yc BR

S_yc_BR.R

yc_get <- function(first_date, last_date) {
  
  first_date <- as.Date(first_date)
  last_date <- as.Date(last_date)
  
  # find biz days in between
  br_cal <- get_calendar()
  
  date_vec <- bizdays::bizseq(first_date, last_date, br_cal)
  
  df_yc <- dplyr::bind_rows(
    purrr::map(date_vec, get_single_yc)
  )
  
  return(df_yc)
  
}

get_calendar <- function() {
  br_cal <- bizdays::create.calendar("Brazil/ANBIMA", 
                                     bizdays::holidaysANBIMA, 
                                     weekdays=c("saturday", "sunday"))
  
  return(br_cal)
}

get_single_yc <- function(ref_date) {
  
  cli::cli_alert_info('Fetching Yield Curve for {ref_date}'  )
  
  base_url <- stringr::str_glue(
    "https://www2.bmf.com.br/pages/portal/bmfbovespa/lumis/lum-taxas-referenciais-bmf-ptBR.asp?",
    "Data={format(ref_date, '%d/%m/%Y')}&Data1={format(ref_date,'%Y%m%d')}&slcTaxa=PRE"
  )
  
  char_vec <- rvest::read_html(base_url) |>
    rvest::html_nodes("td") |>
    rvest::html_text()
  
  len_char_vec <- length(char_vec)

  
  if (len_char_vec == 0) {
    cli::cli_alert('can\'t find data for this date..')
    return(dplyr::tibble())
  } else {
    cli::cli_alert_success('\tsucess, got {len_char_vec} data points')
  }
  
  idx1 <- seq(1, length(char_vec), by = 3)
  idx2 <- seq(2, length(char_vec), by = 3)
  idx3 <- seq(3, length(char_vec), by = 3)
  
  biz_days <- char_vec[idx1]
  r_252 <- char_vec[idx2]
  r_360 <- char_vec[idx3]
  
  my_locale <- readr::locale(decimal_mark = ',')
  br_cal <- get_calendar()
  
  df_single_yc <- dplyr::tibble(
    ref_date,
    biz_days = as.integer(biz_days),
    forward_date =  bizdays::add.bizdays(ref_date, biz_days, br_cal),
    r_252 = readr::parse_double(r_252, locale = my_locale)/100,
    r_360 = readr::parse_double(r_360, locale = my_locale)/100
  )
  
  return(df_single_yc)
}

first_date <- Sys.Date() - 10
last_date <- Sys.Date()

df_yc <- yc_get(first_date, last_date)

library(tidyverse)
graphics.off()

p <- ggplot(df_yc, 
            aes(x = biz_days,
                y = r_360,
                color = factor(ref_date))) + 
  geom_line()

x11() ; p

p <- ggplot(df_yc, 
            aes(x = biz_days,
                y = r_252,
                color = factor(ref_date))) + 
  geom_line()

x11() ; p