Applied stochastic control in econometrics and management science / Alain Bensoussan (1980)

Público ISBD Título : Applied stochastic control in econometrics and management science Tipo de documento: texto impreso Autores: Alain Bensoussan, Editor científico ; Paul Kleindorfer, Editor científico ; Charles S. Tapiero, Editor científico Editorial: Amsterdam ; Oxford : North-Holland Fecha de publicación: 1980 Colección: Contributions to economic analysis num. 130 Número de páginas: XV, 304 p. Dimensiones: 23 cm ISBN/ISSN/DL: 978-0-444-85408-7 Idioma : Inglés (eng) Materias: Econometría Econometría aplicada Clasificación: 519.21 Teoría de probabilidades y procesos estocásticos Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=3536 Applied stochastic control in econometrics and management science [texto impreso] / Alain Bensoussan, Editor científico ; Paul Kleindorfer, Editor científico ; Charles S. Tapiero, Editor científico . - Amsterdam ; Oxford : North-Holland, 1980 . - XV, 304 p. ; 23 cm. - (Contributions to economic analysis; 130) . ISBN : 978-0-444-85408-7 Idioma : Inglés (eng) Materias: Econometría Econometría aplicada Clasificación: 519.21 Teoría de probabilidades y procesos estocásticos Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=3536

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Engineering Risk and Finance / Charles S. Tapiero (2013)  

Público ISBD Título : Engineering Risk and Finance Tipo de documento: documento electrónico Autores: Charles S. Tapiero ; SpringerLink (Online service) Editorial: Boston, MA : Springer US Fecha de publicación: 2013 Otro editor: Imprint: Springer Colección: International Series in Operations Research & Management Science, ISSN 0884-8289 num. 188 Número de páginas: XVIII, 508 p. 41 illus., 30 illus. in color Il.: online resource ISBN/ISSN/DL: 978-1-4614-6234-7 Idioma : Inglés (eng) Palabras clave: Business  Operations  research  Decision  making  Applied  mathematics  Engineering  economics  economy  and  Management  Operation  Research/Decision  Theory  Economics,  Organization,  Logistics,  Marketing  Appl.Mathematics/Computational  Methods  of Clasificación: 658 Empresas. Organización de empresas Resumen: Risk models are models of uncertainty, engineered for some purposes. They are “educated guesses and hypotheses” assessed and valued in terms of well-defined future states and their consequences. They are engineered to predict, to manage countable and accountable futures and to provide a frame of reference within which we may believe that “uncertainty is tamed.” Quantitative-statistical tools are used to reconcile our information, experience and other knowledge with hypotheses that both serve as the foundation of risk models and also value and price risk. Risk models are therefore common to most professions, each with its own methods and techniques based on their needs, experience and a wisdom accrued over long periods of time. This book provides a broad and interdisciplinary foundation to engineering risks and to their financial valuation and pricing. Risk models applied in industry and business, heath care, safety, the environment and regulation are used to highlight their variety while financial valuation techniques are used to assess their financial consequences. This book is technically accessible to all readers and students with a basic background in probability and statistics (with 3 chapters devoted to introduce their elements). Principles of risk measurement, valuation and financial pricing as well as the economics of uncertainty are outlined in 5 chapters with numerous examples and applications. New results, extending classical models such as the CCAPM are presented providing insights to assess the risks and their price in an interconnected, dependent and strategic economic environment. In an environment departing from the fundamental assumptions we make regarding financial markets, the book provides a strategic/game-like approach to assess the risk and the opportunities that such an environment implies. To control these risks, a strategic-control approach is developed that recognizes that many risks result by “what we do” as well as “what others do”. In particular we address the strategic and statistical control of compliance in large financial institutions confronted increasingly with a complex and far more extensive regulation Nota de contenido: Risk: The Convergence -- Risk Management Everywhere -- Probability Elements: An Applied Refresher -- Multivariate Probability Distributions: Applications and Risk Models -- Temporal Risk Processes -- Risk Measurement -- Risk Valuation -- Risk Economics and the Extended CCAPM -- Risk Pricing Models: Applications -- Uncertainty Economics -- Strategic Risk Control and Regulation -- Games, Risk, and Uncertainty En línea: http://dx.doi.org/10.1007/978-1-4614-6234-7 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=36441 Engineering Risk and Finance [documento electrónico] / Charles S. Tapiero ; SpringerLink (Online service) . - Boston, MA : Springer US : Imprint: Springer, 2013 . - XVIII, 508 p. 41 illus., 30 illus. in color : online resource. - (International Series in Operations Research & Management Science, ISSN 0884-8289; 188) . ISBN : 978-1-4614-6234-7 Idioma : Inglés (eng) Palabras clave: Business  Operations  research  Decision  making  Applied  mathematics  Engineering  economics  economy  and  Management  Operation  Research/Decision  Theory  Economics,  Organization,  Logistics,  Marketing  Appl.Mathematics/Computational  Methods  of Clasificación: 658 Empresas. Organización de empresas Resumen: Risk models are models of uncertainty, engineered for some purposes. They are “educated guesses and hypotheses” assessed and valued in terms of well-defined future states and their consequences. They are engineered to predict, to manage countable and accountable futures and to provide a frame of reference within which we may believe that “uncertainty is tamed.” Quantitative-statistical tools are used to reconcile our information, experience and other knowledge with hypotheses that both serve as the foundation of risk models and also value and price risk. Risk models are therefore common to most professions, each with its own methods and techniques based on their needs, experience and a wisdom accrued over long periods of time. This book provides a broad and interdisciplinary foundation to engineering risks and to their financial valuation and pricing. Risk models applied in industry and business, heath care, safety, the environment and regulation are used to highlight their variety while financial valuation techniques are used to assess their financial consequences. This book is technically accessible to all readers and students with a basic background in probability and statistics (with 3 chapters devoted to introduce their elements). Principles of risk measurement, valuation and financial pricing as well as the economics of uncertainty are outlined in 5 chapters with numerous examples and applications. New results, extending classical models such as the CCAPM are presented providing insights to assess the risks and their price in an interconnected, dependent and strategic economic environment. In an environment departing from the fundamental assumptions we make regarding financial markets, the book provides a strategic/game-like approach to assess the risk and the opportunities that such an environment implies. To control these risks, a strategic-control approach is developed that recognizes that many risks result by “what we do” as well as “what others do”. In particular we address the strategic and statistical control of compliance in large financial institutions confronted increasingly with a complex and far more extensive regulation Nota de contenido: Risk: The Convergence -- Risk Management Everywhere -- Probability Elements: An Applied Refresher -- Multivariate Probability Distributions: Applications and Risk Models -- Temporal Risk Processes -- Risk Measurement -- Risk Valuation -- Risk Economics and the Extended CCAPM -- Risk Pricing Models: Applications -- Uncertainty Economics -- Strategic Risk Control and Regulation -- Games, Risk, and Uncertainty En línea: http://dx.doi.org/10.1007/978-1-4614-6234-7 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=36441

