Dear R helpers,
Following is my R code where I am trying to calculate returns and then trying
to create a data.frame. Since, I am not aware how many instruments I will be
dealing so I have constructed a function. My R code is as follows -
library(plyr)
mydata <- data.frame(instru_name =
c("instru_A","instru_A","instru_A","instru_A","instru_A","instru_A","instru_A","instru_A","instru_A","instru_A","instru_A","instru_A","instru_A","instru_A","instru_B","instru_B","instru_B","instru_B","instru_B","instru_B","instru_B","instru_B","instru_B","instru_B","instru_B","instru_B","instru_B","instru_B"),
date = c("10-Jan-12","9-Jan-12","8-Jan-12", "7-Jan-12",
"6-Jan-12","5-Jan-12","4-Jan-12","3-Jan-12","2-Jan-12","1-Jan-12", "31-Dec-11",
"30-Dec-11","29-Dec-11","28-Dec-11","10-Jan-12","9-Jan-12","8-Jan-12",
"7-Jan-12","6-Jan-12","5-Jan-12","4-Jan-12","3-Jan-12","2-Jan-12","1-Jan-12","31-Dec-11","30-Dec-11","29-Dec-11","28-Dec-11"),
price = c(11.9,10.5,13,14.5,14.4,14.8,10.1,12,14.3,
10.7,11.2,10.2,10.2,10.8,41.9,40.5,43,44.5,44.4,48.8,42.1,44,46.3,48.7,46.2,44.2,42.2,40.8))
attach(mydata)
opt_return_volatilty = function(price, instru_name)
{
price_returns = matrix(data = NA, nrow = (length(price)-1), ncol = 1)
for (i in(1:(length(price)-1)))
{
price_returns[i] = log(price[i]/price[i+1])
}
volatility = sd(price_returns)
entity_returns = unique(instru_name)
colnames(price_returns) = entity_returns
write.csv(price_returns, file = paste(entity_returns, ".csv", sep = ""),
row.names = FALSE)
return(data.frame(list(volatility = volatility)))
}
entity_volatility <- ddply(.data=mydata, .variables = "instru_name",
.fun=function(x) opt_return_volatilty(price = x$price,
instru_name = x$instru_name))
> entity_volatility
instru_name volatility
1 instru_A 0.17746897
2 instru_B 0.06565341
fileNames <- list.files(pattern = "instru.*.csv")
> fileNames
[1] "instru_A.csv" "instru_B.csv"
#
_____________________________________________________________________________________
# MY QUERY
# I need to construct the data frame consisting of all the returns. I.e. I need
to have # a data.frame like
instru_A instru_B
0.125163143 0.033983853
-0.2135741 -0.059898142
-0.109199292 -0.034289073
0.006920443 0.00224972
-0.027398974 -0.094490843
I am using following Code
input <- do.call(rbind, lapply(fileNames, function(.name)
{
.data <- read.csv(.name, header = TRUE, as.is = TRUE)
.data$file <- .name
.data
}))
# I get following error.
Error in match.names(clabs, names(xi)) :
names do not match previous names
Kindly guide
Regards
Vincy
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