Machine Learning in Asset Pricing

Machine Learning in Asset Pricing

Author: Stefan Nagel

Publisher: Princeton University Press

ISBN: 9780691218700

Category: Business & Economics

Page: 160

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A groundbreaking, authoritative introduction to how machine learning 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 (ML) 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.
Machine Learning in Asset Pricing
Language: en
Pages: 160
Authors: Stefan Nagel
Categories: Business & Economics
Type: BOOK - Published: 2021-05-11 - Publisher: Princeton University Press

A groundbreaking, authoritative introduction to how machine learning 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 (ML) are
Machine Learning and Asset Pricing Models
Language: en
Pages: 151
Authors: Rafael Amaral Porsani
Categories: Business & Economics
Type: BOOK - Published: 2018 - Publisher:

Even though statistical-learning techniques have become increasingly popular in many scientific areas, few studies in the field of cross-sectional asset pricing have incorporated these in their essence. In the first chapter of this dissertation, we suggest a framework for testing the empirical performance of linear asset-pricing factor models, and for
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Language: en
Pages: 385
Authors: Felix Chan, László Mátyás
Categories: Business & Economics
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This book helps and promotes the use of machine learning tools and techniques in econometrics and explains how machine learning can enhance and expand the econometrics toolbox in theory and in practice. Throughout the volume, the authors raise and answer six questions: 1) What are the similarities between existing econometric
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Language: en
Pages:
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Categories: Business & Economics
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Books about Applications of Textual Analysis and Machine Learning in Asset Pricing
Handbook Of Financial Econometrics, Mathematics, Statistics, And Machine Learning (In 4 Volumes)
Language: en
Pages: 5056
Authors: Cheng-few Lee, John C Lee
Categories: Business & Economics
Type: BOOK - Published: 2020-07-30 - Publisher: World Scientific

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