000			03236cam a22002654a 4500
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003			VRT
005			20250102223943.0
008			100627s2006 njua |b 001 0 eng
020			_a0471716421 (cloth)
039		9	_a201402040205 _bVLOAD _c201007200859 _dmalmash _c201006290844 _dnoor _y201006271359 _zfbaitsaid
050	0	0	_aHG106 _b.L569 2006
100	1		_aLin, X. Sheldon. _932967
245	1	0	_aIntroductory stochastic analysis for finance and insurance / _cX. Sheldon Lin.
260			_aHoboken, N.J. : _bJohn Wiley, _cc2006.
300			_axvi, 224 p. : _bill. ; _c25 cm.
490	0		_aWiley series in probability and statistics
504			_aIncludes bibliographical references (p. 217-219) and index.
505			_aList of Figures. List of Tables. Preface. 1. Introduction. 2. Overview of Probability Theory. 3. Discrete-Time Stochastic Processes. 4. Continuous-Time Stochastic Processes. 5. Stochastic Calculus: Basic Topics. 6. Stochastic Calculus: Advanced Topics. 7. Applications in Insurance. References. Topic Index.
520			_aThis book incorporates the many tools needed for modeling and pricing in finance and insurance. 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. This book evolved from the author's experience as an instructor and has been thoroughly classroom tested. Following an introduction, the author sets forth the fundamental information and tools needed by researchers and practitioners working in the financial and insurance industries: Overview of Probability Theory; Discrete Time stochastic processes; Continuous time stochastic processes; and Stochastic calculus: basic topics. 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. Throughout the text, figures and tables are used to help simplify complex theory and processes. An extensive bibliography opens up additional avenues of research to specialized topics. Ideal for upper level undergraduate and graduate students, this text is recommended for one semest
650		0	_aFinance _xMathematical models. _96606
650		0	_aInsurance _xMathematical models. _932968
650		0	_aStochastic analysis. _919843
942			_2lcc _n0 _cBK
999			_c14392 _d14392