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Properties Of Hierarchical Archimedean Copulas


Properties Of Hierarchical Archimedean Copulas
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Hierarchical Archimedean Copulas


Hierarchical Archimedean Copulas
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Author : Jan Górecki
language : en
Publisher: Springer Nature
Release Date : 2024-05-15

Hierarchical Archimedean Copulas written by Jan Górecki and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-05-15 with Mathematics categories.


This book offers a thorough understanding of Hierarchical Archimedean Copulas (HACs) and their practical applications. It covers the basics of copulas, explores the Archimedean family, and delves into the specifics of HACs, including their fundamental properties. The text also addresses sampling algorithms, HAC parameter estimation, and structure, and highlights temporal models with applications in finance and economics. The final chapter introduces R, MATLAB, and Octave toolboxes for copula modeling, enabling students, researchers, data scientists, and practitioners to model complex dependence structures and make well-informed decisions across various domains.



Properties Of Hierarchical Archimedean Copulas


Properties Of Hierarchical Archimedean Copulas
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Author : Ostap Okhrin
language : en
Publisher:
Release Date : 2009

Properties Of Hierarchical Archimedean Copulas written by Ostap Okhrin and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009 with categories.




Hierarchical Archimedean Copulas


Hierarchical Archimedean Copulas
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Author : Ostap Okhrin
language : en
Publisher:
Release Date : 2007

Hierarchical Archimedean Copulas written by Ostap Okhrin and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007 with categories.




Copula Theory And Its Applications


Copula Theory And Its Applications
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Author : Piotr Jaworski
language : en
Publisher: Springer Science & Business Media
Release Date : 2010-07-16

Copula Theory And Its Applications written by Piotr Jaworski and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-07-16 with Mathematics categories.


Copulas are mathematical objects that fully capture the dependence structure among random variables and hence offer great flexibility in building multivariate stochastic models. Since their introduction in the early 50's, copulas have gained considerable popularity in several fields of applied mathematics, such as finance, insurance and reliability theory. Today, they represent a well-recognized tool for market and credit models, aggregation of risks, portfolio selection, etc. This book is divided into two main parts: Part I - "Surveys" contains 11 chapters that provide an up-to-date account of essential aspects of copula models. Part II - "Contributions" collects the extended versions of 6 talks selected from papers presented at the workshop in Warsaw.



Simulating Copulas


Simulating Copulas
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Author : Jan-Frederik Mai
language : en
Publisher: World Scientific
Release Date : 2012

Simulating Copulas written by Jan-Frederik Mai and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012 with Mathematics categories.


This book provides the reader with a background on simulating copulas and multivariate distributions in general. It unifies the scattered literature on the simulation of various families of copulas (elliptical, Archimedean, Marshall-Olkin type, etc.) as well as on different construction principles (factor models, pair-copula construction, etc.). The book is self-contained and unified in presentation and can be used as a textbook for advanced undergraduate or graduate students with a firm background in stochastics. Alongside the theoretical foundation, ready-to-implement algorithms and many examples make this book a valuable tool for anyone who is applying the methodology.Errata(s)Errata (128 KB)



Simulating Copulas Stochastic Models Sampling Algorithms And Applications Second Edition


Simulating Copulas Stochastic Models Sampling Algorithms And Applications Second Edition
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Author : Jan-frederik Mai
language : en
Publisher: #N/A
Release Date : 2017-06-07

Simulating Copulas Stochastic Models Sampling Algorithms And Applications Second Edition written by Jan-frederik Mai and has been published by #N/A this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-06-07 with Mathematics categories.


'The book remains a valuable tool both for statisticians who are already familiar with the theory of copulas and just need to develop sampling algorithms, and for practitioners who want to learn copulas and implement the simulation techniques needed to exploit the potential of copulas in applications.'Mathematical ReviewsThe book provides the background on simulating copulas and multivariate distributions in general. It unifies the scattered literature on the simulation of various families of copulas (elliptical, Archimedean, Marshall-Olkin type, etc.) as well as on different construction principles (factor models, pair-copula construction, etc.). The book is self-contained and unified in presentation and can be used as a textbook for graduate and advanced undergraduate students with a firm background in stochastics. Besides the theoretical foundation, ready-to-implement algorithms and many examples make the book a valuable tool for anyone who is applying the methodology.



Introduction To Bayesian Estimation And Copula Models Of Dependence


Introduction To Bayesian Estimation And Copula Models Of Dependence
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Author : Arkady Shemyakin
language : en
Publisher: John Wiley & Sons
Release Date : 2017-03-03

Introduction To Bayesian Estimation And Copula Models Of Dependence written by Arkady Shemyakin and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-03-03 with Mathematics categories.


