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Título : Stochastic Control in Insurance Tipo de documento: documento electrónico Autores: Schmidli, Hanspeter ; SpringerLink (Online service) Editorial: London : Springer London Fecha de publicación: 2008 Colección: Probability and Its Applications, ISSN 1431-7028 Número de páginas: XVI, 258 p Il.: online resource ISBN/ISSN/DL: 978-1-84800-003-2 Idioma : Inglés (eng) Palabras clave: Mathematics Finance Actuarial science Mathematical optimization Calculus of variations Probabilities Control engineering Robotics Mechatronics Sciences Probability Theory and Stochastic Processes Variations Optimal Control; Optimization Finance, general Control, Robotics, Clasificación: 51 Matemáticas Resumen: Stochastic control is one of the methods being used to find optimal decision-making strategies in fields such as operations research and mathematical finance. In recent years, stochastic control techniques have been applied to non-life insurance problems, and in life insurance the theory has been further developed. This book provides a systematic treatment of optimal control methods applied to problems from insurance and investment, complete with detailed proofs. The theory is discussed and illustrated by way of examples, using concrete simple optimisation problems that occur in the actuarial sciences. The problems come from non-life insurance as well as life and pension insurance and also cover the famous Merton problem from mathematical finance. Wherever possible, the proofs are probabilistic but in some cases well-established analytical methods are used. The book is directed towards graduate students and researchers in actuarial science and mathematical finance who want to learn stochastic control within an insurance setting, but it will also appeal to applied probabilists interested in the insurance applications and to practitioners who want to learn more about how the method works. Readers should be familiar with basic probability theory and have a working knowledge of Brownian motion, Markov processes, martingales and stochastic calculus. Some knowledge of measure theory will also be useful for following the proofs Nota de contenido: Stochastic Control in Discrete Time -- Stochastic Control in Continuous Time -- Problems in Life Insurance -- Asymptotics of Controlled Risk Processes -- Appendices -- Stochastic Processes and Martingales -- Markov Processes and Generators -- Change of Measure Techniques -- Risk Theory -- The Black-Scholes Model -- Life Insurance -- References -- Index -- List of Principal Notation En línea: http://dx.doi.org/10.1007/978-1-84800-003-2 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=34300 Stochastic Control in Insurance [documento electrónico] / Schmidli, Hanspeter ; SpringerLink (Online service) . - London : Springer London, 2008 . - XVI, 258 p : online resource. - (Probability and Its Applications, ISSN 1431-7028) .
ISBN : 978-1-84800-003-2
Idioma : Inglés (eng)
Palabras clave: Mathematics Finance Actuarial science Mathematical optimization Calculus of variations Probabilities Control engineering Robotics Mechatronics Sciences Probability Theory and Stochastic Processes Variations Optimal Control; Optimization Finance, general Control, Robotics, Clasificación: 51 Matemáticas Resumen: Stochastic control is one of the methods being used to find optimal decision-making strategies in fields such as operations research and mathematical finance. In recent years, stochastic control techniques have been applied to non-life insurance problems, and in life insurance the theory has been further developed. This book provides a systematic treatment of optimal control methods applied to problems from insurance and investment, complete with detailed proofs. The theory is discussed and illustrated by way of examples, using concrete simple optimisation problems that occur in the actuarial sciences. The problems come from non-life insurance as well as life and pension insurance and also cover the famous Merton problem from mathematical finance. Wherever possible, the proofs are probabilistic but in some cases well-established analytical methods are used. The book is directed towards graduate students and researchers in actuarial science and mathematical finance who want to learn stochastic control within an insurance setting, but it will also appeal to applied probabilists interested in the insurance applications and to practitioners who want to learn more about how the method works. Readers should be familiar with basic probability theory and have a working knowledge of Brownian motion, Markov processes, martingales and stochastic calculus. Some knowledge of measure theory will also be useful for following the proofs Nota de contenido: Stochastic Control in Discrete Time -- Stochastic Control in Continuous Time -- Problems in Life Insurance -- Asymptotics of Controlled Risk Processes -- Appendices -- Stochastic Processes and Martingales -- Markov Processes and Generators -- Change of Measure Techniques -- Risk Theory -- The Black-Scholes Model -- Life Insurance -- References -- Index -- List of Principal Notation En línea: http://dx.doi.org/10.1007/978-1-84800-003-2 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=34300 Ejemplares
