Analyzing Intraday Financial Data in R: The highfrequency Package

Onno Kleen; Kris Boudt; Emil Sjørup

doi:10.18637/jss.v104.i08

Analyzing Intraday Financial Data in R: The highfrequency Package

Onno Kleen, Kris Boudt, Emil Sjørup

Econometrics

Research output: Contribution to journal › Article › Academic › peer-review

5 Citations (Scopus)

Abstract

The highfrequency package for the R programming language provides functionality for pre-processing financial high-frequency data, analyzing intraday stock returns, and forecasting stock market volatility. For academics and practitioners alike, it provides a tool chain required to work with such datasets and to conduct statistical analyses dedicated to spot volatility, jumps, realized measures, and many more. We showcase our implemented routines and models on raw high-frequency data from large stock exchanges.

Original language	English
Pages (from-to)	1-36
Number of pages	36
Journal	Journal of Statistical Software
Volume	104
Issue number	8
DOIs	https://doi.org/10.18637/jss.v104.i08
Publication status	Published - 2022

Bibliographical note

Funding Information:
The authors acknowledge Google for financial support via the Google Summer of Code initiative in the years 2012, 2013, 2014, 2019, and 2020. In addition, we thank Chris Blakely, Nabil Bouamara, Jonathan Cornelissen, Dirk Eddelbuettel, Giang Nguyen, Scott Payseur, Brian Peterson, Maarten Schermer, and Eric Zivot for their support in the development of the highfrequency package. Moreover, we thank Andreas Alfons for giving valuable feedback.

Publisher Copyright:
© 2022, American Statistical Association. All rights reserved.

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Cite this

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abstract = "The highfrequency package for the R programming language provides functionality for pre-processing financial high-frequency data, analyzing intraday stock returns, and forecasting stock market volatility. For academics and practitioners alike, it provides a tool chain required to work with such datasets and to conduct statistical analyses dedicated to spot volatility, jumps, realized measures, and many more. We showcase our implemented routines and models on raw high-frequency data from large stock exchanges.",

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Analyzing Intraday Financial Data in R: The highfrequency Package

Abstract

Bibliographical note

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