#---------------------------------
# Google Example
#---------------------------------
#-Histogram and Normality Plot
#-Market Model

library(quantmod)
# Data from Google
getSymbols('GOOG', from = "2005-01-01")
y = GOOG$GOOG.Close

tail(y)

plot(y,type="l",col=20,main="Google",
     xlab="Price",ylab="$")

# Calculate log-returns
n <- length(y)
ret <- diff(log(y))
ret <- ret[-1]
mean(ret)
sd(ret)


hist(ret,breaks=50,prob=T,col=4,main="Google: Daily Returns")

# Market Model 
# Data from SPY, the ETF tracks SP500

getSymbols('SPY', from = "2005-01-01")

x = SPY$SPY.Close

n <- length(x)
SP500ret <- diff(log(x))
SP500ret <- SP500ret[-1]
mean(SP500ret)
sd(SP500ret)

# regression for the market model
googlemkt <- lm(ret ~ SP500ret)

googlemkt

# plot the fitted model
plot(as.vector(SP500ret),as.vector(ret),pch=21,bg='grey',bty='n')
abline(googlemkt,col='red',lwd=2)
title("Google Market Model")


hist(rstudent(googlemkt),nclass=50,col=‘green’)

qqnorm(rstudent(googlemkt),col=‘red’)

qqline(rstudent(googlemkt))