Modeling Analysts’ Recommendations via Bayesian Machine Learning

30 Pages Posted: 13 Nov 2018 Last revised: 17 Dec 2018

See all articles by David Bew

David Bew

Man AHL

Campbell R. Harvey

Duke University - Fuqua School of Business; National Bureau of Economic Research (NBER); Duke Innovation & Entrepreneurship Initiative

Anthony Ledford

Man AHL

Sam Radnor

quantPORT

Andrew Sinclair

Realindex Investments

Date Written: October 23, 2018

Abstract

We apply state-of-the-art Bayesian machine learning to test whether we can extract valuable information from analysts’ recommendations of stock performance. We use a probabilistic model for independent Bayesian classifier combination that has been successfully applied in both the physical and biological sciences. The technique is ideally suited for the particular problem where any individual analyst only focuses on a handful of the thousands of companies and it allows for dynamic inference as we track the performance of the analysts through time. The results suggest this technique holds promise in extracting information that can be deployed in active investment management.

Keywords: Variational Bayes, VB, IBCC, Machine Learning, Data Science, Analysts’ Forecasts, IBES, Analysts’ Recommendations, Forecast Fatigue, Forecast Combination, Dirichlet Distributed Prior, Galaxy Zoo

JEL Classification: G11, G14, G17, C11, C58, M41

Suggested Citation

Bew, David and Harvey, Campbell R. and Ledford, Anthony and Radnor, Sam and Sinclair, Andrew, Modeling Analysts’ Recommendations via Bayesian Machine Learning (October 23, 2018). Available at SSRN: https://ssrn.com/abstract=3269284 or http://dx.doi.org/10.2139/ssrn.3269284

David Bew

Man AHL ( email )

Riverbank House
2 Swan Lane
London, EC4R 3AD
United Kingdom

Campbell R. Harvey (Contact Author)

Duke University - Fuqua School of Business ( email )

Box 90120
Durham, NC 27708-0120
United States
919-660-7768 (Phone)
919-660-8030 (Fax)

National Bureau of Economic Research (NBER)

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

Duke Innovation & Entrepreneurship Initiative ( email )

215 Morris St., Suite 300
Durham, NC 27701
United States

Anthony Ledford

Man AHL ( email )

Riverbank House
2 Swan Lane
London, EC4R 3AD
United Kingdom

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

Sam Radnor

quantPORT ( email )

Vintners Place
68 Upper Thames Street
London, EC4V 3BJ
United Kingdom

Andrew Sinclair

Realindex Investments ( email )

Level 2, Darling Park Tower 1
201 Sussex Street
Sydney, NSW 2000
Australia

Register to save articles to
your library

Register

Paper statistics

Downloads
517
rank
51,787
Abstract Views
1,854
PlumX Metrics