Information system for the quantification of financial risk

The quantification of financial risk such as liquidity risk and others is one of the most frequent concern in the bank and corporative sector, in this sense, the liquidity risk materialization causes big monetary lost when corporations are incapable on give appropriate fulfillment of obligations due...

Full description

Autores:
Tipo de recurso:
Fecha de publicación:
2017
Institución:
Universidad de Medellín
Repositorio:
Repositorio UDEM
Idioma:
spa
OAI Identifier:
oai:repository.udem.edu.co:11407/4265
Acceso en línea:
http://hdl.handle.net/11407/4265
Palabra clave:
Architecture based on pipelines
Liquidity risk
Operational risk
Software engineering
Value at risk
Rights
License
http://purl.org/coar/access_right/c_16ec
id REPOUDEM2_647fe03e9b6024e1018473c67108dc71
oai_identifier_str oai:repository.udem.edu.co:11407/4265
network_acronym_str REPOUDEM2
network_name_str Repositorio UDEM
repository_id_str
dc.title.spa.fl_str_mv Information system for the quantification of financial risk
Sistema de Información para la cuantificación de riesgos financieros
title Information system for the quantification of financial risk
spellingShingle Information system for the quantification of financial risk
Architecture based on pipelines
Liquidity risk
Operational risk
Software engineering
Value at risk
title_short Information system for the quantification of financial risk
title_full Information system for the quantification of financial risk
title_fullStr Information system for the quantification of financial risk
title_full_unstemmed Information system for the quantification of financial risk
title_sort Information system for the quantification of financial risk
dc.contributor.affiliation.spa.fl_str_mv Arias-Serna, M.A., Universidad de Medellín, Medellín, Colombia
Caro-Lopera, F.J., Universidad de Medellín, Medellín, Colombia
Echeverri-Arias, J.A., Universidad de Medellín, Medellín, Colombia
Castaneda-Palacio, D.A., Universidad de Medellín, Medellín, Colombia
Murillo-Gomez, J.G., Universidad de Medellín, Medellín, Colombia
dc.subject.keyword.eng.fl_str_mv Architecture based on pipelines
Liquidity risk
Operational risk
Software engineering
Value at risk
topic Architecture based on pipelines
Liquidity risk
Operational risk
Software engineering
Value at risk
description The quantification of financial risk such as liquidity risk and others is one of the most frequent concern in the bank and corporative sector, in this sense, the liquidity risk materialization causes big monetary lost when corporations are incapable on give appropriate fulfillment of obligations due to lack of liquid resources. On the other hand, when operational risk is present, there are large losses due to fails on the procedures that adversely affect the functioning of the organization. With the goal of systematize the risk quantification it has implement the Information System Financial Risk Management, which was constructed like a suite of software compound by two applications that facilities the quantification of liquidity risk and operational risk. Nowadays the Information System is used by corporations in Colombian financial sector, who by means of use of tools has been reached the fulfillment the results, avoiding the materialization of negative events. © 2017 AISTI.
publishDate 2017
dc.date.accessioned.none.fl_str_mv 2017-12-19T19:36:43Z
dc.date.available.none.fl_str_mv 2017-12-19T19:36:43Z
dc.date.created.none.fl_str_mv 2017
dc.type.eng.fl_str_mv Conference Paper
dc.type.coarversion.fl_str_mv http://purl.org/coar/version/c_970fb48d4fbd8a85
dc.type.coar.fl_str_mv http://purl.org/coar/resource_type/c_c94f
dc.type.driver.none.fl_str_mv info:eu-repo/semantics/conferenceObject
dc.identifier.isbn.none.fl_str_mv 9789899843479
dc.identifier.issn.none.fl_str_mv 21660727
dc.identifier.uri.none.fl_str_mv http://hdl.handle.net/11407/4265
dc.identifier.doi.none.fl_str_mv 10.23919/CISTI.2017.7975680
dc.identifier.reponame.spa.fl_str_mv reponame:Repositorio Institucional Universidad de Medellín
dc.identifier.instname.spa.fl_str_mv instname:Universidad de Medellín
identifier_str_mv 9789899843479
21660727
10.23919/CISTI.2017.7975680
reponame:Repositorio Institucional Universidad de Medellín
instname:Universidad de Medellín
url http://hdl.handle.net/11407/4265
dc.language.iso.none.fl_str_mv spa
language spa
dc.relation.isversionof.spa.fl_str_mv https://www.scopus.com/inward/record.uri?eid=2-s2.0-85027062875&doi=10.23919%2fCISTI.2017.7975680&partnerID=40&md5=75564feff661035e73ab4e701b68cfd1
dc.relation.ispartofes.spa.fl_str_mv Iberian Conference on Information Systems and Technologies, CISTI
dc.relation.references.spa.fl_str_mv (2010). Marco Internacional Para La Medición, Seguimiento y Regulación De Riesgo De Liquidez.
