Skip to content

The highfrequency package contains an extensive toolkit for the use of highfrequency financial data in R. It contains functionality to manage, clean and match highfrequency trades and quotes data. Furthermore, it enables users to: calculate easily various liquidity measures, estimate and forecast volatility, and investigate microstructure noise …

master
Go to file
Code

Latest commit

 

Git stats

Files

Permalink
Failed to load latest commit information.
Type
Name
Latest commit message
Commit time
R
 
 
 
 
 
 
man
 
 
src
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

readme.md

CRAN_Status_Badge Travis-CI Build Status Codecov test coverage Downloads

Highfrequency financial data in R

The package is still under development and is distributed without warranty.

Thanks to report bugs or make suggestions to kris.boudt@ugent.be.

Installation

CRAN:

install.packages("highfrequency")

Development version:

# Install package via devtools
# install.packages("devtools")
library(devtools)
install_github("https://github.com/jonathancornelissen/highfrequency")

Example

library(highfrequency)
# Print raw quotes data to console
sampleQDataRawMicroseconds
# Cleanup quotes leaves 46566 out of 464221 observations.
quotesCleanup(qDataRaw = sampleQDataRawMicroseconds, exchanges = "N")

Special thanks

We would like to thank Brian Peterson, Chris Blakely, Eric Zivot and Maarten Schermer. We are also grateful to Dirk Eddelbuettel for his support as a mentor during the Google Summmer of Code 2019.

About

The highfrequency package contains an extensive toolkit for the use of highfrequency financial data in R. It contains functionality to manage, clean and match highfrequency trades and quotes data. Furthermore, it enables users to: calculate easily various liquidity measures, estimate and forecast volatility, and investigate microstructure noise …

Resources

Releases

No releases published

Packages

No packages published
You can’t perform that action at this time.