Artificially Intelligent Analyst Sentiment and Aggregate Market Behavior

67 Pages Posted: 6 Dec 2022

See all articles by Vidhi Chhaochharia

Vidhi Chhaochharia

University of Miami - Department of Finance

Alok Kumar

University of Miami - Miami Herbert Business School

Ville Rantala

University of Miami - Department of Finance

Alan L. Zhang

Florida International University (FIU)

Date Written: October 16, 2022

Abstract

Using machine learning methods, we develop a new measure of aggregate analyst sentiment. We first train analyst-specific neural network (NN) models that capture each analyst's common biases across firms. Using NN model outputs, we decompose the forecast errors of individual analysts into predictable and non-predictable components. Analyst sentiment captures the aggregated non-predictable errors and reflects the "abnormal optimism" of analysts. Using this aggregate sentiment measure, we find that analyst biases vary systematically along the business cycle and are correlated more strongly with household macroeconomic expectations than those of professional forecasters. Further, analysts systematically under-react to macroeconomic information, where they are over-optimistic during recessions and over-pessimistic during recovery periods. A Long-Short trading strategy based on industry-level analyst sentiment earns annualized risk-adjusted return of over 7%.

Keywords: analyst biases, earnings forecasts, aggregate analyst sentiment, return predictability, machine learning

JEL Classification: C45, D83, G14, G20

Suggested Citation

Chhaochharia, Vidhi and Kumar, Alok and Rantala, Ville and Zhang, Alan L., Artificially Intelligent Analyst Sentiment and Aggregate Market Behavior (October 16, 2022). Available at SSRN: https://ssrn.com/abstract=4249442 or http://dx.doi.org/10.2139/ssrn.4249442

Vidhi Chhaochharia

University of Miami - Department of Finance ( email )

P.O. Box 248094
Coral Gables, FL 33124-6552
United States

Alok Kumar (Contact Author)

University of Miami - Miami Herbert Business School ( email )

517B Jenkins Building
Department of Finance
Coral Gables, FL 33124-6552
United States
305-284-1882 (Phone)

HOME PAGE: http://moya.bus.miami.edu/~akumar

Ville Rantala

University of Miami - Department of Finance ( email )

P.O. Box 248094
Coral Gables, FL 33124-6552
United States

Alan L. Zhang

Florida International University (FIU) ( email )

University Park
11200 SW 8th Street
Miami, FL 33199
United States

HOME PAGE: http://www.alanlzhang.com

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