Power of Deep Learning: Quantifying Language to Explain Cross-Sectional Returns

Posted: 13 Apr 2020

See all articles by Sean Cao

Sean Cao

Georgia State University - J. Mack Robinson College of Business

Yongtae Kim

Santa Clara University - Leavey School of Business

Angie Wang

The Chinese University of Hong Kong (CUHK) - School of Accountancy

Houping Xiao

Georgia State University - J. Mack Robinson College of Business

Date Written: April 3, 2020

Abstract

When quantifying qualitative information from unstructured textual data, traditional bag-of-words approaches capture only semantic features of single words/phrases. The context, the sequence of words, and the relations among words (i.e., higher-order interaction features) are ignored. We introduce deep neural networks (NNs) to encode and mimic human intelligence in processing natural language. Using the NN-based artificial intelligence, we construct a new sentiment measure that is specific to performance discussions and is adjusted for complex contextual negations. We find that this performance-specific sentiment explains cross-sectional returns and future operating performance better than umbrella sentiment proxies used in the literature.

Keywords: textual analysis, machine learning, neural networks, artificial intelligence, natural language processing, sentiment analysis, conference calls

Suggested Citation

Cao, Sean S. and Kim, Yongtae and Wang, Angie and Xiao, Houping, Power of Deep Learning: Quantifying Language to Explain Cross-Sectional Returns (April 3, 2020). Available at SSRN: https://ssrn.com/abstract=3568504

Sean S. Cao

Georgia State University - J. Mack Robinson College of Business ( email )

P.O. Box 4050
Atlanta, GA 30303-3083
United States

Yongtae Kim (Contact Author)

Santa Clara University - Leavey School of Business ( email )

500 El Camino Real
Santa Clara, CA California 95053
United States
(408) 554-4667 (Phone)
(408) 554-2331 (Fax)

Angie Wang

The Chinese University of Hong Kong (CUHK) - School of Accountancy

Shatin, N.T.
Hong Kong

Houping Xiao

Georgia State University - J. Mack Robinson College of Business ( email )

P.O. Box 4050
Atlanta, GA 30303-3083
United States

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