Search results for "Computational Engineering"

showing 10 items of 60 documents

Delay in claim settlement and ruin probability approximations

1995

We introduce a general risk model for portfolios with delayed claims which is a natural extension of the classical Poisson model. We investigate ruin problems for different premium principles and provide approximations for the ruin probability. We conclude with some specific models, for example, for IBNR portfolios and portfolios where the pay-off process depends on the claim size.

Statistics and ProbabilityEconomics and EconometricsActuarial scienceMathematics::Optimization and ControlExtension (predicate logic)Ruin theorysymbols.namesakeRisk modelComputer Science::Computational Engineering Finance and SciencesymbolsPoisson regressionStatistics Probability and UncertaintySettlement (litigation)Mathematical economicsMathematicsScandinavian Actuarial Journal
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The Heisenberg picture in the analysis of stock markets and in other sociological contexts

2007

We review some recent results concerning some toy models of stock markets. Our models are suggested by the discrete nature of the number of shares and of the cash which are exchanged in a real market, and by the existence of conserved quantities, like the total number of shares or some linear combination of the cash and the shares. This suggests to use the same tools used in quantum mechanics and, in particular, the Heisenberg picture to describe the time behavior of the portfolio of each trader. We finally propose the use of this same framework in other sociological contexts.

Statistics and ProbabilityFinancial economicsmedia_common.quotation_subjectGeneral Social SciencesShareholder valueConserved quantityComputer Science::Computational Engineering Finance and ScienceCashEconomicsPortfolioStock marketLinear combinationHeisenberg pictureStock (geology)media_commonQuality & Quantity
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Dynamics of the Number of Trades of Financial Securities

1999

We perform a parallel analysis of the spectral density of (i) the logarithm of price and (ii) the daily number of trades of a set of stocks traded in the New York Stock Exchange. The stocks are selected to be representative of a wide range of stock capitalization. The observed spectral densities show a different power-law behavior. We confirm the $1/f^2$ behavior for the spectral density of the logarithm of stock price whereas we detect a $1/f$-like behavior for the spectral density of the daily number of trades.

Statistics and ProbabilityPhysics::Physics and SocietyStatistical Finance (q-fin.ST)LogarithmStatistical Mechanics (cond-mat.stat-mech)Spectral densityFOS: Physical sciencesQuantitative Finance - Statistical FinanceCondensed Matter PhysicsStock priceFOS: Economics and businessStock exchangeComputer Science::Computational Engineering Finance and ScienceEconometricsStock (geology)Condensed Matter - Statistical MechanicsMathematics
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Engaging universities in social innovation research for understanding sustainability issues

2017

International audience; The paper presents the analysis of a three-stage research conducted by the authors within a social innovation project in collaboration with international master students of Riga Technical University for determining the factors, which motivate people to be involved in the solution of social problems. The authors not only analyse and use the outcomes of the students’ research but also provide feasibility study of using the potential of study research at the university, for implementing serious research projects. Data collection from Africa, Asia, America and Europe was organised jointly by all the students via web-based survey for creating an original data base for the…

Technological innovations. AutomationEntrepreneurshipKnowledge managementEconomics Econometrics and Finance (miscellaneous)Interpersonal communication010501 environmental sciencesManagement Monitoring Policy and LawSocial issueslearning research by doing research01 natural sciencessocial innovationManagement of Technology and Innovation0502 economics and businessGE1-350SociologyBusiness and International Management0105 earth and related environmental sciences[QFIN.GN]Quantitative Finance [q-fin]/General Finance [q-fin.GN][SHS.STAT]Humanities and Social Sciences/Methods and statisticsData collectionbusiness.industryHD45-45.2[INFO.INFO-CE]Computer Science [cs]/Computational Engineering Finance and Science [cs.CE]05 social sciencesstudy researchPublic relationsJEL: O - Economic Development Innovation Technological Change and Growth/O.O1 - Economic Development/O.O1.O15 - Human Resources • Human Development • Income Distribution • Migration[SHS.ECO]Humanities and Social Sciences/Economics and Finance[QFIN.ST]Quantitative Finance [q-fin]/Statistical Finance [q-fin.ST]social problemsEnvironmental sciencesContent analysisSustainabilitySocial innovationbusinessqualitative content analysis050203 business & managementIntrapersonal communicationEntrepreneurship and Sustainability Issues
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Traitement des variabilités métier dans les Systèmes d'Information biologiques

2012

International audience; Les systèmes d'information scientifique nécessitent des fonctionnalités pour supporter deux types de variabilités majeures, la variabilité inter-acteurs et la variabilité inter-études. Nous traitons la variabilité inter-acteurs par un système d'importation des données garant de la qualité des données et la variabilité inter-études par l'utilisation d'un mécanisme d'annotation couplé au mécanisme de persistance. Afin de contrôler la qualité des données lors de leur importation en provenance de différents acteurs ou lors de leur annotation, nous proposons une approche basée sur deux niveaux de connaissance : 1) la connaissance relative aux applications du SI est représ…

