[下载]Peter Jaeckel: Monte Carlo Methods in Finance

Monte Carl Methodologies and Applications for Pricing and Risk Management

by Bruno Dupire

Price: £109.00 Product code: 9487, ISBN: 189933291X, 340 pages, paperback, published by Risk Books, 1st edition, 1998 Description of Monte Carl Methodologies and Applications for Pricing and Risk Management A core reference of classic research and new writing on the methodologies and applications of Monte Carlo simulation - An edited collection of new writing and reference papers structured to provide a unique routemap - Selected and introduced by leading practitioner and theoretician, Bruno Dupire - Covers pricing, Monte Carlo methodologies, yield curves models, fixed income and generalities Contents of Monte Carl Methodologies and Applications for Pricing and Risk Management Authors Introduction Part I: Generalities 1. Options: A Monte Carlo Approach 2. Monte Carlo Methods for Security Pricing 3. Monte Carlo Toolkit Part II: Pricing 4. Dimension Reduction and Other Ways of Speeding Monte Carlo Simulation 5. Average Intelligence 6. Beyond Average Intelligence 7. Strata Gems 8. Recovering Identity 9. Greeks in Monte Carlo 10. Quicker on the Curves 11. Exact Exotics 12. Monte Carlo Simulation of Options on Joint Minima and Maxima 13. Model calibration in the Monte Carlo Framework Part III: American Style 14. Valuing American Options in a Path-Simulation Model 15. Numerical valuation of High-Dimensional Multivariate American Securities 16. Monte Carlo Methods for Pricing High-Dimensional American Options: an Overview Pat IV: Fixed Income 17. Pricing Interest Rate Exotics by Monte Carlo Simulation 18. Efficient and Flexible Bond Option Valuation in the Heath, Jarrow and Morton Framework 19. Term Structure Dynamics and Mortgage Valuation Part V: VAR 20. Calculating Value-at-Risk with Monte Carlo Simulation 21. Beyond VAR and Stress Testing 22. Using Non-Normal Monte Carlo Simulation to Compute Value-at-Risk 23. Scrambled Nets for Value-at-Risk Valuation Part VI: Deterministic Methods 24. Quasi-Monte Carlo Methods in Numerical Finance 25. New Methodologies for Valuing Derivatives 26. Valuation of Mortgage-backed Securities Using Brownian Bridges to Reduce Effective Dimension 27. Smoothness and Dimensions Reduction in Quasi-Monte Carlo Methods 28. Beating Monte Carlo 29. Monte Carlo Motoring 30. Laudable Lattices 31. Inelegant Efficiency Glossary of Monte Carlo Terms

[此贴子已经被作者于2005-9-18 1:01:54编辑过]

怎么后面的只见介绍不见书啊？

Simulation and the Monte Carlo Method

This is a classic introduction to the Monte Carlo method. It starts with basic concepts. It illustrates techniques for generating pseudorandom numbers and pseudorandom variates. The discussions of variance reduction techniques are clear and very accessible. The book closes with discussions of some more specialized topics.

This book is perfect for a quantitatively oriented professional who has some intuitive familiarity with the Monte Carlo method but wants to achieve more formal understanding so they can implement variance reduction techniques in their Monte Carlo analyses.

Contents

1. Systems, Models, Simulation and the Monte Carlo Method 2. Random Number Generation 3. Random Variate Generation 4. Monte Carlo Integration and Variance Reduction Techniques 5. Linear Equations and Markov Chains 6. Regenerative Method for Simulation Analysis 7. Monte Carlo Optimization

[此贴子已经被作者于2005-9-18 1:00:35编辑过]

[Introduction]

Monte Carlo Concepts, Algorithms and Applications

Author:

George S. Fishman

This is the authoritative text on the Monte Carlo method. Fishman covers the standard topics of integral estimation, variance reduction and random number generation. He also includes extensive material on simulating stochastic processes. The treatment is very formal and meticulously detailed. Numerous algorithms are presented, and references are cited extensively. The book is not an easy read. You should read Rubinstein (1981) before attempting Fishman. The book is unsurpassed as a reference.

Contents

Introduction Estimating Volume and Count Generating Samples Increasing Efficiency Random Tours Designing and Analyzing Sample Paths Generating Pseudorandom Numbers

[Introduction]Random Number Generation and Quasi-Monte Carlo Methods

This is an essential text on quasi-random numbers. Neiderreiter is a leading researcher in the field, and much of the work presented is his own. He covers discrepancy measures, low-discrepancy point sets, nets and (t,s)-sequences, lattices, random number generation, and random vector generation. The material on random number and vector generation is outdated, but the rest of the book represents the foundations of today's quasi-Monte Carlo methods. This is a difficult book to read. Neiderreiter makes extensive use of finite field theory and other branches of mathematics that are not common fare, even for financial engineers. If you are going to work with quasi-random numbers, you should read this book.

Contents

1. Monte Carlo Methods and Quasi-Monte Carlo Methods Monte Carlo methods Quasi-Monte Carlo methods 2. Quasi-Monte Carlo Methods for Numerical Integration Discrepancy Error bounds 3. Low-Discrepancy Point Sets and Sequences Classical constructions General discrepancy bounds 4. Nets and (t,s)-Sequences Definitions and discrepancy bounds Combinatorial connections General construction principles A special construction of nets A special construction of (t,s)-sequences 5. Lattice Rules for Numerical Integration The method of good lattice points Existence theorems for good lattice points General lattice rules and their classification Existence theorems for efficient lattice rules 6. Quasi-Monte Carlo Methods for Optimization General theory of quasirandom search methods Low-dispersion point sets and sequences 7. Random Numbers and Pseudorandom Numbers Random number generation Pseudorandom numbers Classical generators 8. Nonlinear Congruential Pseudorandom Numbers The general nonlinear congruential method The inversive congruential method 9. Shift-Register Pseudorandom Numbers The digital multistep method The generalized feedback shift-register (GFSR) method 10. Pseudorandom Vector Generation The matrix method Nonlinear methods

还值，顶！

哥哥,偶没钱,能否赠送一本,我会努力赚钱,等我有钱了还你

后面几本书也请传上来

hehe, 不错，不错，坛子里每天都有新惊喜啊

第一本书和他帖子的介绍不符

原书304页

可是他提供的才235页

希望l楼主解释一下

谢谢