(b) Investors in stocks have different appetites for risk. Data on 24 monthly returns, yt, of...

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(b) Investors in stocks have different appetites for risk. Data on 24 monthly returns, yt, of an airline stock are collected in parallel with monthly returns of the relevant market portfolio (representing a stock index), x. According to the capital asset pricing model (CAPM), the relationship can be expressed as: Yt = a + Bxt + et where a is the risk-free rate of return, ß is the systematic risk (i.e. the risk the stock shares with the market), and is the usual regression error term. The regression results are shown on the next page. Regression for Stock Return Summary ANOVA Table Explained Unexplained Regression Table Constant Market Return Multiple R 0.8417 Degrees of Freedom 1 22 Coefficient R-Square 0.7084 Sum of Squares Adjusted R-square 0.6952 Standard Error Mean of Squares 0.183656901 0.183656901 0.075584138 0.003435643 t-Value Std. Err. of Estimate 0.058614355 F 53.45634595 p-Value 0.008258978 0.021862375 0.377771326 0.7092 1.563186232 0.213801667 7.311384681 <0.0001 Rows Ignored 0 p-Value <0.0001 Outliers 0 Lower Confidence Interval 95% Upper -0.037080812 0.053598769 1.119788713 2.006583751 i. Based on the regression output, what conclusion(s) could an investor draw with respect to the systematic risk of this stock? (5 marks) ii. If you decided to create a multiple linear regression model for this airline stock (i.e. to explain the variation in yt), state two independent variables you would consider including, briefly justifying your choice of each. (4 marks) iii. Would you expect the two independent variables you proposed in part ii. to result in multicollinearity? Justify your answer. (3 marks) (b) Investors in stocks have different appetites for risk. Data on 24 monthly returns, yt, of an airline stock are collected in parallel with monthly returns of the relevant market portfolio (representing a stock index), x. According to the capital asset pricing model (CAPM), the relationship can be expressed as: Yt = a + Bxt + et where a is the risk-free rate of return, ß is the systematic risk (i.e. the risk the stock shares with the market), and is the usual regression error term. The regression results are shown on the next page. Regression for Stock Return Summary ANOVA Table Explained Unexplained Regression Table Constant Market Return Multiple R 0.8417 Degrees of Freedom 1 22 Coefficient R-Square 0.7084 Sum of Squares Adjusted R-square 0.6952 Standard Error Mean of Squares 0.183656901 0.183656901 0.075584138 0.003435643 t-Value Std. Err. of Estimate 0.058614355 F 53.45634595 p-Value 0.008258978 0.021862375 0.377771326 0.7092 1.563186232 0.213801667 7.311384681 <0.0001 Rows Ignored 0 p-Value <0.0001 Outliers 0 Lower Confidence Interval 95% Upper -0.037080812 0.053598769 1.119788713 2.006583751 i. Based on the regression output, what conclusion(s) could an investor draw with respect to the systematic risk of this stock? (5 marks) ii. If you decided to create a multiple linear regression model for this airline stock (i.e. to explain the variation in yt), state two independent variables you would consider including, briefly justifying your choice of each. (4 marks) iii. Would you expect the two independent variables you proposed in part ii. to result in multicollinearity? Justify your answer. (3 marks)

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i Based on the regression output an investor can draw the following conclusions regarding the systematic risk of this stock The coefficient of the Market Return variable is 02138 The pvalue associated ... View the full answer