Allocation of Investments by Country as of 02/2023

library(quantmod) library(PortfolioAnalytics) # Define the portfolio symbols symbols <- c( "EWJ", #iShares Japan "EWG", #iShares Germany "EWU", #iShares UK "EWC", #iShares Canada "EWY", #iShares South Korea "EWA", #iShares Australia "EWH", #iShares Hong Kong "EWS", #iShares Singapore "EWT", #iShares Taiwan "EWZ", #iShares Brazil "EFA", #iShares EAFE "ERUS", #iShares Russia "EZA", #iShares South Africa "EPP", #iShares Pacific Ex Japan "FXI" ,#iShare China Large-Cap "SPY" #US ) # Fetch the closing prices #prices <- data.frame(lapply(symbols, function(sym) Ad(getSymbols(sym, auto.assign = FALSE)))) prices <- data.frame(Date = as.Date("1970-01-01")) for (sym in symbols) { sym_data <- data.frame(Date = index(getSymbols(sym, auto.assign = FALSE)), Ad(getSymbols(sym, auto.assign = FALSE))) colnames(sym_data)[-1] <- sym prices <- merge(prices, sym_data, by = "Date", all = TRUE) } # Define the portfolio portfolio <- portfolio.spec(assets = symbols) # Add constraints portfolio <- add.constraint(portfolio, type = "weight_sum", min_sum = 0.95, max_sum = 1.05) portfolio <- add.constraint(portfolio, type = "box", min = 0.01, max = 0.5) # Define the optimization objective portfolio <- add.objective(portfolio, type = "risk", name = "var", arguments = list(p = 0.95)) library(xts) # Set the date column as row names rownames(prices) <- prices$Date prices$Date <- NULL # Convert to a time series object prices_xts <- xts(prices, order.by = as.Date(rownames(prices))) names(prices_xts) <-c("Japan","Germany","UK","Canada","South Korea","Australia","Hong Kong", "Singapore","Taiwan","Brazil","EAFE","Russia","South Africa","Pacific Ex Japan", "China","U.S.") tail(prices_xts) # Run the portfolio optimization opt_portfolio <- optimize.portfolio(prices_xts, portfolio) # Optimize the portfolio #opt_portfolio <- optimize.portfolio(prices, portfolio) # Display the optimized weights print(opt_portfolio$weights) opt_portfolio #Create a vector of values for the pie chart values <- c(opt_portfolio$weights) #Create a vector of labels for the pie chart labels <- c("Japan", "Germany", "UK", "Canada", "South Korea", "Australia", "Hong Kong", "Singapore", "Taiwan", "Brazil", "EAFE", "Russia", "South Africa", "Pacific Ex Japan", "China", "U.S.") #Create the pie chart pie(values, labels = labels) #Add a title to the pie chart title("Allocation of Investments by Country") percent <- paste0(round(values * 100, 1), "%") legend("topleft", legend = paste(labels, percent, sep = " - "), cex = 0.8, fill = rainbow(length(values)))