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Index Models for IBM and GE returns

See attached data file.

3. Regress excess IBM returns on the excess S&P 500 index returns and report ?, ?, the r-square and whether ? and ? are different from zero at the 5% level of significance. Explain your inference.
4. Use equation 8.10 to decompose total risk for IBM into systematic risk and firm-specific risk. That is, calculate total risk, systematic risk and firm-specific risk for IBM.
5. Regress excess GE returns on the excess S&P 500 index returns and report ?, ?, the r-square and whether ?, ? are different from zero at the 5% level of significance.
6. Use equation 8.10 to decompose total risk for GE into systematic risk and firm-specific risk. That is, calculate total risk, systematic risk and firm-specific risk for GE.
7. Use equation 8.10 to estimate the covariance and correlation of GE and IBM excess returns.

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3. Regress excess IBM returns on the excess S&P 500 index returns and report ñ, ò, the r-square and whether ñ and ò are different from zero at the 5% level of significance. Explain your inference.
We need to first create a variable "GSPC Excess Return" that measures the excess S&P 500 index returns.

Please refer to the attached EXCEL file: spreadsheet â??Q3â? for regression results.
The r-square is 0.3638.

The intercept is ?. Since its p-value is 0.028075 which is lower than the 5% level of significance, it is significantly different from zero.

The coefficient of the excess S&P 500 index returns is ?=0.6258. Since its p-value is 3.38E-07 which is lower than the 5% level of significance, it is significantly different ...

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The following post helps answer questions regarding index models for IBM and GE returns. Step by step calculation are given for each.

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