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Título : Stochastic Control in Discrete and Continuous Time Tipo de documento: documento electrónico Autores: Seierstad, Atle ; SpringerLink (Online service) Editorial: Boston, MA : Springer US Fecha de publicación: 2009 Número de páginas: X, 222 p Il.: online resource ISBN/ISSN/DL: 978-0-387-76617-1 Idioma : Inglés (eng) Palabras clave: Mathematics System theory Calculus of variations Probabilities Economic Probability Theory and Stochastic Processes Theory/Quantitative Economics/Mathematical Methods Variations Optimal Control; Optimization Systems Theory, Control Clasificación: 51 Matemáticas Resumen: This book provides a comprehensive introduction to stochastic control problems in discrete and continuous time. The material is presented logically, beginning with the discrete-time case before proceeding to the stochastic continuous-time models. Central themes are dynamic programming in discrete time and HJB-equations in continuous time. Topics covered include stochastic maximum principles for discrete time and continuous time, even for problems with terminal conditions. Numerous illustrative examples and exercises, with solutions at the end of the book, are included to enhance the understanding of the reader. By interlinking many fields in stochastic control, the material gives the student the opportunity to see the connections between different fields and the underlying ideas that unify them. This text will benefit students in applied mathematics, economics, engineering, and related fields. Prerequisites include a course in calculus and elementary probability theory. No knowledge of measure theory is assumed Nota de contenido: Stochastic Control over Discrete Time -- The HJB Equation for Deterministic Control -- Piecewise Deterministic Optimal Control Problems -- Control of Diffusions -- Appendix: Probability, Concepts, and Results En línea: http://dx.doi.org/10.1007/978-0-387-76617-1 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=33864 Stochastic Control in Discrete and Continuous Time [documento electrónico] / Seierstad, Atle ; SpringerLink (Online service) . - Boston, MA : Springer US, 2009 . - X, 222 p : online resource.
ISBN : 978-0-387-76617-1
Idioma : Inglés (eng)
Palabras clave: Mathematics System theory Calculus of variations Probabilities Economic Probability Theory and Stochastic Processes Theory/Quantitative Economics/Mathematical Methods Variations Optimal Control; Optimization Systems Theory, Control Clasificación: 51 Matemáticas Resumen: This book provides a comprehensive introduction to stochastic control problems in discrete and continuous time. The material is presented logically, beginning with the discrete-time case before proceeding to the stochastic continuous-time models. Central themes are dynamic programming in discrete time and HJB-equations in continuous time. Topics covered include stochastic maximum principles for discrete time and continuous time, even for problems with terminal conditions. Numerous illustrative examples and exercises, with solutions at the end of the book, are included to enhance the understanding of the reader. By interlinking many fields in stochastic control, the material gives the student the opportunity to see the connections between different fields and the underlying ideas that unify them. This text will benefit students in applied mathematics, economics, engineering, and related fields. Prerequisites include a course in calculus and elementary probability theory. No knowledge of measure theory is assumed Nota de contenido: Stochastic Control over Discrete Time -- The HJB Equation for Deterministic Control -- Piecewise Deterministic Optimal Control Problems -- Control of Diffusions -- Appendix: Probability, Concepts, and Results En línea: http://dx.doi.org/10.1007/978-0-387-76617-1 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=33864 Ejemplares
