I've taken this code from this site to make a correlation matrix heatmap. How do I format the numbers in the heatmap to have only 2 decimal places worth?: http://blog.revolutionanalytics.com/2014/08/quantitative-finance-applications-in-r-8.html
library(xts)
library(Quandl)
my_start_date <- "1998-01-05"
SP500.Q <- Quandl("YAHOO/INDEX_GSPC", start_date = my_start_date, type = "xts")
RUSS2000.Q <- Quandl("YAHOO/INDEX_RUT", start_date = my_start_date, type = "xts")
NIKKEI.Q <- Quandl("NIKKEI/INDEX", start_date = my_start_date, type = "xts")
HANG_SENG.Q <- Quandl("YAHOO/INDEX_HSI", start_date = my_start_date, type = "xts")
DAX.Q <- Quandl("YAHOO/INDEX_GDAXI", start_date = my_start_date, type = "xts")
CAC.Q <- Quandl("YAHOO/INDEX_FCHI", start_date = my_start_date, type = "xts")
KOSPI.Q <- Quandl("YAHOO/INDEX_KS11", start_date = my_start_date, type = "xts")
# Depending on the index, the final price for each day is either
# "Adjusted Close" or "Close Price". Extract this single column for each:
SP500 <- SP500.Q[,"Adjusted Close"]
RUSS2000 <- RUSS2000.Q[,"Adjusted Close"]
DAX <- DAX.Q[,"Adjusted Close"]
CAC <- CAC.Q[,"Adjusted Close"]
KOSPI <- KOSPI.Q[,"Adjusted Close"]
NIKKEI <- NIKKEI.Q[,"Close Price"]
HANG_SENG <- HANG_SENG.Q[,"Adjusted Close"]
# The xts merge(.) function will only accept two series at a time.
# We can, however, merge multiple columns by downcasting to *zoo* objects.
# Remark: "all = FALSE" uses an inner join to merge the data.
z <- merge(as.zoo(SP500), as.zoo(RUSS2000), as.zoo(DAX), as.zoo(CAC),
as.zoo(KOSPI), as.zoo(NIKKEI), as.zoo(HANG_SENG), all = FALSE)
# Set the column names; these will be used in the heat maps:
myColnames <- c("SP500","RUSS2000","DAX","CAC","KOSPI","NIKKEI","HANG_SENG")
colnames(z) <- myColnames
# Cast back to an xts object:
mktPrices <- as.xts(z)
# Next, calculate log returns:
mktRtns <- diff(log(mktPrices), lag = 1)
head(mktRtns)
mktRtns <- mktRtns[-1, ] # Remove resulting NA in the 1st row
require(gplots)
generate_heat_map <- function(correlationMatrix, title)
{
heatmap.2(x = correlationMatrix, # the correlation matrix input
cellnote = correlationMatrix, # places correlation value in each cell
main = title, # heat map title
symm = TRUE, # configure diagram as standard correlation matrix
dendrogram="none", # do not draw a row dendrogram
Rowv = FALSE, # keep ordering consistent
trace="none", # turns off trace lines inside the heat map
density.info="none", # turns off density plot inside color legend
notecol="black") # set font color of cell labels to black
}
corr1 <- cor(mktRtns) * 100
generate_heat_map(corr1, "Correlations of World Market Returns, Jan 1998 - Present")
You might want the color values to use the full unrounded number, but show a rounded number.
In that case do this...
generate_heat_map <- function(correlationMatrix, title)
{
heatmap.2(x = correlationMatrix, # the correlation matrix input
cellnote = round(correlationMatrix, 2), # places correlation value in each cell
main = title, # heat map title
symm = TRUE, # configure diagram as standard correlation matrix
dendrogram="none", # do not draw a row dendrogram
Rowv = FALSE, # keep ordering consistent
trace="none", # turns off trace lines inside the heat map
density.info="none", # turns off density plot inside color legend
notecol="black") # set font color of cell labels to black
}
If you want the colors to match the numbers shown exactly. Leave the existing function alone and change the input...
corr1 <- round(cor(mktRtns) * 100, 2)
generate_heat_map(corr1, "Correlations of World Market Returns, Jan 1998 - Present")