{"product_id":"advances-in-heavy-tailed-risk-modeling-isbn-9781118909539","title":"Advances in Heavy Tailed Risk Modeling","description":"ADVANCES IN HEAVY TAILED RISK MODELING \u003cp\u003eA cutting-edge guide for the theories, applications, and statistical methodologies essential to heavy tailed risk modeling \u003c\/p\u003e\u003cp\u003eFocusing on the quantitative aspects of heavy tailed loss processes in operational risk and relevant insurance analytics, \u003ci\u003eAdvances in Heavy Tailed Risk Modeling: A Handbook of Operational Risk\u003c\/i\u003e presents comprehensive coverage of the latest research on the theories and applications in risk measurement and modeling techniques. Featuring a unique balance of mathematical and statistical perspectives, the handbook begins by introducing the motivation for heavy tailed risk processes. \u003c\/p\u003e\u003cp\u003eA companion with \u003ci\u003eFundamental Aspects of Operational Risk and Insurance Analytics: A Handbook of Operational Risk\u003c\/i\u003e, the handbook provides a complete framework for all aspects of operational risk management and includes: \u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eClear coverage on advanced topics such as splice loss models, extreme value theory, heavy tailed closed form loss distribution approach models, flexible heavy tailed risk models, risk measures, and higher order asymptotic approximations of risk measures for capital estimation\u003c\/li\u003e \u003cli\u003eAn exploration of the characterization and estimation of risk and insurance modeling, which includes sub-exponential models, alpha-stable models, and tempered alpha stable models\u003c\/li\u003e \u003cli\u003eAn extended discussion of the core concepts of risk measurement and capital estimation as well as the details on numerical approaches to evaluation of heavy tailed loss process model capital estimates\u003c\/li\u003e \u003cli\u003eNumerous detailed examples of real-world methods and practices of operational risk modeling used by both financial and non-financial institutions\u003c\/li\u003e\n\u003c\/ul\u003e \u003cp\u003e\u003ci\u003eAdvances in Heavy Tailed Risk Modeling: A Handbook of Operational Risk\u003c\/i\u003e is an excellent reference for risk management practitioners, quantitative analysts, financial engineers, and risk managers. The handbook is also useful for graduate-level courses on heavy tailed processes, advanced risk management, and actuarial science. \u003c\/p\u003e\u003cp\u003e1 Motivation for Heavy-Tailed Models 1\u003c\/p\u003e \u003cp\u003e2 Fundamentals of Extreme Value Theory for OpRisk 17\u003c\/p\u003e \u003cp\u003e3 Heavy-Tailed Model Class Characterizations for LDA 105\u003c\/p\u003e \u003cp\u003e4 Flexible Heavy-Tailed Severity Models: α-Stable Family 139\u003c\/p\u003e \u003cp\u003e5 Flexible Heavy-Tailed Severity Models: Tempered Stable and Quantile Transforms 227\u003c\/p\u003e \u003cp\u003e6 Families of Closed-Form Single Risk LDA Models 279\u003c\/p\u003e \u003cp\u003e7 Single Risk Closed-Form Approximations of Asymptotic Tail Behaviour 353\u003c\/p\u003e \u003cp\u003e8 Single Loss Closed-Form Approximations of Risk Measures 433\u003c\/p\u003e \u003cp\u003e9 Recursions for Distributions of LDA Models 517\u003c\/p\u003e \u003cp\u003eA Miscellaneous Definitions and List of Distributions 587\u003c\/p\u003e \u003cp\u003e\u003cb\u003eGareth W. Peters, PhD,\u003c\/b\u003e is Assistant Professor in the Department of Statistical Science, Principal Investigator in Computational Statistics and Machine Learning, and Academic Member of the UK PhD Centre of Financial Computing at University College London. He is also Adjunct Scientist in the Commonwealth Scientific and Industrial Research Organisation, Australia; Associate Member Oxford-Man Institute at the Oxford University; and Associate Member in the Systemic Risk Centre at the London School of Economics. Dr. Peters is also a visiting professor at the Institute of Statistical Mathematics, Tokyo, Japan.\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePavel V. Shevchenko, PhD,\u003c\/b\u003e is Senior Principal Research Scientist in the Division of Computational Informatics at the Commonwealth Scientific and Industrial Research Organisation, Australia, as well as Adjunct Professor at the University of New South Wales and the University of Technology, Sydney. He is also Associate Editor of The \u003ci\u003eJournal of Operational Risk\u003c\/i\u003e. He works on research and consulting projects in the area of financial risk and the development of relevant numerical methods and software, has published extensively in academic journals, consults for major financial institutions, and frequently presents at industry and academic conferences.  \u003c\/p\u003e\u003cp\u003eA cutting-edge guide for the theories, applications, and statistical methodologies essential to heavy tailed risk modeling\u003c\/p\u003e \u003cp\u003eFocusing on the quantitative aspects of heavy tailed loss processes in operational risk and relevant insurance analytics, \u003ci\u003eAdvances in Heavy Tailed Risk Modeling: A Handbook of Operational Risk\u003c\/i\u003e presents comprehensive coverage of the latest research on the theories and applications in risk measurement and modeling techniques. Featuring a unique balance of mathematical and statistical perspectives, the handbook begins by introducing the motivation for heavy tailed risk processes. \u003c\/p\u003e\u003cp\u003eA companion with \u003ci\u003eFundamental Aspects of Operational Risk and Insurance Analytics: A Handbook of Operational Risk\u003c\/i\u003e, the handbook provides a complete framework for all aspects of operational risk management and includes: \u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eClear coverage on advanced topics such as splice loss models, extreme value theory, heavy tailed closed form loss distribution approach models, flexible heavy tailed risk models, risk measures, and higher order asymptotic approximations of risk measures for capital estimation\u003c\/li\u003e \u003cli\u003eAn exploration of the characterization and estimation of risk and insurance modeling, which includes sub-exponential models, alpha-stable models, and tempered alpha stable models\u003c\/li\u003e \u003cli\u003eAn extended discussion of the core concepts of risk measurement and capital estimation as well as the details on numerical approaches to evaluation of heavy tailed loss process model capital estimates\u003c\/li\u003e \u003cli\u003eNumerous detailed examples of real-world methods and practices of operational risk modeling used by both financial and non-financial institutions\u003c\/li\u003e\n\u003c\/ul\u003e \u003cp\u003e\u003ci\u003eAdvances in Heavy Tailed Risk Modeling: A Handbook of Operational Risk\u003c\/i\u003e is an excellent reference for risk management practitioners, quantitative analysts, financial engineers, and risk managers. The handbook is also useful for graduate-level courses on heavy tailed processes, advanced risk management, and actuarial science.\u003c\/p\u003e","brand":"Wiley","offers":[{"title":"Default Title","offer_id":47988681998565,"sku":"NP9781118909539","price":179.95,"currency_code":"USD","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/1842\/7735\/files\/9781118909539.jpg?v=1761781226","url":"https:\/\/k12savings.com\/es\/products\/advances-in-heavy-tailed-risk-modeling-isbn-9781118909539","provider":"K12savings","version":"1.0","type":"link"}