Stock return volatility surrounding management earnings forecasts

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Copyright: Jackson, Andrew Blair
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Abstract
The primary aim of this study is to investigate the stock return volatility surrounding management earnings forecasts. Disclosure by managers of expected earnings are particularly important communications, and as such, it is important to understand the capital market implications surrounding them. In doing so, the research questions are essentially aimed at examining the stock return volatility, first, at the release of a management earnings forecast, and second, at the eventual announcement of the realised earnings for that period. The first test investigates whether there is an increase in volatility surrounding a management earnings forecast for those firms who release them compared to a matched-firm sample of firms without a management earnings forecast at that date, and then further examines that result based on different forecast antecedents and forecast characteristics. Next, this study tests, for firms who do release a management earnings forecast during the year, whether stock volatility is lower than firms who do not release a management earnings forecast at the eventual earnings announcement date. In brief, the evidence using the Garman and Klass [1980] ‘best analytic scale-invariant estimator’ of volatility in an Australian context, between 1993 and 2003, finds that stock return volatility is greater for bad news forecasts, forecasts of low specificity, and forecasts issued by firms perceived ex ante as being of lower credibility using both permutation analysis and modelling daily volatility. At the earnings announcement date, however, there is no evidence that stock return volatility is lower for firms that issue management earnings forecasts during the year. Overall, this result challenges the information asymmetry argument in the literature that disclosure will reduce volatility in the long-run.
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Author(s)
Jackson, Andrew Blair
Supervisor(s)
Balatbat, Maria
Gallery, Gerry
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Publication Year
2010
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Thesis
Degree Type
PhD Doctorate
UNSW Faculty
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