R/DataForEstimation.R

In MultiATSM: Multicountry Term Structure of Interest Rates Models

#' Retrieves data from Excel and build the database used in the model estimation
#'
#' @param t0 Start date of the sample period in the format yyyy-mm-dd.
#' @param tF End date of the sample period in the format yyyy-mm-dd.
#' @param Economies A character vector containing the names of the economies included in the system.
#' @param N Integer. Number of country-specific spanned factors.
#' @param FactorLabels String-list based which contains the labels of all the variables present in the model
#' @param ModelType String-vector containing the label of the model to be estimated
#' @param DataFrequency Character-based-vector. Available options are: "Daily All Days", "Daily Business Days", "Weekly", "Monthly", "Quarterly", "Annually"
#' @param W_type Three possibilities:
#' \itemize{
#'      \item \code{Full Sample}: if one wishes ALL weight matrices of each year from which data is available (it may extrapolate the sample period);
#'      \item \code{Sample Mean}: if one wishes a SINGLE weight matrix containing the average of weights over of the entire sample period;
#'      \item Some year in particular (e.g. "1998", "2005" ...).
#' }
#' @param t_First_Wgvar Sample starting date (year)
#' @param t_Last_Wgvar Sample last date (year)
#' @param DataPathMacro Path of the Excel file containing the macroeconomic data (if any). The default is linked to the excel file present in the package.
#' @param DataPathYields Path of the Excel file containing the yields data (if any). The default is linked to the excel file present in the package.
#' @param DataPathTrade Path of the Excel file containing the trade data (if any). The default is linked to the excel file present in the package.
#'
#' @return A list containing the
#' \enumerate{
#' \item time series of the complete set of bond yields (matrix, J x T or CJ x T);
#' \item time series of the complete set risk factors (matrix, K x T);
#' \item 'GVARFactors': list of all variables that are used in the estimation of the VARX \cr
#'                (see e.g. \code{CM_Factors_GVAR} file). If the estimated model type is not GVAR-based, then returns NULL.
#' }
#'
#' @seealso \code{\link{InputsForOpt}}
#'
#' @examples
#' DomVar <- c("Eco_Act", "Inflation")
#' GlobalVar <- c("GBC", "CPI_OECD")
#' t0 <- "2006-09-01"
#' tF <-  "2019-01-01"
#' Economies <- c("China", "Brazil", "Mexico", "Uruguay", "Russia")
#' N <- 2
#' ModelType <- "JPS original"
#' FactorLabels <-  LabFac(N, DomVar, GlobalVar, Economies, ModelType)
#' DataFrequency <- "Monthly"
#'
#' DataModel <- DataForEstimation(t0, tF, Economies, N, FactorLabels, ModelType, DataFrequency)
#'
#' @export

DataForEstimation <- function(t0, tF, Economies, N, FactorLabels, ModelType, DataFrequency, W_type= NULL,
                              t_First_Wgvar= NULL, t_Last_Wgvar = NULL, DataPathMacro = NULL, DataPathYields = NULL,
                              DataPathTrade = NULL) {

  C <- length(Economies)

  # Compute the transition matrix if the model is GVAR-based
  if (any(ModelType == c('GVAR single','GVAR multi'))) {
    Wgvar <- Transition_Matrix(t_First_Wgvar, t_Last_Wgvar, Economies, W_type, DataPathTrade)
  }

  # Prepare the database
  FactorSet <- DatabasePrep(t0, tF, Economies, N, FactorLabels, ModelType, Wgvar, DataPathMacro, DataPathYields)

  # Gather all bond yields of all countries
  Yields <- c()
  for (i in 1:C) {
    if (i == 1) {
      Yields <- FactorSet[[Economies[i]]]$Yields
    } else {
      Yields <- rbind(Yields, FactorSet[[Economies[i]]]$Yields)
    }
  }

  # Gather the spanned and unspanned factors
  RiskFactors <- RiskFactorsPrep(FactorSet, Economies, FactorLabels, t0, tF, DataFrequency)

  # Gather the factors used in the GVAR estimation
  if (any(ModelType == c('GVAR single', 'GVAR multi'))) {
    GVARFactors <- DataSet_BS(ModelType, RiskFactors, Wgvar, Economies, FactorLabels)
  } else {
    GVARFactors <- NULL
  }

  Outputs <- list(Yields, RiskFactors, GVARFactors)
  names(Outputs) <- c("Yields", "RiskFactors", "GVARFactors")

  return(Outputs)
}