Statistical Inference for Copula and Tail Copula Models With - Applications to Finance and Insuranc

This book covers statistical inference for copula and tail copula models with applications in finance, insurance and risk management.

List of contents

Introduction. Inference for Copula on Independent Data. Inference for Tail Copulas on Independent Data. Inference for Dependent Data. Applications.

About the author

Professor Liang Peng is the Thomas P Bowles Chair professor of Actuarial Science in the Department of Risk Management and Insurance in the Robinson College of Business at Georgia State University, and is the fellow of both Institute of Mathematical Statistics and American Statistical Association. Peng has extensive research experience in extreme value theory, time series analysis, nonparametric statistics, copula models, empirical likelihood methods and uncertainty quanti cation for various risk measures.

Summary

This book will cover statistical inference for copula and tail copula models with applications in finance, insurance and risk management. After giving a quick introduction to copula and tail copula models, it will focus on various up-to-date statistical inference procedures, including point and interval estimation and goodness-of- t tests, for both copulas and tail copulas based on either independent data or dependent data. A chapter on applications in nance, insurance and risk management will be provided with R code.

Product details

• Authors: Liang Peng, Liang (Georgia State University Peng, Zhengjun Zhang
• Publisher: Taylor & Francis Ltd.
• Languages: English
• Product format: Hardback
• Release: 31.05.2019, delayed
• EAN: 9781498768658
• ISBN: 978-1-4987-6865-8
• No. of pages: 200
• Series: Chapman and Hall/CRC Financial Mathematics Series; Chapman & Hall/CRC Financial Mathematics Series; Chapman and Hall/CRC Financial Mathematics Series
• Subjects: Natural sciences, medicine, IT, technology > Mathematics > Probability theory, stochastic theory, mathematical statistics; Social sciences, law, business > Business > General, dictionaries