[ INFO.INFO-DB ] Computer Science [cs]/Databases [cs.DB][INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB][INFO.INFO-CE]Computer Science [cs]/Computational Engineering Finance and Science [cs.CE][INFO.INFO-DB] Computer Science [cs]/Databases [cs.DB][INFO.INFO-CE] Computer Science [cs]/Computational Engineering Finance and Science [cs.CE][ INFO.INFO-CE ] Computer Science [cs]/Computational Engineering Finance and Science [cs.CE]
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Les systèmes d'information coopératifs : le projet DECA

2000

International audience; Ce travail répond aux besoins d'accès uniformes et coopératifs à plusieurs systèmes d'information hétérogènes. Nous décrivons un cadre de travail pour les systèmes d'information coopératifs et présentons le projet DECA qui propose une approche de médiation de contextes. La principale caractéristique de la solution proposée réside dans la résolution dynamique des conflits schématiques et sémantiques des données. Ceci est réalisé à travers le modèle AM UN, modèle orienté objet étendu pour gérer la coopération de systèmes. Une architecture faiblement couplée, basée sur le paradigme multi-agents, est présentée.

[ INFO.INFO-DB ] Computer Science [cs]/Databases [cs.DB][INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB][INFO.INFO-CE]Computer Science [cs]/Computational Engineering Finance and Science [cs.CE][INFO.INFO-DB] Computer Science [cs]/Databases [cs.DB][INFO.INFO-CE] Computer Science [cs]/Computational Engineering Finance and Science [cs.CE][ INFO.INFO-CE ] Computer Science [cs]/Computational Engineering Finance and Science [cs.CE]
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Proceedings of the 8th Linked Data in Architecture and Construction Workshop (LDAC2020)

2020

International audience

[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI][SPI.GCIV]Engineering Sciences [physics]/Civil Engineering[INFO.INFO-LO] Computer Science [cs]/Logic in Computer Science [cs.LO][INFO.INFO-CE]Computer Science [cs]/Computational Engineering Finance and Science [cs.CE][INFO.INFO-LO]Computer Science [cs]/Logic in Computer Science [cs.LO][SPI.GCIV] Engineering Sciences [physics]/Civil Engineering[INFO.INFO-CE] Computer Science [cs]/Computational Engineering Finance and Science [cs.CE]ComputingMilieux_MISCELLANEOUS[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]
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Nouvelles perspectives du BIM

2021

Les dernières avancées dans la modélisation des informations du bâtiment et la maquette numérique ont permis d'améliorer l'efficacité des livraisons et performances, en catalysant des méthodes de travail innovantes dans le domaine général de l'architecture, de l'ingénierie et de la construction (AEC). Malgré les nombreux outils et technologies numériques et les différentes normes ouvertes BIM, il demeure un besoin croissant d'interopérabilité entre acteurs et logiciels.Allant de cas d'études constitués par des projets industriels réels à des projets recherche, les six chapitres de cet ouvrage témoignent de l'intérêt de la filière et des entreprises pour adapter et faire évoluer leurs pratiq…

[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI][SPI.GPROC] Engineering Sciences [physics]/Chemical and Process Engineering[INFO.INFO-ET] Computer Science [cs]/Emerging Technologies [cs.ET][INFO.INFO-CE] Computer Science [cs]/Computational Engineering Finance and Science [cs.CE][SPI.GCIV.CD] Engineering Sciences [physics]/Civil Engineering/Construction durable[INFO.INFO-IA] Computer Science [cs]/Computer Aided Engineering
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Evaluation of Options using the Black-Scholes Methodology

2019

This paper discusses how to obtain the Black-Scholes equation to evaluate options and how to obtain explicit solutions for Call and Put. The Black-Scholes equation, which is the basis for determining explicit solutions for Call and Put, is a rather sophisticated equation. It is a partial differential equation of the second order, parabolic, similar to the heat equation. The terms of the equation express diffusion in a homogeneous environment, convection and reaction. The main objective of the paper is to present the Black-Scholes methodology and apply this methodology on the underlying asset of the nature of the listed stock on the Bucharest Stock Exchange. Also, a secondary objective is to…

lcsh:HB1-3840Computer Science::Computational Engineering Finance and Sciencelcsh:Economic theory. Demographyblack-scholes equationstochasticmonte carlo simulationExpert Journal of Economics
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Functional a posteriori error estimates for boundary element methods

2019

Functional error estimates are well-established tools for a posteriori error estimation and related adaptive mesh-refinement for the finite element method (FEM). The present work proposes a first functional error estimate for the boundary element method (BEM). One key feature is that the derived error estimates are independent of the BEM discretization and provide guaranteed lower and upper bounds for the unknown error. In particular, our analysis covers Galerkin BEM and the collocation method, what makes the approach of particular interest for scientific computations and engineering applications. Numerical experiments for the Laplace problem confirm the theoretical results.

osittaisdifferentiaaliyhtälötDiscretizationApplied MathematicsComputationNumerical analysisNumerical Analysis (math.NA)adaptive mesh-refinementFinite element methodMathematics::Numerical Analysisboundary element methodComputational MathematicsComputer Science::Computational Engineering Finance and ScienceCollocation methodMathematikFOS: MathematicsApplied mathematicsA priori and a posterioriMathematics - Numerical Analysisnumeerinen analyysivirheanalyysiGalerkin methodBoundary element methodfunctional a posteriori error estimate65N38 65N15 65N50MathematicsNumerische Mathematik
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