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Does analyst forecast dispersion represent investors’ perceived uncertainty toward earnings?

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  • Jundong (Jeff) Wang

Abstract

Purpose - This paper aims to investigate the association between analyst forecast dispersion and investors’ perceived uncertainty toward earnings. Design/methodology/approach - A new measure for investors’ expectations of earnings announcement uncertainty is constructed, using changes in implied volatility of option contracts prior to earnings announcements. Unlike other proxies of uncertainty, this measure isolates the incremental uncertainty regarding the upcoming earnings announcement and is a forward-looking measure. Findings - Using this new proxy, this paper finds a significant negative correlation between analyst forecast dispersion and investors’ uncertainty regarding the upcoming earnings announcements. Further tests show that this negative correlation is driven by analysts’ private information acquisition rather than analysts; uncertainty toward upcoming earnings announcements. Additional cross-sectional tests show that this negative relationship is more pronounced in the subsample with lower earnings quality. Social implications - This paper helps to further the understanding of the information content of analyst forecast dispersion, particularly the ways in which they gather and produce private information and their incentives for so doing. Originality/value - This paper introduces a new market-based and forward-looking proxy of earnings announcement uncertainty that should be useful in future research. This paper also provides original empirical evidence that analysts gather and produce an additional private information to the market when facing noisy signals and that their information reduces investors’ uncertainty toward upcoming earnings announcements.

Suggested Citation

  • Jundong (Jeff) Wang, 2020. "Does analyst forecast dispersion represent investors’ perceived uncertainty toward earnings?," Review of Accounting and Finance, Emerald Group Publishing Limited, vol. 19(3), pages 289-312, April.
    • Handle: RePEc:eme:rafpps:raf-10-2018-0224
    DOI: 10.1108/RAF-10-2018-0224
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    Citations

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    Cited by:

    1. Zheng, Jingling & Li, Zeyun & Ghardallou, Wafa & Wei, Xuecheng, 2023. "Natural resources and economic performance: Understanding the volatilities caused by financial, political and economic risk in the context of China," Resources Policy, Elsevier, vol. 84(C).
    2. Gong, Qinyi & Ying, Limeng & Dai, Jiapeng, 2023. "Green finance and energy natural resources nexus with economic performance: A novel evidence from China," Resources Policy, Elsevier, vol. 84(C).
    3. Chen, Han-Sheng & Lin, Ying-Chou & Lin, Yu-Chen, 2024. "Reexamining information asymmetry related to corporate spin-offs," The Quarterly Review of Economics and Finance, Elsevier, vol. 94(C), pages 190-205.
    4. Huang, Lilong & Dong, Dongdong & Dong, Xueqin, 2023. "Natural resources extraction, financial expansion and remittances: South Asian economies perspective of sustainable development," Resources Policy, Elsevier, vol. 84(C).
    5. Umar, Muhammad & Mirza, Nawazish & Rizvi, Syed Kumail Abbas & Naqvi, Bushra, 2022. "ESG scores and target price accuracy: Evidence from sell-side recommendations in BRICS," International Review of Financial Analysis, Elsevier, vol. 84(C).
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    7. Umar, Muhammad & Mirza, Nawazish & Ribeiro-Navarrete, Samuel, 2023. "The impact of financial restatements on sell-side recommendation accuracy," Finance Research Letters, Elsevier, vol. 55(PA).
    8. Mirza, Nawazish & Umar, Muhammad & Mangafic, Jasmina, 2023. "Covid-19 vaccines and investment performance: Evidence from equity funds in European Union," Finance Research Letters, Elsevier, vol. 53(C).
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    10. Taufiq Choudhry & Gishan Dissanaike & Ranadeva Jayasekera & Woo-Young Kang & Matthias Nnadi, 2021. "Loss sensitive investors and positively biased analysts in Hong Kong stock market," Review of Quantitative Finance and Accounting, Springer, vol. 57(4), pages 1345-1371, November.
    11. Wang, Canghong & Zheng, Chaoliang & Hu, Caishuang & Luo, Yibin & Liang, Miya, 2023. "Resources sustainability and energy transition in China: Asymmetric role of digital trade and policy uncertainty using QARDL," Resources Policy, Elsevier, vol. 85(PB).
    12. Fang, Shuya & Fang, Wei, 2023. "How fiscal decentralization and trade diversification influence sustainable development: Moderating role of resources dependency," Resources Policy, Elsevier, vol. 84(C).
    13. Liao, Qi & Zeng, Heng, 2023. "How do financial development and ICT moderate financial resource curse hypothesis in developing countries?," Resources Policy, Elsevier, vol. 85(PA).
    14. Yang, Bin & Wu, Qiong & Sharif, Arshian & Uddin, Gazi Salah, 2023. "Non-linear impact of natural resources, green financing, and energy transition on sustainable environment: A way out for common prosperity in NORDIC countries," Resources Policy, Elsevier, vol. 83(C).

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