sampleTData | R Documentation |
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
.
sampleTData
A data.table object.
## Not run: # 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") ## End(Not run)
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