Large-scale simulations of synthetic markets

High-frequency trading has been experiencing an increase of interest both for practical purposes within nancial institutions and within academic research; recently, the UK Government O ce for Science reviewed the state of the art and gave an outlook analysis. Therefore, models for tick-by-tick nanci...

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Detalhes bibliográficos
Autores: Gerardo-Giorda, L., Germano, G., Scalas, E.
Formato: artículo
Estado:Versión publicada
Fecha de publicación:2015
País:España
Recursos:Basque Center for Applied Mathematics (BCAM)
Repositorio:BIRD. BCAM's Institutional Repository Data
OAI Identifier:oai:bird.bcamath.org:20.500.11824/320
Acesso em linha:http://hdl.handle.net/20.500.11824/320
Access Level:acceso abierto
Palavra-chave:synthetic markets
large scale simulation
heteroskedasticity
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spelling Large-scale simulations of synthetic marketsGerardo-Giorda, L.Germano, G.Scalas, E.synthetic marketslarge scale simulationheteroskedasticityHigh-frequency trading has been experiencing an increase of interest both for practical purposes within nancial institutions and within academic research; recently, the UK Government O ce for Science reviewed the state of the art and gave an outlook analysis. Therefore, models for tick-by-tick nancial time series are becoming more and more important. Together with high-frequency trading comes the need for fast simulations of full synthetic markets for several purposes including scenario analyses for risk evaluation. These simulations are very suitable to be run on massively parallel architectures. Aside more traditional large-scale parallel computers, high-end personal computers equipped with several multi-core CPUs and general-purpose GPU programming are gaining importance as cheap and easily available alternatives. A further option are FPGAs. In all cases, development can be done in a uni ed framework with standard C or C++ code and calls to appropriate libraries like MPI (for CPUs) or CUDA for (GPGPUs). Here we present such a prototype simulation of a synthetic regulated equity market. The basic ingredients to build a synthetic share are two sequences of random variables, one for the inter-trade durations and one for the tick-by-tick logarithmic returns. Our extensive simulations are based on several distributional choices for the above random variables, including Mittag-Le er distributed inter-trade durations and alpha-stable tick-by-tick logarithmic returns.Economic and Social Research Council (ESRC) grant number ES/K002309/1.201620162015info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttp://hdl.handle.net/20.500.11824/320reponame:BIRD. BCAM's Institutional Repository Datainstname:Basque Center for Applied Mathematics (BCAM)Ingléshttp://caim.simai.eu/index.php/caim/article/view/535/pdfinfo:eu-repo/grantAgreement/MINECO//SEV-2013-0323info:eu-repo/grantAgreement/Gobierno Vasco/BERC/BERC.2014-2017Reconocimiento-NoComercial-CompartirIgual 3.0 Españahttp://creativecommons.org/licenses/by-nc-sa/3.0/es/info:eu-repo/semantics/openAccessoai:bird.bcamath.org:20.500.11824/3202026-06-19T12:47:47Z
dc.title.none.fl_str_mv Large-scale simulations of synthetic markets
title Large-scale simulations of synthetic markets
spellingShingle Large-scale simulations of synthetic markets
Gerardo-Giorda, L.
synthetic markets
large scale simulation
heteroskedasticity
title_short Large-scale simulations of synthetic markets
title_full Large-scale simulations of synthetic markets
title_fullStr Large-scale simulations of synthetic markets
title_full_unstemmed Large-scale simulations of synthetic markets
title_sort Large-scale simulations of synthetic markets
dc.creator.none.fl_str_mv Gerardo-Giorda, L.
Germano, G.
Scalas, E.
author Gerardo-Giorda, L.
author_facet Gerardo-Giorda, L.
Germano, G.
Scalas, E.
author_role author
author2 Germano, G.
Scalas, E.
author2_role author
author
dc.subject.none.fl_str_mv synthetic markets
large scale simulation
heteroskedasticity
topic synthetic markets
large scale simulation
heteroskedasticity
description High-frequency trading has been experiencing an increase of interest both for practical purposes within nancial institutions and within academic research; recently, the UK Government O ce for Science reviewed the state of the art and gave an outlook analysis. Therefore, models for tick-by-tick nancial time series are becoming more and more important. Together with high-frequency trading comes the need for fast simulations of full synthetic markets for several purposes including scenario analyses for risk evaluation. These simulations are very suitable to be run on massively parallel architectures. Aside more traditional large-scale parallel computers, high-end personal computers equipped with several multi-core CPUs and general-purpose GPU programming are gaining importance as cheap and easily available alternatives. A further option are FPGAs. In all cases, development can be done in a uni ed framework with standard C or C++ code and calls to appropriate libraries like MPI (for CPUs) or CUDA for (GPGPUs). Here we present such a prototype simulation of a synthetic regulated equity market. The basic ingredients to build a synthetic share are two sequences of random variables, one for the inter-trade durations and one for the tick-by-tick logarithmic returns. Our extensive simulations are based on several distributional choices for the above random variables, including Mittag-Le er distributed inter-trade durations and alpha-stable tick-by-tick logarithmic returns.
publishDate 2015
dc.date.none.fl_str_mv 2015
2016
2016
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/20.500.11824/320
url http://hdl.handle.net/20.500.11824/320
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv http://caim.simai.eu/index.php/caim/article/view/535/pdf
info:eu-repo/grantAgreement/MINECO//SEV-2013-0323
info:eu-repo/grantAgreement/Gobierno Vasco/BERC/BERC.2014-2017
dc.rights.none.fl_str_mv Reconocimiento-NoComercial-CompartirIgual 3.0 España
http://creativecommons.org/licenses/by-nc-sa/3.0/es/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Reconocimiento-NoComercial-CompartirIgual 3.0 España
http://creativecommons.org/licenses/by-nc-sa/3.0/es/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:BIRD. BCAM's Institutional Repository Data
instname:Basque Center for Applied Mathematics (BCAM)
instname_str Basque Center for Applied Mathematics (BCAM)
reponame_str BIRD. BCAM's Institutional Repository Data
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