Key Features
• 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
Description
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.
Readership
Academics, researchers, and practitioners in quantitative finance, financial risk management; economics, and other areas of math, science and engineering
Mathematical Modelling and Numerical Methods in Finance, 1st Edition
Table of Contents
Part I: Mathematical Models
1. On Model Risk
2. Robust Optimization Problems in Finance
3. A Survey of Stochastic Portfolio Theory
4. Stochastic Volatility Modeling and Use of Perturbation Methods
5. Downside and Drawdown Risk Characteristics of Optimal Continuous Time
6. Portfolio of Choice and Valuation in Incomplete Markets
7. Integration by Parts Formulas for Levy Processes Application in Finance.
Part II: Computational Methods
8. On the Discrete Time Capital Asset Pricing Model
9. Quantization Methods and Applications to Numerical Problems in Finance
10. Recombining Binomial Tree Approximations for Diffusions
11. Computational Methods for Calibration
12. Numerical Methods in Finance: Monte Carlo Methods
Part III: Applications
13. Real Options
14. Anticipative Stochastic Control for Levy Processes with Application to Insider Trading
15. Functional Quantization and Applications to the Pricing of Path-Dependent Derivatives.
16. Stochastic Clock in Financial Markets
17. Exotic Options
18. Filtering a Regime Switching VG Price Process
