ISBN: 3540423338
TITLE: Weak Convergence of Financial Markets
AUTHOR: Prigent
TOC:

Contents
1. Weak Convergence of Stochastic Processes 1
1.1 Basic Properties of Stochastic Processes 2
1.1.1 Stochastic Basis, Filtration, Stopping Times 2
1.1.2 Stochastic Processes 3
1.1.3 Martingales 7
1.1.4 Semimartingales and Stochastic Integrals 14
1.1.5 Markov Processes and Stochastic Differential Equations 40
1.1.6 The Discrete Time Case 58
1.2 Weak Convergence 64
1.2.1 The Skorokhod Topology 64
1.2.2 Continuity for the Skorokhod Topology 67
1.2.3 Definition of Weak Convergence 69
1.2.4 Criteria for Tightness in D^k 72
1.2.5 The Meyer-Zheng Topology 74
1.3 Weak Convergence to a Semimartingale 75
1.3.1 Functional Convergence and Characteristics 75
1.3.2 Limits of Martingales 87
1.3.3 Limit Theorems for Markov Processes 88
1.3.4 Convergence of Triangular Arrays 92
1.4 Weak Convergence of Stochastic Integrals 100
1.4.1 Introduction 100
1.4.2 The Uniform Tightness Condition U.T 101
1.4.3 Functional Limit Theorems for Sequences of Stochastic Integrals and Stochastic Differential Equations 104
1.5 Limit Theorems, Density Processes and Contiguity 108
1.5.1 Hellinger Integral and Hellinger Process 108
1.5.2 Contiguity and Entire Separation 115
1.5.3 Convergence of the Density Processes 121
1.5.4 The Statistical Invariance Principle 125
2. Weak Convergence of Financial Markets 129
2.1 Convergence of Optimal Consumption-Portfolio Strategies 130
2.1.1 Weak Convergence of Controlled Processes 131
2.1.2 The Martingale Approach 161
2.2 Convergence of Options Prices 185
2.2.1 Problems and Examples 185
2.2.2 Contiguity Properties 194
2.2.3 The Case of Incomplete Markets 198
2.2.4 Transaction Costs 218
2.2.5 American Options 230
2.3 Convergence of Hedging Strategies 240
2.3.1 Binomial Case and Clark-Haussman Formula 243
2.3.2 Weak Convergence of Integrands 251
2.3.3 The Local Risk-Minimizing Strategy 256
3. The Basic Models of Approximations 267
3.1 General Remarks 267
3.1.1 Some numerical methods for forward and backward stochastic differential equations 268
3.1.2 Some numerical methods for computations of Greeks 272
3.2 Lattice 274
3.2.1 Simple Binomial Processes as Diffusion Approximations 274
3.2.2 Correction Terms for Path-Dependent Options 287
3.2.3 Adjustment Prior to Maturity and Smoothing of the Payoff Functions 295
3.2.4 Fast Accurate Binomial Pricing 301
3.2.5 Approximating a Diffusion by a Trinomial Tree 305
3.3 Alternative Approximations 309
3.3.1 ARCH Approximations 309
3.3.2 Lvy Processes 321
3.3.3 Convergence for Random Time Intervals 345
3.3.4 Deterministic or Random Discretizations of Continuous-Time Processes 359
3.4 Approximations of Term Structure Models 371
3.4.1 Bonds and Interest Rate Derivatives 371
3.4.2 Basic Interest Models and their Approximations 377
3.4.3 Two-factors Model 387
3.4.4 Market Models : Discretization of Lognormal Forward
Libor and Swap Rate Models 388
3.4.5 Discretization of Deflated Bond Prices 388
3.4.6 Pricing Interest Rate or Equity Derivatives and Discretization 395
Index 419
END
