similar to: Adding dates to time series

Hi there, What is the best way to get a time series of daily stock price observations into R (from excel). The time series are daily but there are spaces for w/e's and holidays etc. So I am not sure a ts object will be suitable but I am not sure what I should use? What ever package you recemmned i need to be able to run a corrolelagram. Thanks Hugh -- View this message in context:

m0<-epxression((4*theta1*theta2-theta3^2)/(2*x*theta3^2)-0.5*theta1*x) params<-all.vars(m0) this reads all the params from m0 so theta1,2 and 3 correct? params<-params[-which(params=="x")] checks which params are multiplied by x? np<-length(params) for(i in 1:6){ esp<-get(sprintf("m%d",i-1))

Hi there, I have a ts object that I would like wo split into arbirary sizes. Can'tfind how to do this? I realise its probaly very simple buy I can't sem to find the right function? -- View this message in context: http://r.789695.n4.nabble.com/Split-an-array-into-arbirtary-sizes-tp3948938p3948938.html Sent from the R help mailing list archive at Nabble.com.

Hi there, I have a largish optimisation problem (10 years of daily observations). I want to optimise between 4 and 6 parameters. I'd like to utilise parallel computing if I can as I will have to run it with different starting values etc. I have a quad core PC with 16GB ram running windows 7. Having done a little reading it seems the two best options for me are: 1.) Use the academic

Hi there, I ran the following code: vols=read.csv(file="C:/Documents and Settings/Hugh/My Documents/PhD/Swaption vols.csv" , header=TRUE, sep=",") X<-ts(vols[,2]) #X dcOU<-function(x,t,x0,theta,log=FALSE){ Ex<-theta[1]/theta[2]+(x0-theta[1]/theta[2])*exp(-theta[2]*t) Vx<-theta[3]^2*(1-exp(-2*theta[2]*t))/(2*theta[2]) dnorm(x,mean=Ex,sd=sqrt(Vx),log=log) }

Hello! Please help - can't find any options how to remove very big spaces between two dates containing intraday prices plotted by plot.xts. It looks like the following: on the left side of the plot window is the first bunch of points, the same is for the right hand side and a long line connecting them in the middle. I would want to merge them (cut spaces) somehow. In any case thanks for

I have a xts object made of daily closing prices I have acquired using quantmod. Here is my code: library(xts) library(quantmod) library(lubridate) # Gets SPY data getSymbols("SPY") # Subset Prices to just closing price SP500 <- Cl(SPY) # Show day of the week for each date using 2-6 for monday-friday SP500wd <- wday(SP500) # Add Price and days of week together

I'm having troubles with the names of columns. quantmod deal with stock quotes. I've created an array of the first 5 closing prices from Jan 2007. (Is there a problem that the name is the same as the variable name? There shouldn't be.) > close close 2007-01-03 1416.60 2007-01-04 1418.34 2007-01-05 1409.71 2007-01-08 1412.84 2007-01-09 1412.11 When I try to

Hello, I coming across a strange problem doing math on an xts object. If I have an xts object of stock prices (perhaps 5 minute bars of open, high, low,close) and want to do some math, the results fail. For example: d$close[10] - d$open[10] works perfectly d$close[10] - d$open[9] fails. I just get an answer of "numeric(0) Index: numeric(0)". My guess is that xts is breaking

I work with a list of crypto assets daily closing prices in a xts class. Here is a limited example: asset.xts.lst <- list(BTCUSDT = structure(c(26759.63, 26862, 26852.48, 27154.15, 27973.45), dim = c(5L, 1L), index = structure(c(1697068800, 1697155200, 1697241600, 1697328000, 1697414400), tzone = "UTC", tclass = "Date"), class = c("xts", "zoo")), ETHUSDT

dear members, I am using quantmod to work with stock prices... I am trying to append the data got from getQuote to the one got by getSymbols. The function is named "apnd". The code is as follows: function(x){ if ((class(x) == "xts") || (class(x) == "zoo")){ sym <- deparse(substitute(x))

Hello, I have a series of intraday (high-frequency) price data in the form of POSIX timestamp followed by the value. I sucesfuly loaded that into "its" package object. I would like to create from it a regularly spaced time series of prices (for example 1min, 5min, etc apart) so i could calcualte returns. There is an interpolation function locf() that for timestamp with value NA uses last

Hi, I am fairly new to R so this may be easy for some. I have one column that is the Type="A, B' T" and I have another column that lists Price='894, 895, 896' I wanted to plot three different series based upon the Type...If B than xts..If T yts... How exactly do I do this? Thanks in advance -- View this message in context:

Hi all, I've got an xts time series of stock symbols and closing prices. > head(x) symbol close 2010-01-04 "AFB" "13.46" 2010-01-04 "AKP" "12.80" 2010-01-04 "APX" " 8.78" 2010-01-04 "AYN" "13.15" 2010-01-04 "BAF" "13.50" 2010-01-04 "BBF" "12.86" >

Arnaud, Short answer may be that the tibble data structure will not be supporting row names and you may want to simply save those names in an additional column or externally. My first thought was to simply save the names you need and then put them back on the tibble. In your code, something like this: save.names <- names(my.ret.lst) result.tib <- as_tibble_col(unlist(my.ret.lst),

R version 2.12.0, 64 bit on Windows. Here is a short script that illustrates the problem: library(tseries) library(xts) setwd('C:\\cygwin\\home\\Ted\\New.Task\\NKs-01-08-12\\NKs\\tests') x = read.table("quotes_h.2.dat", header = FALSE, sep="\t", skip=0) str(x) y <- data.frame(as.POSIXlt(paste(x$V2,substr(x$V4,4,8),sep=" "),format='%Y-%m-%d

I used quantmod to pull in price data from the ticker SPY. The data has date and closing price. I would like to show the day of the week for each closing price. Is that possible? Also, I would like to add the back into the data frame in a new column without changing the structure of the data set if possible. SPY 2009-01-02 92.96 2009-01-05 92.85 2009-01-06 93.47

Hi all, I'm stuck trying to get syntax correct for the follwing type of loop. I would like to find the column with the largest value in a given row, and create a new column with a categorical variable indicating which column the highest value of "i" comes from. too=data.frame(A=rnorm(10,1),B=rnorm(10,2),C=rnorm(10,1.5)) too$large=0 too$large=for (i in 1:length(too[,c(1,2,3)]))

Dear R-help group, I have a dataset with daily closing prices from a stock exchange (consecutive 5 trading days) from a firm trading a specific commodity. The date variable looks like: quote_date 20080411 With the format; yyyymmdd. Moreover, I have another data set with a (average) weekly price of the underlying commodity. The date variables in this dataset are only year and a week number. I

Hi everyone: I did a search over the internet and still couldn't find answer to my problem. I have a series of prices that I'm trying to clean up by removing any prices greater than 3 times the standard deviations. So, say that prices are: price1 2010-06-18 08:00:06.916 2730 2010-06-18 08:00:07.005 2730 2010-06-18 08:00:07.005 2729 2010-06-18 08:00:07.451