rbcb

An interface to information provided by the Brazilian Centra Bank. This package interfaces the Brazilian Central Bank web services to provide data already formatted into R's data structures and download currency data from Brazilian Centra Bank web site.

Install

While it's not on CRAN, the way to get it installed is through devtools

devtools::install_github('wilsonfreitas/rbcb')

Usage

Downloading time series from BCB web services

Download series calling rbcb::get_series passing the time series code is as the first argument. For example, let's download the USDBRL time series which has code = 1.

rbcb::get_series(1)

# A tibble: 8,024 × 2
                  data valor
*               <dttm> <dbl>
1  1984-11-28 12:00:00  2828
2  1984-11-29 12:00:00  2828
3  1984-11-30 12:00:00  2881
4  1984-12-03 12:00:00  2881
5  1984-12-04 12:00:00  2881
6  1984-12-05 12:00:00  2923
7  1984-12-06 12:00:00  2923
8  1984-12-07 12:00:00  2923
9  1984-12-10 12:00:00  2965
10 1984-12-11 12:00:00  2965
# ... with 8,014 more rows

Note that this series starts at 1984 and has approximately 8000 rows. To download recent values you should use the argument last = N, see below.

rbcb::get_series(1, last = 10)

# A tibble: 10 × 2
                  data  valor
*               <dttm>  <dbl>
1  2016-11-28 12:00:00 3.3996
2  2016-11-29 12:00:00 3.4060
3  2016-11-30 12:00:00 3.3967
4  2016-12-01 12:00:00 3.4362
5  2016-12-02 12:00:00 3.4650
6  2016-12-05 12:00:00 3.4598
7  2016-12-06 12:00:00 3.4354
8  2016-12-07 12:00:00 3.3895
9  2016-12-08 12:00:00 3.4008
10 2016-12-09 12:00:00 3.3858

The series can be downloaded as tibble, xts or data.frame, but the default is tibble. See the next example where the Brazilian Broad Consumer Price Index (IPCA) is downloaded as xts object.

rbcb::get_series(433, last = 12, as = 'xts')

                     433
2015-12-01 12:00:00 0.96
2016-01-01 12:00:00 1.27
2016-02-01 12:00:00 0.90
2016-03-01 12:00:00 0.43
2016-04-01 12:00:00 0.61
2016-05-01 12:00:00 0.78
2016-06-01 12:00:00 0.35
2016-07-01 12:00:00 0.52
2016-08-01 12:00:00 0.44
2016-09-01 12:00:00 0.08
2016-10-01 12:00:00 0.26
2016-11-01 12:00:00 0.18

Downloading currency data

Use currency functions to download currency rates from the BCB web site.

get_currency("USD", "2017-03-01", "2017-03-10")

# A tibble: 8 × 3
        date    bid    ask
      <date>  <dbl>  <dbl>
1 2017-03-01 3.0970 3.0976
2 2017-03-02 3.1132 3.1138
3 2017-03-03 3.1358 3.1364
4 2017-03-06 3.1105 3.1111
5 2017-03-07 3.1179 3.1185
6 2017-03-08 3.1471 3.1477
7 2017-03-09 3.1729 3.1735
8 2017-03-10 3.1617 3.1623

The rates come quoted in BRL, so 3.0970 is worth 1 USD in BRL. Trying another currency.

get_currency("JPY", "2017-03-01", "2017-03-10")

# A tibble: 8 × 3
        date     bid     ask
      <date>   <dbl>   <dbl>
1 2017-03-01 0.02726 0.02727
2 2017-03-02 0.02721 0.02722
3 2017-03-03 0.02739 0.02740
4 2017-03-06 0.02734 0.02735
5 2017-03-07 0.02735 0.02736
6 2017-03-08 0.02744 0.02745
7 2017-03-09 0.02762 0.02764
8 2017-03-10 0.02750 0.02751

To see the avaliable currencies call list_currencies.

list_currencies()

# A tibble: 216 × 5
                          name  code symbol          country_name country_code
*                        <chr> <dbl>  <chr>                 <chr>        <dbl>
1            AFEGANE AFEGANIST     5    AFN           AFEGANISTAO          132
2             RANDE/AFRICA SUL   785    ZAR         AFRICA DO SUL         7560
3              LEK ALBANIA REP   490    ALL ALBANIA, REPUBLICA DA          175
4                         EURO   978    EUR              ALEMANHA          230
5                KWANZA/ANGOLA   635    AOA                ANGOLA          400
6        DOLAR CARIBE ORIENTAL   215    XCD              ANGUILLA          418
7        DOLAR CARIBE ORIENTAL   215    XCD     ANTIGUA E BARBUDA          434
8  GUILDER ANTILHAS HOLANDESAS   325    ANG   ANTILHAS HOLANDESAS          477
9            RIAL/ARAB SAUDITA   820    SAR        ARABIA SAUDITA          531
10              DINAR ARGELINO    95    DZD               ARGELIA          590
# ... with 206 more rows

There are 216 currencies available.

Cross currency rates

The API provides a matrix with the relations between exchange rates, this is the matrix of cross currency rates. This is a square matrix with the all exchange rates between all currencies.

x <- get_currency_cross_rates("2017-03-10")
dim(x)

[1] 156 156

Since there are many currencies it is interesting to subset the matrix.

cr <- c("USD", "BRL", "EUR", "CAD")
x[cr, cr]

          USD    BRL       EUR       CAD
USD 1.0000000 3.1623 0.9380896 1.3465764
BRL 0.3162255 1.0000 0.2966479 0.4258218
EUR 1.0659963 3.3710 1.0000000 1.4354454
CAD 0.7426240 2.3484 0.6966479 1.0000000

The rates are quoted by its columns labels, so the numbers in the BRL column are worth one currency unit in BRL.