Bibliografische Daten
ISBN/EAN: 9783319358611
Sprache: Englisch
Umfang: xi, 438 S., 84 s/w Illustr., 438 p. 84 illus.
Einband: kartoniertes Buch
Beschreibung
Provides a bridge between methodological advances and applications in risk managementFocuses on modern techniques such as dependence modeling, LIBOR modeling and counterparty credit riskFeatures contributions from well-known experts from both academia and practiceIncludes supplementary material: sn.pub/extras
Autorenportrait
Kathrin Glau is Junior professor for Mathematical Finance at the Technische Universität München. Her research faces the complex demands on numerical tools and modeling in today's market reality. Her approach merges recent advances from numerical analysis and financial modeling. Thereby pricing methods in advanced models with a thorough error analysis are developed. Her speciality are Galerkin methods for partial integro differential equations for (pure) jump Levy driven models.Matthias Scherer is Professor for Mathematical Finance at the Technische Universität München. His research interests comprise various topics in Financial Mathematics, Actuarial Science, and Probability Theory. Concerning applications in risk management, he has published research articles on portfolio-credit risk, dependence modeling, and model risk. He is an active member of the management boards of the DGVFM and the KPMG Center of Excellence in Risk Management. He is co-author of the book "Simulating Copulas: Stochastic Models, Sampling Algorithms, and Applications" and provides executive seminars for different financial institutions.Rudi Zagst is Professor for Mathematical Finance, Director of the Center of Mathematics and member of the management board of the KPMG Center of Excellence in Risk Management at Technische Universität München. He is also President of risklab GmbH, a German-based consulting company offering advanced asset management solutions and is a professional trainer to a number of leading institutions. His current research interests are in financial engineering, risk and asset management.