The methodology matters: What influences market reaction, and post-issue returns in seasoned equity offerings? - C. N. V. Krishnan; Minghao Wu (Journal of Risk and Financial Management, 2022)
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.
Keywords: G14; 650; seasoned equity offerings; SEO; announcement period abnormal stock returns; long-run post-issue abnormal returns; principal components analysis; random forest regression; key determinants