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Future Perspectives in Risk Models and Finance / SpringerLink (Online service) ; Alain Bensoussan ; Dominique Guegan ; Charles S. Tapiero (2015)  

Público ISBD Título : Future Perspectives in Risk Models and Finance Tipo de documento: documento electrónico Autores: SpringerLink (Online service) ; Alain Bensoussan ; Dominique Guegan ; Charles S. Tapiero Editorial: Cham : Springer International Publishing Fecha de publicación: 2015 Otro editor: Imprint: Springer Colección: International Series in Operations Research & Management Science, ISSN 0884-8289 num. 211 Número de páginas: XIV, 315 p. 45 illus., 31 illus. in color Il.: online resource ISBN/ISSN/DL: 978-3-319-07524-2 Idioma : Inglés (eng) Palabras clave: Business  Operations  research  Decision  making  Economics,  Mathematical  Macroeconomics  and  Management  Operation  Research/Decision  Theory  Quantitative  Finance  Macroeconomics/Monetary  Economics//Financial  Economics Clasificación: 658 Empresas. Organización de empresas Resumen: This book provides a perspective on a number of approaches to financial modelling and risk management. It examines both theoretical and practical issues. Theoretically, financial risks models are models of a real and a financial “uncertainty”, based on both common and private information and economic theories defining the rules that financial markets comply to. Financial models are thus challenged by their definitions and by a changing financial system fueled by globalization, technology growth, complexity, regulation and the many factors that contribute to rendering financial processes to be continuously questioned and re-assessed. The underlying mathematical foundations of financial risks models provide future guidelines for risk modeling. The book’s chapters provide selective insights and developments that can contribute to better understand the complexity of financial modelling and its ability to bridge financial theories and their practice.   Future Perspectives in Risk Models and Finance begins with an extensive outline by Alain Bensoussan et al. of GLM estimation techniques combined with proofs of fundamental results. Applications to static and dynamic models provide a unified approach to the estimation of nonlinear risk models.  A second section is concerned with the definition of risks and their management. In particular, Guegan and Hassani review a number of risk models definition emphasizing the importance of bi-modal distributions for financial regulation. An additional chapter provides a review of stress testing and their implications. Nassim Taleb, and Sandis provide an anti-fragility approach based on “skin in the game”. To conclude, Raphael Douady discusses the noncyclical CAR (Capital Adequacy Rule) and their effects of aversion of systemic risks.  A third section emphasizes analytic financial modelling approaches and techniques. Tapiero and Vallois provide an overview of mathematical systems and their use in financial modeling. These systems span the fundamental Arrow-Debreu framework underlying financial models of complete markets and subsequently, mathematical systems departing from this framework but yet generalizing their approach to dynamic financial models. Explicitly, models based on fractional calculus, on persistence (short memory) and on entropy-based non-extensiveness. Applications of these models are used to define a modeling approach to incomplete financial models and their potential use as a “measure of incompleteness”.  Subsequently Bianchi and Pianese provide an extensive overview of multi-fractional models and their important applications to Asset price modeling. Finally, Tapiero and Jinquyi consider the binomial pricing model by discussing the effects of memory on the pricing of asset prices Nota de contenido: Estimation Theory for Generalized Linear Models -- New Distorsion Risk Measure Based on Bimodal Distributions -- Stress Testing Engineering: Risk Vs Incident -- The Skin In The Game Heuristic for Protection Against Tail Events -- The Fragility Theorem -- Financial Modeling, Memory and Mathematical Systems -- Asset price modeling: from Fractional to Multifractional Processes -- Financial Analytics and A