Stress Testing as a Banking Risk Assessment Tool: A Review of International Practice, Methods and Methodology

2020 ◽  
pp. 99-117
Author(s):  
Davit S. Bidzhoyan
Keyword(s):  
Stress Testing ◽  
Assessment Tool ◽  
Research Area ◽  
Interest Rate Risk ◽  
Economic Science ◽  
Testing Methods ◽  
Financial Condition ◽  
Comprehensive Classification ◽  
Practice Methods

Stress testing is a broad research area, at the interference of many disciplines (finance, banking, econometrics, macroeconomics, microeconomics, mathematical analysis etc.), and is of interest to both theoretical scientists and practitioners. The usefulness of this approach became evident after the financial crisis of 2007–2009, which prompted many researchers to develop and constantly improve stress-testing methodologies, using which it is possible to accurately forecast the behavior of banks and the financial sector in crisis periods. It allows banks to assess the scale of losses and timely take the necessary measures to strengthen the financial condition. Today, economic science has the biggest arsenal of stress testing methods that allow us to assess potential losses in crisis periods that correspond to extreme but plausible events. The stress testing methodologies cover all-important types of risks (credit, interest rate risk, liquidity risk etc.), as well as specific risks. The presence of a huge number of stress testing methods guarantees its versatility and depth, which could be explained by the attempt using this methods to create a behavior model of banks, which are quite complex in structure and functionality. The purpose of this study is to provide a concise, but at the same time comprehensive classification of stress testing methods, as well as a review of the current approaches to stress testing or to solving its various aspects (for example, developing stress scenarios) presented by scientists, international organizations, central banks and other interested parties. This paper is an introduction to the vast field of analytics – stress testing, and is oriented to banking and financial analysts, macroeconomists who want either to familiarize themselves with stress testing as a tool for assessing banking risks, or to systematize all the accumulated knowledge in this area in order to better understand economic processes.

scholarly journals UV Spectral Classification of B Stars

1985 ◽  
Vol 111 ◽  
pp. 411-413
Author(s):  
Janet Rountree ◽  
George Sonneborn ◽  
Robert J. Panek
Keyword(s):  
Classification System ◽  
Classification Criteria ◽  
High Dispersion ◽  
Spectral Classification ◽  
Early Type ◽  
B Stars ◽  
Dimensional Classification ◽  
Early Type Stars ◽  
Comprehensive Classification

Previous studies of ultraviolet spectral classification have been insufficient to establish a comprehensive classification system for ultraviolet spectra of early-type stars because of inadequate spectral resolution. We have initiated a new study of ultraviolet spectral classification of B stars using high-dispersion IUE archival data. High-dispersion SWP spectra of MK standards and other B stars are retrieved from the IUE archives and numerically degraded to a uniform resolution of 0.25 or 0.50 Å. The spectra (in the form of plots or photowrites) are then visually examined with the aim of setting up a two-dimensional classification matrix. We follow the method used to create the MK classification system for visual spectra. The purpose of this work is to examine the applicability of the MK system (and in particular, the set of standard stars) in the ultraviolet, and to establish classification criteria in this spectral region.

Music Neurotechnology for Sound Synthesis: Sound Synthesis with Spiking Neuronal Networks

Leonardo ◽  
2009 ◽  
Vol 42 (5) ◽  
pp. 439-442 ◽  
Author(s):  
Eduardo R. Miranda ◽  
John Matthias
Keyword(s):  
Cortical Neurons ◽  
Neuronal Networks ◽  
Research Area ◽  
Sound Synthesis ◽  
Ongoing Research ◽  
Computer Interfaces ◽  
Engineering Sciences ◽  
New Research ◽  
Sound Files

Music neurotechnology is a new research area emerging at the crossroads of neurobiology, engineering sciences and music. Examples of ongoing research into this new area include the development of brain-computer interfaces to control music systems and systems for automatic classification of sounds informed by the neurobiology of the human auditory apparatus. The authors introduce neurogranular sampling, a new sound synthesis technique based on spiking neuronal networks (SNN). They have implemented a neurogranular sampler using the SNN model developed by Izhikevich, which reproduces the spiking and bursting behavior of known types of cortical neurons. The neurogranular sampler works by taking short segments (or sound grains) from sound files and triggering them when any of the neurons fire.

scholarly journals ICD-11 extension codes support detailed clinical abstraction and comprehensive classification

2021 ◽  
Vol 21 (S6) ◽  
Author(s):  
Saskia E. Drösler ◽  
Stefanie Weber ◽  
Christopher G. Chute
Keyword(s):  
Clinical History ◽  
International Classification Of Diseases ◽  
Disease Stage ◽  
Clinical State ◽  
Classification Of Diseases ◽  
Icd 10 ◽  
Clinical Detail ◽  
History Of ◽  
Comprehensive Classification

Abstract Background The new International Classification of Diseases—11th revision (ICD-11) succeeds ICD-10. In the three decades since ICD-10 was released, demands for detailed information on the clinical history of a morbid patient have increased. Methods ICD-11 has now implemented an addendum chapter X called “Extension Codes”. This chapter contains numerous codes containing information on concepts including disease stage, severity, histopathology, medicaments, and anatomical details. When linked to a stem code representing a clinical state, the extension codes add significant detail and allow for multidimensional coding. Results This paper discusses the purposes and uses of extension codes and presents three examples of how extension codes can be used in coding clinical detail. Conclusion ICD-11 with its extension codes implemented has the potential to improve precision and evidence based health care worldwide.

