 Название: Machine Learning in Asset Pricing
Автор: Stefan Nagel
Издательство: Princeton University Press
Год: 2021
Страниц: 157
Язык: английский
Формат: pdf (true)
Размер: 10.1 MB
A groundbreaking, authoritative introduction to how Machine Learning (ML) can be applied to asset pricing.
Investors in financial markets are faced with an abundance of potentially value-relevant information from a wide variety of different sources. In such data-rich, high-dimensional environments, techniques from the rapidly advancing field of Machine Learning are well-suited for solving prediction problems. Accordingly, ML methods are quickly becoming part of the toolkit in asset pricing research and quantitative investing. In this book, Stefan Nagel examines the promises and challenges of ML applications in asset pricing.
Asset pricing problems are substantially different from the settings for which ML tools were developed originally. To realize the potential of ML methods, they must be adapted for the specific conditions in asset pricing applications. Economic considerations, such as portfolio optimization, absence of near arbitrage, and investor learning can guide the selection and modification of ML tools. Beginning with a brief survey of basic supervised ML methods, Nagel then discusses the application of these techniques in empirical research in asset pricing and shows how they promise to advance the theoretical modeling of financial markets.
Machine Learning in Asset Pricing presents the exciting possibilities of using cutting-edge methods in research on financial asset valuation.
Contents:
Preface ix
Chapter 1
Introduction 1
Chapter 2
Supervised Learning 11
Chapter 3
Supervised Learning in Asset Pricing 31
Chapter 4
ML in Cross-Sectional Asset Pricing 64
Chapter 5
ML as Model of Investor Belief Formation 93
Chapter 6
A Research Agenda 119
Bibliography 135
Index 141
Скачать Machine Learning in Asset Pricing
|
Навигация
Вход на сайт
Реклама
Machine Learning in Asset Pricing 
