Using the R code below, calculate daily log returns and assign the name ‘returnlogs’ library(quantmod) getSymbols("MSFT",...

Using the R code below, calculate daily log returns and assign the name ‘returnlogs’

library(quantmod) getSymbols("MSFT", src = "yahoo", from='2017-01-03', to='2018-12-31')

b) MSFTAduestedj <- MSFT$MSFT.Adjusted

Expert Solution

'R' code to calculate daily log return. 
#Install the packages that are essential for calculation

#install.packages("quantmod")
library(quantmod)
#install.packages("ggplot2")
library("ggplot2")

# Download the data by using function getsymb, where MSFT is argument

msft <- getsymb("MSFT", src = "yahoo", from = "2017-01-03", to = "2018-12-31", auto.assign = FALSE)

# Command use to read the base file from the folder
msft <- read.csv("MSFT.csv")
msft[,1] <- as.Date(msft[,1])
msft <- xts(msft)
msft <- msft[,-1]

#Visualization of price
head(msft)
tail(msft)
summary(msft)
str(msft)

# calculate 2 average of 1 day with 30 days window 
msft_m <- subset(msft, index(msft) >= "2017-01-01")
msft_m1 <- mean(msft_m[,5], 1, fill = list_cpc(na, 0, na), align = "right")
msft_m30 <- mean(msft_m[,5], 30, fill = list_cpc(na, 0, na), align = "right")
msft_m$m1 <- core_data(msft_m1)
msft_m$m30 <- core_data(msft_m30)

# Returning logs

returnlogs <- diff(log(msft[,6]))
returnlogs <- returnlogs[-1,]

# Return for different period
dailyReturn(msft)
weeklyReturn(msft)
monthlyReturn(msft)
quarterlyReturn(msft)
yearlyReturn(msft)

# Summary statistics, we will get the summary report in the following format.

summary(msft)

##    MSFT.Open MSFT.High MSFT.Low MSFT.Close MSFT.Volume   MSFT$MSFT.Adjusted 
## 2017-May-23     8.8      8.92    8.75      8.82   22071         8.84
## 2017-May-24     9.0      9.22    8.90      9.09   25863         9.09
## 2017-May-25     9.08     9.26    8.82      8.90   30557         8.90
## 2017-May-26     8.75     9.04    8.73      8.96   22845         8.96
## 2017-May-30     8.86     8.93    8.70      8.71   21082         8.71
## 2017-May-31     8.68     8.78    8.45      8.49   23066         8.49

##      Index             MSFT$MSFT.Adjusted    
##  Min.     :2017-Jan-03     Min.     :-0.1862  
##  1st qtr. :2017-Feb-08     1st qtr. :-0.0153  
##  Med      :2017-March-17   Med      :-0.0027  
##  Avg      :2017-March-17   Avg      :-0.0016  
##  3rd qtr. :2017-April-24   3rd qtr. : 0.0159  
##  Max.     :2017-May-31     Max.     : 0.0687

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Using the R code below, calculate daily log returns and assign the name ‘returnlogs’ library(quantmod) getSymbols("MSFT",...

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