#
#
########### Taking a look at Gold, IBM, and the DOW Jones Industrials.
#
################################################################################
#
# The 'quantmod' package is very handy if you're interested in financial modeling,
# or simply curious about market indices.
# The persistent CRAN link for the package is:
# http://cran.r-project.org/web/packages/quantmod/index.html

library(quantmod)

# The 'getMetals' function is limited to 500 data points per query; an easy
# way to overcome that is to simply import each year separately.

gold.0 <- getMetals(Metals = "XAU", from = "2012-01-02", to = "2012-02-29",
    base.currency = "USD", auto.assign = FALSE)
gold.1 <- getMetals(Metals = "XAU", from = "2011-01-02", to = "2012-01-01",
    base.currency = "USD", auto.assign = FALSE)
gold.2 <- getMetals(Metals = "XAU", from = "2010-01-02", to = "2011-01-01",
    base.currency = "USD", auto.assign = FALSE)
gold.3 <- getMetals(Metals = "XAU", from = "2009-01-02", to = "2010-01-01",
    base.currency = "USD", auto.assign = FALSE)
gold.4 <- getMetals(Metals = "XAU", from = "2008-01-02", to = "2009-01-01",
    base.currency = "USD", auto.assign = FALSE)
gold.5 <- getMetals(Metals = "XAU", from = "2007-01-02", to = "2008-01-01",
    base.currency = "USD", auto.assign = FALSE)
gold.6 <- getMetals(Metals = "XAU", from = "2006-01-02", to = "2007-01-01",
    base.currency = "USD", auto.assign = FALSE)
gold.7 <- getMetals(Metals = "XAU", from = "2005-01-02", to = "2006-01-01",
    base.currency = "USD", auto.assign = FALSE)
gold.8 <- getMetals(Metals = "XAU", from = "2004-01-02", to = "2005-01-01",
    base.currency = "USD", auto.assign = FALSE)
gold.9 <- getMetals(Metals = "XAU", from = "2003-01-02", to = "2004-01-01",
    base.currency = "USD", auto.assign = FALSE)
gold.10 <- getMetals(Metals = "XAU", from = "2002-01-02", to = "2003-01-01",
    base.currency = "USD", auto.assign = FALSE)
gold <- rbind(gold.0, gold.1, gold.2, gold.3, gold.4, gold.5,
              gold.6, gold.7, gold.8, gold.9, gold.10)
rm(gold.0, gold.1, gold.2, gold.3, gold.4, gold.5,
   gold.6, gold.7, gold.8, gold.9, gold.10)

nrow(gold)
head(gold)
tail(gold)
plot(gold)

# Starting January 01, 2011.

plot(gold[3287:3702,])

# When the markets crashed, gold skyrocketed.

plot(gold[2490:3550])

# Cleaning up the workspace.

graphics.off()
rm(gold)

detach("package:quantmod")
detach("package:TTR")
detach("package:Defaults")
detach("package:xts")
detach("package:zoo")

################################################################################
#
############## IBM stock:

library(tseries)

ibm.ts <- get.hist.quote(instrument="ibm", start="2002-01-02",
  end="2012-02-29", quote=c("O","H","L","C","A","V"), provider="yahoo",
  retclass="zoo")
nrow(ibm.ts)
head(ibm.ts)
tail(ibm.ts)

ibm.close <- get.hist.quote(instrument="ibm", start="2002-01-02",
  end="2012-03-02", quote="C", provider="yahoo",
  retclass="zoo")
nrow(ibm.close)
head(ibm.close)
tail(ibm.close)
plot(ibm.close)

# Larger time span.

ibm.close <- get.hist.quote(instrument="ibm", start="1992-01-02",
  end="2012-02-29", quote="C", provider="yahoo",
  retclass="zoo")

# The crash of 2008 - 2009.

plot(ibm.close[4000:4335,])

# More specifically, Summer 2008 - Spring 2009.

plot(ibm.close[4150:4330,])

# Cleaning up the workspace.

rm(ibm.ts, ibm.close)
graphics.off()
detach("package:tseries")

################################################################################
# Yahoo no longer has a license to provide DOW data, although it
# can be viewed on their website. For example purposes, the
# DOW data was downloaded and hosted locally.
#
############### DOW Jones Industrials.
#
# Data was downloaded from:
# http://research.stlouisfed.org/fred2/series/DJIA/downloaddata
# and then reposted to:
# http://www.unt.edu/rss/class/Jon/R_SC/Module10/DJIA_20130408.txt

# Import the data from the web.

dji.df <- read.table("http://www.unt.edu/rss/class/Jon/R_SC/Module10/DJIA_20130408.txt",
   header=TRUE, sep=",", na.strings="NA", dec=".", strip.white=TRUE)
head(dji.df, 15)
nrow(dji.df)
tail(dji.df, 15)

my.dates <- as.Date(dji.df[, 1])

dji.mat <- matrix(dji.df[,2], ncol = 1, dimnames = list(dji.df[,1],"Close"))
head(dji.mat)

################################################################################

library(zoo)
dji.zoo <- zoo(dji.df[,2], order.by = my.dates)
length(dji.zoo)
head(dji.zoo)
tail(dji.zoo)

# help(zoo)

detach("package:zoo")

################################################################################

dji.ts <- ts(dji.zoo, class = "zoo")

head(dji.ts)

library(tseries)
plot(dji.ts)

# Cleaning up the workspace.

graphics.off()
rm(dji.df, dji.mat, dji.ts, dji.zoo, my.dates)
detach("package:tseries")


################################################################################
#
# Recommended books:
#
# Ahamed, L. (2009). Lords of finance: The bankers who broke the world. New York:
#     Penguin Press.
#
# Patterson, S. (2010). The quants: How a new breed of math whizzes conquered
#     Wall Street and nearly destroyed it. New York: Crown Business.
#
# Taleb, N., N. (2007). The black swan: The impact of the highly improbable.
#     New York: Random House.
#

# End; Feb. 29, 2012.