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 t...

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Bibliographic Details
Published inJournal of physics. Conference series Vol. 2438; no. 1; pp. 12068 - 12073
Main Authors 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
Format Journal Article
LanguageEnglish
Published Bristol IOP Publishing 01.02.2023
Subjects
Data analysis
Data structures
Finance
Physics
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Summary: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.
ISSN:1742-6588
1742-6596
DOI:10.1088/1742-6596/2438/1/012068