###The value of beta for the stock market will always be 1; thus, stocks that tend to rise and fall with the stock market will also have a beta close to 1. Betas greater than 1 indicate that the stock is more volatile than the market, and betas less than 1 indicate that the stock is less volatile than the market. For instance, if a stock has a beta of 1.4, it is 40% more vola- tile than the market, and if a stock has a beta of .4, it is 60% less volatile than the market.
#Descriptive Statistics
# Get data
df <- read.csv("~/Desktop/BSTAT_14_Case1_Beta.csv")
attach(df)
summary(df)## Month Microsoft Exxon.Mobil Caterpillar
## Length:36 Min. :-0.082010 Min. :-0.11646 Min. :-0.10060
## Class :character 1st Qu.:-0.037648 1st Qu.:-0.00926 1st Qu.:-0.03042
## Mode :character Median : 0.004000 Median : 0.01278 Median : 0.04081
## Mean : 0.005026 Mean : 0.01664 Mean : 0.03010
## 3rd Qu.: 0.043075 3rd Qu.: 0.03911 3rd Qu.: 0.06871
## Max. : 0.088830 Max. : 0.23217 Max. : 0.21847
## Johnson...Johnson McDonald.s Sandisk Qualcomm
## Min. :-0.059170 Min. :-0.11443 Min. :-0.28331 Min. :-0.12170
## 1st Qu.:-0.017570 1st Qu.:-0.02685 1st Qu.:-0.06935 1st Qu.:-0.04827
## Median :-0.001475 Median : 0.03701 Median : 0.07414 Median : 0.03871
## Mean : 0.005296 Mean : 0.02447 Mean : 0.06926 Mean : 0.02836
## 3rd Qu.: 0.026353 3rd Qu.: 0.05877 3rd Qu.: 0.16625 3rd Qu.: 0.07992
## Max. : 0.103340 Max. : 0.18257 Max. : 0.50165 Max. : 0.21055
## Procter...Gamble S.P.500
## Min. :-0.05365 Min. :-0.03429
## 1st Qu.:-0.01240 1st Qu.:-0.01305
## Median : 0.01333 Median : 0.01034
## Mean : 0.01059 Mean : 0.01010
## 3rd Qu.: 0.02772 3rd Qu.: 0.02167
## Max. : 0.08783 Max. : 0.08104lm1 <- lm(Microsoft~S.P.500, data=df)
summary(lm1)##
## Call:
## lm(formula = Microsoft ~ S.P.500, data = df)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.079550 -0.038259 0.005656 0.025712 0.080186
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.0003984 0.0079355 0.050 0.960
## S.P.500 0.4583448 0.2848864 1.609 0.117
##
## Residual standard error: 0.04438 on 34 degrees of freedom
## Multiple R-squared: 0.07075, Adjusted R-squared: 0.04341
## F-statistic: 2.588 on 1 and 34 DF, p-value: 0.1169lm2 <- lm(Exxon.Mobil~S.P.500, data=df)
summary(lm2)##
## Call:
## lm(formula = Exxon.Mobil ~ S.P.500, data = df)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.112751 -0.030479 -0.003176 0.017337 0.209095
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.009259 0.009414 0.983 0.3323
## S.P.500 0.730907 0.337966 2.163 0.0377 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.05264 on 34 degrees of freedom
## Multiple R-squared: 0.1209, Adjusted R-squared: 0.09507
## F-statistic: 4.677 on 1 and 34 DF, p-value: 0.03769lm3 <- lm(Caterpillar~S.P.500, data=df)
summary(lm3)##
## Call:
## lm(formula = Caterpillar ~ S.P.500, data = df)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.099586 -0.030686 -0.000617 0.031065 0.179221
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.01502 0.01019 1.474 0.149664
## S.P.500 1.49320 0.36588 4.081 0.000256 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.05699 on 34 degrees of freedom
## Multiple R-squared: 0.3288, Adjusted R-squared: 0.3091
## F-statistic: 16.66 on 1 and 34 DF, p-value: 0.0002565lm4 <- lm(Johnson...Johnson~S.P.500, data=df)
summary(lm4)##
