Profitability of Portfolio Strategies Based on Analyst Consensus EPS Forecasts

51 Pages Posted: 29 Nov 2014 Last revised: 19 Aug 2020

See all articles by Rainer Baule

Rainer Baule

University of Hagen

Florian Borchard

affiliation not provided to SSRN

Hannes Wilke

Deutsche Bundesbank

Date Written: August 18, 2020

Abstract

We introduce a new measure of stock misevaluation, š¯‘„, which is consistent with the Gordon growth model for firm valuation. In our empirical application, we use š¯‘„ to relate analyst forecasts to stock returns and measure the profitability of investment strategies that rely on information in analyst earnings-per-share forecasts and stock prices. Over a time period of more than 40 years, we analyze portfolio strategies within a highly liquid US stock universe. Over the whole period, self-financing trading strategies yield annualized Fama and French five-factor alphas of up %-|-|-|. These strategies clearly outperform existing pure earnings-forecast momentum strategies and remain profitable after transaction costs. We show that analysts provide valuable information until the end of the 20th century, while they lose some of their informational advantages in the 21st century.

Keywords: asset pricing, analyst research, earnings per share consensus forecasts, earnings forecast momentum, market efficiency, sell-side analysts

JEL Classification: G10, G11, G12, G14, G17

Suggested Citation

Baule, Rainer and Borchard, Florian and Wilke, Hannes, Profitability of Portfolio Strategies Based on Analyst Consensus EPS Forecasts (August 18, 2020). 28th Australasian Finance and Banking Conference Paper, 2016 Financial Markets and Corporate Governance, Available at SSRN: https://ssrn.com/abstract=2531810 or http://dx.doi.org/10.2139/ssrn.2531810

Rainer Baule

University of Hagen ( email )

Universitaetsstrasse 41
Hagen, 58097
Germany

Florian Borchard

affiliation not provided to SSRN

Hannes Wilke (Contact Author)

Deutsche Bundesbank ( email )

Wilhelm-Epstein-Str. 14
Frankfurt/Main, 60431
Germany

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