Uncertainty and Financial Analysts’ Optimism: A Comparison between High-Tech and Low-Tech European Firms

Taoufik Elkemali ()
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Taoufik Elkemali: MRM - Montpellier Research in Management - UPVD - Université de Perpignan Via Domitia - UM - Université de Montpellier, KFU - King Faisal University, FSEG Mahdia - Faculté des Sciences Économiques et de Gestion de Mahdia [Univ Monastir] - UM - جامعة المنستير - Université de Monastir - University of Monastir

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Abstract: This study investigates the impact of information uncertainty on analysts' earnings forecasts for a sample of European companies from 2010 to 2019. We argue that representativeness, anchoring and adjustment, and leniency biases jointly influence analysts' forecasts and lead to optimism. We suggest that uncertainty boosts analysts' optimism as behavioral biases increase in situations of low predictability. We test analysts' optimism through the association between forecast errors and, separately, two modifications (forecast revision and forecast change) when these modifications are upwards and downwards. To examine the uncertainty effect, we implement descriptive and regression analyses for two subsamples of high-tech and low-tech firms. The evidence indicates that analysts are optimistic, as they overreact to positive prediction modifications and underreact to negative prediction modifications. The optimism is more significant for high-tech firms and increases considerably with the forecast horizon. For robustness, we utilize analysts' forecast dispersion as a second proxy for uncertainty, and we obtain comparable results.

Keywords: high-tech; forecast change; forecast revision; earnings release; overreaction; underreaction; optimism; uncertainty (search for similar items in EconPapers)
Date: 2023-01-26
Note: View the original document on HAL open archive server: https://hal.science/hal-05268609v1
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Published in Sustainability, 2023, 15 (3), pp.2270. ⟨10.3390/su15032270⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-05268609

DOI: 10.3390/su15032270

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