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《隨機積分和微分方程(第2版)》是真正用函數解析法來錶達半鞅和隨機積分,這使得新的方法並沒有得到很好的應用。盡管這《隨機積分和微分方程(第2版)》不再適閤稱其為一種新的方法。然而新版本的及時齣現,在很大程度上完善瞭原版本。
內容簡介
本書是第2版(全英文版)。第1版本的《隨機積分和微分方程》問世13年以來,有關這方麵的書不斷湧現,特彆是在數學金融方麵具有很強應用性的書更是發展迅速。然而沒有一本書是真正用函數解析法來錶達半鞅和隨機積分,這使得新的方法並沒有得到很好的應用。盡管這本書不再適閤稱其為一種新的方法。然而新版本的及時齣現,在很大程度上完善瞭原版本。
這版較第1版做瞭一些調整,並且增加瞭不少新的內容。第3章增加瞭停時的分類和Bichteler-Dellacherie定理;第4張增加瞭鞅錶示的Jacod-Yor定理、鞅錶示的例子以及Sigma鞅;增加瞭新的一章第6章。並且每章的後麵增加瞭不少練習,這些可以作為學習本教材的很好的補充。
目錄
Introduction
1 Preliminaries
1 Basic Definitions and Notation
2 Martingales
3 The Poisson Process and Brownian Motion
4 Levv Processes
5 Why the Usual Hypotheses?
6 Local Martingales
7 Stieltjes Integration and Change of Variables
8 Naive Stochastic Integration is Impossible
Bibliographic Notes
Exercises for Chapter 1
2 Semimartingales and Stochastic Integrals
1 Introduction to Semimartingales
2 Stability Properties of Semimartingales
3 Elementary Examples of Semimartingales
4 Stochastic Integrals
5 Properties of Stochastic Integrals
6 The Quadratic Variation of a Semimartingale
7 Itos Formula (Change of Variables)
8 Applications of Itos Formula
Bibliographic Notes
Exercises for Chapter 2
3 Semimartingales and Decomposable Processes
1 Introduction
2 The Classification of Stopping Times
3 The Doob-Meyer Decompositions
4 Quasimartingales
5 Compensators
6 The Fundamental Theorem of Local Martingales
7 Classical Semimartingales
8 Girsanovs Theorem
9 The Bichteler-Dellacherie Theorem
Bibliographic Notes
Exercises for Chapter 3
4 General Stochastic Integration and Local Times
1 Introduction
2 Stochastic Integration for Predictable Integrands
3 Martingale Representation
4 Martingale Duality and the Jacod-Yor Theorem on
Martingale Representation
5 Examples of Martingale Representation
6 Stochastic Integration Depending on a Parameter
7 Local Times
8 Az6mas Martingale
9 Sigma Martingales
Bibliographic Notes
Exercises for Chapter 4
5 Stochastic Differential Equations
1 Introduction
2 The H___p Norms for Semimartingales
3 Existence and Uniqueness of Solutions
4 Stability of Stochastic Differential Equations
5 Fisk-Stratonovich Integrals and Differential Equations
6 The Markov Nature of Solutions
7 Flows of Stochastic Differential Equations: Continuity and
Differentiability
8 Flows as Diffeomorphisms: The Continuous Case
9 General Stochastic Exponentials and Linear Equations
10 Flows as Diffeomorphisms: The General Case
11 Eclectic Useful Results on Stochastic Differential Equations
Bibliographic Notes
Exercises for Chapter 5
6 Expansion of Filtrations
1 Introduction
2 Initial Expansions
3 Progressive Expansions
4 Time Reversal
Bibliographic Notes
Exercises for Chapter 6
References
Subject Index
前言/序言
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