similar to: Porting optimisation setup from Excel Solver to R

Dear Colleagues, I am attempting to develop an optimization routine for a river suspended sediment mixing model. I have Calcium and Magnesium concentrations (%) for sediments from 4 potential source areas (Topsoil, Channel Banks, Roads, Drains) and I want to work out, based on the suspended sediment calcium and magnesium concentrations, what are the optimal contributions from each source area to

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 all, # consider the following code (please, run it: # it's fully working and requires just few minutes # to finish): require(CreditMetrics) require(clusterGeneration) install.packages("Rdonlp2", repos= c("http://R-Forge.R-project.org", getOption("repos"))) install.packages("Rsolnp2", repos= c("http://R-Forge.R-project.org",

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,

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

I have a set of data for US t-bill returns and US stock returns frm 1980-2012. I am trying to bootstrap the data and obtain the minimum variance portfolio and repeat this portfolio 1000 times. However I am unable to get the correct code function for the minimum variance portfolio. When I tried to enter Opt(OriData+1, 1, 5, 0), I get "error:subscript out of bounds" Please help!

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

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

i am working on the project to analyze hedge fund performance, i would appreciate that if you guys could spare some time helping me out with the R code. Thanks. The senario is: i applied BOXPLOT() to plot the performance of all hedge funds with 7 strategies. And right now in this boxplot I need to plot the points of 30 individual hedge funds from my portfolio. And I applied POINTS() and

Hi R-Group, I am stuck with the following problem: I am constructing a portfolio of 2 variables x and y x <- rnorm(100, mean=100, sd=4) y <- rnorm(100, mean=120, sd=10) which I am combining as follows to a portfolio for sampling purposes: portfolio <- c(rep(x, 8), rep(y, 2)) In this case I have assigned the weights of 8 and 2 to calculate the bootstrapped mean: mean.boot <-