Alexander, C., & Sarabia, J. M. (2010). Endogenizing model risk to quantile estimates. ICMA Centre Discussion Papers in Finance.
Antioquia, C. F. D. (2016). Reporte Beneficion Del Sistema De Informacion FRM.
Bain, L. J., & Engelhardt, M. (1992). Introduction to Probability and Mathematical Statistics.
Bass, L., Clements, P., & Kazman, R. (1998). Software architecture in practice. Software Architecture in Practice.
Clements, P., Kazman, R., & Klein, M. (2002). Evaluating Software Architectures: Methods and Case Studies.
Echeverri Arias, J. A., Murillo Gomez, J. G., Arias Serna, M. A., Klein, C., & Franco Arbelaez, L. C. (2015). Design of information system for the liquidity risk management in financial institutions. De Atas Da 10a Conferência Ibérica De Sistema.
Gorge, P. (2000). Some remarks on the value-at-risk and the conditional value-at-risk. Probabilistic Constrained Optimization: Methodology and Applications.
Holton, G. A. (2003). Value-at-Risk: Theory and Practice.
Ian, S. (2005). Ingeniería Del Software.
Irisarri, G., Mokhtari, S., & Ilya, W. (2014). Systems and Methods for Parameter Estimation for use in Determining Value-at-Risk.
James, M. (2006). Agile Estimation and Planning.
Jorion, P. (1997). VaR: The new benchmark for managing financial risk. Value at Risk: The New Benchmark for Controlling Market Risk.
McNeil, A. J., Frey, R., & Embrechts, P. (2005). Quantitative risk management: Concepts, techniques, and tools. Quantitative risk management: Concepts, techniques, and tools.
Morgan, J. P. (1996). Riskmetrics TM Technology.
Pao, D., & Lu, Z. (2014). A multi-pipeline architecture for high-speed packet classification. Computer Communications, 54, 84-96. doi:10.1016/j.comcom.2014.08.004
Rockafellar, R. T., & Uryasev, S. (2002). Conditional value-at-risk for general loss distributions. Journal of Banking and Finance, 26(7), 1443-1471. doi:10.1016/S0378-4266(02)00271-6
Serna, M. A. A., Arias, J. A. E., Gomez, J. G. M., Lopera, F. J. C., & Arbelaez, L. C. F. (2016). Information system for the quantification of operational risk in financial institutions. Paper presented at the Iberian Conference on Information Systems and Technologies, CISTI, 2016-July doi:10.1109/CISTI.2016.7521570
Takala, J., Nikara, J., Akopian, D., Astola, J., & Saarinen, J. (2000). Pipeline architecture for 8×8 discrete cosine transform. Paper presented at the ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, 6 3303-3306. doi:10.1109/ICASSP.2000.860106
dc.rights.coar.fl_str_mv http://purl.org/coar/access_right/c_16ec
rights_invalid_str_mv http://purl.org/coar/access_right/c_16ec
dc.publisher.spa.fl_str_mv IEEE Computer Society
dc.publisher.faculty.spa.fl_str_mv Facultad de Ingenierías
Facultad de Ciencias Básicas
dc.source.spa.fl_str_mv Scopus
institution Universidad de Medellín
repository.name.fl_str_mv Repositorio Institucional Universidad de Medellin
repository.mail.fl_str_mv repositorio@udem.edu.co
_version_ 1814159111933132800
spelling 2017-12-19T19:36:43Z2017-12-19T19:36:43Z2017978989984347921660727http://hdl.handle.net/11407/426510.23919/CISTI.2017.7975680reponame:Repositorio Institucional Universidad de Medellíninstname:Universidad de MedellínThe quantification of financial risk such as liquidity risk and others is one of the most frequent concern in the bank and corporative sector, in this sense, the liquidity risk materialization causes big monetary lost when corporations are incapable on give appropriate fulfillment of obligations due to lack of liquid resources. On the other hand, when operational risk is present, there are large losses due to fails on the procedures that adversely affect the functioning of the organization. With the goal of systematize the risk quantification it has implement the Information System Financial Risk Management, which was constructed like a suite of software compound by two applications that facilities the quantification of liquidity risk and operational risk. Nowadays the Information System is used by corporations in Colombian financial sector, who by means of use of tools has been reached the fulfillment the results, avoiding the materialization of negative events. © 2017 AISTI.spaIEEE Computer SocietyFacultad de IngenieríasFacultad de Ciencias Básicashttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85027062875&doi=10.23919%2fCISTI.2017.7975680&partnerID=40&md5=75564feff661035e73ab4e701b68cfd1Iberian Conference on Information Systems and Technologies, CISTI(2010). Marco Internacional Para La Medición, Seguimiento