similar to: About the risk code in the fportfolio package

Running R version 2.6.1 under Gentoo Linux and using the fPortfolio package, I am having trouble specifying a sector constraint. One of the constraints to be imposed is that assets 1 and 2 together account for no more than 13.63% of the portfolio. My attempt at coding that constraint, "maxsumW[1:2Assets]=13.63" fails. The relevant section of my code file and the resulting error

Am I missing a Package? I'm not sure why is won't read the functions. Any help is much appreciated. > PData = Data[,3:10] > Spec = portfolioSpec() Error: could not find function "portfolioSpec" > setTargetReturn(Spec) = mean(colMeans(PData)) Error in setTargetReturn(Spec) = mean(colMeans(PData)) : object 'Spec' not found > Constraints =

Hello, I have some simulations of financial data, I have 17 variables simulated 1000 times to three horizons. I am tring to plot the efficient frontier which I already obtained using th fPortfolio package. I am using the following commands: Data=timeSeries(X[1,,]) lppSpec <- portfolioSpec() longFrontier <- portfolioFrontier(Data, lppSpec) plot(longFrontier) Selección: 1 Error en

Could anyone help me with some little problem? When I plot the frontier I get the following message: *"Error in dimnames(x) <- dn : length of 'dimnames' [1] not equal to array extent"*(see below for detail). How could I solve this. Thanks a lot. ##---------------------------- Portfolio construction & Optimisation------------------------ #Assets: LUTAX,

Hello everybody, I'm running into an issue with the fPortfolio package. 1. What I want: Calculate the minimum-variance portfolio on 20 assets with respect to the following constraints: - min weight per asset = 0% (i.e. no short-selling) - max weight per asset = 10% - min sum of asset weights = 100% (i.e. fully invested) - max sum of asset weights = 100% (i.e. no leverage) 2. What I

Hello everyone, I have been spending many hours on a seemingly simple portfolio optimization problem using the package fPortfolio. My optimization problem is slightly different than a standard one such that I have a known set of asset returns. My problem is how to collect this information into my functions and pass them onto the optimization function. I have written my own covariance estimation

I'm trying to get a reference to this object in C SWX.RET[1:6,c("SBI,"SPI","SII")] While i am able to access and use a plain SWX.RET object, I'm getting confused on how to create an object with the array subscripts like above. Here is what I tried to do. It doesn't work because "[" is obviously not an operation or function on SWX.RET. So how do I

Hi I'm trying to implement something similar to the following R snippet using C. I seem to have hit the wall on accessing class slots using C. library(fPortfolio) lppData <- 100 * LPP2005.RET[, 1:6] ewSpec <- portfolioSpec() nAssets <- ncol(lppData) setWeights(ewSpec) <- rep(1/nAssets, times = nAssets) ewPortfolio <- feasiblePortfolio( data = lppData, spec = ewSpec,

Hello. I am trying to use the portfolio backtesting function in fPortfolio package, but I don't now why in my version of fPortfolio I don't have either the portfolioBactest nor the portfolioBacktesting functions. Does anybody knows what might be going on? thank you Felipe Parra [[alternative HTML version deleted]]

Hello, I would like to do a portfolio optimization in R and I tried to use the function in "fPortfolio", but it appears there does not exist such function. Could anyone give me some advice? Many thanks -- View this message in context: http://www.nabble.com/fPortfolio-Package-tf4492927.html#a12813809 Sent from the R help mailing list archive at Nabble.com.

Hello, I hesitate to call this a bug, because I could have forgotten something important, but the MarkowitzPortfolio example in fPortfolio does not work for me. Here's my code: > library(fPortfolio) > >xmpPortfolio("\nStart: Load monthly data set of returns > ") > data(berndtInvest) > # Exclude Date, Market and Interest Rate columns from data

Dear All, I am using package fPortfolio to run minimum variance portfolio optimizations in R. I already know how to set portfolioSpecs, portfolio objects and constraints. Unfortunately I am not able to set the following type of constraints. I have a timeSeries object with returns data for roughly 1.5k assets for 261 subperiods (workingdays) and want to compute the global minimum variance

Hi - First posting here. I am using fPortfolio to try and optimize a simple portfolio consisting of 5 daily return series. I want to maximize return subject to setTargetRisk(myspec)=0.08 using only constraints="LongOnly" I can run feasiblePortfolio() using a spec file that specifies the weights, and it works fine. When I run maxreturnPortfolio(mydata,myspec,"LongOnly"),

Hello R-help. I believe I may be coding the offset incorrectly in my formula. I am testing significance between different group pairings using the VGAM package. My data are zero-truncated and poisson-distributed and overdispersed, so I'm using the posnegbinomial function in vglm (code below). I've spent a very long time working out this model and am pretty sure it's the best for

I keep expecting R to have something analogous to the =count function in Excel, but I can't find anything. I simply want to count the data for a given category. I've been using the ddply() function in the plyr package to summarize means and st dev of my data, with this code: ddply(NZ_Conifers,.(ElevCat, DataSource, SizeClass), summarise, avgDensity=mean(Density),

Hello, I'm not a Stata user so I'm trying to reproduce Stata results that are given to me in R. I would like to use a GLM with a complementary log-log function. The stata code I have is: glm c IndA fia, family(binomial s) link(cloglog) offset(offset) The R code is: glmt <- glm(data=dataset, c ~ IndA + fia, offset = offset, family = binomial(link = cloglog)) Which yields

Hi I'm getting the following errors while using the efficientPortfolio function even though I'm setting the target return to the mean of the TargetReturn I obtain from the portfolio object created by the feasiblePortfolio function. First Error: Error: targetReturn >= min(mu) is not TRUE Second Error: Error in .rquadprog(Dmat = args$Dmat, dvec = args$dvec, Amat = args$Amat, :

Hello. I don't understand a particular output of portfolio.optim (tseries). I have 4 assets and the portfolio.optim returns an asset with weight equals to zero. If I do a portfolio.optim with 3 assets, without the asset with weight equals to zero, it returns a completely different result. That's I would expected the same weights as the run with 4 assets. Below the code. Thanks in

Hi I have some problems in defining new generic functions and classes. Just have a look at the following example: require(fPortfolio) setClass("PROBECLASS", representation( type="character" ) ) isGeneric("setType<-") #Returns TRUE #I would like to define a specific function for

Hi I have some problems in defining new generic functions and classes. Just have a look at the following example: require(fPortfolio) setClass("PROBECLASS", representation( type="character" ) ) isGeneric("setType<-") #Returns TRUE #I would like to define a specific function for