---

＜電子ブック＞
Monte Carlo Methods in Financial Engineering / by Paul Glasserman
(Stochastic Modelling and Applied Probability. ISSN:2197439X ; 53)

版	1st ed. 2003.
出版者	(New York, NY : Springer New York : Imprint: Springer)
出版年	2003
本文言語	英語
大きさ	XIII, 596 p. 4 illus : online resource
著者標目	*Glasserman, Paul author SpringerLink (Online service)
件　名	LCSH:Mathematics LCSH:Finance, Public LCSH:Probabilities LCSH:Social sciences -- Mathematics  全ての件名で検索 LCSH:Statistics  LCSH:Econometrics FREE:Applications of Mathematics FREE:Public Economics FREE:Probability Theory FREE:Mathematics in Business, Economics and Finance FREE:Statistical Theory and Methods FREE:Quantitative Economics
一般注記	1 Foundations -- 2 Generating Random Numbers and Random Variables -- 3 Generating Sample Paths -- 4 Variance Reduction Techniques -- 5 Quasi-Monte Carlo -- 6 Discretization Methods -- 7 Estimating Sensitivities -- 8 Pricing American Options -- 9 Applications in Risk Management -- A Appendix: Convergence and Confidence Intervals -- A.1 Convergence Concepts -- A.2 Central Limit Theorem and Confidence Intervals -- B Appendix: Results from Stochastic Calculus -- B.1 Itô’s Formula -- B.2 Stochastic Differential Equations -- B.3 Martingales -- B.4 Change of Measure -- C Appendix: The Term Structure of Interest Rates -- C.1 Term Structure Terminology -- C.2 Interest Rate Derivatives -- References Monte Carlo simulation has become an essential tool in the pricing of derivative securities and in risk management. These applications have, in turn, stimulated research into new Monte Carlo methods and renewed interest in some older techniques. This book develops the use of Monte Carlo methods in finance and it also uses simulation as a vehicle for presenting models and ideas from financial engineering. It divides roughly into three parts. The first part develops the fundamentals of Monte Carlo methods, the foundations of derivatives pricing, and the implementation of several of the most important models used in financial engineering. The next part describes techniques for improving simulation accuracy and efficiency. The final third of the book addresses special topics: estimating price sensitivities, valuing American options, and measuring market risk and credit risk in financial portfolios. The most important prerequisite is familiarity with the mathematical tools used to specify and analyze continuous-time models in finance, in particular the key ideas of stochastic calculus. Prior exposure to the basic principles of option pricing is useful but not essential. The book is aimed at graduate students in financial engineering, researchers in Monte Carlo simulation, and practitioners implementing models in industry HTTP:URL=https://doi.org/10.1007/978-0-387-21617-1

 類似資料