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...
Autores principales: | , , , , , , , , , , |
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Lenguaje: | eng |
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2023
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Materias: | |
Acceso en línea: | https://dx.doi.org/10.1088/1742-6596/2438/1/012068 http://cds.cern.ch/record/2871818 |
_version_ | 1780978568824619008 |
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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 |
record_format | invenio |
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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