As Amit already said, zero is a better answer than -100. log returns don't behave well with -100x compounding returns. This is what is causing Inf/-Inf problems. there is a 'zerofill' utility function available in PerformanceAnalytics to make this replacement easier.
see: ?zerofill If you are *also* having a problem with order.by, your sample data would b e insufficient to reproduce it, since the index in the subset you pasted seems well-formed. If Amit's and my suggestion to replace NA with 0 in your returns doesn't solve the problem, then please reply to this thread with a fully reproducible example (including data e.g. using dput function the or reprex package). Regards, Brian -- Brian G. Peterson http://braverock.com/brian/ Ph: 773-459-4973 IM: bgpbraverock On Tue, 2018-09-25 at 17:03 -0400, Simon Hovmark wrote: > I am trying to run the following optimize.portfolio.rebalancing: > > opt <- optimize.portfolio.rebalancing(R=returns, portfolio=tranch1, > optimize_method="ROI", > #momentFUN = > tranch1_boudt, > rebalance_on = > rebal.freq, > training_period = > training.period, > rolling_window = > rolling.window) > But when I use summary(opt) I get the following error: > > xts(x, order.by = order.by, frequency = frequency, ...) :'order.by' > cannot contain 'NA', 'NaN', or 'Inf' > I can see that other has had a similar problem, but I've not been > able to solve it using their answers. When I sum NA, NaN and InF on > returns$dato I get 0. > > A subset of my data is here: > > dato stock_1 stock_2 stock_3 > 1999-10-14 -0.002006019 0.016164145 -100 > 1999-10-15 0.000000000 0.000000000 -100 > 1999-10-18 -0.036813973 -0.049017341 -100 > 1999-10-19 0.016529302 0.000000000 -100 > 1999-10-20 0.016260521 0.011996238 -100 > 1999-10-21 0.008032172 0.005806736 -100 > 1999-10-22 0.000000000 0.000000000 -100 > 1999-10-25 0.039220713 0.023164955 -100 > 1999-10-26 0.028437935 0.002152853 -100 > 1999-10-27 -0.032291505 0.014941580 -100 > 1999-10-28 0.030420597 0.011061477 -100 > 1999-10-29 0.000000000 0.000000000 -100 > 1999-11-02 0.027702603 -0.003410734 -100 > 1999-11-03 0.007259560 -0.007650743 -100 > 1999-11-04 0.003610112 0.000000000 -100 > 1999-11-05 0.000000000 0.000000000 -100 > 1999-11-08 0.014311514 0.005546033 -100 > 1999-11-09 0.007079676 -0.002373106 -100 > 1999-11-10 0.039763233 0.024512309 -100 > 1999-11-11 -0.001696353 -0.018721296 -100 > 1999-11-12 0.000000000 0.000000000 -100 > And here is my full code. > > rebal.freq <- "years" > training.period <- 0 > rolling.window <- 120 > > returns <- read_excel("HEX.xlsx", sheet = 1, col_names = TRUE) > returns <- xts(returns[,-1], order.by= returns[,1]) > returns <- Return.calculate(returns, method = "log") > returns <- returns[-1,] > > returns[!is.finite(returns)] <- NA > returns[!is.finite(returns)] <- NA > returns <- na.fill(returns, fill = -100) > sum(is.nan(returns$dato)) #returns 0 > sum(is.infinite(returns$dato)) #returns 0 > sum(is.na(returns$dato)) #returns 0 > > fund.names <- colnames(returns) > tranch1 <- portfolio.spec(assets = fund.names) > tranch1 <- add.constraint(portfolio = tranch1, type = "leverage") > tranch1 <- add.constraint(portfolio = tranch1, type = "long_only") > tranch1 <- add.objective(portfolio=tranch1, type="return", > name="mean") > tranch1 <- add.objective(portfolio=tranch1, type="risk", > name="StdDev") > > opt <- optimize.portfolio.rebalancing(R=returns, portfolio=tranch1, > optimize_method="ROI", > #momentFUN = > tranch1_boudt, > rebalance_on = > rebal.freq, > training_period = > training.period, > rolling_window = > rolling.window) > > > summary(opt) > And my sessioninfo: > > R version 3.3.1 (2016-06-21) > Platform: x86_64-apple-darwin13.4.0 (64-bit) > Running under: OS X 10.13.3 (unknown) > > locale: > [1] C > > attached base packages: > [1] stats graphics grDevices > utils datasets methods base > > other attached packages: > [1] RColorBrewer_1.1- > 2 readxl_0.1.1 DEoptimR_1.0- > 8 > [4] > PortfolioAnalytics_1.0.3636 PerformanceAnalytics_1.4.3541 forea > ch_1.4.4 > [7] xts_0.10-1 zoo_1.7-13 > > loaded via a namespace (and not attached): > [1] > compiler_3.3.1 parallel_3.3.1 tools_3.3.1 Rcpp_0.12.9 > codetools_0.2-14 > [6] grid_3.3.1 iterators_1.0.8 DEoptim_2.2-4 lattice_0.20- > 34 > EDIT When I read in the Excel file, then class(returns$Dato) returns > > class(returns$Dato) [1] "POSIXct" "POSIXt" > Then instead of the below > > returns <- xts(returns[,-1], order.by= returns[,1]) > I tried using > > returns <- xts(returns[, -1], order.by=as.Date(paste(returns$Dato, > "%m/%d/%Y"))) > and run the optimization but summary(opt) again returned > > xts(x, order.by = order.by, frequency = frequency, ...) :’order.by' > cannot contain 'NA', 'NaN', or 'Inf' > > > [[alternative HTML version deleted]] > > _______________________________________________ > [email protected] mailing list > https://stat.ethz.ch/mailman/listinfo/r-sig-finance > -- Subscriber-posting only. If you want to post, subscribe first. > -- Also note that this is not the r-help list where general R > questions should go. > _______________________________________________ [email protected] mailing list https://stat.ethz.ch/mailman/listinfo/r-sig-finance -- Subscriber-posting only. If you want to post, subscribe first. -- Also note that this is not the r-help list where general R questions should go.
