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Mathematical finance is a prolific scientific domain in which there exists a particular characteristic of developing both advanced theories and practical techniques simultaneously. Mathematical Modelling and Numerical Methods in Finance addresses the three most important aspects in the field: mathematical models, computational methods, and applications, and provides a solid overview of major new ideas and results in the three domains. - Coverage of all aspects of quantitative finance including models, computational methods and applications
- Provides an overview of new ideas and results
- Contributors are leaders of the field
Part I: Mathematical Models1. On Model Risk2. Robust Optimization Problems in Finance3. A Survey of Stochastic Portfolio Theory4. Stochastic Volatility Modeling and Use of Perturbation Methods5. Downside and Drawdown Risk Characteristics of Optimal Continuous Time6. Portfolio of Choice and Valuation in Incomplete Markets7. Integration by Parts Formulas for Levy Processes Application in Finance Part II: Computational Methods8. On the Discrete Time Capital Asset Pricing Model9. Quantization Methods and Applications to Numerical Problems in Finance10. Recombining Binomial Tree Approximations for Diffusions11. Computational Methods for Calibration12. Numerical Methods in Finance: Monte Carlo Methods Part III: Applications13. Real Options14. Anticipative Stochastic Control for Levy Processes with Application to Insider Trading15. Functional Quantization and Applications to the Pricing of Path-Dependent Derivatives.16. Stochastic Clock in Financial Markets17. Exotic Options18. Filtering a Regime Switching VG Price Process