Fin 360 Week 3 Linear Regression Analysis

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Fin 360 Write Up Professor Ullrich Dec 6, 2013 After importing both tables consisting of data from the GXP Company and the S&P 500, I merged them to calculate and see if electricity price variation helps determine the stock price for those companies who operate in that market. I calculated the excess returns first by simply subtracting the risk free rate from both the S&P 500 return and the GXP return which produced the independent and dependent variables. I performed a linear regression with the excess return on GXP as the dependent variable and the excess return on the S&P 500 being the independent variable. After completing the regression it turns out that the excess return on the market explains very little of the excess return on the GXP stock with the r-squared being only 14.4%, which is the…show more content…
The remaining 85.6% of GXP stock excess return variation is the nonsystematic component. The beta for GXP is .45 which is its sensitivity to movements in the market and means that the excess return on the market is positively correlated with the excess return on GXP. It moves in same direction as market at large but less susceptible to day-to-day fluctuations. Since this number is less than one its risk is lower than that of the market. As shown in the fit put charts the S&P500 and GXP returns can be proven to be positively correlated by looking at the line of best fit with the data shown. The standard error is low as well being at 2.92%. The intercept or alpha in this regression is .0001809 which is not significantly different from zero. The t value is 15.56 which is greater than the t stat for a 5% significance level and the p value is less than .0001 which is the

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