# Libraries
if(!require("pacman")) {
install.packages("pacman")
}
pacman::p_load(
data.table,
scales,
ggplot2,
plotly,
DT)
# Set knitr params
knitr::opts_chunk$set(
comment = NA,
fig.width = 12,
fig.height = 8,
out.width = '100%'
)
# Load annual data only
path <-
"~/Desktop/David/Projects/new_constructs_targets/_targets/objects/"
red_flags <-
readRDS(paste0(path, "nc_annual_red_flags"))
annual_data <-
readRDS(paste0(path, "nc_annual_final"))
Key Findings
1999-2000 was an exceptional period for both “Red Flag” prevalence and return differentiation, though apparent benefits of the strategy appear in most periods.
Approximately 2.0% of filings we checked had 5 or more “Red Flags” among annual and quarterly filings, so sparsity is ...
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