This function allows you to obtain daily interbank money market rates and volumes of transactions according to tenure. (2015 - present) from the BNM API.
Usage
get_interest_volume(
product = "money_market_operations",
date = NULL,
year = NULL,
month = NULL
)Arguments
- product
One of "money_market_operations", "interbank" or "overall"
- date
Character string of date with format as defined by RFC 3339, section 5.6 (YYYY-MM-DD). If specified, return values for the specified date.
- year
Year and month as integers. If date, year and month left blank, return today's values.
- month
Year and month as integers. If date, year and month left blank, return today's values.
Examples
if (FALSE) get_interest_volume()
get_interest_volume(date = "2018-01-01")
#> # A tibble: 1 x 5
#> date overnight `1_week` `1_month` other
#> <chr> <int> <int> <int> <int>
#> 1 2018-01-01 33100 1430 200 5030
get_interest_volume(year = 2016, month = 2)
#> # A tibble: 29 x 8
#> date overnight `1_week` `1_month` `3_month` `6_month` `1_year` other
#> <chr> <int> <int> <int> <lgl> <lgl> <lgl> <int>
#> 1 2016-02-01 32000 3860 NA NA NA NA 3140
#> 2 2016-02-02 32000 1860 7030 NA NA NA 4355
#> 3 2016-02-03 32000 NA NA NA NA NA 4180
#> 4 2016-02-04 32000 3000 NA NA NA NA NA
#> 5 2016-02-05 30000 NA NA NA NA NA 3050
#> 6 2016-02-06 30000 NA NA NA NA NA 3050
#> 7 2016-02-07 30000 NA NA NA NA NA 3050
#> 8 2016-02-08 30000 NA NA NA NA NA 3050
#> 9 2016-02-09 30000 NA NA NA NA NA 3050
#> 10 2016-02-10 30000 3800 NA NA NA NA 3280
#> # ... with 19 more rows
get_interest_volume(product = "overall", year = 2016, month = 2)
#> # A tibble: 28 x 8
#> date overnight `1_week` `1_month` `3_month` `6_month` `1_year` other
#> <chr> <dbl> <int> <dbl> <lgl> <lgl> <lgl> <int>
#> 1 2016-02-01 34068. 3860 150 NA NA NA 3362
#> 2 2016-02-02 33709. 2160 7110 NA NA NA 4355
#> 3 2016-02-03 34533. 155 50 NA NA NA 4180
#> 4 2016-02-04 34696. 3290 NA NA NA NA 150
#> 5 2016-02-05 32216. 200 NA NA NA NA 3750
#> 6 2016-02-06 32216. 200 NA NA NA NA 3750
#> 7 2016-02-07 32216. 200 NA NA NA NA 3750
#> 8 2016-02-08 32216. 200 NA NA NA NA 3750
#> 9 2016-02-10 32486. 3900 NA NA NA NA 3530
#> 10 2016-02-11 34464. 2500 NA NA NA NA 1250
#> # ... with 18 more rows