search for: ftse

I have the following simple for-loop, which makes R crash every time. The length of the vectors is about 1200 rows, 1 column. n = max(length(GSPC),length(FTSE)) for(i in 1:1000) { if (row.names(GSPC)[i]==row.names(FTSE)[i]){ } else { if (row.names(GSPC)[i]>row.names(FTSE)[i]){ GSPC<-rbind(GSPC[1:(i-1),],GSPC[(i-1):length(GSPC),]) row.names(GSPC)[i]=row.names(FTSE)[i] } else { FTSE<-rbind(FTSE[1:(i-1),],FTSE[(i-1):length(FTSE),])...

Dear all, I am looking for a way to work out if a file on the internet exists before attempting to download it using the function download.file(). For example, using a url that does not exist url <- "http://finance.yahoo.com/ftse.csv" destfile <- tempfile() download.file(url = url, destfile = destfile) # gives the following response ... trying URL 'http://finance.yahoo.com/ftse.csv' Error in download.file(url = url, destfile = destfile) : cannot open URL 'http://finance.yahoo.com/ftse.csv' In ad...

Dear All, There is an example for the priceIts function (the its package) which does not work for me as expected. > ?priceIts > x1 <- priceIts(instrument = c("^ftse"), start = "1998-01-01", + quote = "Close") Error in validObject(.Object) : invalid class "its" object: Missing values in dates > x2 <- priceIts(instrument = c("^gdax"), start = "1998-01-01", +...

...still obscures the first. Consider this example: col1 <- adjustcolor("red", alpha.f=0.3) col2 <- adjustcolor("blue", alpha.f=0.3) EU <- data.frame(EuStockMarkets) with(EU, plot(DAX, CAC, col=col2, type="h", ylim=c(0,6000))) par(new=TRUE) with(EU, plot(DAX, FTSE, col=col1, type="h", ylim=c(0,6000))) The density of the red plot around 2000 completely obscures the blue plot behind it. What I would like to do is plot both plots in solid colors, then alpha the entire thing, and then overlay them. Or some other method that achieves a comparable res...

...useRs, I am trying to calculate the Sharpe ratio with "sharpe" of the library "tseries". The documentation requires the univariate time series to be a portfolio's cumulated returns. In this case, the example given data(EuStockMarkets) dax <- log(EuStockMarkets[,"FTSE"]) is however not the cumulated returns but rather the daily returns of the FTSE stock index. Is this way of calculating the Sharpe ratio correct? Here are my own data: year Index PercentReturns 1985 117 0.091 1986 129.9 0.11 1987 149.9 0.154 1988 184.8 0.233...

...(fruit[, 1:5])# only first five used in combinations #X.SSMII = head(fruit[, 6])# Keep it for referebce nmax = NULL n = ncol(mD)# dont take the last column for reference purpose if(is.null(nmax)) nmax = n mDD = apply(combn(5, 1),1, FUN= function(y) mD[, y])# to fg = lm( X.SSMII ~ X.GDAXI + X.FTSE + X.FCHI + X.IBEX, data = mDD )# regress on combos s = cbind(s, Residuals = residuals(fg))# take residuals print(mD) -- View this message in context: http://www.nabble.com/Applying-lm-to-data-with-combn-tp15359204p15359204.html Sent from the R help mailing list archive at Nabble.com.

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...min(EU$DAX) xa <- max(EU$DAX) plot(interleave(EU$DAX, MIN=xi, MAX=xa, N=130, channel=1 ), EU$CAC, col = "#6600EE07", type = "h", ylim = c(0,6000), xlab = "DAX") points(interleave(EU$DAX, MIN = xi, MAX = xa, N = 130, channel = 2 ), EU$FTSE, col = "#EE000007", type = "h") Cheers, B. > On 2018-05-31, at 16:56, Ed Siefker <ebs15242 at gmail.com> wrote: > > I have two chromatograms I want plotted on the same axes. > I would like the plots to be transparent, so the first chart is >...

Hi, I would like to use R to estimate the following model: X(t) = a + b1*X(t-1) + b2*X(t-2) + c1*Y(t) + c2*Y(t-1) + c3*Y(t-2) Is there any R function that performs this type of estimation? I know that if I only have one time series (i.e. lagged value of X) on the right hand side then there are R functions to do the estimation. I am thinking a work around by preparing X(t-1), X(t-2),Y(t),Y(t-1)

...de and hope you could give me some pointers. My aim is to calculate the lm-regression coefficients of individual stocks against an index. I am interested in both the coefficient and the pval. While I could do this manually for a select hand full, I hope to scale this up say for 30+ stocks (DAX-30, FTSE-100 etc.) to eventually have a matrix of coefficients and p-values for each individual stock. First, let's get share prices: library(tseries) sie <- get.hist.quote(instrument="SIE.DE", start="2010-01-01", quote="AdjClose") vow <- get.hist.quote(instrument=...

...adjusted daily returns on a stock # let rmt denote daily returns on the appropriate benchmark e.g. SP500 # rt = alphat + betat * rmt + et # alphat = alphat_1 + n1t # betat = betat_1 + n2t # where et ~ N(0,H) # (n1t,n2t) ~ N(0,Q) #load required packages library(tseries) library(FKF) # load data FTSE100 <- get.hist.quote(instrument = "^FTSE", start = "2007-01-01", quote = "Close", retclass = "zoo", quiet = TRUE) BP <- get.hist.quote(instrument = "BP", start = "2007-01-01", quote = "AdjClose", retclass = "zoo"...

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Hi, R experts. I am a new user of R and trying to learn this program. I have a problem. Here is the code. d<-as.Date(c("2000/01/03","2000/01/05","2000/01/19","2000/01/28")) r<-rnorm(4) da<-data.frame(d,r) a<-as.Date("01/01/2000","%d/%m/%Y") b<-as.Date("30/01/2000","%d/%m/%Y") ab<-seq(a,b,by=1)

...p it for referebce > > nmax = NULL > > n = ncol(mD)# dont take the last column for reference purpose > > if(is.null(nmax)) nmax = n > > > > mDD = apply(combn(5, 1),1, FUN= function(y) mD[, y])# to > > > > > > > > fg = lm( X.SSMII ~ X.GDAXI + X.FTSE + X.FCHI + X.IBEX, data = mDD )# > > regress on combos > > > > s = cbind(s, Residuals = residuals(fg))# take residuals > > > > print(mD) > > > > > > -- > View this message in context: http://www.nabble.com/Applying-lm-to-data-with-combn-tp15359204...