Granularity Theory with Applications to Finance and Insurance

Granularity Theory with Applications to Finance and Insurance

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Product Details

ISBN-13: 9781107662889
Publisher: Cambridge University Press
Publication date: 10/06/2014
Series: Themes in Modern Econometrics
Pages: 202
Product dimensions: 6.02(w) x 8.98(h) x 0.43(d)

About the Author

Patrick Gagliardini is full Professor of Econometrics at Universit... 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.

Table 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.

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