Package: highfrequency 1.0.1
Kris Boudt
highfrequency: Tools for Highfrequency Data Analysis
Provide functionality to manage, clean and match highfrequency trades and quotes data, calculate various liquidity measures, estimate and forecast volatility, detect price jumps and investigate microstructure noise and intraday periodicity. A detailed vignette can be found in the open-access paper "Analyzing Intraday Financial Data in R: The highfrequency Package" by Boudt, Kleen, and Sjoerup (2022, <doi:10.18637/jss.v104.i08>).
Authors:
highfrequency_1.0.1.tar.gz
highfrequency_1.0.1.tar.gz(r-4.5-noble)highfrequency_1.0.1.tar.gz(r-4.4-noble)
highfrequency_1.0.1.tgz(r-4.4-emscripten)highfrequency_1.0.1.tgz(r-4.3-emscripten)
highfrequency.pdf |highfrequency.html✨
highfrequency/json (API)
NEWS
| # Install 'highfrequency' in R: |
| install.packages('highfrequency', repos = 'https://cloud.r-project.org') |
Bug tracker:https://github.com/jonathancornelissen/highfrequency/issues5 issues
- SPYRM - SPY realized measures
- sampleMultiTradeData - Multivariate tick by tick data
- sampleOneMinuteData - One minute data
- sampleQData - Sample of cleaned quotes for stock XXX for 2 days measured in microseconds
- sampleQDataRaw - Sample of raw quotes for stock XXX for 2 days measured in microseconds
- sampleTData - Sample of cleaned trades for stock XXX for 2 days
- sampleTDataEurope - European data
- sampleTDataRaw - Sample of raw trades for stock XXX for 2 days
Last updated 1 years agofrom:018058644b. Checks:1 OK, 2 NOTE. Indexed: no.
| Target | Result | Latest binary |
|---|---|---|
| Doc / Vignettes | OK | Mar 30 2025 |
| R-4.5-linux-x86_64 | NOTE | Mar 30 2025 |
| R-4.4-linux-x86_64 | NOTE | Mar 30 2025 |
Exports:aggregatePriceaggregateQuotesaggregateTradesaggregateTSAJjumpTestautoSelectExchangeQuotesautoSelectExchangeTradesBNSjumpTestbusinessTimeAggregationdriftBurstsexchangeHoursOnlygatherPricesgetAlphaVantageDatagetCriticalValuesgetLiquidityMeasuresgetTradeDirectionHARmodelHEAVYmodelintradayJumpTestIVinferenceJOjumpTestknChooseReMeDIleadLaglistAvailableKernelslistCholCovEstimatorsmakeOHLCVmakePsdmakeReturnsmakeRMFormatmatchTradesQuotesmergeQuotesSameTimestampmergeTradesSameTimestampnoZeroPricesnoZeroQuotesplotTQDataquotesCleanuprankJumpTestrAVGCovrBACovrBetarBPCovrCholCovrCovrefreshTimeReMeDIReMeDIAsymptoticVariancerHYCovrKernelCovrKurtrMedRQrMedRQuarrMedRVrMedRVarrMinRQrMinRQuarrMinRVrMinRVarrmLargeSpreadrmNegativeSpreadrmOutliersQuotesrmOutliersTradesrMPVrMPVarrMRCrMRCovrmTradeOutliersUsingQuotesrOWCovrQPVarrQuarrRTSCovrRVarrSemiCovrSkewrSVrSVarrThresholdCovrTPQuarrTSCovRVsalesConditionselectExchangespotDriftspotVolspreadPricestradesCleanuptradesCleanupUsingQuotestradesCondition
Dependencies:curldata.tableDEoptimRjsonlitelatticenumDerivquantmodRcppRcppArmadilloRcppRollrobustbaseRsolnpsandwichtruncnormTTRxtszoo
Citation
To cite highfrequency in publications use:
Kris Boudt, Onno Kleen, Emil Sjørup (2022). Analyzing Intraday Financial Data in R: The highfrequency Package. Journal of Statistical Software, 104(8), 1-36.
Corresponding BibTeX entry:
@Article{,
title = {Analyzing Intraday Financial Data in R: The highfrequency
Package},
author = {Kris Boudt and Onno Kleen and Emil Sj{\o}rup},
journal = {Journal of Statistical Software},
year = {2022},
volume = {104},
number = {8},
pages = {1--36},
doi = {10.18637/jss.v104.i08},
}