Indexes Composition and Weights
The composition of B3 indexes are available through the function rb3::index_weights_get. This function returns a data.frame with the current compostion of the requested index, all symbols that compound the index, their weights and theoretical position. Here the IBOVESPA (IBOV) Index has its composition listed.
index_weights_get("IBOV")
#> # A tibble: 92 × 3
#> symbol weight position
#> <chr> <dbl> <dbl>
#> 1 ABEV3 0.0325 4386652506
#> 2 ALPA4 0.00202 202765994
#> 3 AMER3 0.00443 596086291
#> 4 ARZZ3 0.00268 60358029
#> 5 ASAI3 0.0072 795949801
#> 6 AZUL4 0.00253 327646296
#> 7 B3SA3 0.0357 5901731302
#> 8 BBAS3 0.0289 1420731069
#> 9 BBDC3 0.0115 1508883586
#> 10 BBDC4 0.0477 5156077326
#> # … with 82 more rows
The IBr100 Index (IBXX)
index_weights_get("IBXX")
#> # A tibble: 100 × 3
#> symbol weight position
#> <chr> <dbl> <dbl>
#> 1 ABEV3 0.0311 4386652506
#> 2 ALPA4 0.00193 202765994
#> 3 AMBP3 0.00057 43853759
#> 4 AMER3 0.00424 596086291
#> 5 ARZZ3 0.00257 60358029
#> 6 ASAI3 0.00689 795949801
#> 7 AURE3 0.00207 301966318
#> 8 AZUL4 0.00242 327646296
#> 9 B3SA3 0.0342 5901731302
#> 10 BBAS3 0.0277 1420731069
#> # … with 90 more rows
The Small Caps Index (SMLL)
index_weights_get("SMLL")
#> # A tibble: 134 × 3
#> symbol weight position
#> <chr> <dbl> <dbl>
#> 1 AALR3 0.00281 42288232
#> 2 ABCB4 0.00449 67449065
#> 3 AERI3 0.00173 227070796
#> 4 AESB3 0.0106 324190156
#> 5 AGRO3 0.0049 51771532
#> 6 ALSO3 0.00737 122470927
#> 7 ALUP11 0.0132 140050337
#> 8 AMAR3 0.00129 154147193
#> 9 AMBP3 0.00413 43853759
#> 10 ANIM3 0.00478 272558877
#> # … with 124 more rows
Index Composition
rb3::index_comp_get returns a vector with symbols that compound the given index.
index_comp_get("SMLL")
#> [1] "AALR3" "ABCB4" "AERI3" "AESB3" "AGRO3" "ALSO3" "ALUP11" "AMAR3"
#> [9] "AMBP3" "ANIM3" "ARML3" "ARZZ3" "AZUL4" "BEEF3" "BKBR3" "BLAU3"
#> [17] "BMOB3" "BOAS3" "BPAN4" "BRAP3" "BRAP4" "BRML3" "BRPR3" "BRSR6"
#> [25] "CAML3" "CASH3" "CBAV3" "CEAB3" "CLSA3" "COGN3" "CSMG3" "CURY3"
#> [33] "CVCB3" "CYRE3" "DESK3" "DIRR3" "DMMO3" "DXCO3" "ECOR3" "EMBR3"
#> [41] "ENAT3" "ENBR3" "ENJU3" "ESPA3" "EVEN3" "EZTC3" "FESA4" "FHER3"
#> [49] "FLRY3" "GETT11" "GFSA3" "GGPS3" "GMAT3" "GOAU4" "GOLL4" "GRND3"
#> [57] "GUAR3" "HBOR3" "HBSA3" "IFCM3" "IGTI11" "INTB3" "IRBR3" "JALL3"
#> [65] "JHSF3" "KEPL3" "LAVV3" "LEVE3" "LIGT3" "LJQQ3" "LOGG3" "LOGN3"
#> [73] "LWSA3" "MATD3" "MDIA3" "MEAL3" "MEGA3" "MILS3" "MLAS3" "MODL11"
#> [81] "MOVI3" "MRFG3" "MRVE3" "MTRE3" "MYPK3" "NGRD3" "ODPV3" "ONCO3"
#> [89] "OPCT3" "ORVR3" "PARD3" "PCAR3" "PETZ3" "PGMN3" "PNVL3" "POMO4"
#> [97] "POSI3" "PTBL3" "QUAL3" "RANI3" "RAPT4" "RCSL3" "RECV3" "ROMI3"
#> [105] "RRRP3" "SAPR11" "SBFG3" "SEER3" "SEQL3" "SIMH3" "SLCE3" "SMFT3"
#> [113] "SOMA3" "SQIA3" "STBP3" "SULA11" "SYNE3" "TASA4" "TECN3" "TEND3"
#> [121] "TGMA3" "TRAD3" "TRIS3" "TTEN3" "TUPY3" "UNIP6" "USIM3" "USIM5"
#> [129] "VIIA3" "VIVA3" "VLID3" "VULC3" "WIZS3" "YDUQ3"
Index by Segment
rb3::index_by_segment_get returns a data.frame with all stocks that are in the index, their economic segment, weights, position and segment weight in the index.
