Predictive Modeling of Nigeria’s Currency in Circulation Using X-12 Autoregressive Integrated Moving Average Method
Autor(a) principal: | |
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Data de Publicação: | 2023 |
Outros Autores: | |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10400.26/45247 https://doi.org/Bamanga, M. A., and Adams, S. O. (2022). Predictive Modeling of Nigeria’s Currency in Circulation Using X-12 Autoregressive Integrated Moving Average Method. Dutch Journal of Finance and Management, 5(1), 21473. https://doi.org/10.55267/djfm/13340 https://doi.org/10.55267/djfm/13340 |
Resumo: | In Nigeria, the average monthly quantity of currency in circulation (CIC) has increased by 269 billion nairas, reaching 2.13 trillion as of 2019 and 2.41 trillion as of 2020. The current value of currency in circulation is expected to be 2.88 trillion naira. The economy of Nigeria is impacted by the seasonal fluctuations in its currency, and it is unavoidable that the economy would need to be adjusted. The purpose of this study was to adjust the seasonal effect of eight days to Easter and Muslim holidays on CIC, model and predict the CIC in Nigeria using the United State Census Bureau's X-12 ARIMA Seasonal adjustment software. The data utilized in the study was the monthly amount of money in circulation that was taken from the Central Bank of Nigeria (CBN) Bulletin between January 2012 and March 2022. Natural logarithm was used to standardize the data, and series seasonality was removed using seasonal differencing. Based on these data, it is clear that X-12-ARIMA (2 1 1)(0 1 1) is the most accurate forecasting approach for Nigeria's CIC. The money in circulation in Nigeria from April 2022 through December 2022 will rise at a positive rate of 2.8% growth rate each month, with a predicted monthly mean CIC of 3.40 trillion by the end of the year 2022, according to this method's predictions. This is the first study on modeling and forecast of CIC in Nigeria that have utilize the United State Census Bureau X-12-ARIMA software, the findings can be extrapolated to the coming year, Nigerians may want to get ready for an increase in the amount of money in circulation during this time. |
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Predictive Modeling of Nigeria’s Currency in Circulation Using X-12 Autoregressive Integrated Moving Average MethodCBNCurrency in circulationMoney SupplySeasonalitySeasonal AdjustmentX-12 ARIMAIn Nigeria, the average monthly quantity of currency in circulation (CIC) has increased by 269 billion nairas, reaching 2.13 trillion as of 2019 and 2.41 trillion as of 2020. The current value of currency in circulation is expected to be 2.88 trillion naira. The economy of Nigeria is impacted by the seasonal fluctuations in its currency, and it is unavoidable that the economy would need to be adjusted. The purpose of this study was to adjust the seasonal effect of eight days to Easter and Muslim holidays on CIC, model and predict the CIC in Nigeria using the United State Census Bureau's X-12 ARIMA Seasonal adjustment software. The data utilized in the study was the monthly amount of money in circulation that was taken from the Central Bank of Nigeria (CBN) Bulletin between January 2012 and March 2022. Natural logarithm was used to standardize the data, and series seasonality was removed using seasonal differencing. Based on these data, it is clear that X-12-ARIMA (2 1 1)(0 1 1) is the most accurate forecasting approach for Nigeria's CIC. The money in circulation in Nigeria from April 2022 through December 2022 will rise at a positive rate of 2.8% growth rate each month, with a predicted monthly mean CIC of 3.40 trillion by the end of the year 2022, according to this method's predictions. This is the first study on modeling and forecast of CIC in Nigeria that have utilize the United State Census Bureau X-12-ARIMA software, the findings can be extrapolated to the coming year, Nigerians may want to get ready for an increase in the amount of money in circulation during this time.info:eu-repo/semantics/publishedVersionIADITI Editions2023-06-20T16:21:49Z2023-06-202023-06-04T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://hdl.handle.net/10400.26/45247https://doi.org/Bamanga, M. A., and Adams, S. O. (2022). Predictive Modeling of Nigeria’s Currency in Circulation Using X-12 Autoregressive Integrated Moving Average Method. Dutch Journal of Finance and Management, 5(1), 21473. https://doi.org/10.55267/djfm/13340http://hdl.handle.net/10400.26/45247https://doi.org/10.55267/djfm/13340eng2542-4750https://www.djfm-journal.com/article/predictive-modeling-of-nigerias-currency-in-circulation-using-x-12-autoregressive-integrated-moving-13340http://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessBamanga, Muhammad ArdoAdams, Samuel Olorunfemireponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-06-24T06:25:14Zoai:comum.rcaap.pt:10400.26/45247Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T18:01:26.743995Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Predictive Modeling of Nigeria’s Currency in Circulation Using X-12 Autoregressive Integrated Moving Average Method |
