B3 is the main financial exchange in Brazil,
offering access to trading systems for stocks, futures, options, and
other financial instruments. The rb3 package provides tools for
downloading, processing, and analyzing market data from B3, including:
- Stocks & Equities: Historical price data through COTAHIST files
- Futures Contracts: Settlement prices for futures contracts
- Yield Curves: Historical yield curves calculated from futures contracts
- ETFs & BDRs: Data for Exchange Traded Funds and Brazilian Depositary Receipts
- REITs (FIIs): Data for Brazilian Real Estate Investment Trusts
- Options: Equity and index options contracts
- Market Indices: B3 indices composition and historical data
The package uses webscraping tools to obtain data directly from B3’s website, making it accessible in R as structured datasets. These datasets are valuable for financial analysis, academic research, and investment decision-making.
# From CRAN (stable version)
install.packages("rb3")
# Development version from GitHub
if (!require(devtools)) install.packages("devtools")
devtools::install_github("ropensci/rb3")
The rb3 package uses a template system to standardize the downloading
and processing of different data types. To see available templates:
library(rb3)
# List available templates
list_templates()
#> # A tibble: 5 × 4
#> Description Template Reader Downloader
#> <chr> <chr> <chr> <chr>
#> 1 Arquivo de Preços de Mercado - BVBG-086 b3-bvbg… ✅ ✅
#> 2 Cotações Históricas do Pregão de Ações - Arquivo D… b3-cota… ✅ ✅
#> 3 Cotações Históricas do Pregão de Ações - Arquivo A… b3-cota… ✅ ✅
#> 4 Preços de Ajustes Diários de Contratos Futuros b3-futu… ✅ ✅
#> 5 Taxas referenciais b3-refe… ✅ ✅
The main function for fetching data is fetch_marketdata(), which
downloads data based on a template and parameters:
# Download yield curve data for specific dates
library(bizdays)
fetch_marketdata("b3-reference-rates",
refdate = bizseq("2024-01-01", "2024-01-31", "Brazil/B3"),
curve_name = c("PRE", "DIC")
)
# Download yearly COTAHIST files
fetch_marketdata("b3-cotahist-yearly", year = 2023)
# Access the data
ch <- cotahist_get("yearly")
# Filter for stocks
eq <- ch |>
filter(year(refdate) == 2023) |>
cotahist_filter_equity()
# Get top 10 most traded stocks
symbols <- eq |>
group_by(symbol) |>
summarise(volume = sum(volume)) |>
arrange(desc(volume)) |>
head(10) |>
pull(symbol)
# Access yield curve data
library(ggplot2)
# Get Brazilian nominal yield curve (PRE)
yc_data <- yc_brl_get() |>
filter(refdate == "2024-01-31") |>
collect()
# Plot the yield curve
ggplot(yc_data, aes(x = forward_date, y = r_252)) +
geom_line() +
labs(
title = "Brazilian Yield Curve (PRE)",
x = "Forward Date",
y = "Annual Interest Rate"
) +
scale_y_continuous(labels = scales::percent)
# Get futures settlement prices
futures_data <- futures_get() |>
filter(commodity == "DI1") |>
collect()
# Calculate implied rates
di1_futures <- futures_data |>
mutate(
maturity_date = maturity2date(maturity_code),
business_days = bizdays(refdate, maturity_date, "Brazil/ANBIMA"),
implied_rate = (100000 / price)^(252 / business_days) - 1
)
For comprehensive documentation and examples, visit:
- Package Website
- Vignettes (in-depth tutorials):
If you use rb3 in your research, please cite it:
To cite rb3 in publications use:
Download and parse public files released by B3 and convert them into
useful formats and data structures common to data analysis
practitioners.
A BibTeX entry for LaTeX users is
@Manual{rb3-package,
title = {Download and Parse Public Data Released by B3 Exchange},
author = {Wilson Freitas and Marcelo Perlin},
year = {2023},
note = {R package version 0.0.8},
url = {https://github.com/ropensci/rb3},
}