The Analysis of High-Frequency Finance Data using ROOT

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 s...

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Autores principales: 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
Lenguaje:eng
Publicado: 2023
Materias:
Acceso en línea:https://dx.doi.org/10.1088/1742-6596/2438/1/012068
http://cds.cern.ch/record/2871818
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author 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
author_facet 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
author_sort Debie, P
collection CERN
description 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.
id cern-2871818
institution Organización Europea para la Investigación Nuclear
language eng
publishDate 2023
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spelling cern-28718182023-09-20T21:01:03Zdoi:10.1088/1742-6596/2438/1/012068http://cds.cern.ch/record/2871818engDebie, PVerhulst, M EPennings, J M ETekinerdogan, BCatal, CNaumann, ADemirel, SMoneta, LAlskaif, TRembser, Jvan Leeuwen, PThe Analysis of High-Frequency Finance Data using ROOTComputing and ComputersHigh-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.oai:cds.cern.ch:28718182023
spellingShingle Computing and Computers
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
The Analysis of High-Frequency Finance Data using ROOT
title The Analysis of High-Frequency Finance Data using ROOT
title_full The Analysis of High-Frequency Finance Data using ROOT
title_fullStr The Analysis of High-Frequency Finance Data using ROOT
title_full_unstemmed The Analysis of High-Frequency Finance Data using ROOT
title_short The Analysis of High-Frequency Finance Data using ROOT
title_sort analysis of high-frequency finance data using root
topic Computing and Computers
url https://dx.doi.org/10.1088/1742-6596/2438/1/012068
http://cds.cern.ch/record/2871818
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