riqbal-k

riqbal-k

data<-read.csv("FTSESF.csv")
head(data)
str(data)

riqbal-k

getwd() # get working directory
setwd('') # set working directory
install.packages("PerformanceAnalytics") 
library (PerformanceAnalytics) # load the package
ms<-read.csv("Microsoft.csv", header=TRUE) #load Microsoft daily prices
head(ms)
sp<-read.csv("SP.csv", header=TRUE) # load S and P 500 daily prices
head(sp)
class(ms)
class(sp)

riqbal-k

require(zoo)
#Microsoft
ms$Dates <- as.Date(ms$Dates, "%d/%m/%Y")
class(ms$Dates)
ms.z = zoo(x=ms$Close, order.by=ms$Dates)
#S and P 500
sp$Dates <- as.Date(sp$Dates, "%d/%m/%Y")
class(sp$Dates)
sp.z = zoo(x=sp$Close, order.by=sp$Dates)

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ms.monthly<-to.monthly(ms.z,OHLC = FALSE)
head(ms.monthly)
sp.monthly<-to.monthly(sp.z,OHLC = FALSE)
head(sp.monthly)

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#combine Microsoft and SP daily data
ms.sp.dp<-merge(ms.z, sp.z)
head(ms.sp.dp)
#combine Microsoft and sP monthly data
ms.sp.dm<-merge(ms.monthly, sp.monthly)
head(ms.sp.dm)

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#Microsoft montly and daily log  returns
ms.monthly.r<-Return.calculate(ms.monthly, method = "log")
ms.daily.r<-Return.calculate(ms.z, method = "log")
head(ms.monthly.r)
head(ms.daily.r)
#S and P montly and daily log  returns
sp.monthly.r<-Return.calculate(sp.monthly, method = "log")
sp.daily.r<-Return.calculate(sp.z, method = "log")
head(sp.monthly.r)
head(sp.daily.r)

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ms.monthly.r<-ms.monthly.r[-1]
ms.daily.r<-ms.daily.r[-1]
sp.monthly.r<-sp.monthly.r[-1]
sp.daily.r<-sp.daily.r[-1]
ms.sp.dp.r<-ms.sp.dp.r[-1]
ms.sp.dm.r<-ms.sp.dm.r[-1]

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#Daily prices line plot for Microsoft
plot.zoo(ms.z, main = "Microsoft Daily Prices", xlab =
         "Time", ylab = "Daily Prices", lwd = 2, col = "blue")
#Monthly prices line plot for Microsoft      
plot.zoo(ms.monthly, main = "Microsoft Monthly Prices Plot",xlab =
         "Time", ylab = "Monthly Prices", lwd = 2, col = "red")

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#plot for merged daily data
plot.zoo(ms.sp.dp, main = "Microsoft and S&P Daily Prices Plot", lwd = 2, col = "red")