Description: Structured Dependence between Stochastic Processes by Tomasz R. Bielecki, Jacek Jakubowski, Mariusz Niewȩgłowski The theory of structured dependence has many real-life applications in areas such as finance, insurance, seismology, neuroscience, and genetics. The first book to be devoted to this research area, this is a useful tool for researchers and practitioners in the field, as well as graduate students. FORMAT Hardcover LANGUAGE English CONDITION Brand New Publisher Description The relatively young theory of structured dependence between stochastic processes has many real-life applications in areas including finance, insurance, seismology, neuroscience, and genetics. With this monograph, the first to be devoted to the modeling of structured dependence between random processes, the authors not only meet the demand for a solid theoretical account but also develop a stochastic processes counterpart of the classical copula theory that exists for finite-dimensional random variables. Presenting both the technical aspects and the applications of the theory, this is a valuable reference for researchers and practitioners in the field, as well as for graduate students in pure and applied mathematics programs. Numerous theoretical examples are included, alongside examples of both current and potential applications, aimed at helping those who need to model structured dependence between dynamic random phenomena. Author Biography Tomasz R. Bielecki is Professor of Applied Mathematics at the Illinois Institute of Technology, Chicago. He co-authored Credit Risk: Modelling, Valuation and Hedging (2002), Credit Risk Modelling (2010) and Counterparty Risk and Funding (2014), and he currently serves as an associate editor of several journals, including Stochastics: An International Journal of Probability and Stochastic Processes. Jacek Jakubowski is Professor of Mathematics at the University of Warsaw. He is the author of numerous research papers in the areas of functional analysis, probability theory, stochastic processes, stochastic analysis, and mathematical finance, and he has co-authored several books in Polish, including Introduction to Probability Theory (2000), which is now in its fourth edition. Mariusz Niewgowski is currently an Assistant Professor in the Faculty of Mathematics and Information Science at Warsaw University of Technology. The areas of his current research include financial mathematics with a focus on credit risk and stochastic analysis with a focus on modeling of dependence between stochastic processes. Table of Contents 1. Introduction; Part I. Consistencies: 2. Strong Markov consistency of multivariate Markov families and processes; 3. Consistency of finite multivariate Markov chains; 4. Consistency of finite multivariate conditional Markov chains; 5. Consistency of multivariate special semimartingales; Part II. Structures: 6. Strong Markov family structures; 7. Markov chain structures; 8. Conditional Markov chain structures; 9. Special semimartingale structures Part III. Further Developments: 10. Archimedean survival processes, Markov consistency, ASP structures; 11. Generalized multivariate Hawkes processes; Part IV. Applications of Stochastic Structures: 12. Applications of stochastic structures; Appendix A. Stochastic analysis: selected concepts and results used in this book; Appendix B. Markov processes and Markov families; Appendix C. Finite Markov chains: auxiliary technical framework; Appendix D. Crash course on conditional Markov chains and on doubly stochastic Markov chains; Appendix E. Evolution systems and semigroups of linear operators; Appendix F. Martingale problem: some new results needed in this book; Appendix G. Function spaces and pseudo-differential operators; References; Notation index; Subject index. Review This is a timely book on an important topic, and it is well written. John Masson Noble, MathSciNetThe authors follow good traditions, starting with exact definitions, commenting on essential properties, asking appropriate questions, formulating theorems, lemmas or propositions and giving explicit conditions under which complete proofs are provided for the statements. Jordan M. Stoyanov, zbMATH Promotional Comprehensive presentation of the technical aspects and applications of the theory of structured dependence between random processes. Long Description The relatively young theory of structured dependence between stochastic processes has many real-life applications in areas including finance, insurance, seismology, neuroscience, and genetics. With this monograph, the first to be devoted to the modeling of structured dependence between random processes, the authors not only meet the demand for a solid theoretical account but also develop a stochastic processes counterpart of the classical copula theory that exists for finite-dimensional random variables. Presenting both the technical aspects and the applications of the theory, this is a valuable reference for researchers and practitioners in the field, as well as for graduate students in pure and applied mathematics programs. Numerous theoretical examples are included, alongside examples of both current and potential applications, aimed at helping those who need to model structured dependence between dynamic random phenomena. Promotional "Headline" Comprehensive presentation of the technical aspects and applications of the theory of structured dependence between random processes. Description for Bookstore The theory of structured dependence has many real-life applications in areas such as finance, insurance, seismology, neuroscience, and genetics. The first book to be devoted to this research area, this is a useful tool for researchers and practitioners in the field, as well as graduate students. Description for Library The theory of structured dependence has many real-life applications in areas such as finance, insurance, seismology, neuroscience, and genetics. The first book to be devoted to this research area, this is a useful tool for researchers and practitioners in the field, as well as graduate students. Details ISBN1107154251 Year 2020 ISBN-10 1107154251 ISBN-13 9781107154254 Format Hardcover Pages 278 Series Encyclopedia of Mathematics and its Applications Imprint Cambridge University Press Subtitle Consistencies and Copulae Place of Publication Cambridge Country of Publication United Kingdom Author Mariusz Niewgowski Publisher Cambridge University Press Affiliation Uniwersytet Warszawski, Poland Language English Series Number 175 DEWEY 519.22 Publication Date 2020-08-27 UK Release Date 2020-08-27 AU Release Date 2020-08-27 NZ Release Date 2020-08-27 Alternative 9781316650530 Illustrations Worked examples or Exercises Audience Professional & Vocational We've got this At The Nile, if you're looking for it, we've got it. With fast shipping, low prices, friendly service and well over a million items - you're bound to find what you want, at a price you'll love! TheNile_Item_ID:130153462;
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ISBN-13: 9781107154254
Book Title: Structured Dependence between Stochastic Processes
Number of Pages: 278 Pages
Language: English
Publication Name: Structured Dependence between Stochastic Processes
Publisher: Cambridge University Press
Publication Year: 2020
Subject: Geology, Finance, Biology, Mathematics
Item Height: 240 mm
Item Weight: 600 g
Type: Textbook
Author: Jacek Jakubowski, Mariusz Nieweglowski, Tomasz R. Bielecki
Subject Area: Data Analysis
Item Width: 165 mm
Format: Hardcover
