Publication:
The role of sentiment and stock characteristics in the translation of analysts’ forecasts into recommendations

Consultable a partir de

2021-07-01

Date

2019

Director

Publisher

Elsevier
Acceso abierto / Sarbide irekia
Artículo / Artikulua
Versión aceptada / Onetsi den bertsioa

Project identifier

MINECO//ECO2012-35946-C02-01/ES/

Abstract

The purpose of this paper is to further understanding of the determinants of analysts’ translational effectiveness and, specifically, the role of stock characteristics in the impact of sentiment in the translation of analysts’ forecasts into recommendations. We construct a proxy of intrinsic value of a stock based on that of Ohlson (1995), which incorporates all the information contained in the analysts’ earnings forecasts. Our results show that, although analysts do translate their earnings forecast valuations into recommendations, the effectiveness of this process is reduced by investor sentiment only in highly sentiment-sensitive stocks. This suggests the degree of analyst coverage as a potential conditioner of the observable results in a market. While not totally eliminating this observed effect, the Market Abuse Directive regulation does contribute to reduce the skew between analysts’ earnings forecasts and their recommendations. Finally, analysis of this effect reveals that this kind of skew enables investment strategies yielding positive risk-adjusted returns in highly sentiment-sensitive stocks, during periods of high market sentiment.

Keywords

Investor sentiment, Financial analyst, Analysts coverage, Recommendation, Earning forecast, Translational effectiveness

Department

Enpresen Kudeaketa / Institute for Advanced Research in Business and Economics - INARBE / Gestión de Empresas

Faculty/School

Degree

Doctorate program

Editor version

Funding entities

This paper has received financial support from the Spanish Ministry of Economy and Competitiveness (ECO2012-35946-C02-01 and ECO2016-77631-R (AEI/FEDER, UE). Elena Ferrer would also like to acknowledge a Scientific Research Grant from the Fundación Banco Herrero 2012.

© 2019 Elsevier Inc. This manuscript version is made available under the CC-BY-NC-ND 4.0.

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