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Título : Stochastic Analysis 2010 Tipo de documento: documento electrónico Autores: SpringerLink (Online service) ; Crisan, Dan Editorial: Berlin, Heidelberg : Springer Berlin Heidelberg Fecha de publicación: 2011 Número de páginas: VIII, 299 p Il.: online resource ISBN/ISSN/DL: 978-3-642-15358-7 Idioma : Inglés (eng) Palabras clave: Mathematics Probabilities Probability Theory and Stochastic Processes Clasificación: 51 Matemáticas Resumen: Stochastic Analysis aims to provide mathematical tools to describe and model high dimensional random systems. Such tools arise in the study of Stochastic Differential Equations and Stochastic Partial Differential Equations, Infinite Dimensional Stochastic Geometry, Random Media and Interacting Particle Systems, Super-processes, Stochastic Filtering, Mathematical Finance, etc. Stochastic Analysis has emerged as a core area of late 20th century Mathematics and is currently undergoing a rapid scientific development. The special volume “Stochastic Analysis 2010” provides a sample of the current research in the different branches of the subject. It includes the collected works of the participants at the Stochastic Analysis section of the 7th ISAAC Congress organized at Imperial College London in July 2009 Nota de contenido: D.Crisan: Introduction to the Volume -- V. Bally and E. Clément: Integration by Parts Formula with Respect to Jump Times for Stochastic Differential Equations -- V. Ortiz-López and M. Sanz-Solé: A Laplace Principle for a Stochastic Wave Equation in Spatial Dimension Three -- X.-M. Li: Intertwinned Diffusions Operators by Examples -- L. G. Gyurkó and T. Lyons: Effcient and practical implementations of Cubature on Wiener space -- T. Kurtz: Equivalence of Stochastic Equations and Martingale Problems -- I. Gyöngy and N.V. Krylov: Accelerated Numerical Schemes for PDEs and SPDEs -- A. Papavasilio: Coarse-Grained Modeling of Multiscale Diffusions: The p-variation Estimates -- V.N. Stanciulescu and M.V. Tretyakov: Numerical Solution of the Dirichlet Problem for Linear Parabolic SPDEs Based on Averaging over Characteristics -- S. Davie: Individual Path Uniqueness of Solutions of Stochastic differential equations -- V. Kolokoltsov: Stochastic Integrals and SDE Driven by Nonlinear Levy Noise -- R. Tunaru: Discrete Algorithms for Multivariate Financial Calculus -- D. Brody, L. Hughston and A. Macrina: Credit Risk, Market Sentiment, and Randomly-Timed Default -- M. Kelbert and Y. Suhov: Continuity of mutual entropy in the limiting signal-to-noise ratio regimes En línea: http://dx.doi.org/10.1007/978-3-642-15358-7 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=33380 Stochastic Analysis 2010 [documento electrónico] / SpringerLink (Online service) ; Crisan, Dan . - Berlin, Heidelberg : Springer Berlin Heidelberg, 2011 . - VIII, 299 p : online resource.
ISBN : 978-3-642-15358-7
Idioma : Inglés (eng)
Palabras clave: Mathematics Probabilities Probability Theory and Stochastic Processes Clasificación: 51 Matemáticas Resumen: Stochastic Analysis aims to provide mathematical tools to describe and model high dimensional random systems. Such tools arise in the study of Stochastic Differential Equations and Stochastic Partial Differential Equations, Infinite Dimensional Stochastic Geometry, Random Media and Interacting Particle Systems, Super-processes, Stochastic Filtering, Mathematical Finance, etc. Stochastic Analysis has emerged as a core area of late 20th century Mathematics and is currently undergoing a rapid scientific development. The special volume “Stochastic Analysis 2010” provides a sample of the current research in the different branches of the subject. It includes the collected works of the participants at the Stochastic Analysis section of the 7th ISAAC Congress organized at Imperial College London in July 2009 Nota de contenido: D.Crisan: Introduction to the Volume -- V. Bally and E. Clément: Integration by Parts Formula with Respect to Jump Times for Stochastic Differential Equations -- V. Ortiz-López and M. Sanz-Solé: A Laplace Principle for a Stochastic Wave Equation in Spatial Dimension Three -- X.-M. Li: Intertwinned Diffusions Operators by Examples -- L. G. Gyurkó and T. Lyons: Effcient and practical implementations of Cubature on Wiener space -- T. Kurtz: Equivalence of Stochastic Equations and Martingale Problems -- I. Gyöngy and N.V. Krylov: Accelerated Numerical Schemes for PDEs and SPDEs -- A. Papavasilio: Coarse-Grained Modeling of Multiscale Diffusions: The p-variation Estimates -- V.N. Stanciulescu and M.V. Tretyakov: Numerical Solution of the Dirichlet Problem for Linear Parabolic SPDEs Based on Averaging over Characteristics -- S. Davie: Individual Path Uniqueness of Solutions of Stochastic differential equations -- V. Kolokoltsov: Stochastic Integrals and SDE Driven by Nonlinear Levy Noise -- R. Tunaru: Discrete Algorithms for Multivariate Financial Calculus -- D. Brody, L. Hughston and A. Macrina: Credit Risk, Market Sentiment, and Randomly-Timed Default -- M. Kelbert and Y. Suhov: Continuity of mutual entropy in the limiting signal-to-noise ratio regimes En línea: http://dx.doi.org/10.1007/978-3-642-15358-7 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=33380 Ejemplares
