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qlcal brings the calendaring functionality from the QuantLib project to R.
qlcal lets us access various global (exchange or
settlement) calendars. Here is a quick example for the NYSE in 2022
where Juneteenth is making a first appearance as the most recently added
federal holiday:
> library(qlcal)
> setCalendar("UnitedStates/NYSE")
> getHolidays(as.Date("2022-01-01"), as.Date("2022-12-31"))
[1] "2022-01-17" "2022-02-21" "2022-04-15" "2022-05-30" "2022-06-20"
[6] "2022-07-04" "2022-09-05" "2022-11-24" "2022-12-26"
>This package started as an integration of the (somewhat experimental) Quantuccia package (see next section) to R by means of Rcpp in package RcppQuantuccia. But Quantuccia did not continue beyond its initial proof of concept. So as of RcppQuantuccia release 0.0.5, we have refocused it on an even smaller subset of QuantLib: just the calendaring. So code for pricers, math, models, schedules, … that was in Quantuccia has been removed. The calendaring, along with all its support code, is now current with the current QuantLib release which, as of this writing, is 1.24.
Going forward, the idea is to regroup the QuantLib calendaring
functionality in a small and self-contained library qlcal,
and provide frontends such as this R package.
Here we examine holiday lists for given calendars, specified by country and possibly exchange:
R> library(qlcal)
R> fromD <- as.Date("2017-01-01")
R> toD <- as.Date("2017-12-31")
R> getHolidays(fromD, toD) # default calender ie TARGET
[1] "2017-04-14" "2017-04-17" "2017-05-01" "2017-12-25" "2017-12-26"
R> setCalendar("UnitedStates")
R> getHolidays(fromD, toD) # US aka US::Settlement
[1] "2017-01-02" "2017-01-16" "2017-02-20" "2017-05-29" "2017-07-04" "2017-09-04"
[7] "2017-10-09" "2017-11-10" "2017-11-23" "2017-12-25"
R> setCalendar("UnitedStates::NYSE")
R> getHolidays(fromD, toD) # US New York Stock Exchange
[1] "2017-01-02" "2017-01-16" "2017-02-20" "2017-04-14" "2017-05-29" "2017-07-04"
[7] "2017-09-04" "2017-11-23" "2017-12-25"
R>This shows the difference between the default US settlement calendar and the NYSE calendar which we selected explicitly.
As all calendars are now supported (and are listed in a convenience
vector calendars):
> library(qlcal)
> calendars
[1] "TARGET" "UnitedStates"
[3] "UnitedStates/LiborImpact" "UnitedStates/NYSE"
[5] "UnitedStates/GovernmentBond" "UnitedStates/NERC"
[7] "UnitedStates/FederalReserve" "Argentina"
[9] "Australia" "Austria"
[11] "Austria/Exchange" "Bespoke"
[13] "Botswana" "Brazil"
[15] "Brazil/Exchange" "Canada"
[17] "Canada/TSX" "Chile"
[19] "China" "China/IB"
[21] "CzechRepublic" "Denmark"
[23] "Finland" "France"
[25] "France/Exchange" "Germany"
[27] "Germany/FrankfurtStockExchange" "Germany/Xetra"
[29] "Germany/Eurex" "Germany/Euwax"
[31] "HongKong" "Hungary"
[33] "Iceland" "India"
[35] "Indonesia" "Israel"
[37] "Italy" "Italy/Exchange"
[39] "Japan" "Mexico"
[41] "NewZealand" "Norway"
[43] "Null" "Poland"
[45] "Romania" "Russia"
[47] "SaudiArabia" "Singapore"
[49] "Slovakia" "SouthAfrica"
[51] "SouthKorea" "SouthKorea/KRX"
[53] "Sweden" "Switzerland"
[55] "Taiwan" "Thailand"
[57] "Turkey" "Ukraine"
[59] "UnitedKingdom" "UnitedKingdom/Exchange"
[61] "UnitedKingdom/Metals" "WeekendsOnly"
>We can then for example quickly count number of holiday per calendar (by computing the length of the returned vector of holidays) and show a shortened print, all in a handful of lines continuing from above
> getHols <- function(cal) { # simple helper function
+ setCalendar(cal)
+ getHolidays(as.Date("2022-01-01"), as.Date("2022-12-31"))
+ }
> D <- data.table(calendar=calendars)
> D[ , `:=`(n = length(getHols(calendar)),
+ holidays = paste(format(getHols(calendar),"%d %b"), collapse=",")),
+ by = calendar ]
> D
> D
calendar n holidays
1: TARGET 3 15 Apr,18 Apr,26 Dec
2: UnitedStates 10 17 Jan,21 Feb,30 May,20 Jun,04 Jul,05 Sep,10 Oct,11 Nov,24 Nov,26 Dec
3: UnitedStates/LiborImpact 10 17 Jan,21 Feb,30 May,20 Jun,04 Jul,05 Sep,10 Oct,11 Nov,24 Nov,26 Dec
4: UnitedStates/NYSE 9 17 Jan,21 Feb,15 Apr,30 May,20 Jun,04 Jul,05 Sep,24 Nov,26 Dec
5: UnitedStates/GovernmentBond 11 17 Jan,21 Feb,15 Apr,30 May,20 Jun,04 Jul,05 Sep,10 Oct,11 Nov,24 Nov,26 Dec
---
58: Ukraine 10 03 Jan,07 Jan,08 Mar,25 Apr,02 May,09 May,13 Jun,28 Jun,24 Aug,14 Oct
59: UnitedKingdom 9 03 Jan,15 Apr,18 Apr,02 May,02 Jun,03 Jun,29 Aug,26 Dec,27 Dec
60: UnitedKingdom/Exchange 9 03 Jan,15 Apr,18 Apr,02 May,02 Jun,03 Jun,29 Aug,26 Dec,27 Dec
61: UnitedKingdom/Metals 9 03 Jan,15 Apr,18 Apr,02 May,02 Jun,03 Jun,29 Aug,26 Dec,27 Dec
62: WeekendsOnly 0
>Here we set the year to 2022 as it includes the added US holiday of Juneteenth.
We can also access the calendar ‘name’ from the underlying (QuantLib Calendar) object:
> D[, name := { setCalendar(calendar); getName() }, by=calendar][, .(calendar,name)]
calendar name
1: TARGET TARGET
2: UnitedStates US settlement
3: UnitedStates/LiborImpact US with Libor impact
4: UnitedStates/NYSE New York stock exchange
5: UnitedStates/GovernmentBond US government bond market
---
58: Ukraine Ukrainian stock exchange
59: UnitedKingdom UK settlement
60: UnitedKingdom/Exchange London stock exchange
61: UnitedKingdom/Metals London metals exchange
62: WeekendsOnly weekends only
>The package can be installed from CRAN via
install.packages("qlcal")or if you prefer non-release development version these can be installed from GitHub via e.g.
remotes::install_github("qlcal/qlcal-r")It only requires Rcpp and BH both of which
are available whereever R itself runs.
Note that the package requires C++14 or newer due to the
BH (i.e. Boost) use. As R nags when we set
CXX_STD we switched to requested
R (>= 4.2.0) where this requirement is implicitly
satisfied. On an older R version, the configure scripts
uncomments CXX_STD = CXX14 in src/Makevars (or
src/Makevars.win).
Luigi Ballabio describes Holidays in QuantLib in an introductory article at the Implementing QuantLib blog.
Dirk Eddelbuettel for the package and integration.
The authors and contributors of QuantLib for the underlying calendaring code.
GPL (>= 2)
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.