Patrick Gagliardini

Granularity Theory with Applications to Finance and Insurance (eBook, ePUB)

• Format: ePub

Produktbeschreibung

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.

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Produktdetails

• Verlag: Cambridge University Press
• Erscheinungstermin: 6. Oktober 2014
• Englisch
• ISBN-13: 9781316054765
• Artikelnr.: 49267993

Autorenporträt

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.

Inhaltsangabe

1. The standard asymptotic theorems and their limitations
2. Gaussian static factor
3. Static qualitative factor model
4. Nonlinear dynamic panel-data model
5. Prediction and basket derivative pricing
6. Granularity for risk measures.