Useful Financial R packages I've come across

Intro

I’ve been doing side project. One of the area I am interested in financial securities mostly stocks, ETFs, REITs, and options.

I came across congress financial security trading records. I cleaned the data and currently figuring out what the response / outcome column is.

I came across a few R packages along the way that have been useful for me for this endearvour and I’d like to share them. All these R packages was found through a youtube tutorial.

Packages

Adorable toddler and bear

RQuantLib Package

This package is very useful for getting and finding all trading dates of the US market.

Example:

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# 2023-11-15 - Wednesday
# 2023-11-12 - Sunday
RQuantLib::isBusinessDay(
  calendar = "UnitedStates/NYSE", 
  dates = as.Date(c('2023-11-15','2023-11-12')))
# Output: [1]  TRUE FALSE

Source: https://github.com/eddelbuettel/rquantlib

Of course Dirk Eddelbuettel is involved. The dude is a legend in R circle (and anything related to C++ and R crossover).

rvest Package

It’s a webscraping package.

I used this to grab the EPS and earning dates to create a response/outcome variable for congress trading dataset.

Credit for the code. quantRoom youtube.

Example:

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###
# get EPS by Ticker - includes Earning date
###

getEPS <- function(ticker) {
  Sys.sleep(3)
  url <- paste0(
    "https://finance.yahoo.com/calendar/earnings/?symbol=",
    ticker)
  # read in page html
  pg <- rvest::read_html(url)
  # locate table
  TABLE <- 
    pg %>%
    rvest::html_nodes("table") %>%
    rvest::html_table()
  # row bind results and convert to data.frame
  TABLE <- as.data.frame(t(do.call(rbind,TABLE[[1]])))
  # remove timezone from Earnings Date
  TABLE$`Earnings Date` <- gsub("EST","",TABLE$`Earnings Date`)
  TABLE$`Earnings Date` <- gsub("EDT","",TABLE$`Earnings Date`)
  # fix Earning Date/time
  TABLE$`Earnings Date` <- 
    as.POSIXct(TABLE$`Earnings Date`, 
               format = "%b %d, %Y, %I %p", 
               tz = "EST")
  # fix EPS
  TABLE$`EPS Estimate` <- as.numeric(TABLE$`EPS Estimate`) %>% 
    suppressWarnings()
  TABLE$`Reported EPS` <- as.numeric(TABLE$`Reported EPS`) %>% 
    suppressWarnings()
  # fix earning surprise percentage
  TABLE$`Surprise(%)` <- (
    as.numeric(gsub("\\+","",TABLE$`Surprise(%)`)) %>% 
    suppressWarnings()
  )/100
  # return ALL
  TABLE
}

EPS <- getEPS(ticker="ADM")