EfficientFrontierPortfolioOptimization/mockJSON.R at main · NAT-9000/EfficientFrontierPortfolioOptimization · GitHub

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library("jsonlite")
#import("jsonlite")
#export("generateJSON")

#### Function that generates a mok JSON file for testing ##########

### Execute function ######
#generateJSON(historicalData, constraintsData, optimizationType, target, dataDirectory)

dataDirectory <- "location of file"
historicalData <- paste0(dataDirectory, "allHistory.csv")
# Historical data to be used. It will take a csv file with historical data of a number of funds.
# Leftmost column must be dates and first row must include some sort of asset identifier.
# It must contain at least 5 consecutive years of daily data.

constraintsData <- paste0(dataDirectory,"constraints.csv")
# The constraints file must be a file where on the leftmost column there is a list of the names of
# assets and next to each name (second column) a percentage maximum allocation (i.e. first row could
# read (GoldFund, 20)).

optimizationType <- "custom"
# One of four possibilities "risk", "riskClass", "return", "custom".
# "risk" optimizes the portfolio to a given volatility level (which will later be chosen as "target")
# "riskClass" optimizes the portfolio to a volatility level out of 1 to 5. 1 corresponding to very low volatility 5 corresponding to 15%.
# "return" optimizes to a chosen level of return. The optimizer will internally cap it at the maximum possible.
# "custom" will not optimize. It will just calculate all statistics for a portfolio with the percentages of allocation entered in the
# constraintsData table.

target <- 7.5
# Double. Must correspond to the chosen method of optimization above.


#### Generating JSON ###########
#generateJSON <-function(csvFile, constraintFile, typeOptimization, target,
#                        resultLocation){
  all_history <-
    read.csv(
      file = historicalData,
      header = TRUE,
      sep = ",",
      dec = ".",
      stringsAsFactors = FALSE,
      na.strings = c("NA")
    )
  n <- ncol(all_history)-1

  history_list <- list()
  for(i in 1:n){
    history_list[[i]] <- data.frame(all_history[ , c(1, i+1)])
    names(history_list[[i]])<-c("date", "value")
  }
  percfunds <- read.csv(file=constraintsData,
                        header = FALSE)


  composition_list <- list()
  for(i in 1:n){
    composition_list[[i]] <- list()
    composition_list[[i]]$AssetTypes <- list()
    composition_list[[i]]$AssetRegions <- list()
  }

  fundsList <- list(
    isin = as.vector(percfunds$V1),
    #name = as.vector(percfunds$V2),
    percent = percfunds$V2,
    values = history_list

  )

  mock <- list(
    optimizationMode = optimizationType,
    fundPercentageMode = "custom", #"custom"
    riskPercentage = c(target),
    riskClass = c(target),
    return = c(target),
    optimizationPeriod = c(5),
    LB_active = 0,
    funds = fundsList
   # isinHistoric = isinHistoricList
   #constraint = constraintList,
  )

  write_json(mock, simplyfyVector=TRUE, pretty=TRUE, path = paste0(dataDirectory, paste0("mockfunds")))