Welcome the the second vignette for the insiderTrades package. If it is your first time using the package, it is best to read through the insiderTrades vignette which will introduce you to the different types of transactions (and the associated scrapers) and the variables that are included in the final dataframe. This vignette builds upon the insiderTrades vignette in two ways. First, the family of scrapers that integrate both the pull from the SEC website and the scrape are introduced. Second, how to use key words in determining which filings to scrape is introduced.
Release version (CRAN)
Development version (GitHub):
The functions that integrate both the pull from SEC and the scraping are the following:
All of the scraping functions (not just the pullAndScrape functions) have the ability to use key words to determine if a transaction should be included in the final dataframe. The different types of keywords are the following:
An important item of note is that a transaction will be included as long as it fulfills only one of the key words. Thus a good way to think about the key words is that they are connected by OR rather than by AND. Thus any transaction that contains "gift" or "charity" or "charitable" in the footnotes or contains the name "SMITH" or is a gift transaction will be included.
library(insiderTrades) dat1 <- insiderTrades::nonderivativeHoldingsPullAndScrape(quarter = 1, year = 2021, form = 4, name = "Your Name", email = "YourEmail@YourEmail.com", footnoteKeywords = c("gift", "charity", "charitable"), transactionType = "G", rptOwnerKeywords = "SMITH") dat2 <- insiderTrades::nonderivativeHoldingsPullAndScrape(quarter = 1, year = 2021, form = 4, name = "Your Name", email = "YourEmail@YourEmail.com", footnoteKeywords = c("gift", "charity", "charitable"))
As mentioned in the insiderTrades vignette, it takes 22-24 hours for the functions to check for keywords and wrangle the desired transactions into a dataframe for each quarter. Throughout the run, you will get percent completion updates.