Regression Analysis. To test whether the immediate market response to earnings surprises announced on a Friday is slower than for those announced on other weekdays, produce a table similar to Della Vigna and Pollet, Table II, Panel A. Use three different specifications for the regressions: (1) CAR[-1/+1] = Bo+ BFrlx+ SurQx+ zFrl{xSurQck+ Bek CAR[-1/+1]= Bo+BFrlx+SurQ11x+Frlx*SurQ11k+q CAR[-1/+1]ck = Bo+ BFrl+x+ BSurQTop+x+ BFrlx*SurQTopik + 8k (3) (2) In the above regression equations, Fri is a dummy indicating a Friday earnings announcement, SurQ is the bin number of the earnings surprise, i.e. a number from 1 to 11, SurQ11 is a dummy for bin #11 of earnings surprises, and SurQTop is a dummy for the two highest bins of earnings surprises, Q10 and Q11. The indices t and k stand for the fiscal quarter and the firm, respectively. For regression (2) you need to drop all date in bins 2-10 before running the regression. (Why?) For regression (3) you need to drop bins 3-9. For each regression model, run two regressions, one without additional controls and one with what Della Vigna and Pollet call "standard controls (interacted)". If you do not have all the controls in your dataset, just use those that you can construct