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This book provides the first comprehensive overview of the granularity theory and its usefulness for risk analysis, statistical estimation, and derivative pricing.
List of contents
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.
About the author
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.
Summary
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.
