For this problem use the Yahoo Finance website httpfinance y

For this problem, use the Yahoo! Finance website (http://finance yahoo.com/) or a Bloomberg terminal. Choose an equity and download its daily prices for the whole year of 2016. Read the input file into a variable and print its first lines of data using the command head. Study how the plot command works and make a plot of the daily close prices (if you downloaded data from Yahoo! Finance, use the Adj. Close column). Please include a title and labels for each of the axes in the plot With the close prices once again, compute the corresponding series of log-returns. Make another plot and report the summary statistics using the command summary. Do a box plot of the log-returns and verify if there are any outliers. Do a normal qqplot with the log-returns series and comment your results. Using the log-returns computed in Problem 2, do the following: Compute the mean and standard deviation of the series without using the built-in mean and std functions (of course, you can always use these functions to verify your results). Use your code from (a) to create a function that receives a vector as input and outputs its mean and standard deviation.

Solution

1)

a) mydata = read.csv(\"mydata.csv\");

head(mydata,1)

b)

plot(mydata$Close,type = \"o\", col = \"red\", xlab = \"Index\", ylab = \"Close\",
main = \"close chart\")

c)

close<-mydata$Close;

lc<-sapply(close,function(x) log(x));

logclose<-sapply(lc,function(x) diff(x));

plot(x=logclose,y=x,type = \"o\", xlim=c(0,10),col = \"red\", xlab = \"close\", ylab = \"lab\",
+ main = \"close log chart\")

summary(logclose)

d) boxplot(logclose, las = 2,ylim=c(0,10))

e)

qqline(lc)

2)

mean<-sapply(lc,function(x) sum(x)/length(x));

sd<-sd(lc);