Leveraging Return Prediction Approaches for Improved Value-at-Risk Estimation

Value at risk is a statistic used to anticipate the largest possible losses over a specific time frame and within some level of confidence, usually 95% or 99%. For risk management and regulators, it offers a solution for trustworthy quantitative risk management tools. VaR has become the most widely used and accepted indicator of downside risk. Today, commercial banks and financial institutions utilize it as a tool to estimate the size and probability of upcoming losses in portfolios and, as a result, to estimate and manage the degree of risk exposure. The goal is to obtain the average number of VaR “failures” or “breaches” (losses that are more than the VaR) as near to the target rate as possible. It is also desired that the losses be evenly distributed as possible. VaR can be modeled in a variety of ways. The simplest method is to estimate volatility based on prior returns according to the assumption that volatility is constant. Otherwise, the volatility process can be modeled using the GARCH model. Machine learning techniques have been used in recent years to carry out stock market forecasts based on historical time series. A machine learning system is often trained on an in-sample dataset, where it can adjust and improve specific hyperparameters in accordance with the underlying metric. The trained model is tested on an out-of-sample dataset. We compared the baselines for the VaR estimation of a day (d) according to different metrics (i) to their respective variants that included stock return forecast information of d and stock return data of the days before d and (ii) to a GARCH model that included return prediction information of d and stock return data of the days before d. Various strategies such as ARIMA and a proposed ensemble of regressors have been employed to predict stock returns. We observed that the versions of the univariate techniques and GARCH integrated with return predictions outperformed the baselines in four different marketplaces

Citation prediction by leveraging transformers and natural language processing heuristics

In scientific papers, it is common practice to cite other articles to substantiate claims, provide evidence for factual assertions, reference limitations, and research gaps, and fulfill various other purposes. When authors include a citation in a given sentence, there are two considerations they need to take into account: (i) where in the sentence to place the citation and (ii) which citation to choose to support the underlying claim. In this paper, we focus on the first task as it allows multiple potential approaches that rely on the researcher's individual style and the specific norms and conventions of the relevant scientific community. We propose two automatic methodologies that leverage transformers architecture for either solving a Mask-Filling problem or a Named Entity Recognition problem. On top of the results of the proposed methodologies, we apply ad-hoc Natural Language Processing heuristics to further improve their outcome. We also introduce s2orc-9K, an open dataset for fine-tuning models on this task. A formal evaluation demonstrates that the generative approach significantly outperforms five alternative methods when fine-tuned on the novel dataset. Furthermore, this model's results show no statistically significant deviation from the outputs of three senior researchers

Data-Driven Methodology for Knowledge Graph Generation Within the Tourism Domain

The tourism and hospitality sectors have become increasingly important in the last few years and the companies operating in this field are constantly challenged with providing new innovative services. At the same time, (big-) data has become the 'new oil' of this century and Knowledge Graphs are emerging as the most natural way to collect, refine, and structure this heterogeneous information. In this paper, we present a methodology for semi-automatic generating a Tourism Knowledge Graph (TKG), which can be used for supporting a variety of intelligent services in this space, and a new ontology for modelling this domain, the Tourism Analytics Ontology (TAO). Our approach processes and integrates data from Booking.com, Airbnb, DBpedia, and GeoNames. Due to its modular structure, it can be easily extended to include new data sources or to apply new enrichment and refinement functions. We report a comprehensive evaluation of the functional, logical, and structural dimensions of TKG and TAO

Automating Citation Placement with Natural Language Processing and Transformers

In scientific writing, references are crucial in supporting claims, spotlighting evidence, and highlighting research gaps. However, where to add a reference and which reference to cite are subjectively chosen by the papers’ authors; thus the automation of the task is challenging and requires proper investigations. This paper focuses on the automatic placement of references, considering its diverse approaches depending on writing style and community norms, and investigates the use of transformers and Natural Language Processing heuristics to predict i) if a reference is needed in a scientific statement, and ii) where the reference should be placed within the statement. For this investigation, this paper investigates two techniques, namely Mask-filling (MF) and Named Entity Recognition (NER), and provides insights on how to solve this task

Citrus of the world: a Citrus directory

De nombreuses classifications ont tenté de structurer le genre citrus qui constitue un groupe végétal complexe. L'importance des noms locaux, issus de la tradition orale, et plus récemment, l'apparition de dénominations commerciales augmentent encore le nombre des appellations. Cet annuaire représente une tentative d'identification et de standardisation du groupe. Il s'appuie sur la classification très détaillée du Japonais Tanaka, les équivalences avec celle de l'Américain Swingle sont données en annexes. Les tableaux indiquent pour chaque nom rencontré (nom local, appellation commerciale, variante orthographique...) son binôme latin et son nom standardisé. Un synthèse des appellations hybrides complète cet annuair

