This authoritative book draws on the latest research to explore the interplay of high-dimensional statistics with optimization. Through an accessible analysis of fundamental problems of hypothesis testing and signal recovery, Anatoli Juditsky and Arkadi Nemirovski show how convex optimization theory
Multi-Period Trading via Convex Optimization
β Scribed by Stephen Boyd
- Publisher
- NOW Publishers
- Year
- 2017
- Tongue
- English
- Leaves
- 77
- Category
- Library
No coin nor oath required. For personal study only.
β¦ Table of Contents
1 Introduction......Page 5
2.1 Portfolio asset and cash holdings......Page 9
2.2 Trades......Page 11
2.3 Transaction cost......Page 12
2.4 Holding cost......Page 14
2.5 Self-financing condition......Page 15
2.6 Investment......Page 17
2.7 Aspects not modeled......Page 18
2.8 Simulation......Page 20
3.1 Absolute metrics......Page 22
3.2 Metrics relative to a benchmark......Page 23
4 Single-Period Optimization......Page 25
4.1 Risk-return optimization......Page 26
4.2 Risk measures......Page 29
4.3 Forecast error risk......Page 33
4.4 Holding constraints......Page 35
4.5 Trading constraints......Page 38
4.6 Soft constraints......Page 39
4.7 Convexity......Page 40
4.8 Using single-period optimization......Page 43
5.1 Motivation......Page 47
5.2 Multi-period optimization......Page 49
5.3 Computation......Page 53
5.5 Multi-scale optimization......Page 54
6 Implementation......Page 56
6.1 Components......Page 57
7.1 Data for simulation......Page 59
7.2 Portfolio simulation......Page 60
7.3 Single-period optimization......Page 61
7.4 Multi-period optimization......Page 68
7.5 Simulation time......Page 71
References......Page 73
π SIMILAR VOLUMES
This authoritative book draws on the latest research to explore the interplay of high-dimensional statistics with optimization. Through an accessible analysis of fundamental problems of hypothesis testing and signal recovery, Anatoli Juditsky and Arkadi Nemirovski show how convex optimization theory
<p>This authoritative book draws on the latest research to explore the interplay of high-dimensional statistics with optimization. Through an accessible analysis of fundamental problems of hypothesis testing and signal recovery, Anatoli Juditsky and Arkadi Nemirovski show how convex optimization the
Recent results on non-convex multi-objective optimization problems and methods are presented in this book, with particular attention to expensive black-box objective functions. Multi-objective optimization methods facilitate designers, engineers, and researchers to make decisions on appropriate trad
<p>Recent results on non-convex multi-objective optimization problems and methods are presented in this book, with particular attention to expensive black-box objective functions. Multi-objective optimization methods facilitate designers, engineers, and researchers to make decisions on appropriate t