efficient.frontier.06jun2015.R

# efficient.frontier.06jun2015.R

# R code re: CapitalSpecator.com post on efficient frontier analytics:
# "Efficient Frontier Portfolios–Impractical But Still Useful"
# 6 July 2015
# By James Picerno
# http://www.capitalspectator.com/efficient-frontier-portfolios-impractical-but-still-useful/

# Keep in mind that results will change depending on when you run the code
# due to fluctuating market conditions

# load packages
library(fPortfolio)
library(xts)
library(timeSeries)
library(tseries)
library(TTR)
library(quantmod)
library(PerformanceAnalytics)

# download data, generate monthly returns
symbols <-c("SPY","IJS","EFA","EEM","IEF","LQD","VWEHX","RPIBX","PREMX","QRACX","VGSIX")
getSymbols(symbols, src='yahoo', from='2000-12-31')

for(symbol in symbols) {
  x <- get(symbol)
  indexFormat(x) <- '%Y-%m-%d'
  colnames(x) <- gsub("x",symbol,colnames(x))
  x <- x[,6]
  assign(symbol,x)
}

prices <- do.call(merge, lapply(symbols, get))
colnames(prices) <-c(symbols)

prices.m <-to.period(prices,period="months",k=1,indexAt="lastof",OHLC=FALSE)
prices.ret <-na.omit(ROC(prices.m,12,"discrete"))
prices.ret.ts <-as.timeSeries(prices.ret)

assets <- dim(prices.ret.ts)[2] # number of columns

########################################
# specific model and generate          #
# efficient frontier data              #
# no allocation constraints: long only #
########################################
spec <- portfolioSpec()
setSolver(spec) <- "solveRquadprog"
setNFrontierPoints(spec) <- 30

constraints <- c("LongOnly") 

frontier.1 <- portfolioFrontier(prices.ret.ts, spec, constraints)

# Note: I use modified code to create the graphics in the blog post. 
# For simplicity here, the default fPortfolio graphic functions are cited.
tailoredFrontierPlot(object = frontier.1)      # rmetrics plotting function for efficient frontier
weightsPlot(frontier.1, col = rainbow(assets)) # rmetrics plotting funciton for portfolio weights

########################################
# specific model and generate          #
# efficient frontier data              #
# with constraints: long only          #
# 5% minimum, 50% maximum allocation   #
# for each asset                       #
########################################
spec <- portfolioSpec()
setSolver(spec) <- "solveRquadprog"
setNFrontierPoints(spec) <- 30

constraints <- c("minW[1:assets]=0.05", "maxW[1:assets]=0.5")
frontier.2 <- portfolioFrontier(prices.ret.ts, spec, constraints) 

tailoredFrontierPlot(object = frontier.2)      # rmetrics plotting function for efficient frontier
weightsPlot(frontier.2, col = rainbow(assets)) # rmetrics plotting funciton for portfolio weights

### END ###