highfrequency (version 1.0.1)

sampleTData: Sample of cleaned trades for stock XXX for 2 days

Description

A data.table object containing the trades for the pseudonymized stock XXX for 2 days, in the typical NYSE TAQ database format. This is the cleaned version of the data sample sampleTDataRaw, using tradesCleanupUsingQuotes.

Usage

sampleTData

Format

A data.table object.

Examples

if (FALSE) {
# The code to create the sampleTData dataset from raw data is
sampleQData <- quotesCleanup(qDataRaw = sampleQDataRaw,
                                         exchanges = "N", type = "standard", report = FALSE)

tradesAfterFirstCleaning <- tradesCleanup(tDataRaw = sampleTDataRaw, 
                                          exchanges = "N", report = FALSE)

sampleTData <- tradesCleanupUsingQuotes(
  tData = tradesAfterFirstCleaning,
  qData = sampleQData,
  lagQuotes = 0)[, c("DT", "EX", "SYMBOL", "PRICE", "SIZE")]
# Only some columns are included. These are the ones that were historically included.

# For most applications, we recommend aggregating the data at a high frequency
# For example, every second.
aggregated <- aggregatePrice(sampleTData[, list(DT, PRICE)],
              alignBy = "seconds", alignPeriod = 1)
acf(diff(aggregated[as.Date(DT) == "2018-01-02", PRICE]))
acf(diff(aggregated[as.Date(DT) == "2018-01-03", PRICE]))

signature <- function(x, q){
res <- x[, (rCov(diff(log(PRICE), lag = q, differences = 1))/q), by = as.Date(DT)]
return(res[[2]])
}
rvAgg <- matrix(nrow = 100, ncol = 2)
for(i in 1:100) rvAgg[i, ] <- signature(aggregated, i)
plot(rvAgg[,1], type = "l")
plot(rvAgg[,2], type = "l")
}