scholarly journals An Evolutionary Method for Combining Different Feature Selection Criteria in Microarray Data Classification

2009 ◽  
Vol 2009 ◽  
pp. 1-10 ◽  
Author(s):  
Nicoletta Dessì ◽  
Barbara Pes
Keyword(s):  
Microarray Data ◽  
Selection Criteria ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Research Area ◽  
Svm Classifier ◽  
Ranking Methods ◽  
Wrapper Approach ◽  
Relevant Gene

The classification of cancers from gene expression profiles is a challenging research area in bioinformatics since the high dimensionality of microarray data results in irrelevant and redundant information that affects the performance of classification. This paper proposes using an evolutionary algorithm to select relevant gene subsets in order to further use them for the classification task. This is achieved by combining valuable results from different feature ranking methods into feature pools whose dimensionality is reduced by a wrapper approach involving a genetic algorithm and SVM classifier. Specifically, the GA explores the space defined by each feature pool looking for solutions that balance the size of the feature subsets and their classification accuracy. Experiments demonstrate that the proposed method provide good results in comparison to different state of art methods for the classification of microarray data.

Analysing the features of negative sentiment tweets

2018 ◽  
Vol 36 (5) ◽  
pp. 782-799 ◽  
Author(s):  
Ling Zhang ◽  
Wei Dong ◽  
Xiangming Mu
Keyword(s):  
Research Area ◽  
Small Sample ◽  
Negative Word ◽  
Social Media Data ◽  
Content Type ◽  
Word Use ◽  
Part Of Speech ◽  
Negative Sentiment ◽  
Media Data

Purpose This paper aims to address the challenge of analysing the features of negative sentiment tweets. The method adopted in this paper elucidates the classification of social network documents and paves the way for sentiment analysis of tweets in further research. Design/methodology/approach This study classifies negative tweets and analyses their features. Findings Through negative tweet content analysis, tweets are divided into ten topics. Many related words and negative words were found. Some indicators of negative word use could reflect the degree to which users release negative emotions: part of speech, the density and frequency of negative words and negative word distribution. Furthermore, the distribution of negative words obeys Zipf’s law. Research limitations/implications This study manually analysed only a small sample of negative tweets. Practical implications The research explored how many categories of negative sentiment tweets there are on Twitter. Related words are helpful to construct an ontology of tweets, which helps people with information retrieval in a fixed research area. The analysis of extracted negative words determined the features of negative tweets, which is useful to detect the polarity of tweets by machine learning method. Originality/value The research provides an initial exploration of a negative document classification method and classifies the negative tweets into ten topics. By analysing the features of negative tweets, related words, negative words, the density of negative words, etc. are presented. This work is the first step to extend Plutchik’s emotion wheel theory into social media data analysis by constructing filed specific thesauri, referred to as local sentimental thesauri.

Towards Smarter Cities and Roads

2014 ◽  
pp. 16-50 ◽  
Author(s):  
Irina Tal ◽  
Gabriel-Miro Muntean
Keyword(s):  
Architectural Design ◽  
Vehicular Ad Hoc Networks ◽  
Ad Hoc ◽  
Clustering Algorithms ◽  
Research Area ◽  
General Classification ◽  
Comprehensive Survey ◽  
Hoc Networks ◽  
Promising Avenue

This chapter highlights the importance of Vehicular Ad-Hoc Networks (VANETs) in the context of smarter cities and roads, a topic that currently attracts significant academic, industrial, and governmental planning, research, and development efforts. In order for VANETs to become reality, a very promising avenue is to bring together multiple wireless technologies in the architectural design. Clustering can be employed in designing such a VANET architecture that successfully uses different technologies. Moreover, as clustering addresses some of VANETs' major challenges, such as scalability and stability, it seems clustering will have an important role in the desired vehicular connectivity in the cities and roads of the future. This chapter presents a comprehensive survey of clustering schemes in the VANET research area, covering aspects that have never been addressed before in a structured manner. The survey presented in this chapter provides a general classification of the clustering algorithms, presents some of the most advanced and latest algorithms in VANETs, and in addition, constitutes the only work in the literature to the best of authors' knowledge that also reviews the performance assessment of clustering algorithms.

Taxonomy of Grid Systems

2010 ◽  
pp. 20-43 ◽  
Author(s):  
Heba Kurdi ◽  
Maozhen Li ◽  
H. S. Al-Raweshidy
Keyword(s):  
Grid Computing ◽  
End Users ◽  
Grid Systems ◽  
Solid Foundation ◽  
Comprehensive Classification

Advances in Grid computing are stimulating the emergence of novel types of Grids. Accessible Grids, manageable Grids, interactive Grids and personal Grids represent a significant evolution of Grid computing. More and more researchers are realising the potentials of emerging Grids in bridging the current gap between Grid technologies and end users. Nevertheless, no reviews or classifications on emerging Grids are available. Therefore, this chapter aims to give a review on Grid systems. It sets out to develop a comprehensive classification of both traditional and emerging Grid systems with an aim to motivate further research and to assist in establishing a solid foundation in such a rapidly developing and expanding field.

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