Presents an introduction to Bayesian statistics, presents an emphasis on Bayesian methods (prior and posterior), Bayes estimation, prediction, MCMC,Bayesian regression, and Bayesian analysis of statistical modelsof dependence, and features a focus on copulas for risk management Introduction to Bayesian Estimation and Copula Models of Dependence emphasizes the applications of Bayesian analysis to copula modeling and equips readers with the tools needed to implement the procedures of Bayesian estimation in copula models of dependence. This book is structured in two parts: the first four chapters serve as a general introduction to Bayesian statistics with a clear emphasis on parametric estimation and the following four chapters stress statistical models of dependence with a focus of copulas. A review of the main concepts is discussed along with the basics of Bayesian statistics including prior information and experimental data, prior and posterior distributions, with an emphasis on Bayesian parametric estimation. The basic mathematical background of both Markov chains and Monte Carlo integration and simulation is also provided. The authors discuss statistical models of dependence with a focus on copulas and present a brief survey of pre-copula dependence models. The main definitions and notations of copula models are summarized followed by discussions of real-world cases that address particular risk management problems. In addition, this book includes: • Practical examples of copulas in use including within the Basel Accord II documents that regulate the world banking system as well as examples of Bayesian methods within current FDA recommendations • Step-by-step procedures of multivariate data analysis and copula modeling, allowing readers to gain insight for their own applied research and studies • Separate reference lists within each chapter and end-of-the-chapter exercises within Chapters 2 through 8 • A companion website containing appendices: data files and demo files in Microsoft® Office Excel®, basic code in R, and selected exercise solutions Introduction to Bayesian Estimation and Copula Models of Dependence is a reference and resource for statisticians who need to learn formal Bayesian analysis as well as professionals within analytical and risk management departments of banks and insurance companies who are involved in quantitative analysis and forecasting. This book can also be used as a textbook for upper-undergraduate and graduate-level courses in Bayesian statistics and analysis. ARKADY SHEMYAKIN, PhD, is Professor in the Department of Mathematics and Director of the Statistics Program at the University of St. Thomas. A member of the American Statistical Association and the International Society for Bayesian Analysis, Dr. Shemyakin's research interests include informationtheory, Bayesian methods of parametric estimation, and copula models in actuarial mathematics, finance, and engineering. ALEXANDER KNIAZEV, PhD, is Associate Professor and Head of the Department of Mathematics at Astrakhan State University in Russia. Dr. Kniazev's research interests include representation theory of Lie algebras and finite groups, mathematical statistics, econometrics, and financial mathematics.



Applied Quantitative Finance


Applied Quantitative Finance
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Author : Wolfgang Karl Härdle
language : en
Publisher: Springer
Release Date : 2017-08-02

Applied Quantitative Finance written by Wolfgang Karl Härdle and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-08-02 with Business & Economics categories.


This volume provides practical solutions and introduces recent theoretical developments in risk management, pricing of credit derivatives, quantification of volatility and copula modeling. This third edition is devoted to modern risk analysis based on quantitative methods and textual analytics to meet the current challenges in banking and finance. It includes 14 new contributions and presents a comprehensive, state-of-the-art treatment of cutting-edge methods and topics, such as collateralized debt obligations, the high-frequency analysis of market liquidity, and realized volatility. The book is divided into three parts: Part 1 revisits important market risk issues, while Part 2 introduces novel concepts in credit risk and its management along with updated quantitative methods. The third part discusses the dynamics of risk management and includes risk analysis of energy markets and for cryptocurrencies. Digital assets, such as blockchain-based currencies, have become popular b ut are theoretically challenging when based on conventional methods. Among others, it introduces a modern text-mining method called dynamic topic modeling in detail and applies it to the message board of Bitcoins. The unique synthesis of theory and practice supported by computational tools is reflected not only in the selection of topics, but also in the fine balance of scientific contributions on practical implementation and theoretical concepts. This link between theory and practice offers theoreticians insights into considerations of applicability and, vice versa, provides practitioners convenient access to new techniques in quantitative finance. Hence the book will appeal both to researchers, including master and PhD students, and practitioners, such as financial engineers. The results presented in the book are fully reproducible and all quantlets needed for calculations are provided on an accompanying website. The Quantlet platform quantlet.de, quantlet.com, quantlet.org is an integrated QuantNet environment consisting of different types of statistics-related documents and program codes. Its goal is to promote reproducibility and offer a platform for sharing validated knowledge native to the social web. QuantNet and the corresponding Data-Driven Documents-based visualization allows readers to reproduce the tables, pictures and calculations inside this Springer book.



Dependence Modeling With Copulas


Dependence Modeling With Copulas
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Author : Harry Joe
language : en
Publisher: CRC Press
Release Date : 2014-06-26

Dependence Modeling With Copulas written by Harry Joe and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-06-26 with Mathematics categories.


Dependence Modeling with Copulas covers the substantial advances that have taken place in the field during the last 15 years, including vine copula modeling of high-dimensional data. Vine copula models are constructed from a sequence of bivariate copulas. The book develops generalizations of vine copula models, including common and structured factor models that extend from the Gaussian assumption to copulas. It also discusses other multivariate constructions and parametric copula families that have different tail properties and presents extensive material on dependence and tail properties to assist in copula model selection. The author shows how numerical methods and algorithms for inference and simulation are important in high-dimensional copula applications. He presents the algorithms as pseudocode, illustrating their implementation for high-dimensional copula models. He also incorporates results to determine dependence and tail properties of multivariate distributions for future constructions of copula models.



Copulae In Mathematical And Quantitative Finance


Copulae In Mathematical And Quantitative Finance
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Author : Piotr Jaworski
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-06-18

Copulae In Mathematical And Quantitative Finance written by Piotr Jaworski and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-06-18 with Business & Economics categories.


Copulas are mathematical objects that fully capture the dependence structure among random variables and hence offer great flexibility in building multivariate stochastic models. Since their introduction in the early 1950s, copulas have gained considerable popularity in several fields of applied mathematics, especially finance and insurance. Today, copulas represent a well-recognized tool for market and credit models, aggregation of risks, and portfolio selection. Historically, the Gaussian copula model has been one of the most common models in credit risk. However, the recent financial crisis has underlined its limitations and drawbacks. In fact, despite their simplicity, Gaussian copula models severely underestimate the risk of the occurrence of joint extreme events. Recent theoretical investigations have put new tools for detecting and estimating dependence and risk (like tail dependence, time-varying models, etc) in the spotlight. All such investigations need to be further developed and promoted, a goal this book pursues. The book includes surveys that provide an up-to-date account of essential aspects of copula models in quantitative finance, as well as the extended versions of talks selected from papers presented at the workshop in Cracow.