30.sim_ccm_stockPortfolio - #=> 2 <=#=> main functions...

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#===> ((((( 2 ))))) <===#
#===> main functions <===#
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#===> obtain a lot of tickers via included data set <===#
library(stockPortfolio)
#DATA:
ticker <- c("C", "KEY", "WFC", "JPM", "SO", "DUK", "D", "HE", "EIX", "LUV",
"AMR", "AMGN", "GILD", "CELG", "GENZ", "BIIB", "CAT", "DE", "HIT", "IMO",
"MRO", "HES", "YPF", "^GSPC")
#===> get data <===#
gr1 <- getReturns(ticker, start='1999-12-31', end='2004-12-31')
summary(gr1)
gr1$R # returns
gr1$ticker # original ticker
gr1$period # sample spacing
gr1$start # when collection started
gr1$end # when collection ended
#===> simple model building <===#
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#No model - classical Markowitz model:
m1 <- stockModel(gr1, drop=24) # drop index
summary(m1)
#Find the point of tangency:
op1 <- optimalPort(m1)
#Type op1 to see the composition of the point of tangency:
op1
#Plot the 24 stocks and point G (point of tangency):
plot(op1, xlim=c(0,0.3))
#Add the portfolio possibilities curve:
portPossCurve(m1, add=TRUE)
#Add the tangent (the following will draw the line only up to G:
segments(0,0,op1$risk,op1$R)
#If you want to extend the tangent beyond G:
slope <- (op1$R-0)/op1$risk
segments(0,0,2*op1$risk, m1$Rf+slope*2*op1$risk)
#Add a cloud of points for visualization:
portCloud(m1)
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