Summary |
Introductory stochastic analysis for finance and insurance introduces readers to the topics needed to master and use basic stochastic analysis techniques for mathematical finance. The author presents the theories of stochastic processes and stochastic calculus and provides the necessary tools for modeling and pricing in finance and insurance. Practical in focus, the book’s emphasis is on application, intuition, and computation, rather than theory.
Consequently, the text is of interest to graduate students, researchers, and practitioners interested in these areas. While the text is self-contained, an introductory course in probability theory is beneficial to prospective readers.
The final two chapters, stochastic calculus: advanced topics and applications in insurance, are devoted to more advanced topics. Readers learn the Feynman-kac formula, the girsanov’s theorem, and complex barrier hitting times distributions. Finally, readers discover how stochastic analysis and principles are applied in practice through two insurance examples: valuation of equity-linked annuities under a stochastic interest rate environment and calculation of reserves for universal life insurance.
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