1,720,986 research outputs found
Wrong Way Risk corrections to CVA in CIR reduced-form models
Full text linkIn this paper we provide an efficient methodology to compute the credit value adjustment of a European contingent claim subject to some default event concerning the issuer solvability, when the underlying and the default event are correlated. In particular, in a Black and Scholes market/CIR intensity-default model, we consider
a second order expansion around the origin of a vulnerable call option with respect to a correlation parameter , which may be used to describe the wrong way risk of the contract, measuring the dependence between the underlying asset price and the option’s issuer default intensity. Numerical implementations of this approach are compared with the benchmark Monte Carlo simulations
Probabilistic and statistical methods in commodity risk management
No full textThe vast landscape of the financial sector is characterized by the continuous introduction of innovative financial
instruments, providing investors with diverse opportunities for an efficient capital allocation. In this dynamic context,
commodities emerge as a cornerstone, encapsulating an ancient financial exchange mechanism that carries profound
contemporary implications. The historical significance of commodities as tradable assets intertwines with their crucial
role in modern financial markets. Investments in commodities and their associated derivatives stand out as fundamental
subjects in both academic and applied financial literature. The framework surrounding these investments has witnessed
continual evolution, shaping the ongoing development of sophisticated models and methods to understand and predict
their behavior.
Within the expansive theme of commodities market modeling, two closely interlinked aspects accentuate its specific
relevance within the broader scope of investment theory and practical applications.
First, from a quantitative perspective, the intricacies of commodity price dynamics present a motivating challenge.
The complexities arise from the distinctive features inherent in these prices, encompassing elements such as seasonality,
the occurrence of pronounced peaks, and the dynamic nature of volatility over time. Consequently, the development
of effective stochastic models for accurate price forecasting demands a specific approach. These models must exhibit a
dual quality, being not only sufficiently comprehensive to encapsulate the nuanced idiosyncrasies of commodity price
behavior but also maintaining a level of mathematical tractability that facilitates practical application and interpretation.
Striking this delicate balance is imperative to ensure that the models not only accurately capture the multifaceted
nature of commodity markets but also remain practical tools for decision-makers navigating the intricacies of financial
decision-making. Therefore, building effective stochastic models for price prediction becomes a truly conceptual effort
that requires models to be simultaneously suitable and mathematically tractable. Some of the papers within this Special
Issue employ sophisticated stochastic models to describe the dynamics of the phenomena of interest.
In addition to traditional statistical approaches, the profound influence ofmachine learning methods on the financial
landscape is unmistakable. Notably—as we will see in detail below—methodologies such as Reinforcement Learning are
prominently featured in some of the presented papers, underscoring the transformative role these advanced techniques
play in the realm of finance.
Second, froma more business perspective, commodities offer a rational alternative to conventional financial securities.
This is particularly noteworthy in the aftermath of the recent financial crisis, where the vulnerabilities of traditional
securities have been thoroughly examined. Commodities, by contrast, have gained prominence in the global financial
industry, not only for their potential to enhance inflation-adjusted returns but also for the diversification benefits they
can provide in comparison to more traditional fixed-income and equity investments. This underscores the multifaceted
significance of commodities within the broader context of investment strategy and risk management.
The contributions in the special issue can be clustered into some relevant categories in a no unique way, according to
different criteria.We here advance a detailed discussion of them in the light of a meaningful classification
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
CVA in fractional and rough volatility models
No full textIn this work we present a general representation formula for the price of a vulnerable European option, and the related CVA in stochastic (either rough or not) volatility models for the underlying’s price, when admitting correlation with the default event. We specialize it for some volatility models and we provide price approximations, based on the representation formula. We study numerically their accuracy, comparing the results with Monte Carlo simulations, and we run a theoretical study of the error. We also introduce a seminal study of roughness influence on the claim’s price
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
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