Book contents
- Frontmatter
- Contents
- Contributors
- Preface
- Interacting With Investors And Asset Owners
- Towards Better Risk Intermediation
- Part III High Frequency Finance
- Part IV Advanced Optimization Techniques
- Part V New Frontiers for Stochastic Control in Finance
- 18 Introduction to Part V. Machine Learning and Applied Mathematics: a Game of Hide-and-Seek?
- 19 The Curse of Optimality, and How to Break it?
- 20 Deep Learning for Mean Field Games and Mean Field Control with Applications to Finance
- 21 Reinforcement Learning for Mean Field Games, with Applications to Economics
- 22 NeuralNetworks-Based Algorithms for Stochastic Control and PDEs in Finance
- 23 Generative Adversarial Networks: Some Analytical Perspectives
- Connections With The Real Economy
- Index
18 - Introduction to Part V. Machine Learning and Applied Mathematics: a Game of Hide-and-Seek?
from Part V - New Frontiers for Stochastic Control in Finance
Published online by Cambridge University Press: 12 May 2023
- Frontmatter
- Contents
- Contributors
- Preface
- Interacting With Investors And Asset Owners
- Towards Better Risk Intermediation
- Part III High Frequency Finance
- Part IV Advanced Optimization Techniques
- Part V New Frontiers for Stochastic Control in Finance
- 18 Introduction to Part V. Machine Learning and Applied Mathematics: a Game of Hide-and-Seek?
- 19 The Curse of Optimality, and How to Break it?
- 20 Deep Learning for Mean Field Games and Mean Field Control with Applications to Finance
- 21 Reinforcement Learning for Mean Field Games, with Applications to Economics
- 22 NeuralNetworks-Based Algorithms for Stochastic Control and PDEs in Finance
- 23 Generative Adversarial Networks: Some Analytical Perspectives
- Connections With The Real Economy
- Index
Summary
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- Type
- Chapter
- Information
- Machine Learning and Data Sciences for Financial MarketsA Guide to Contemporary Practices, pp. 343 - 353Publisher: Cambridge University PressPrint publication year: 2023