clean_enhanced_trace <- function(cusips,
connection,
start_date = as.Date("2002-01-01"),
end_date = today()) {
# Packages (required)
library(dplyr)
library(lubridate)
library(dbplyr)
library(RPostgres)
# Function checks ---------------------------------------------------------
# Input parameters
## Cusips
if (length(cusips) == 0 | any(is.na(cusips))) stop("Check cusips.")
## Dates
if (!is.Date(start_date) | !is.Date(end_date)) stop("Dates needed")
if (start_date < as.Date("2002-01-01")) stop("TRACE starts later.")
if (end_date > today()) stop("TRACE does not predict the future.")
if (start_date >= end_date) stop("Date conflict.")
## Connection
if (!dbIsValid(connection)) stop("Connection issue.")
# Enhanced Trace ----------------------------------------------------------
# Main file
trace_all <- tbl(
connection,
I("trace.trace_enhanced")
) |>
filter(cusip_id %in% cusips) |>
filter(trd_exctn_dt >= start_date & trd_exctn_dt <= end_date) |>
select(
cusip_id, msg_seq_nb, orig_msg_seq_nb,
entrd_vol_qt, rptd_pr, yld_pt, rpt_side_cd, cntra_mp_id,
trd_exctn_dt, trd_exctn_tm, trd_rpt_dt, trd_rpt_tm,
pr_trd_dt, trc_st, asof_cd, wis_fl,
days_to_sttl_ct, stlmnt_dt, spcl_trd_fl
) |>
collect()
# Enhanced Trace: Post 06-02-2012 -----------------------------------------
# Trades (trc_st = T) and correction (trc_st = R)
trace_post_TR <- trace_all |>
filter(
(trc_st == "T" | trc_st == "R"),
trd_rpt_dt >= as.Date("2012-02-06")
)
# Cancellations (trc_st = X) and correction cancellations (trc_st = C)
trace_post_XC <- trace_all |>
filter(
(trc_st == "X" | trc_st == "C"),
trd_rpt_dt >= as.Date("2012-02-06")
)
# Cleaning corrected and cancelled trades
trace_post_TR <- trace_post_TR |>
anti_join(trace_post_XC,
join_by(
cusip_id, msg_seq_nb, entrd_vol_qt,
rptd_pr, rpt_side_cd, cntra_mp_id,
trd_exctn_dt, trd_exctn_tm
)
)
# Reversals (trc_st = Y)
trace_post_Y <- trace_all |>
filter(
trc_st == "Y",
trd_rpt_dt >= as.Date("2012-02-06")
)
# Clean reversals
## match the orig_msg_seq_nb of the Y-message to
## the msg_seq_nb of the main message
trace_post <- trace_post_TR |>
anti_join(trace_post_Y,
join_by(
cusip_id,
msg_seq_nb == orig_msg_seq_nb,
entrd_vol_qt, rptd_pr, rpt_side_cd,
cntra_mp_id, trd_exctn_dt, trd_exctn_tm
)
)
# Enhanced TRACE: Pre 06-02-2012 ------------------------------------------
# Cancellations (trc_st = C)
trace_pre_C <- trace_all |>
filter(
trc_st == "C",
trd_rpt_dt < as.Date("2012-02-06")
)
# Trades w/o cancellations
## match the orig_msg_seq_nb of the C-message
## to the msg_seq_nb of the main message
trace_pre_T <- trace_all |>
filter(
trc_st == "T",
trd_rpt_dt < as.Date("2012-02-06")
) |>
anti_join(trace_pre_C,
join_by(
cusip_id,
msg_seq_nb == orig_msg_seq_nb,
entrd_vol_qt, rptd_pr, rpt_side_cd,
cntra_mp_id, trd_exctn_dt, trd_exctn_tm
)
)
# Corrections (trc_st = W) - W can also correct a previous W
trace_pre_W <- trace_all |>
filter(
trc_st == "W",
trd_rpt_dt < as.Date("2012-02-06")
)
# Implement corrections in a loop
## Correction control
correction_control <- nrow(trace_pre_W)
correction_control_last <- nrow(trace_pre_W)
## Correction loop
while (correction_control > 0) {
# Corrections that correct some msg
trace_pre_W_correcting <- trace_pre_W |>
semi_join(trace_pre_T,
join_by(
cusip_id, trd_exctn_dt,
orig_msg_seq_nb == msg_seq_nb
)
)
# Corrections that do not correct some msg
trace_pre_W <- trace_pre_W |>
anti_join(trace_pre_T,
join_by(cusip_id, trd_exctn_dt,
orig_msg_seq_nb == msg_seq_nb
)
)
# Delete msgs that are corrected and add correction msgs
trace_pre_T <- trace_pre_T |>
anti_join(trace_pre_W_correcting,
join_by(
cusip_id, trd_exctn_dt,
msg_seq_nb == orig_msg_seq_nb
)
) |>
union_all(trace_pre_W_correcting)
# Escape if no corrections remain or they cannot be matched
correction_control <- nrow(trace_pre_W)
