Book contents
- Frontmatter
- Contents
- Contributors
- Preface
- Interacting With Investors And Asset Owners
- Towards Better Risk Intermediation
- Connections With The Real Economy
- Part VI Nowcasting with Alternative Data
- Part VII Biases and Model Risks of Data-Driven Learning
- 30 Introduction to Part VII. Towards the Ideal Mix between Data and Models
- 31 Generative Pricing Model Complexity: The Case for Volatility-Managed Portfolios
- 32 Bayesian Deep Fundamental Factor Models
- 33 Black-Box Model Risk in Finance
- Index
32 - Bayesian Deep Fundamental Factor Models
from Part VII - Biases and Model Risks of Data-Driven Learning
Published online by Cambridge University Press: 12 May 2023
- Frontmatter
- Contents
- Contributors
- Preface
- Interacting With Investors And Asset Owners
- Towards Better Risk Intermediation
- Connections With The Real Economy
- Part VI Nowcasting with Alternative Data
- Part VII Biases and Model Risks of Data-Driven Learning
- 30 Introduction to Part VII. Towards the Ideal Mix between Data and Models
- 31 Generative Pricing Model Complexity: The Case for Volatility-Managed Portfolios
- 32 Bayesian Deep Fundamental Factor Models
- 33 Black-Box Model Risk in Finance
- Index
Summary
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- Type
- Chapter
- Information
- Machine Learning and Data Sciences for Financial MarketsA Guide to Contemporary Practices, pp. 661 - 686Publisher: Cambridge University PressPrint publication year: 2023