Binomial Pricing Model En línea: http://dx.doi.org/10.1007/978-3-319-07524-2 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=35423 Future Perspectives in Risk Models and Finance [documento electrónico] / SpringerLink (Online service) ; Alain Bensoussan ; Dominique Guegan ; Charles S. Tapiero . - Cham : Springer International Publishing : Imprint: Springer, 2015 . - XIV, 315 p. 45 illus., 31 illus. in color : online resource. - (International Series in Operations Research & Management Science, ISSN 0884-8289; 211) . ISBN : 978-3-319-07524-2 Idioma : Inglés (eng) Palabras clave: Business  Operations  research  Decision  making  Economics,  Mathematical  Macroeconomics  and  Management  Operation  Research/Decision  Theory  Quantitative  Finance  Macroeconomics/Monetary  Economics//Financial  Economics Clasificación: 658 Empresas. Organización de empresas Resumen: This book provides a perspective on a number of approaches to financial modelling and risk management. It examines both theoretical and practical issues. Theoretically, financial risks models are models of a real and a financial “uncertainty”, based on both common and private information and economic theories defining the rules that financial markets comply to. Financial models are thus challenged by their definitions and by a changing financial system fueled by globalization, technology growth, complexity, regulation and the many factors that contribute to rendering financial processes to be continuously questioned and re-assessed. The underlying mathematical foundations of financial risks models provide future guidelines for risk modeling. The book’s chapters provide selective insights and developments that can contribute to better understand the complexity of financial modelling and its ability to bridge financial theories and their practice.   Future Perspectives in Risk Models and Finance begins with an extensive outline by Alain Bensoussan et al. of GLM estimation techniques combined with proofs of fundamental results. Applications to static and dynamic models provide a unified approach to the estimation of nonlinear risk models.  A second section is concerned with the definition of risks and their management. In particular, Guegan and Hassani review a number of risk models definition emphasizing the importance of bi-modal distributions for financial regulation. An additional chapter provides a review of stress testing and their implications. Nassim Taleb, and Sandis provide an anti-fragility approach based on “skin in the game”. To conclude, Raphael Douady discusses the noncyclical CAR (Capital Adequacy Rule) and their effects of aversion of systemic risks.  A third section emphasizes analytic financial modelling approaches and techniques. Tapiero and Vallois provide an overview of mathematical systems and their use in financial modeling. These systems span the fundamental Arrow-Debreu framework underlying financial models of complete markets and subsequently, mathematical systems departing from this framework but yet generalizing their approach to dynamic financial models. Explicitly, models based on fractional calculus, on persistence (short memory) and on entropy-based non-extensiveness. Applications of these models are used to define a modeling approach to incomplete financial models and their potential use as a “measure of incompleteness”.  Subsequently Bianchi and Pianese provide an extensive overview of multi-fractional models and their important applications to Asset price modeling. Finally, Tapiero and Jinquyi consider the binomial pricing model by discussing the effects of memory on the pricing of asset prices Nota de contenido: Estimation Theory for Generalized Linear Models -- New Distorsion Risk Measure Based on Bimodal Distributions -- Stress Testing Engineering: Risk Vs Incident -- The Skin In The Game Heuristic for Protection Against Tail Events -- The Fragility Theorem -- Financial Modeling, Memory and Mathematical Systems -- Asset price modeling: from Fractional to Multifractional Processes -- Financial Analytics and A Binomial Pricing Model En línea: http://dx.doi.org/10.1007/978-3-319-07524-2 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=35423

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