Compensation Disclosures and Corporate Governance through Shareholder Voting

Cadman, Brian D.; Carrizosa, Richard; Peng, Xiaoxia

doi:10.2139/ssrn.2673518

Cited by 1 publication

(1 citation statement)

References 23 publications

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“…10 Based on overlapping observations, expected volatility collected using our algorithm has a Pearson (Spearman) correlation of 0.92 (0.94) with the Compustat variable (optvol), which underscores the quality of our data. 11 Firms can disclose expected volatility used to calculate stock compensation expense in the annual report (10-K) or in the annual proxy statement (DEF 14A) (Cadman et al 2020). Disclosure in either the 10-K or the proxy statement may be incorporated by reference in the other filing.…”

Section: Sample Descriptionmentioning

confidence: 99%

Management Forecasts of Volatility

Ellahie

Peng

2019

SSRN Journal

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We examine the predictive information content of the management forecasts of stock return volatility (i.e., expected volatility) that are disclosed in annual reports. We find that expected volatility predicts near-term and longer-term stock return volatility and earnings volatility incremental to implied volatility, historical volatility, firm characteristics, and alternative measures of uncertainty. We also find that expected volatility reflects managers' private information about their firms' future investment activities, such as mergers and acquisitions and R&D intensity. Finally, we find that the predictive power of expected volatility shrinks when managers have stronger incentives to manage earnings. Overall, we provide novel evidence that management forecasts of volatility contain private information about future uncertainty that can help forecast volatility.

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Section: Sample Descriptionmentioning

confidence: 99%