a network effect which biases digital reputation, revealing that P2P networks display exceedingly high levels of reciprocity. In fact, these are much higher than those compatible with a null assumption that preserves the empirically observed level of agreement between all pairs of nodes, and rather close to the highest levels structurally compatible with the networks' reputation landscape. This indicates that the crowdsourcing process underpinning digital reputation can be significantly distorted by the attempt of users to mutually boost reputation, or to retaliate, through the exchange of ratings. We uncover that the least active users are predominantly responsible for such reciprocity-induced bias, and that this fact can be exploited to obtain more reliable reputation estimates. Our findings are robust across different P2P platforms, including both cases where ratings are used to vote on the content produced by users and to vote on user profiles
Ranking mobility and impact inequality in early academic careers
Full text linkHow difficult is it for an early career academic to climb the ranks of their
discipline? We tackle this question with a comprehensive bibliometric analysis
of 57 disciplines, examining the publications of more than 5 million authors
whose careers started between 1986 and 2008. We calibrate a simple random walk
model over historical data of ranking mobility, which we use to (1) identify
which strata of academic impact rankings are the most/least mobile and (2)
study the temporal evolution of mobility. By focusing our analysis on cohorts
of authors starting their careers in the same year, we find that ranking
mobility is remarkably low for the top and bottom-ranked authors, and that this
excess of stability persists throughout the entire period of our analysis. We
further observe that mobility of impact rankings has increased over time, and
that such rise has been accompanied by a decline of impact inequality, which is
consistent with the negative correlation that we observe between such two
quantities. These findings provide clarity on the opportunities of new scholars
entering the academic community, with implications for academic policymaking
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
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