random.rebalancing.a.08sep2015.R

# R code re: CapitalSpecator.com post on random rebalancing dates:
# "Skewed By Randomness"
# www.capitalspectator.com/skewed-by-randomness-testing-arbitrary-rebalancing-dates/#more-6039
# 08 Sep 2015
# By James Picerno
# http://www.capitalspectator.com/
# (c) 2015 by Beta Publishing LLC

# load packages
library(quantmod)
library(tseries)
library(PerformanceAnalytics)

# download prices
symbols <-c("SPY","IJS","EFA","EEM","IEF","LQD","VWEHX","RPIBX","PREMX","QRACX","VGSIX")
getSymbols(symbols, src='yahoo', from='2003-12-31')

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)
}

# merge price histories into one dataset   
port.global.prices <- do.call(merge, lapply(symbols, get))
colnames(port.global.prices) <-c(symbols)

# generate daily return series for funds
port.global.returns <-na.omit(ROC(port.global.prices,1,"discrete"))
colnames(port.global.returns) <-c("spy","ijs","efa","eem","ief","lqd","vwehx","rpibx","premx","qraax","vgsix")
  
# calculate weighted total returns for portfolios

# asset weights
w.global = c(0.25,0.05,0.20,0.05,0.10,0.10,0.05,0.05,0.05,0.05,0.05) # global aa
  
# buy and hold portfolio/no rebalancing
port.global.bh <-Return.portfolio(port.global.returns,
                                  weights=w.global,wealth.index=TRUE,verbose=TRUE)

# year-end rebalanced portfolios  
port.global.dec31rebal <-Return.portfolio(port.global.returns,
                                     rebalance_on="years",
                                     weights=w.global,wealth.index=TRUE,verbose=TRUE)
 
# randomly rebalanced portfolios

# function to generate data for 13 randomly selected rebalancing dates for 1.1.2003-9.4.2015
rand.sample <-function(x) { # x=port.global.returns
  dates <-index(x)
  dates.sample.1 <-sample(dates,11)
  dates.sample.2 <-dates.sample.1[ order(dates.sample.1 )]
  dates.sample.2
  
  initial.w  <- xts(matrix(c(w.global), nrow=1, ncol=11,byrow=TRUE),index(first(port.global.prices)))
  w.global.sample.a <- xts(matrix(c(w.global),nrow=11, ncol=11,byrow=TRUE),dates.sample.2)
  w.global.sample <-rbind(initial.w,w.global.sample.a)
  
  a <-Return.portfolio(x,
                       rebalance_on="daily",
                       weights=w.global.sample,wealth.index=TRUE,verbose=FALSE)
  b <-as.numeric(a)
  b
  }

# generate multiple return series of random rebalancing dates
rand.sample.data <-replicate(1000,rand.sample(port.global.returns)) # note: this will take several minutes for 1000 portfolios
rand.sample.data.1 <-xts(rand.sample.data,index(port.global.returns)) # add dates

# merge portfolio returns into one dataset for charting, analytics:
# buy & hold, year-end rebalancing, and random rebalancing dates

port.all <-merge(port.global.bh$wealthindex,
                 port.global.dec31rebal$wealthindex,
                 rand.sample.data.1)

### END