The Analysis of High-Frequency Finance Data using ROOT

P. Debie; M.E. Verhulst; J.M.E. Pennings; B. Tekinerdogan; C. Catal; A. Naumann; S. Demirel; L. Moneta; T. Alskaif; J. Rembser; P. Van Leeuwen

doi:10.1088/1742-6596/2438/1/012068

The Analysis of High-Frequency Finance Data using ROOT

P. Debie^*, M.E. Verhulst, J.M.E. Pennings, B. Tekinerdogan, C. Catal, A. Naumann, S. Demirel, L. Moneta, T. Alskaif, J. Rembser, P. Van Leeuwen

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference paper › Academic › peer-review

1 Citation (Scopus)

Abstract

High-frequency financial market data is conceptually distinct from high energy physics (HEP) data. Market data is a time series generated by market participants, while HEP data is a set of independent events generated by collisions between particles. However, there are similarities within the data structure and required tools for data analysis, and both fields share a similar set of problems facing the increasing size of data generated. This paper describes some of the core concepts of financial markets, discusses the data similarities and differences with HEP, and provides an implementation to use ROOT, an open-source data analysis framework in HEP, with financial market data. This implementation makes it possible to take advantage of the rich set of features available in ROOT and extends research in finance.

Original language	English
Title of host publication	20th International Workshop on Advanced Computing and Analysis Techniques in Physics Research (ACAT 2021)
Publisher	IOP Publishing
DOIs	https://doi.org/10.1088/1742-6596/2438/1/012068
Publication status	Published - 15 Feb 2023

Publication series

Name	Journal of Physics: Conference series
Publisher	IOP Publishing
Volume	2438
ISSN (Print)	1742-6588

Access to Document

10.1088/1742-6596/2438/1/012068Licence: CC BY

https://edepot.wur.nl/588647Licence: CC BY

HighLO: High Energy Physics Tools in Limit Order Book Analysis
Pennings, J. (Project Leader), Alskaif, T. (PI), Verhulst, M. (PI) & Debie, P. (PI)
1/09/19 → 1/09/26
Project: Research

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Debie, P., Verhulst, M. E., Pennings, J. M. E., Tekinerdogan, B., Catal, C., Naumann, A., Demirel, S., Moneta, L., Alskaif, T., Rembser, J., & Van Leeuwen, P. (2023). The Analysis of High-Frequency Finance Data using ROOT. In 20th International Workshop on Advanced Computing and Analysis Techniques in Physics Research (ACAT 2021) Article 012068 (Journal of Physics: Conference series; Vol. 2438). IOP Publishing. https://doi.org/10.1088/1742-6596/2438/1/012068

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title = "The Analysis of High-Frequency Finance Data using ROOT",

abstract = "High-frequency financial market data is conceptually distinct from high energy physics (HEP) data. Market data is a time series generated by market participants, while HEP data is a set of independent events generated by collisions between particles. However, there are similarities within the data structure and required tools for data analysis, and both fields share a similar set of problems facing the increasing size of data generated. This paper describes some of the core concepts of financial markets, discusses the data similarities and differences with HEP, and provides an implementation to use ROOT, an open-source data analysis framework in HEP, with financial market data. This implementation makes it possible to take advantage of the rich set of features available in ROOT and extends research in finance.",

author = "P. Debie and M.E. Verhulst and J.M.E. Pennings and B. Tekinerdogan and C. Catal and A. Naumann and S. Demirel and L. Moneta and T. Alskaif and J. Rembser and \{Van Leeuwen\}, P.",

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Debie, P , Verhulst, ME , Pennings, JME , Tekinerdogan, B , Catal, C, Naumann, A, Demirel, S, Moneta, L, Alskaif, T, Rembser, J & Van Leeuwen, P 2023, The Analysis of High-Frequency Finance Data using ROOT. in 20th International Workshop on Advanced Computing and Analysis Techniques in Physics Research (ACAT 2021)., 012068, Journal of Physics: Conference series, vol. 2438, IOP Publishing. https://doi.org/10.1088/1742-6596/2438/1/012068

The Analysis of High-Frequency Finance Data using ROOT. / Debie, P.; Verhulst, M.E.; Pennings, J.M.E. et al.
20th International Workshop on Advanced Computing and Analysis Techniques in Physics Research (ACAT 2021). IOP Publishing, 2023. 012068 (Journal of Physics: Conference series; Vol. 2438).

Research output: Chapter in Book/Report/Conference proceeding › Conference paper › Academic › peer-review

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AU - Catal, C.

AU - Naumann, A.

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AU - Rembser, J.

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N2 - High-frequency financial market data is conceptually distinct from high energy physics (HEP) data. Market data is a time series generated by market participants, while HEP data is a set of independent events generated by collisions between particles. However, there are similarities within the data structure and required tools for data analysis, and both fields share a similar set of problems facing the increasing size of data generated. This paper describes some of the core concepts of financial markets, discusses the data similarities and differences with HEP, and provides an implementation to use ROOT, an open-source data analysis framework in HEP, with financial market data. This implementation makes it possible to take advantage of the rich set of features available in ROOT and extends research in finance.

AB - High-frequency financial market data is conceptually distinct from high energy physics (HEP) data. Market data is a time series generated by market participants, while HEP data is a set of independent events generated by collisions between particles. However, there are similarities within the data structure and required tools for data analysis, and both fields share a similar set of problems facing the increasing size of data generated. This paper describes some of the core concepts of financial markets, discusses the data similarities and differences with HEP, and provides an implementation to use ROOT, an open-source data analysis framework in HEP, with financial market data. This implementation makes it possible to take advantage of the rich set of features available in ROOT and extends research in finance.

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DO - 10.1088/1742-6596/2438/1/012068

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BT - 20th International Workshop on Advanced Computing and Analysis Techniques in Physics Research (ACAT 2021)

PB - IOP Publishing

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The Analysis of High-Frequency Finance Data using ROOT

Abstract

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HighLO: High Energy Physics Tools in Limit Order Book Analysis

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