index_by_segment_get("IBOV")
#> # A tibble: 92 × 6
#> symbol segment weight segme…¹ posit…² refdate
#> <chr> <chr> <dbl> <dbl> <dbl> <date>
#> 1 WEGE3 Bens Indls / Máqs e Equips 0.0276 0.0276 1.48e9 2022-12-14
#> 2 EMBR3 Bens Indls / Mat Transporte 0.00512 0.00512 7.35e8 2022-12-14
#> 3 AZUL4 Bens Indls/Transporte 0.00175 0.0196 3.28e8 2022-12-14
#> 4 CCRO3 Bens Indls/Transporte 0.00598 0.0196 1.12e9 2022-12-14
#> 5 ECOR3 Bens Indls/Transporte 0.0007 0.0196 3.34e8 2022-12-14
#> 6 GOLL4 Bens Indls/Transporte 0.00073 0.0196 1.90e8 2022-12-14
#> 7 RAIL3 Bens Indls/Transporte 0.0105 0.0196 1.22e9 2022-12-14
#> 8 POSI3 Comput e Equips 0.0003 0.0003 7.36e7 2022-12-14
#> 9 BRFS3 Cons N Básico / Alimentos Process… 0.00402 0.0209 1.08e9 2022-12-14
#> 10 JBSS3 Cons N Básico / Alimentos Process… 0.0122 0.0209 1.13e9 2022-12-14
#> # … with 82 more rows, and abbreviated variable names ¹segment_weight,
#> # ²position
Indexes Time Series
rb3 downloads data from B3 website to build time series for B3 indexes.
The function rb3::index_get downloads data from B3 for the given index name and returns data structured in a data.frame. The index names are obtained with rb3::indexes_get function.
index_name <- "IBOV"
index_data <- index_get(index_name, as.Date("2019-01-01"))
head(index_data)
#> # A tibble: 6 × 3
#> refdate index_name value
#> <date> <chr> <dbl>
#> 1 2019-02-01 IBOV 97861.
#> 2 2019-03-01 IBOV 94604.
#> 3 2019-04-01 IBOV 96054.
#> 4 2019-07-01 IBOV 101340.
#> 5 2019-08-01 IBOV 102126.
#> 6 2019-10-01 IBOV 104053.
The returned data.frame has three columns: refdate, index_name and value.
index_data |>
ggplot(aes(x = refdate, y = value)) +
geom_line() +
labs(
x = NULL, y = "Index",
title = str_glue("{index_name} Historical Data"),
caption = str_glue("Data imported using rb3")
)
The IBOVESPA index starts at 1968 and the series is adjusted for all economic events the that affected the Brazilian currency in the 80-90’s decades.
index_data <- index_get(index_name, as.Date("1968-01-01"))
index_data |>
ggplot(aes(x = refdate, y = value)) +
geom_line() +
scale_y_log10() +
labs(
x = NULL, y = "Index (log scale)",
title = str_glue("{index_name} Historical Data - since 1968"),
caption = str_glue("Data imported using rb3")
)
The y-axis was transformed to log scale in order to get the visualization improved.
Change index_name to get data for other indexes, for example, the Small Caps Index SMLL.
index_name <- "SMLL"
index_data <- index_get(index_name, as.Date("2010-01-01"))
index_data |>
ggplot(aes(x = refdate, y = value)) +
geom_line() +
labs(
x = NULL, y = "Index",
title = str_glue("{index_name} Historical Data"),
caption = str_glue("Data imported using rb3")
)