if (correction_control == correction_control_last) {
correction_control <- 0
}
correction_control_last <- nrow(trace_pre_W)
}
# Clean reversals
## Record reversals
trace_pre_R <- trace_pre_T |>
filter(asof_cd == "R") |>
group_by(
cusip_id, trd_exctn_dt, entrd_vol_qt,
rptd_pr, rpt_side_cd, cntra_mp_id
) |>
arrange(trd_exctn_tm, trd_rpt_dt, trd_rpt_tm) |>
mutate(seq = row_number()) |>
ungroup()
## Remove reversals and the reversed trade
trace_pre <- trace_pre_T |>
filter(is.na(asof_cd) | !(asof_cd %in% c("R", "X", "D"))) |>
group_by(
cusip_id, trd_exctn_dt, entrd_vol_qt,
rptd_pr, rpt_side_cd, cntra_mp_id
) |>
arrange(trd_exctn_tm, trd_rpt_dt, trd_rpt_tm) |>
mutate(seq = row_number()) |>
ungroup() |>
anti_join(trace_pre_R,
join_by(
cusip_id, trd_exctn_dt, entrd_vol_qt,
rptd_pr, rpt_side_cd, cntra_mp_id, seq
)
) |>
select(-seq)
# Agency trades -----------------------------------------------------------
# Combine pre and post trades
trace_clean <- trace_post |>
union_all(trace_pre)
# Keep angency sells and unmatched agency buys
## Agency sells
trace_agency_sells <- trace_clean |>
filter(
cntra_mp_id == "D",
rpt_side_cd == "S"
)
# Agency buys that are unmatched
trace_agency_buys_filtered <- trace_clean |>
filter(
cntra_mp_id == "D",
rpt_side_cd == "B"
) |>
anti_join(trace_agency_sells,
join_by(
cusip_id, trd_exctn_dt,
entrd_vol_qt, rptd_pr
)
)
# Agency clean
trace_clean <- trace_clean |>
filter(cntra_mp_id == "C") |>
union_all(trace_agency_sells) |>
union_all(trace_agency_buys_filtered)
# Additional Filters ------------------------------------------------------
trace_add_filters <- trace_clean |>
mutate(days_to_sttl_ct2 = stlmnt_dt - trd_exctn_dt) |>
filter(
is.na(days_to_sttl_ct) | as.numeric(days_to_sttl_ct) <= 7,
is.na(days_to_sttl_ct2) | as.numeric(days_to_sttl_ct2) <= 7,
wis_fl == "N",
is.na(spcl_trd_fl) | spcl_trd_fl == "",
is.na(asof_cd) | asof_cd == ""
)
# Output ------------------------------------------------------------------
# Only keep necessary columns
trace_final <- trace_add_filters |>
arrange(cusip_id, trd_exctn_dt, trd_exctn_tm) |>
select(
cusip_id, trd_exctn_dt, trd_exctn_tm,
rptd_pr, entrd_vol_qt, yld_pt, rpt_side_cd, cntra_mp_id
) |>
mutate(trd_exctn_tm = format(
as_datetime(
trd_exctn_tm,
tz = "America/New_York"),
"%H:%M:%S"
)
)
# Return
return(trace_final)
}Clean Enhanced TRACE with R
Note
You are reading Tidy Finance with R. You can find the equivalent chapter for the sibling Tidy Finance with Python here.
This appendix contains code to clean enhanced TRACE with R. It is also available via the following GitHub gist. Hence, you could also source the function with devtools::source_gist("3a05b3ab281563b2e94858451c2eb3a4"). We need this function in Chapter TRACE and FISD to download and clean enhanced TRACE trade messages following Dick-Nielsen (2009) and Dick-Nielsen (2014) for enhanced TRACE specifically. Relatedly, WRDS provides SAS code and there is Python code available by the project Open Source Bond Asset Pricing.
The function takes a vector of CUSIPs (in cusips), a connection to WRDS (connection) explained in Chapter 3, and a start and end date (start_date and end_date, respectively). Specifying too many CUSIPs will result in very slow downloads and a potential failure due to the size of the request to WRDS. The dates should be within the coverage of TRACE itself, i.e., starting after 2002, and the dates should be supplied using the class date. The output of the function contains all valid trade messages for the selected CUSIPs over the specified period.
References
Dick-Nielsen, Jens. 2009. “Liquidity biases in TRACE.” The Journal of Fixed Income 19 (2): 43–55. https://doi.org/10.3905/jfi.2009.19.2.043.
———. 2014. “How to clean enhanced TRACE data.” Working Paper. https://ssrn.com/abstract=2337908.