Null Hypothesis: Microsoft Typically has high beta values. An Old S regression of Micrsoft has revealed estimated Beta at 1.318 with a low standard error of 0.16. Confidence intervals too reveal that the Microsit values are close to 1, mostly on positive side. However, the probability of this test being low, descriptive statistics of Microsoft Beta (msft Beta ) were looked at.
- The Confidence intervals for GE between 0.704 and 1.090 and 95% values of beta lie within this margin. The risk profile is defensive
- The Confidence intervals is between 0.861564 and 1.662 and 95% values of beta lie within this margin. This implies that the variability of the returns is high.
- The Confidence Intervals of Disney suggest is 0.654 and 1.141, denoting a neutral risk profile.
The Beta values or the fiited equation of Microsoft was taken and the expected value was calculated
Expected Returns are Calculated as Actual Returns “r” X Probability.
Probability msft X rmsft – Probability riskfree X r riskfree = β ( Probability mkt X r mkt – Probability riskfree X r riskfree)
Given that r riskfree is 0 ,
Probability msft X rmsft = β ( Probability mkt X r mkt)
According to Answer 1, Probability msft = 0.000
Probability mkt = 0.5
r riskfree =0.05
The Expected Returns are 0.025 or 2.5 % returns and Standard Deviation is 0.017678
Probability msft = 0.000
Probability mkt = 0.5
r riskfree = - 0.05
The Expected Returns are - 0.025 or 2.5 % returns Standard Deviation is 0.017678
7) The Three stocks that are recommended in the portfolio are
Aggressive: Microsoft - The stock has highest Beta values are highest with shortest confidence intervals. The Lower boundary level of confidence is also higher than 1, indicating high gains. There is less downside.
Neutral: IBM - This stock has a high beta (more than 1) and a relatively smaller margin for error.
Defensive: GE: GE the shortest confidence interval with a beta value that is close to one.
8) R2 is the square of residuals and describes the “Goodness of Fit” of the actual values. The closer the residuals are to the actual values, the more the equation is applicable for various data points. The R2 is close to one in most cases for this series. This means that the dependent variable may have many regressor or high residuals.