## Call:
## lm(formula = Johnson...Johnson ~ S.P.500, data = df)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.06423 -0.02289 -0.00657 0.02123 0.09806
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.005207 0.006326 0.823 0.416
## S.P.500 0.008757 0.227098 0.039 0.969
##
## Residual standard error: 0.03537 on 34 degrees of freedom
## Multiple R-squared: 4.373e-05, Adjusted R-squared: -0.02937
## F-statistic: 0.001487 on 1 and 34 DF, p-value: 0.9695lm5 <- lm(McDonald.s~S.P.500, data=df)
summary(lm5)##
## Call:
## lm(formula = McDonald.s ~ S.P.500, data = df)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.116819 -0.032679 0.003738 0.032409 0.151472
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.009299 0.010054 0.925 0.361536
## S.P.500 1.503201 0.360942 4.165 0.000201 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.05622 on 34 degrees of freedom
## Multiple R-squared: 0.3378, Adjusted R-squared: 0.3183
## F-statistic: 17.34 on 1 and 34 DF, p-value: 0.0002015lm6 <- lm(Sandisk~S.P.500, data=df)
summary(lm6)##
## Call:
## lm(formula = Sandisk ~ S.P.500, data = df)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.4180 -0.1311 -0.0068 0.1427 0.3261
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.04297 0.03320 1.294 0.2043
## S.P.500 2.60484 1.19176 2.186 0.0358 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.1856 on 34 degrees of freedom
## Multiple R-squared: 0.1232, Adjusted R-squared: 0.09741
## F-statistic: 4.777 on 1 and 34 DF, p-value: 0.03582lm7 <- lm(Qualcomm~S.P.500, data=df)
summary(lm7)##
## Call:
## lm(formula = Qualcomm ~ S.P.500, data = df)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.24311 -0.05192 0.01269 0.04835 0.13106
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.01409 0.01410 0.999 0.32494
## S.P.500 1.41389 0.50632 2.793 0.00852 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.07887 on 34 degrees of freedom
## Multiple R-squared: 0.1866, Adjusted R-squared: 0.1626
## F-statistic: 7.798 on 1 and 34 DF, p-value: 0.008524lm8 <- lm(Procter...Gamble~S.P.500, data=df)
summary(lm8)##
## Call:
## lm(formula = Procter...Gamble ~ S.P.500, data = df)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.062278 -0.023855 0.000239 0.017048 0.078124
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.005475 0.006275 0.873 0.3890
## S.P.500 0.506533 0.225268 2.249 0.0311 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.03509 on 34 degrees of freedom
## Multiple R-squared: 0.1295, Adjusted R-squared: 0.1039
## F-statistic: 5.056 on 1 and 34 DF, p-value: 0.03113The most volatile stocks:
Caterpillar: Beta = 1.49
Qualcomm: Beta = 1.41
Mcdonalds: Beta = 1.5
Least Volatile Stocks:
Johnson & johnson = 0.008
Sandisk: Beta = 0.04
P & G: Beta = 0.51
Microsoft: Beta = 0.45
Exxonmobil: Beta = 0.73
# Microsoft ~ S.P.500
summary(lm1)$r.squared## [1] 0.07074523# Exxon.Mobil~S.P.500
summary(lm2)$r.squared## [1] 0.1209275# Caterpillar ~ S.P.500
summary(lm3)$r.squared## [1] 0.3288034# Johnson & Johnson ~ S.P.500
summary(lm4)$r.squared## [1] 4.373112e-05# McDonald.s ~ S.P.500
summary(lm5)$r.squared## [1] 0.3378055# Sandisk ~ S.P.500
summary(lm6)$r.squared## [1] 0.123198# Qualcomm ~ S.P.500
summary(lm7)$r.squared## [1] 0.1865655# Procter...Gamble~S.P.500
summary(lm8)$r.squared## [1] 0.1294575