Publication:
Applications to risk theory of a Montecarlo multiple integration method

dc.contributor.authorUsábel Rodrigo, Miguel Arturo
dc.date.accessioned2023-06-21T01:36:13Z
dc.date.available2023-06-21T01:36:13Z
dc.date.issued1997
dc.description.abstractThe evaluation of multiple integrals is a commonly encountered problem in risk theory, specially in ruin probability. Using Monte Carlo simulation we will obtain an unbiased and consistent point estimator, and also confidence intervals as approximations of a special case of multiple integral frequently used in risle theory. The variance reduction achieved compared to straight simulation and some specific properties malee this approach interesting when approximating ruin probabilities.
dc.description.departmentDecanato
dc.description.facultyFac. de Ciencias Económicas y Empresariales
dc.description.refereedTRUE
dc.description.statuspub
dc.eprint.idhttps://eprints.ucm.es/id/eprint/27020
dc.identifier.citationBahvalov, N.S. (1959). On approximate calculation of multiple integrals, Vestnik Moscov. Univ. Ser. Mat. Meh. ABt. Fiz. Rim., 4, 3-8. Bratley, P.; Fox, B.L. & Schrage, L.E. (1987). A guide to simulation, Springer-Verlag, New York. Büh1mann,H. (1970). Mathematical methods in Risk Theory. Springer-Verlag, New York. Burden, R.L. and Fau·es, J.D.(1985). Numerical Analysis, P.W.S., Boston. De Vylder, Fo and Goovaerts, M.J. (1988). Recursive Calculation of Finite-time ruin probabilities, Insmance: Mathematics and Economics, 7, 1-7. Fishman, G.S. (1996). Monte Cado: concepts, algorithms and applications. Springer series in operations research. Springer-Verlag, New York. Haber, S. (1970). Numerical evaluation of multiple integrals, SIAM Rev., 12, 481-526. Niederreiter, H. (1978). Quasi-Monte Cario methods and pseudorandom numbers, Bull. Amer. l'vfath. Soco, 84, 957-1041. - (1992). Random number generation and Quasi-Monte Cario methods, Society for industrial and applied mathematics, Philadelphia, PA. Panjer, H.H. (1981). Recursive evaluation of a family of compound distributions, ASTlN Bulletin, 12, 22-26. Panjer, H.H. & Willrnot, G.E. (1992). Ins'urance risk Models, Society of Actuaries, Schaumbmg. Rubulsteul, R.y. (1981). Simulation and the Monte Cado Meihod, Wiley, New York. Usábel, M.A. (1995). Cálculo numérico de probabilidades de ruina: Aplicación de la teoría de la renovación y de la simulación, Unpublished Ph. D. Thesis, Department of Finance and actuarial science, Universidad Complutense de Madrid, Spain. - (1995). A numerical method of estimating ruin probabilities in a simple financial model, Proc. XXV International Congress of Actuaries, September 1995, Brussels.
dc.identifier.issn2255-5471
dc.identifier.relatedurlhttps://economicasyempresariales.ucm.es/working-papers-ccee
dc.identifier.urihttps://hdl.handle.net/20.500.14352/64129
dc.issue.number20
dc.language.isoeng
dc.page.total21
dc.publication.placeMadrid
dc.publisherFacultad de Ciencias Económicas y Empresariales. Decanato
dc.relation.ispartofseriesDocumentos de Trabajo de la Facultad de Ciencias Económicas y Empresariales
dc.rightsAtribución-NoComercial-CompartirIgual 3.0 España
dc.rights.accessRightsopen access
dc.rights.urihttps://creativecommons.org/licenses/by-nc-sa/3.0/es/
dc.subject.keywordProcesos estocásticos
dc.subject.keywordRiesgo
dc.subject.keywordModelos matemáticos.
dc.subject.ucmProcesos estocásticos
dc.subject.ucmTeoría de la decisión
dc.subject.unesco1208.08 Procesos Estocásticos
dc.subject.unesco1209.04 Teoría y Proceso de decisión
dc.titleApplications to risk theory of a Montecarlo multiple integration method
dc.typetechnical report
dc.volume.number1997
dspace.entity.typePublication
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