An investigation on impacts of structural changes in stocks’ past returns on financial analysts’ earnings forecasting rationality

Zhixin Kang

doi:10.1108/jcms-06-2019-0033

Abstract

Purpose The purpose of this paper is to test whether financial analysts’ rationality in making stocks’ earnings forecasts is homogenous or not across different information regimes in stocks’ past returns. Design/methodology/approach By treating stocks’ past returns as the information variable in this study, the authors employ a threshold regression model to capture and test threshold effects of stocks’ past returns on financial analysts’ rationality in making earnings forecasts in different information regimes. Findings The results show that three significant structural breaks and four respective information regimes are identified in stocks’ past returns in the threshold regression model. Across the four different information regimes, financial analysts react to stocks’ past returns quite differently when making one-quarter ahead earnings forecasts. Furthermore, the authors find that financial analysts are only rational in a certain information regime of stocks’ past returns depending on a certain return-window such as one-quarter, two-quarter or four-quarter time period. Originality/value This study is different from those in the existing literature by arguing that there could exist heterogeneity in financial analysts’ rationality in making earnings forecasts when using stocks’ past returns information. The finding that financial analysts react to stocks’ past returns differently in the different information regimes of past returns adds value to the research on financial analysts’ rationality.

Highlights

Financial analysts routinely make forecasts on earnings per share (EPS) for the stocks they follow
The results show that three significant structural breaks and four respective information regimes are identified in stocks’ past returns
Across the four different information regimes, financial analysts react to past returns quite differently when making one-quarter ahead earnings forecasts

Summary

Introduction

Financial analysts routinely make forecasts on earnings per share (EPS) for the stocks they follow. Both institutional and individual investors incorporate earnings forecasts information in their stock investment decision making and transactions. As such, studying the mechanism of financial analysts’ earnings forecasts is very important to stock investors. There has been a rich literature exploring financial analysts’ rationality in making EPS forecasts. Financial analysts’ rationality is referred to as a decision-making process in which a forecasted EPS is logically based on the information available at the forecasting time (Keane and Runkle, 1990). When making EPS forecasts, financial analysts use different sources of information. This study focuses on investigating financial analysts’ rationality in using stocks’ past return information to make EPS forecasts. This study focuses on investigating financial analysts’ rationality in using stocks’ past return information to make EPS forecasts. Abarbanell (1991) shows that financial analysts do not fully use the information reflected in stocks’ past returns. Lys and Sohn (1990) report that analysts’ earnings forecasts do not incorporate the full information contained in stocks’ past returns prior to forecast-release dates. Basu and Markov (2004), using a linear loss regression methodology, show that financial analysts’ earnings forecasts are not statistically efficient

Objectives

Methods

Results

Conclusion