Urogenital Abnormalities in Adenosine Deaminase Deficiency

BACKGROUND: Improved survival in ADA-SCID patients is revealing new aspects of the systemic disorder. Although increasing numbers of reports describe the systemic manifestations of adenosine deaminase deficiency, currently there are no studies in the literature evaluating genital development and pubertal progress in these patients. METHODS: We collected retrospective data on urogenital system and pubertal development of 86 ADA-SCID patients followed in the period 2000-2017 at the Great Ormond Street Hospital (UK) and 5 centers in Italy. In particular, we recorded clinical history and visits, and routine blood tests and ultrasound scans were performed as part of patients' follow-up. RESULTS AND DISCUSSION: We found a higher frequency of congenital and acquired undescended testes compared with healthy children (congenital, 22% in our sample, 0.5-4% described in healthy children; acquired, 16% in our sample, 1-3% in healthy children), mostly requiring orchidopexy. No urogenital abnormalities were noted in females. Spontaneous pubertal development occurred in the majority of female and male patients with a few cases of precocious or delayed puberty; no patient presented high FSH values. Neither ADA-SCID nor treatment performed (PEG-ADA, BMT, or GT) affected pubertal development or gonadic function. CONCLUSION: In summary, this report describes a high prevalence of cryptorchidism in a cohort of male ADA-SCID patients which could represent an additional systemic manifestation of ADA-SCID. Considering the impact urogenital and pubertal abnormalities can have on patients' quality of life, we feel it is essential to include urogenital evaluation in ADA-SCID patients to detect any abnormalities, initiate early treatment, and prevent long-term complications

The EGFR family members sustain the neoplastic phenotype of ALK+ lung adenocarcinoma via EGR1.

In non-small cell lung cancer (NSCLC), receptor tyrosine kinases (RTKs) stand out among causal dominant oncogenes, and the ablation of RTK signaling has emerged as a novel tailored therapeutic strategy. Nonetheless, long-term RTK inhibition leads invariably to acquired resistance, tumor recurrence and metastatic dissemination. In ALK+ cell lines, inhibition of ALK signaling was associated with coactivation of several RTKs, whose pharmacological suppression reverted the partial resistance to ALK blockade. Remarkably, ERBB2 signaling synergized with ALK and contributed to the neoplastic phenotype. Moreover, the engagement of wild-type epidermal growth factor receptor or MET receptors could sustain cell viability through early growth response 1 (EGR1) and/or Erk1/2; Akt activation and EGR1 overexpression prevented cell death induced by combined ALK/RTK inhibition. Membrane expression of ERBB2 in a subset of primary naive ALK+ NSCLC could be relevant in the clinical arena. Our data demonstrate that the neoplastic phenotype of ALK-driven NSCLC relays ‘ab initio' on the concomitant activation of multiple RTK signals via autocrine/paracrine regulatory loops. These findings suggest that molecular and functional signatures are required in de novo lung cancer patients for the design of efficacious and multi-targeted ‘patient-specific' therapies

Therapeutic emails

BACKGROUND: In this paper, we show how counselors and psychologists can use emails for online management of substance abusers, including the anatomy and content of emails that clinicians should send substance abusers. Some investigators have attempted to determine if providing mental health services online is an efficacious delivery of treatment. The question of efficacy is an empirical issue that cannot be settled unless we are explicitly clear about the content and nature of online treatment. We believe that it is not the communications via internet that matters, but the content of these communications. The purpose of this paper is to provide the content of our online counseling services so others can duplicate the work and investigate its efficacy. RESULTS: We have managed nearly 300 clients online for recovery from substance abuse. Treatment included individual counseling (motivational interviewing, cognitive-behavior therapy, relapse prevention assignments), participation in an electronic support group and the development of a recovery team. Our findings of success with these interventions are reported elsewhere. Our experience has led to development of a protocol of care that is described more fully in this paper. This protocol is based on stages of change and relapse prevention theories and follows a Motivational Interviewing method of counseling. CONCLUSION: The use of electronic media in providing mental health treatment remains controversial due to concerns about confidentiality, security and legal considerations. More research is needed to validate and generalize the use of online treatment for mental health problems. If researchers have to build on each others work, it is paramount that we share our protocols of care, as we have done in this paper

Protons in near earth orbit

The proton spectrum in the kinetic energy range 0.1 to 200 GeV was measured by the Alpha Magnetic Spectrometer (AMS) during space shuttle flight STS-91 at an altitude of 380 km. Above the geomagnetic cutoff the observed spectrum is parameterized by a power law. Below the geomagnetic cutoff a substantial second spectrum was observed concentrated at equatorial latitudes with a flux ~ 70 m^-2 sec^-1 sr^-1. Most of these second spectrum protons follow a complicated trajectory and originate from a restricted geographic region.Comment: 19 pages, Latex, 7 .eps figure

Search for antihelium in cosmic rays

The Alpha Magnetic Spectrometer (AMS) was flown on the space shuttle Discovery during flight STS-91 in a 51.7 degree orbit at altitudes between 320 and 390 km. A total of 2.86 * 10^6 helium nuclei were observed in the rigidity range 1 to 140 GV. No antihelium nuclei were detected at any rigidity. An upper limit on the flux ratio of antihelium to helium of < 1.1 * 10^-6 is obtained.Comment: 18 pages, Latex, 9 .eps figure