similar to: Acknowledgments in package documentation

R-devel, I'm in the process of choosing a name for a new package. I've already decided that the name will have two parts, 'portfolio' and 'sim', but can't decide between 'portfolioSim' and 'portfolio.sim'. Is there any good reason to choose one over the other? Thanks in advance, Jeff -- Jeff Enos Kane Capital Management jeff at kanecap.com

We would like to announce the availability of the 'portfolio' package in R for analysing equity portfolios. Version 0.2-0 is now available on CRAN. To take a look, you can: > install.packages("portfolio") ... > vignette("portfolio") and play around. Those who would just like to check out an introduction can simply look at:

We would like to announce the availability of the 'portfolio' package in R for analysing equity portfolios. Version 0.2-0 is now available on CRAN. To take a look, you can: > install.packages("portfolio") ... > vignette("portfolio") and play around. Those who would just like to check out an introduction can simply look at:

R-devel, I'm interested in looking at some examples of existing R packages that rely heavily on S4 classes to get a feel for varying styles and package organization techniques. Could you recommend any packages that might serve as a good starting point? Thanks in advance, Jeff

R-devel, I'm interested in looking at some examples of existing R packages that rely heavily on S4 classes to get a feel for varying styles and package organization techniques. Could you recommend any packages that might serve as a good starting point? Thanks in advance, Jeff

I''m a total Rails newbie and i''ve been struggling for hours today with one (prolly very silly) problem: I have a table portfolios that has many images: class Portfolio < ActiveRecord::Base has_many :images end class Image < ActiveRecord::Base belongs_to :portfolios end In the controller i define a list of active portfolios: @active_portfolios =

Hi everyone! I have a data frame with 1112 time series and I am going to randomly sampling r samples for z times to compose different portfolio size(r securities portfolio). As for r=2 and z=10000,that's: z=10000 A=seq(1:1112) x1=sample(A,z,replace =TRUE) x2=sample(A,z,replace =TRUE) M=cbind(x1,x2) # combination of 2 series Because in a portfolio with x1[i]=x2[i],(i=1,2,...,10000) means a 1

[whit at linuxsvr R.packages]$ sudo R CMD INSTALL portfolio.construction * Installing to library '/usr/local/lib64/R/library' * Installing *source* package 'portfolio.construction' ... ** R ** preparing package for lazy loading Loading required package: fts Loading required package: quadprog Loading required package: Rexcelpoi terminate called after throwing an instance of

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

Dear sir, I am extremely sorry for messing up the logic asking for help w.r.t. my earlier mails   I have tried to explain below what I am looking for.     I have a database (say, currency_rates) storing datewise currency exchange rates with some base currency XYZ.   currency_rates <- data.frame(date = c("12/31/2010", "12/30/2010", "12/29/2010",

Hello, After installing and loading the package "portfolio", I tried to run the example code provided, and it would not run. this is the link: http://rss.acs.unt.edu/Rdoc/library/tseries/html/portfolio.optim.html this is the example code, as found at the link: x <- rnorm(1000) dim(x) <- c(500,2) res <- portfolio.optim(x) res$pw the error I get is: Error: could not find

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

Below I have written out some simplified data from my dataset. My goal is to interpolate Price based on timestamp. Therefore the closer a Price is in time to another price, the more like that price it will be. I want the interpolations for each St and not across St (St is a factor with levels A, B, and C). Unfortunately, I get error messages from code I wrote. In the end only IDs 10 and 14 will

Hi, I need some help with Portfolio Optimization problem. I am trying to find the minimum variance portfolio subjected to constraints on weights like /x1< w1 <x2 x3< w2 <x4</i> I need help with solving for the minimum variance portfolio as solve.QP doesn't allow me to specify the lower boundaries. Thanks Mahesh -- View this message in context:

Hi Has someone got a package/script at hand to do a historical simulation to calculate the Value at Risk? If your not sure what Historical Simulation is: In simple terms, Historical Simulation (HS) is just taking sample percentiles over a moving sample. Suppose we want to use HS to predict a portfolio's Value-at-Risk at a confidence level of 99 percent and the window size is chosen to be 250

How to use R to solve the optimisaton problem Minimize: ?*w^T*omega*w+mu^T*w+c^T(w-w0) for w>w0 long position ?*w^T*omega*w+mu^T*w-c^T(w-w0) for w<w0 short position W: is the update weight of portfolio Wo is the initial weight of portfolio Omega is the variance covariance matrix mu is the vector of return rate of stocks in the portfolio C is the vector coefficient of transaction cost

Can someone verify for me if the for loop below is really calculating the nonzero min for each row of a matrix? I have a bug somewhere in the is section of code. My first guess is how I am find the the nonzero min of each row of my matrix. The overall idea is to make sure I am investing all of my money, i.e. new.set is a set of indicator variables for each stock for a particular portfolio, i.e.

Hi, I'm an R newbie and I've been struggling with a optimization problem for the past couple of days now. Here's the problem - I have a matrix of expected payouts from different stock option strategies. Each column in my matrix represents a different stock and each row represents the return to the strategy given a certain market move. So the rows are not a time series of percentage

Hi all, I am currently optimising a small portfolio I have created as a part of my research project in Excel. I am unable to find the appropriate package to port this into R. My problem set up is as follows Minimise ABS(Sum(Xi-Xi')+10*Sum(XiMi)/Mavg) Subject to: 0 <= Xi <= 0.05 ABS(Sum(Xi)) = 0.2 where Mi - Market Cap of Stock i Xi - Initial weight of Stock i Xi' - New weight of

Dear R users. I have zoo object "size_june" containing market-capital values: > dim(size_june) # market-cap data of 625 firms for 20 years [1] 20 625 > class(size_june) [1] "zoo" > size_june # colnames = "size.firmcode" size.34020 size.4710 size.11050 size.10660 size.9540 size.8060 size.16160 size.8080 size.9280 1988-06-30 NA