The recent financial crisis has heightened the need for appropriate methodologies for managing and monitoring complex risks in financial markets. The measurement, management, and regulation of risks in portfolios composed of credits, credit derivatives, or life insurance contracts is difficult because of the nonlinearities of risk models, dependencies between individual risks, and the several thousands of contracts in large portfolios. The granularity principle was introduced in the Basel regulations for credit risk to solve these difficulties in computing capital reserves. In this book, authors Patrick Gagliardini and Christian Gouriéroux provide the first comprehensive overview of the granularity theory and illustrate its usefulness for a variety of problems related to risk analysis, statistical estimation, and derivative pricing in finance and insurance. They show how the granularity principle leads to analytical formulas for risk analysis that are simple to implement and accurate even when the portfolio size is large.
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Patrick Gagliardini is full Professor of Econometrics at Università della Svizzera italiana, Lugano, Switzerland. He graduated from the ETH in Zürich with a degree in physics in 1998 and received his PhD in economics from the University of Lugano in 2003. He has also held a position of assistant professor at the University of St Gallen. His research interests lie in econometrics and financial econometrics and focus especially on large-scale factor models, credit risk, asset pricing, and semi- and non-parametric methods. He is coauthor of research articles published in Econometrica, the Review of Financial Studies, the Journal of Econometrics, and Econometric Theory.
Christian Gouriéroux is director of the Laboratory of Finance and Insurance at the Center for Research in Economics and Statistics (CREST) in Paris and professor at the University of Toronto. He has published numerous papers on both theoretical and applied econometrics, with a special emphasis on credit, finance, insurance, and systemic risk. He is the coauthor of Statistics and Econometric Models and Time Series and Dynamic Models, both published by Cambridge University Press, and of Financial Econometrics and Econometrics of Individual Risks. He has also received the Tjalling C. Koopmans Econometric Theory Prize. Gouriéroux was scientific adviser for credit scoring and implementation of Basel regulation at BNP Paribas. He is a member of the scientific committees of the French Financial Market Authority and the Prudential Supervision and Resolution Authority.
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Paperback. Etat : new. Paperback. The recent financial crisis has heightened the need for appropriate methodologies for managing and monitoring complex risks in financial markets. The measurement, management, and regulation of risks in portfolios composed of credits, credit derivatives, or life insurance contracts is difficult because of the nonlinearities of risk models, dependencies between individual risks, and the several thousands of contracts in large portfolios. The granularity principle was introduced in the Basel regulations for credit risk to solve these difficulties in computing capital reserves. In this book, authors Patrick Gagliardini and Christian Gourieroux provide the first comprehensive overview of the granularity theory and illustrate its usefulness for a variety of problems related to risk analysis, statistical estimation, and derivative pricing in finance and insurance. They show how the granularity principle leads to analytical formulas for risk analysis that are simple to implement and accurate even when the portfolio size is large. This book provides the first comprehensive overview of the granularity theory applied to risk analysis in finance and insurance. The granularity principle leads to analytical formulas for risk analysis that are simple to implement and accurate even when the portfolio size is large. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. N° de réf. du vendeur 9781107662889
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