Hi: Thanks for the correction and reference. Eric uses monthly returns in the example in his book and I would think that using daily data would result in very unstable betas but I've been wrong before. Hopefully others can comment.
Mark On Fri, May 25, 2012 at 12:44 PM, and_mue <and_muel...@bluewin.ch> wrote: > For the analysis I follow the approach of Keown & Pinkerton ( > http://e-m-h.org/KePi81.pdf http://e-m-h.org/KePi81.pdf ). They do also > use > daily data to compute alphas and betas of the market model. These estimated > coefficients are then used to estimate abnormal returns for a given period. > > market model would be: > Rjt=ajt+bjt*Rmt+ejt > > Rjt is the return of company j on day t > Rmt is the return of the market on day t (Index) > ejt is the unsystematic component of firm j's return > > after estimation I want to estimate abnormal returns: > êjt=Rjt-(âj+bj*Rmt) > aj and bj are the estimatet coefficients from the equation above. > > -- > View this message in context: > http://r.789695.n4.nabble.com/Problem-with-Autocorrelation-and-GLS-Regression-tp4631336p4631355.html > Sent from the R help mailing list archive at Nabble.com. > > ______________________________________________ > R-help@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide > http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. > [[alternative HTML version deleted]]
______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
