Всичко за тази електронна книга
Features of the significantly enlarged and revised second edition:
- Offers insight into new methods and the applicability of the stochastic technology
- Provides the tools, instruments and (online) algorithms for recent techniques in quantitative finance and modern treatments in insurance calculations
- Covers topics such as
- expected shortfall for heavy tailed and mixture distributions*
- pricing of variance swaps*
- volatility smile calibration in FX markets
- pricing of catastrophe bonds and temperature derivatives*
- building loss models and ruin probability approximation
- insurance pricing with GLM*
- equity linked retirement plans*(new topics in the second edition marked with*) - Presents extensive examples
Оценки и отзиви
За автора
Pavel Cížek is professor of econometrics and statistics at Tilburg University. He teaches various courses covering time-series, simulation-based, and semiparametric estimation methods. His research interests are methods of semiparametric and robust statistics and econometrics with applications primarily in microeconomics and quantitative finance.
Wolfgang Karl Härdle is professor of statistics at the Humboldt-Universität zu Berlin and director of C.A.S.E. – the Centre for Applied Statistics and Economics. He teaches quantitative finance and semiparametric statistical methods. His research focuses on dynamic factor models, multivariate statistics in finance and computational statistics. He is an elected ISI member and advisor to the Guanghua School of Management, Peking University.
Rafał Weron is professor of economics at Wrocław University of Technology (WUT). His research focuses on developing risk management and forecasting tools for the energy industry and computational statistics as applied to finance and insurance. He is periodically engaged as a consultant to energy (Tauron Polska Energia, Vattenfall) and financial (BRE Bank, Bank Millennium) companies. He teaches graduate level courses on energy and financial markets at NTNU (Trondheim) and WUT.
