Where you are using data / data.frame use na.omit(data) na.omit(df) instead it will remove the rows with NAs or any market/asset. If you want to replace with zeroes etc instead of losing rows where NAs are included in your data, there are other options to transform missing data using is.na()
https://stats.idre.ucla.edu/r/faq/how-does-r-handle-missing-values/ Best Regards ______________________________ Amit Mittal Ph.D. in Finance and Accounting (tbd) Indian Institute of Management, Lucknow http://ssrn.com/author=2665511 Mob: +91 7899381263 ______________________________ ________________________________ From: R-SIG-Finance <[email protected]> on behalf of Simon Hovmark <[email protected]> Sent: Wednesday, September 26, 2018 2:33:12 AM To: [email protected] Subject: [R-SIG-Finance] xts 'order.by' cannot contain 'NA', 'NaN', or 'Inf' in optimize.portfolio.rebalancing 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 foreach_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. [[alternative HTML version deleted]]
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