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Título : Stochastic Analysis with Financial Applications : Hong Kong 2009 Tipo de documento: documento electrónico Autores: SpringerLink (Online service) ; Kohatsu-Higa, Arturo ; Privault, Nicolas ; Sheu, Shuenn-Jyi Editorial: Basel : Springer Basel Fecha de publicación: 2011 Colección: Progress in Probability, ISSN 1050-6977 num. 65 Número de páginas: IX, 430 p. 17 illus., 14 illus. in color Il.: online resource ISBN/ISSN/DL: 978-3-0348-0097-6 Idioma : Inglés (eng) Palabras clave: Mathematics Economics, Mathematical Probabilities Probability Theory and Stochastic Processes Quantitative Finance Clasificación: 51 Matemáticas Resumen: Stochastic analysis has a variety of applications to biological systems as well as physical and engineering problems, and its applications to finance and insurance have bloomed exponentially in recent times. The goal of this book is to present a broad overview of the range of applications of stochastic analysis and some of its recent theoretical developments. This includes numerical simulation, error analysis, parameter estimation, as well as control and robustness properties for stochastic equations. The book also covers the areas of backward stochastic differential equations via the (non-linear) G-Brownian motion and the case of jump processes. Concerning the applications to finance, many of the articles deal with the valuation and hedging of credit risk in various forms, and include recent results on markets with transaction costs. Contributors: T.R. Bielecki N. Bouleau S. Chakraborty T.S. Chiang S.N. Cohen J.M. Corcuera S. Crépey A.B. Cruzeiro L. Denis J. Duan R.J. Elliott S. Fang M. Fukasawa F.Q. Gao B. Goldys S. Han Y. Ishikawa M. Jeanblanc H. Jiang B. Jourdain A. Kohatsu-Higa E.T. Kolkovska H. Lee L. Li J.A. López-Mimbela J. Luo B. Øksendahl J. Ren M. Rutkowski E. Shamarova S.J. Sheu A. Sulem A. Takeuchi N. Vaytis R. Wang J. Wei J. Wu J. Yang H. Yang K. Yasuda X. Zhang En línea: http://dx.doi.org/10.1007/978-3-0348-0097-6 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=33260 Stochastic Analysis with Financial Applications : Hong Kong 2009 [documento electrónico] / SpringerLink (Online service) ; Kohatsu-Higa, Arturo ; Privault, Nicolas ; Sheu, Shuenn-Jyi . - Basel : Springer Basel, 2011 . - IX, 430 p. 17 illus., 14 illus. in color : online resource. - (Progress in Probability, ISSN 1050-6977; 65) .
ISBN : 978-3-0348-0097-6
Idioma : Inglés (eng)
Palabras clave: Mathematics Economics, Mathematical Probabilities Probability Theory and Stochastic Processes Quantitative Finance Clasificación: 51 Matemáticas Resumen: Stochastic analysis has a variety of applications to biological systems as well as physical and engineering problems, and its applications to finance and insurance have bloomed exponentially in recent times. The goal of this book is to present a broad overview of the range of applications of stochastic analysis and some of its recent theoretical developments. This includes numerical simulation, error analysis, parameter estimation, as well as control and robustness properties for stochastic equations. The book also covers the areas of backward stochastic differential equations via the (non-linear) G-Brownian motion and the case of jump processes. Concerning the applications to finance, many of the articles deal with the valuation and hedging of credit risk in various forms, and include recent results on markets with transaction costs. Contributors: T.R. Bielecki N. Bouleau S. Chakraborty T.S. Chiang S.N. Cohen J.M. Corcuera S. Crépey A.B. Cruzeiro L. Denis J. Duan R.J. Elliott S. Fang M. Fukasawa F.Q. Gao B. Goldys S. Han Y. Ishikawa M. Jeanblanc H. Jiang B. Jourdain A. Kohatsu-Higa E.T. Kolkovska H. Lee L. Li J.A. López-Mimbela J. Luo B. Øksendahl J. Ren M. Rutkowski E. Shamarova S.J. Sheu A. Sulem A. Takeuchi N. Vaytis R. Wang J. Wei J. Wu J. Yang H. Yang K. Yasuda X. Zhang En línea: http://dx.doi.org/10.1007/978-3-0348-0097-6 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=33260 Ejemplares
