fixed bug in bizdays() #124

ChangeLog

@@ -5,6 +5,7 @@ Version 6.2
   * Fixed bug in accuracy() when non-integer seasonality used.
   * Made auto.arima() robust to non-integer seasonality.
   * Fixed bug in auto.arima where allowmean was ignored when stepwise=FALSE.
+	* Fixed bug in bizdays().
 
 Version 6.1 (11 May 2015)
   * Made auto.arima more robust

R/calendar.R

@@ -1,36 +1,47 @@
-bizdays <- function(x, FinCenter) {
+bizdays <- function(x, FinCenter = c("New York", "London", "NERC", "Tokyo",
+                                     "Zurich")) {
   # Return the number of trading days corresponding to the input ts
   #
   # Args:
   #   x: a ts object
-  #   FinCenter: inherits "FinCenter" from "timeDate" package
+  #   FinCenter: inherits holiday calendar from "timeDate" package
   #
   # Returns:
   #   A matrix contains the number of trading days
   if (is.null(tsp(x))) {
     stop("We cannot handle a time series without time attributes.")
   }
-  if (missing(FinCenter)) {
-    FinCenter <- "GMT"
-  }
   # Convert tsp to date
   freq <- frequency(x)
+  years <- start(x)[1L]:end(x)[1L]
+  # Grab the holidays from years and financial center
+  FinCenter <- match.arg(FinCenter)
+  if (FinCenter == "New York") {
+    holidays <- timeDate::holidayNYSE(years)
+  } else if (FinCenter == "London") {
+    holidays <- timeDate::holidayLONDON(years)
+  } else if (FinCenter == "NERC") {
+    holidays <- timeDate::holidayNERC(years)
+  } else if (FinCenter == "Tokyo") {
+    holidays <- timeDate::holidayTSX(years)
+  } else if (FinCenter == "Zurich") {
+    holidays <- timeDate::holidayZURICH(years)
+  }
   if (freq == 12L) {  # monthly data
     date <- zoo::as.Date(time(x))
     start <- date[1L]
     end <- seq(date[length(date)], length = 2L, by = "month")[2L] - 1L
-    days.len <- as.timeDate(seq(start, end, by = "days"), FinCenter = FinCenter)
+    days.len <- timeDate::timeSequence(from = start, to = end)
     # Grab business days
-    biz <- days.len[isBizday(days.len, 
-                             holidays = unique(format(days.len, "%Y")))]
-    bizdays <- format(biz, format = "%Y %b")
+    biz <- days.len[timeDate::isBizday(days.len, holidays = holidays)]
+    bizdays <- format(biz, format = "%Y-%m")
   } else if (freq == 4L) {  # Quarterly data
     date <- zoo::as.Date(time(x))
     start <- date[1L]
     end <- seq(date[length(date)], length = 2L, by = "3 month")[2L] - 1L
-    days.len <- as.timeDate(seq(start, end, by = "days"), FinCenter = FinCenter)
-    biz <- days.len[isBizday(days.len, 
-                             holidays = unique(format(days.len, "%Y")))]
+    days.len <- timeDate::timeSequence(from = start, to = end)
+    # Grab business days
+    biz <- days.len[timeDate::isBizday(days.len, holidays = holidays)]
     bizdays <- format(as.yearqtr(biz), format = "%Y Qtr%q")
 
   } # else if (freq == 52L) {  # Weekly data

man/bizdays.Rd

@@ -1,16 +1,13 @@
 \name{bizdays}
 \alias{bizdays}
 \title{Number of trading days in each season}
-\usage{bizdays(x, FinCenter)}
+\usage{bizdays(x, FinCenter = c("New York", "London", "NERC", "Tokyo", "Zurich"))}
 
 \arguments{
 \item{x}{Monthly or quarterly time series}
-\item{FinCenter}{A character with the the location of the financial center named as "continent/city". 
-  This concept allows to handle data records collected in different time zones and mix them up to have
-  always the proper time stamps with respect to your personal financial center, or alternatively to the
-  GMT reference time. More details on \code{\link[timeDate]{finCenter}}.}
+\item{FinCenter}{Major financial center.}
 }
-\description{Returns number of trading days in each month or quarter of the observed time period.}
+\description{Returns number of trading days in each month or quarter of the observed time period in a major financial center.}
 
 \details{Useful for trading days length adjustments. More on how to define "business days",
 please refer to \code{\link[timeDate]{isBizday}}.} 
@@ -19,6 +16,7 @@ please refer to \code{\link[timeDate]{isBizday}}.}
 
 \author{Earo Wang}
 \examples{
-  bizdays(wineind, FinCenter = "Sydney")
+  x <-  ts(rnorm(30), start = c(2013, 2), frequency = 12)
+  bizdays(x, FinCenter = "New York")
 }
 \keyword{ts}