The OLS model used to examine the day-of-the-week effect is given by: Rt = ? + ?1 dummy1 + ?2 dummy2 +?3 dummy3 +?4 dummy4 + e where e is the error term. ???is the return of the benchmark category...

The OLS model used to examine the day-of-the-week effect is given by: Rt = ? + ?1 dummy1 + ?2 dummy2 +?3 dummy3 +?4 dummy4 + e where e is the error term. ???is the return of the benchmark category which is Friday in the analysis Four dummy variables are created to take care of five day effect in a week. The dummy variables are defined as: Dummy1 = 1 for Monday, 0 for others Dummy2 = 1 for Tuesday, 0 for others Dummy3 = 1 for Wednesday, 0 for others Dummy4 = 1 for Thursday, 0 for others To avoid the dummy variable trap we need to use n-1 dummy The correlogram of log return shows that the log return series is not stationary Date: 04/27/12 Time: 05:23Sample: 1 2087Included observations: 2086AutocorrelationPartial CorrelationAC  PAC Q-Stat Prob        | |        | |10.0050.0050.05130.821        | |        | |2-0.032-0.0322.24950.325        | |        | |3-0.055-0.0548.52020.036        | |        | |40.0640.06417.1020.002        | |        | |5-0.056-0.06023.5820.000        | |        | |60.0000.00223.5820.001        | |        | |70.0090.01323.7610.001        | |        | |80.0300.01925.6390.001        | |        | |9-0.057-0.05032.4600.000        | |        | |10-0.007-0.00732.5720.000        | |        | |110.0200.01833.3710.000        | |        | |120.0570.04940.2200.000        | |        | |130.0220.03141.1990.000        | |        | |140.0080.00841.3500.000        | |        | |15-0.023-0.02042.4560.000        |* |        |* |160.0920.09460.4350.000        | |        | |170.0380.04263.5000.000        | |        | |18-0.027-0.02665.0540.000       *| |        | ...