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I'm trying to use garchFit from fSeries, with Student or Skewed Student conditionnal distribution. Let's say that eps (vector) is my series of daily log-returns: data(EuStockMarkets) eps = diff(log(EuStockMarkets[,"CAC"])) library(fSeries) g = garchFit(series = eps, formula.var = ~garch(2,2), cond.dist = "dstd") s = g at fit$series All the coefficients are ok (checked with SAS 9.1) except nu (degrees of freedom of the student) and the log-likelyhood. I...

...unexpected behavior. When head(a,n) is applied on data.frame or matrix, it returns a data-frame or matrix with first n obs of *each* variable. When applied to a mts object, it returns first n obs of *first* variable only, not of all... The same for tail(). See: head(freeny) ###mts object head(EuStockMarkets) #is equivalent to: head(EuStockMarkets[,1]) I guess it comes from absence of a head method for mts. Does it seem reasonable to have also a head.mts or did I misunderstand something? Thanks

Dear list-reader, by running the following script: library(zoo) sessionInfo() search() packageDescription("zoo") data(EuStockMarkets) dax <- as.zoo(EuStockMarkets[1:10, "DAX"]) daxr <- diff(log(dax)) identical(as.vector(qnorm(daxr)), qnorm(coredata(daxr))) qqnorm(coredata(daxr)) qqnorm(daxr) qqnorm() produces an error: > qqnorm(daxr) Fehler in if (xi == xj) 0L else if (xi > xj) 1L else -1L : Argument...

Hi 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 0.11 198...

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Hello, Could someone help me to explain the VERY big difference in applying two tests on multivariate normality: library(mvnormtest) data(EuStockMarkets) mshapiro.test(t(EuStockMarkets[15:29,1:4])) Shapiro-Wilk normality test data: Z W = 0.8161, p-value = 0.005955 and library(energy) mvnorm.etest( EuStockMarkets[15:29,1:4] ) Energy test of multivariate normality: estimated parameters data: x, sample size 15, dimension 4, r...

Hello everyone, a problem with the plot.zoo function. In the parameters of the function, cex.lab is ignored. I tried to reduce the size of the yaxis labels by at least 50%. ------------------ Example: sample <- as.zoo(EuStockMarkets) par(las=1) plot.zoo(sample, plot.type="multiple", main="Time Series", xlab="Date", yaxt="n", cex.lab=0.5, xaxs="i") # Try playing with different values for cex.lab par(las=0) --------------- Any hints or suggestions? THX Nico [[alternative...

...ram is so dense with datapoints that they overlap and the entire graph just ends up a solid color. The second histogram 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 co...

...er directly R related. Suppose I have return series ret with mean zero. And I want to fit a Garch(1,1) on this. my is r[t] = h[i]*z[t] h[t] = w + alpha*r[t-1]^2 + beta*h[t-1] I want to estimate the three parameters here; the R syntax is as follows: # download data: data(EuStockMarkets) r <- diff(log(EuStockMarkets))[,"DAX"] r = r - mean(r) # fit a garch(1,1) on this: library(tseries) garch(r) The estimated parameters are given below: ***** ESTIMATION WITH ANALYTICAL GRADIENT ***** Call: garch(x = r) Coefficient(s): a0 a1 b1 4.746e...

Hi, i would like to plot a few hundred .csv files. Each file contains one curve with x,y values to plot. I have been searching for "gnu r read many files qplot" and similar words. I found for loops that use assign to generate one variable containing a dataframe. When i uesed the classic "plot' command i could add the curves with something like for... {

...ess time which excludes weekends and holidays so deltat is not constant. My file looks like the following: date close 2003.0055 47.05 2003.0082 45.71 2003.0164 43.45 2003.0192 42.96 2003.0219 44.56 2003.0247 42.99 2003.0274 42.28 2003.0356 41.74 etc. >From what I saw in the EuStockMarkets file, it appears that they are also using years and fractions of years as the measure of time. How do I read my file and still keep 'date' as the date? Thanks! A. Andres 95 Wellington St W Toronto, Ontario M5J 2N7

Hello, I'm trying to get a few turnpoints for a financial time series. There is a function in pastecs that does that. However, I get a large number of turnpoints: library(pastecs) data(EuStockMarkets) dax <-EuStockMarkets[,1] plot(dax) turnp <-turnpoints(dax) summary(turnp) #gives 925 peaks/pits!!! How can specify to get only 30 turnpoints? Second question: the extract function extract(turnp,30) gives me this: > extract(turnp,30) [1] 0 0 -1 1 0 -1 0 1 -1 0 1 0 0 -1...

...from fGarch library. However, I get the following error message: Error in.garchInitParameters (formula.mean = formula.mean, formula.var = formula.var, ): object "alpha" not found I tried to estimate this model with different series, but I always get this error message. For example, data(EuStockMarkets) dax <- diff(log(EuStockMarkets))[,"DAX"] g=garchFit(formula=~garch(0,1),data=dax,cond.dist="dstd",include.mean=FALSE) Series Initialization: ARMA model: arma Formula mean: ~ arma(0, 0) GARCH model: garch Formula var:...

Hello everybody, I've got a matrix called EUROPEDATA and I want to calculate the adf test statistic (part of the tseries package) on a rolling basis for window my.win on each column; i.e. each column of EUROPEDATA represents a particular variable; for the first column I calculate the adf test statistic for window my.win = 60 for example, roll forward one observation, calculate the adf

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)

Dear R-help, Has anyone implemented sparklines in the strips of a lattice plot? What I have in mind is, say, highlighting that part of a time series that one is examining in more detail in a set of lattice plots. Regads,. Mark Difford. PS: (Andreas Loffler has implemented a simple but functional version for TeX/LaTeX: http://www.tug.org/tex-archive/help/Catalogue/entries/sparklines.html)

To dear Dr Sarkar and anyone that knows about Lattice package, I make 4 graphs by Lattice package. Each of the graphs has two time series. All the series are plotted in plain lines by default, and I would like one series to be in plain line and the other to be in dotted line in each graph. How can I modify the command of xyplot in the following line to achieve this? It seems that

...; overlap and the entire graph just ends up a solid color. The > second histogram 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 l...

...ead (BJsales) Sales Data with Leading Indicator BOD Biochemical Oxygen Demand CO2 Carbon Dioxide uptake in grass plants ChickWeight Weight versus age of chicks on different diets DNase Elisa assay of DNase EuStockMarkets Daily Closing Prices of Major European Stock Indices, 1991-1998 Formaldehyde Determination of Formaldehyde HairEyeColor Hair and Eye Color of Statistics Students Harman23.cor Harman Example 2.3 Harman74.cor Harman Example...