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Título : Stochastic and Integral Geometry Tipo de documento: documento electrónico Autores: Schneider, Rolf ; SpringerLink (Online service) ; Weil, Wolfgang Editorial: Berlin, Heidelberg : Springer Berlin Heidelberg Fecha de publicación: 2008 Colección: Probability and Its Applications, ISSN 1431-7028 Número de páginas: XII, 694 p Il.: online resource ISBN/ISSN/DL: 978-3-540-78859-1 Idioma : Inglés (eng) Palabras clave: Mathematics Convex geometry Discrete Probabilities Probability Theory and Stochastic Processes Geometry Clasificación: 51 Matemáticas Resumen: Stochastic geometry has in recent years experienced considerable progress, both in its applications to other sciences and engineering, and in its theoretical foundations and mathematical expansion. This book, by two eminent specialists of the subject, provides a solid mathematical treatment of the basic models of stochastic geometry -- random sets, point processes of geometric objects (particles, flats), and random mosaics. It develops, in a measure-theoretic setting, the integral geometry for the motion and the translation group, as needed for the investigation of these models under the usual invariance assumptions. A characteristic of the book is the interplay between stochastic and geometric arguments, leading to various major results. Its main theme, once the foundations have been laid, is the quantitative investigation of the basic models. This comprises the introduction of suitable parameters, in the form of functional densities, relations between them, and approaches to their estimation. Much additional information on stochastic geometry is collected in the section notes. As a combination of probability theory and geometry, the volume is intended for readers from either field. Probabilists with interest in random spatial structures, or motivated by the prospect of applications, will find an in-depth presentation of the geometric background. Geometers can see integral geometry "at work" and may be surprised to learn how classical results from convex geometry have elegant applications in a stochastic setting Nota de contenido: Foundations of Stochastic Geometry -- Prolog -- Random Closed Sets -- Point Processes -- Geometric Models -- Integral Geometry -- Averaging with Invariant Measures -- Extended Concepts of Integral Geometry -- Integral Geometric Transformations -- Selected Topics from Stochastic Geometry -- Some Geometric Probability Problems -- Mean Values for Random Sets -- Random Mosaics -- Non-stationary Models -- Facts from General Topology -- Invariant Measures -- Facts from Convex Geometry En línea: http://dx.doi.org/10.1007/978-3-540-78859-1 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=34377 Stochastic and Integral Geometry [documento electrónico] / Schneider, Rolf ; SpringerLink (Online service) ; Weil, Wolfgang . - Berlin, Heidelberg : Springer Berlin Heidelberg, 2008 . - XII, 694 p : online resource. - (Probability and Its Applications, ISSN 1431-7028) .
ISBN : 978-3-540-78859-1
Idioma : Inglés (eng)
Palabras clave: Mathematics Convex geometry Discrete Probabilities Probability Theory and Stochastic Processes Geometry Clasificación: 51 Matemáticas Resumen: Stochastic geometry has in recent years experienced considerable progress, both in its applications to other sciences and engineering, and in its theoretical foundations and mathematical expansion. This book, by two eminent specialists of the subject, provides a solid mathematical treatment of the basic models of stochastic geometry -- random sets, point processes of geometric objects (particles, flats), and random mosaics. It develops, in a measure-theoretic setting, the integral geometry for the motion and the translation group, as needed for the investigation of these models under the usual invariance assumptions. A characteristic of the book is the interplay between stochastic and geometric arguments, leading to various major results. Its main theme, once the foundations have been laid, is the quantitative investigation of the basic models. This comprises the introduction of suitable parameters, in the form of functional densities, relations between them, and approaches to their estimation. Much additional information on stochastic geometry is collected in the section notes. As a combination of probability theory and geometry, the volume is intended for readers from either field. Probabilists with interest in random spatial structures, or motivated by the prospect of applications, will find an in-depth presentation of the geometric background. Geometers can see integral geometry "at work" and may be surprised to learn how classical results from convex geometry have elegant applications in a stochastic setting Nota de contenido: Foundations of Stochastic Geometry -- Prolog -- Random Closed Sets -- Point Processes -- Geometric Models -- Integral Geometry -- Averaging with Invariant Measures -- Extended Concepts of Integral Geometry -- Integral Geometric Transformations -- Selected Topics from Stochastic Geometry -- Some Geometric Probability Problems -- Mean Values for Random Sets -- Random Mosaics -- Non-stationary Models -- Facts from General Topology -- Invariant Measures -- Facts from Convex Geometry En línea: http://dx.doi.org/10.1007/978-3-540-78859-1 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=34377 Ejemplares
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