Stock market liquidity and information asymmetry around voluntary earnings disclosures: New evidence from France
Purpose – The purpose of this paper is to examine whether non-mandated earnings disclosures include value-relevant information and affect information asymmetry and stock market liquidity. Design/methodology/approach – The event study methodology explores the informational content of good, bad and neutral voluntary earnings disclosures. The OLS panel regression framework is, then, used to analyze information asymmetry and stock market liquidity subsequent to both categories of voluntary earnings disclosures (i.e. earnings forecasts and quarterly earnings disclosures). Findings – Empirical tests show that voluntary earnings disclosures include material information and that bad news is released in an untimely fashion leading to information leakage in the pre-announcement period. The results also indicate that quarterly earnings enhance stock market liquidity by shrinking bid-ask spreads. However, earnings forecasts exacerbate information asymmetry before and after the announcement date. This result confirms the existence of information leakage and suggests that managers have considerable discretion whether to make a forecast, and in deciding its timing, form, and specificity. Research limitations/implications – This paper examines stock market liquidity around voluntary earnings disclosures using effective spreads. Future research should examine other proxies for market liquidity, i.e. market depth. Practical implications – The results provide insights on the positive benefits of a disclosure policy. Companies have to provide investors with better and timely information in order to mitigate the information leakage risk and thus improve stock market liquidity. Originality/value – This paper provides new evidence about information content, information asymmetry and stock market liquidity around voluntary earnings disclosures in France. Unlike financial statements disclosures, quarterly earnings and earnings forecasts are isolated events that can be evaluated by the market with less noise.
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