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

Kang, Zhixin (2019) An investigation on impacts of structural changes in stocks’ past returns on financial analysts’ earnings forecasting rationality. Journal of Capital Markets Studies, 3 (2). pp. 188-202. ISSN 2514-4774

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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.

Item Type: Article
Uncontrolled Keywords: Structural change, Earnings forecasting, Financial analysts’ rationality, Information regime
Subjects: H Social Sciences > HA Statistics
H Social Sciences > HG Finance
Divisions: Faculty of Engineering, Science and Mathematics > School of Mathematics
Depositing User: Unnamed user with email [email protected]
Date Deposited: 01 Mar 2024 04:10
Last Modified: 01 Mar 2024 04:10
URI: https://repository.itesa.ac.id/id/eprint/235

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