R Notebook

STOCK MARKET DATA

• We then examine some numerical and graphical summaries of the Smarket data, which is part of the ISLR library.

library (ISLR)

package 㤼㸱ISLR㤼㸲 was built under R version 3.3.3

names(Smarket)

[1] "Year"      "Lag1"      "Lag2"      "Lag3"      "Lag4"      "Lag5"      "Volume"   
[8] "Today"     "Direction"

dim(Smarket)

[1] 1250    9

summary(Smarket)

      Year           Lag1                Lag2                Lag3                Lag4          
 Min.   :2001   Min.   :-4.922000   Min.   :-4.922000   Min.   :-4.922000   Min.   :-4.922000  
 1st Qu.:2002   1st Qu.:-0.639500   1st Qu.:-0.639500   1st Qu.:-0.640000   1st Qu.:-0.640000  
 Median :2003   Median : 0.039000   Median : 0.039000   Median : 0.038500   Median : 0.038500  
 Mean   :2003   Mean   : 0.003834   Mean   : 0.003919   Mean   : 0.001716   Mean   : 0.001636  
 3rd Qu.:2004   3rd Qu.: 0.596750   3rd Qu.: 0.596750   3rd Qu.: 0.596750   3rd Qu.: 0.596750  
 Max.   :2005   Max.   : 5.733000   Max.   : 5.733000   Max.   : 5.733000   Max.   : 5.733000  
      Lag5              Volume           Today           Direction 
 Min.   :-4.92200   Min.   :0.3561   Min.   :-4.922000   Down:602  
 1st Qu.:-0.64000   1st Qu.:1.2574   1st Qu.:-0.639500   Up  :648  
 Median : 0.03850   Median :1.4229   Median : 0.038500             
 Mean   : 0.00561   Mean   :1.4783   Mean   : 0.003138             
 3rd Qu.: 0.59700   3rd Qu.:1.6417   3rd Qu.: 0.596750             
 Max.   : 5.73300   Max.   :3.1525   Max.   : 5.733000             

• We use the cor() function that produces a matrix that conating all of the pairwise correlations among the predictors in a data set.

cor(Smarket)

Error in cor(Smarket) : 'x' must be numeric

cor(Smarket [,-9])

             Year         Lag1         Lag2         Lag3         Lag4         Lag5      Volume
Year   1.00000000  0.029699649  0.030596422  0.033194581  0.035688718  0.029787995  0.53900647
Lag1   0.02969965  1.000000000 -0.026294328 -0.010803402 -0.002985911 -0.005674606  0.04090991
Lag2   0.03059642 -0.026294328  1.000000000 -0.025896670 -0.010853533 -0.003557949 -0.04338321
Lag3   0.03319458 -0.010803402 -0.025896670  1.000000000 -0.024051036 -0.018808338 -0.04182369
Lag4   0.03568872 -0.002985911 -0.010853533 -0.024051036  1.000000000 -0.027083641 -0.04841425
Lag5   0.02978799 -0.005674606 -0.003557949 -0.018808338 -0.027083641  1.000000000 -0.02200231
Volume 0.53900647  0.040909908 -0.043383215 -0.041823686 -0.048414246 -0.022002315  1.00000000
Today  0.03009523 -0.026155045 -0.010250033 -0.002447647 -0.006899527 -0.034860083  0.01459182
              Today
Year    0.030095229
Lag1   -0.026155045
Lag2   -0.010250033
Lag3   -0.002447647
Lag4   -0.006899527
Lag5   -0.034860083
Volume  0.014591823
Today   1.000000000

• The correlations between the lag variables and today’s returns are close to zero. Meaning, there appears to be little correlation between today’s returns and previous days’ returns. The only substantial correlation is between Year and Volume. By plotting the data we see that Volume is increasing over time.

attach(Smarket)

plot(Volume)

• Here, we see that the number of shares traded daily has increased as years have passed by.