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Erscheinungsjahr: 
2022
Quellenangabe: 
[Journal:] Journal of Risk and Financial Management [ISSN:] 1911-8074 [Volume:] 15 [Issue:] 10 [Article No.:] 473 [Year:] 2022 [Pages:] 1-18
Verlag: 
MDPI, Basel
Zusammenfassung: 
Using a large database of U.S. seasoned equity offering (SEO) announcements from 2010 to 2015, we examine the effects of several explanatory variables-firm specific, macroeconomic, fixed income, and stock market variables-on the announcement period abnormal stock returns and on the longer-run post-issue abnormal returns. We use five different statistical methods-multivariate linear regression, regression on a reduced model using principal components analysis, year-by-year regression on a reduced model using principal components analysis, random forest regression on the whole sample, and year-by-year random forest regression. In general, across the methods, we find that firm's profitability in the recent past is an important explanatory factor in both short-term and long-term abnormal stock returns, but several other significant explanatory factors change based on the statistical method used. Therefore, the statistical method used affects the results reported.
Schlagwörter: 
seasoned equity offerings
SEO
announcement period abnormal stock returns
long-run post-issue abnormal returns
principal components analysis
random forest regression
key determinants
JEL: 
G14
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