1 Firm Return PE PS 4.4 14.35 2.39 w NP 2 -4.5 11 0.81 5.9 11.97 2.28 5 4 5 11.31 1.33 NM + 6000 5 -11.3 9.8 1.84 6 20.9

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1 Firm Return Pe Ps 4 4 14 35 2 39 W Np 2 4 5 11 0 81 5 9 11 97 2 28 5 4 5 11 31 1 33 Nm 6000 5 11 3 9 8 1 84 6 20 9 1 (255.51 KiB) Viewed 24 times

1 Firm Return PE PS 4.4 14.35 2.39 w NP 2 -4.5 11 0.81 5.9 11.97 2.28 5 4 5 11.31 1.33 NM + 6000 5 -11.3 9.8 1.84 6 20.9 15.66 0.79 7 64.3 16.09 1.61 8 18.9 8.97 1.01 10 9 -15.2 11.36 2.76 11 10 48 13.71 1.46 12 11 7.3 11.49 1.18 13 12 20.9 14.33 1.31 14 13 -18.5 8.15 0.82 15 14 2.9 9.48 2.7 1.95 16 15 12.4 11.17 17 16 -3.7 2.73 12.63 9.66 18 17 1.6 1.98 19 18 15.9 13.48 1.13 20 19 22.8 14.95 3.38 21 20 -1.2 8.94 2.38 22 21 -8.1 10.57 3.74 23 22 -3.3 7.94 2.19 24 23 15.6 16.4 4.56 25 24 21.1 0.89 26 25 6.3 16.31 15.05 9.16 2.33 27 26 0.98 12 13.3 14.91 1.39 15.4 15.58 0.9 28 27 29 28 30 29 31 30 1 12.56 0.48 1.96 16.3 13.97 32

UT 5 LIICK nere for the Excel Data File a-1. Estimate: Return = B@ + B1PE + B2PS + E. (Negative values should be indicated by a minus sign. Round your answers to 2 decimal places.) 20 points Predicted Return = PE + PS eBook Reference a-2. Are the signs on the coefficients as expected? Yes No b. Interpret the slope coefficient of the PS ratio. As the PS ratio increases by 1 unit, the predicted return of the firm increases by 3.37%, holding PE constant. As the PS ratio increases by 1 unit, the predicted return of the firm decreases by 4.39%, holding PE constant. As the PS ratio increases by 1 unit, the predicted return the firm decreases by 3.37%, holding PE constant. As the PS ratio decreases by 1 unit, the predicted return of the firm decreases by 5.37%, holding PE constant. c. What is the predicted return for a firm with a PE ratio of 10 and a PS ratio of 2? (Negative value should be indicated by a minus sign. Do not round intermediate calculations. Round final answer to 2 decimal places.) Predicted Return d. What is the standard error of the estimate? (Round your answer to 2 decimal places.) Standard error e. Interpret R2 40.08% of the sample variation in y is explained by the sample regression equation. 40.08% of the sample variation in x is explained by the sample regression equation. 63.31% of the sample variation in x is explained by the sample regression equation. 35.65% of the sample variation in y is explained by the sample regression equation.