The implementation of sound quantitative risk models is a vital concern for all financial institutions, and this trend has accelerated in recent years with regulatory processes such as Basel II. This book provides a comprehensive treatment of the theoretical concepts and modelling techniques of quantitative risk management and equips readers--whether financial risk analysts, actuaries, regulators, or students of quantitative finance--with practical tools to solve real-world problems. The authors cover methods for market, credit, and operational risk modelling; place standard industry approaches on a more formal footing; and describe recent developments that go beyond, and address main deficiencies of, current practice.

The book's methodology draws on diverse quantitative disciplines, from mathematical finance through statistics and econometrics to actuarial mathematics. Main concepts discussed include loss distributions, risk measures, and risk aggregation and allocation principles. A main theme is the need to satisfactorily address extreme outcomes and the dependence of key risk drivers. The techniques required derive from multivariate statistical analysis, financial time series modelling, copulas, and extreme value theory. A more technical chapter addresses credit derivatives. Based on courses taught to masters students and professionals, this book is a unique and fundamental reference that is set to become a standard in the field.

实施健全的定量风险模型是所有金融机构的重要关注点，近年来随着巴塞尔协议等监管进程的推进，这一趋势已经加速。本书对定量风险管理的理论概念和建模技术进行了全面的处理，并使读者--无论是金融风险分析师、精算师、监管者，还是定量金融的学生--拥有解决现实世界问题的实用工具。作者涵盖了市场、信用和操作风险建模的方法；将标准的行业方法放在更正式的基础上；并描述了超越和解决当前实践中主要缺陷的最新发展。
本书的方法借鉴了不同的定量学科，从数学金融到统计学和计量经济学再到精算数学。讨论的主要概念包括损失分布、风险度量、以及风险聚集和分配原则。一个主要的主题是需要令人满意地解决极端结果和关键风险驱动因素的依赖性。所需的技术来自于多变量统计分析、金融时间序列建模、共线性和极值理论。有一章是关于信用衍生品的，技术性更强。基于为硕士生和专业人士教授的课程，本书是一本独特的基本参考书，将成为该领域的标准。