Part I Introduction 1
1 Overview of Optimization Models 3
2 Linear Programming: Theory and Algorithms11
3 Linear Programming Models:Asset–Liability Management 35
4 Linear Programming Models: Arbitrage andAsset Pricing 53
Part II Single-Period Models 69
5 Quadratic Programming: Theory andAlgorithms 71
6 Quadratic Programming Models:Mean–Variance Optimization 90
7 Sensitivity of Mean–Variance Models toInput Estimation 124
8 Mixed Integer Programming: Theory andAlgorithms 140
9Mixed Integer Programming Models:Portfolios with Combinatorial Constraints 161
10 Stochastic Programming: Theory andAlgorithms 173
11 Stochastic Programming Models: RiskMeasures 181
Part III Multi-Period Models 195
12 Multi-Period Models: Simple Examples 197
13 Dynamic Programming: Theory andAlgorithms 212
14 Dynamic Programming Models: Multi-PeriodPortfolio Optimization 225
15 Dynamic Programming Models: the BinomialPricing Model 238
16 Multi-Stage Stochastic Programming 248
17 Stochastic Programming Models:Asset–Liability Management 262
Part IV Other Optimization Techniques 275
18 Conic Programming: Theory and Algorithms277
19 Robust Optimization 289 19.1 UncertaintySets 289
20 Nonlinear Programming: Theory andAlgorithms 305
Appendices 321
References 327
Index 334