y Regulación De Riesgo De Liquidez.Alexander, C., & Sarabia, J. M. (2010). Endogenizing model risk to quantile estimates. ICMA Centre Discussion Papers in Finance.Antioquia, C. F. D. (2016). Reporte Beneficion Del Sistema De Informacion FRM.Bain, L. J., & Engelhardt, M. (1992). Introduction to Probability and Mathematical Statistics.Bass, L., Clements, P., & Kazman, R. (1998). Software architecture in practice. Software Architecture in Practice.Clements, P., Kazman, R., & Klein, M. (2002). Evaluating Software Architectures: Methods and Case Studies.Echeverri Arias, J. A., Murillo Gomez, J. G., Arias Serna, M. A., Klein, C., & Franco Arbelaez, L. C. (2015). Design of information system for the liquidity risk management in financial institutions. De Atas Da 10a Conferência Ibérica De Sistema.Gorge, P. (2000). Some remarks on the value-at-risk and the conditional value-at-risk. Probabilistic Constrained Optimization: Methodology and Applications.Holton, G. A. (2003). Value-at-Risk: Theory and Practice.Ian, S. (2005). Ingeniería Del Software.Irisarri, G., Mokhtari, S., & Ilya, W. (2014). Systems and Methods for Parameter Estimation for use in Determining Value-at-Risk.James, M. (2006). Agile Estimation and Planning.Jorion, P. (1997). VaR: The new benchmark for managing financial risk. Value at Risk: The New Benchmark for Controlling Market Risk.McNeil, A. J., Frey, R., & Embrechts, P. (2005). Quantitative risk management: Concepts, techniques, and tools. Quantitative risk management: Concepts, techniques, and tools.Morgan, J. P. (1996). Riskmetrics TM Technology.Pao, D., & Lu, Z. (2014). A multi-pipeline architecture for high-speed packet classification. Computer Communications, 54, 84-96. doi:10.1016/j.comcom.2014.08.004Rockafellar, R. T., & Uryasev, S. (2002). Conditional value-at-risk for general loss distributions. Journal of Banking and Finance, 26(7), 1443-1471. doi:10.1016/S0378-4266(02)00271-6Serna, M. A. A., Arias, J. A. E., Gomez, J. G. M., Lopera, F. J. C., & Arbelaez, L. C. F. (2016). Information system for the quantification of operational risk in financial institutions. Paper presented at the Iberian Conference on Information Systems and Technologies, CISTI, 2016-July doi:10.1109/CISTI.2016.7521570Takala, J., Nikara, J., Akopian, D., Astola, J., & Saarinen, J. (2000). Pipeline architecture for 8×8 discrete cosine transform. Paper presented at the ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, 6 3303-3306. doi:10.1109/ICASSP.2000.860106ScopusInformation system for the quantification of financial riskSistema de Información para la cuantificación de riesgos financierosConference Paperinfo:eu-repo/semantics/conferenceObjecthttp://purl.org/coar/version/c_970fb48d4fbd8a85http://purl.org/coar/resource_type/c_c94fArias-Serna, M.A., Universidad de Medellín, Medellín, ColombiaCaro-Lopera, F.J., Universidad de Medellín, Medellín, ColombiaEcheverri-Arias, J.A., Universidad de Medellín, Medellín, ColombiaCastaneda-Palacio, D.A., Universidad de Medellín, Medellín, ColombiaMurillo-Gomez, J.G., Universidad de Medellín, Medellín, ColombiaArias-Serna M.A.Caro-Lopera F.J.Echeverri-Arias J.A.Castaneda-Palacio D.A.Murillo-Gomez J.G.Universidad de Medellín, Medellín, ColombiaArchitecture based on pipelinesLiquidity riskOperational riskSoftware engineeringValue at riskThe quantification of financial risk such as liquidity risk and others is one of the most frequent concern in the bank and corporative sector, in this sense, the liquidity risk materialization causes big monetary lost when corporations are incapable on give appropriate fulfillment of obligations due to lack of liquid resources. On the other hand, when operational risk is present, there are large losses due to fails on the procedures that adversely affect the functioning of the organization. With the goal of systematize the risk quantification it has implement the Information System Financial Risk Management, which was constructed like a suite of software compound by two applications that facilities the quantification of liquidity risk and operational risk. Nowadays the Information System is used by corporations in Colombian financial sector, who by means of use of tools has been reached the fulfillment the results, avoiding the materialization of negative events. © 2017 AISTI.http://purl.org/coar/access_right/c_16ec11407/4265oai:repository.udem.edu.co:11407/42652020-05-27 15:49:33.29Repositorio Institucional Universidad de Medellinrepositorio@udem.edu.co

Publicaciones similares