Analyzing intraday financial data in R: The highfrequency package

39 Pages Posted: 7 Sep 2021 Last revised: 28 Oct 2022

See all articles by Kris Boudt

Kris Boudt

Ghent University; Vrije Universiteit Brussel; Vrije Universiteit Amsterdam

Onno Kleen

Erasmus University Rotterdam (EUR) - Erasmus School of Economics (ESE); Tinbergen Institute

Emil Sjørup

affiliation not provided to SSRN

Date Written: October 27, 2022

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.

Keywords: financial markets, high-frequency data, realized measures, jumps, R

JEL Classification: C53, C58, G12

Suggested Citation

Boudt, Kris and Kleen, Onno and Sjørup, Emil, Analyzing intraday financial data in R: The highfrequency package (October 27, 2022). Available at SSRN: https://ssrn.com/abstract=3917548 or http://dx.doi.org/10.2139/ssrn.3917548

Kris Boudt (Contact Author)

Ghent University ( email )

Sint-Pietersplein 5
Gent, 9000
Belgium

Vrije Universiteit Brussel ( email )

Pleinlaan 2
http://www.vub.ac.be/
Brussels, 1050
Belgium

Vrije Universiteit Amsterdam ( email )

De Boelelaan 1105
Amsterdam, ND North Holland 1081 HV
Netherlands

Onno Kleen

Erasmus University Rotterdam (EUR) - Erasmus School of Economics (ESE) ( email )

P.O. Box 1738
3000 DR Rotterdam, NL 3062 PA
Netherlands

Tinbergen Institute ( email )

Burg. Oudlaan 50
Rotterdam, 3062 PA
Netherlands

Emil Sjørup

affiliation not provided to SSRN

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