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Estimate the CAPM betas for ALL stock you see above. What are your conclusion?
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-40 -30 -20 -10 0 01.05.2016 10 graph2.1 ERBIST 100 01.08.2016 1.11.2016 01.02.2017 01.05.2017 01.08.2017 1.11.2017 01.02.2018 01.05.2018 01.08.2018 1.11.2018 01.02.2019 01.05.2019 01.08.2019 1.11.2019 01.02.2020 01.05.2020 01.08.2020 1.11.2020 01.02.2021 01.05.2021 ERKOC 10 graph2.2 D 0 -10 ERKOC -20 -30 -40 -30 -20 -10 0 10 ERBIST 100 Dependent Variable: ERKOC Method: Least Squares Date: 05/31/21 Time: 19:20 Sample (adjusted): 2 61 Included observations: 60 after adjustments Variable Coefficient Std. Error t-Statistic Prob. C ERBIST100 0.050543 1.026605 1.112359 0.073689 0.045438 13.93159 0.9639 0.0000 R-squared Adjusted R-squared S.E. of regression Sum squared resid Log likelihood F-statistic Prob(F-statistic) 0.769923 Mean dependent var 0.765956 S.D. dependent var 4.738615 Akaike info criterion 1302.360 Schwarz criterion -177.4640 Hannan-Quinn criter. 194.0892 Durbin-Watson stat 0.000000 -12.89236 9.794957 5.982132 6.051944 6.009439 1.838731 -40 -30 -20 -10 0 01.05.2016 10 graph2.1 ERBIST 100 01.08.2016 1.11.2016 01.02.2017 01.05.2017 01.08.2017 1.11.2017 01.02.2018 01.05.2018 01.08.2018 1.11.2018 01.02.2019 01.05.2019 01.08.2019 1.11.2019 01.02.2020 01.05.2020 01.08.2020 1.11.2020 01.02.2021 01.05.2021 ERKOC 10 graph2.2 D 0 -10 ERKOC -20 -30 -40 -30 -20 -10 0 10 ERBIST 100 Dependent Variable: ERKOC Method: Least Squares Date: 05/31/21 Time: 19:20 Sample (adjusted): 2 61 Included observations: 60 after adjustments Variable Coefficient Std. Error t-Statistic Prob. C ERBIST100 0.050543 1.026605 1.112359 0.073689 0.045438 13.93159 0.9639 0.0000 R-squared Adjusted R-squared S.E. of regression Sum squared resid Log likelihood F-statistic Prob(F-statistic) 0.769923 Mean dependent var 0.765956 S.D. dependent var 4.738615 Akaike info criterion 1302.360 Schwarz criterion -177.4640 Hannan-Quinn criter. 194.0892 Durbin-Watson stat 0.000000 -12.89236 9.794957 5.982132 6.051944 6.009439 1.838731
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