title |
Predictive Modeling of Nigeria’s Currency in Circulation Using X-12 Autoregressive Integrated Moving Average Method |
spellingShingle |
Predictive Modeling of Nigeria’s Currency in Circulation Using X-12 Autoregressive Integrated Moving Average Method Bamanga, Muhammad Ardo CBN Currency in circulation Money Supply Seasonality Seasonal Adjustment X-12 ARIMA |
title_short |
Predictive Modeling of Nigeria’s Currency in Circulation Using X-12 Autoregressive Integrated Moving Average Method |
title_full |
Predictive Modeling of Nigeria’s Currency in Circulation Using X-12 Autoregressive Integrated Moving Average Method |
title_fullStr |
Predictive Modeling of Nigeria’s Currency in Circulation Using X-12 Autoregressive Integrated Moving Average Method |
title_full_unstemmed |
Predictive Modeling of Nigeria’s Currency in Circulation Using X-12 Autoregressive Integrated Moving Average Method |
title_sort |
Predictive Modeling of Nigeria’s Currency in Circulation Using X-12 Autoregressive Integrated Moving Average Method |
author |
Bamanga, Muhammad Ardo |
author_facet |
Bamanga, Muhammad Ardo Adams, Samuel Olorunfemi |
author_role |
author |
author2 |
Adams, Samuel Olorunfemi |
author2_role |
author |
dc.contributor.author.fl_str_mv |
Bamanga, Muhammad Ardo Adams, Samuel Olorunfemi |
dc.subject.por.fl_str_mv |
CBN Currency in circulation Money Supply Seasonality Seasonal Adjustment X-12 ARIMA |
topic |
CBN Currency in circulation Money Supply Seasonality Seasonal Adjustment X-12 ARIMA |
description |
In Nigeria, the average monthly quantity of currency in circulation (CIC) has increased by 269 billion nairas, reaching 2.13 trillion as of 2019 and 2.41 trillion as of 2020. The current value of currency in circulation is expected to be 2.88 trillion naira. The economy of Nigeria is impacted by the seasonal fluctuations in its currency, and it is unavoidable that the economy would need to be adjusted. The purpose of this study was to adjust the seasonal effect of eight days to Easter and Muslim holidays on CIC, model and predict the CIC in Nigeria using the United State Census Bureau's X-12 ARIMA Seasonal adjustment software. The data utilized in the study was the monthly amount of money in circulation that was taken from the Central Bank of Nigeria (CBN) Bulletin between January 2012 and March 2022. Natural logarithm was used to standardize the data, and series seasonality was removed using seasonal differencing. Based on these data, it is clear that X-12-ARIMA (2 1 1)(0 1 1) is the most accurate forecasting approach for Nigeria's CIC. The money in circulation in Nigeria from April 2022 through December 2022 will rise at a positive rate of 2.8% growth rate each month, with a predicted monthly mean CIC of 3.40 trillion by the end of the year 2022, according to this method's predictions. This is the first study on modeling and forecast of CIC in Nigeria that have utilize the United State Census Bureau X-12-ARIMA software, the findings can be extrapolated to the coming year, Nigerians may want to get ready for an increase in the amount of money in circulation during this time. |
publishDate |
2023 |
dc.date.none.fl_str_mv |
2023-06-20T16:21:49Z 2023-06-20 2023-06-04T00:00:00Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10400.26/45247 https://doi.org/Bamanga, M. A., and Adams, S. O. (2022). Predictive Modeling of Nigeria’s Currency in Circulation Using X-12 Autoregressive Integrated Moving Average Method. Dutch Journal of Finance and Management, 5(1), 21473. https://doi.org/10.55267/djfm/13340 http://hdl.handle.net/10400.26/45247 https://doi.org/10.55267/djfm/13340 |
url |
http://hdl.handle.net/10400.26/45247 https://doi.org/Bamanga, M. A., and Adams, S. O. (2022). Predictive Modeling of Nigeria’s Currency in Circulation Using X-12 Autoregressive Integrated Moving Average Method. Dutch Journal of Finance and Management, 5(1), 21473. https://doi.org/10.55267/djfm/13340 https://doi.org/10.55267/djfm/13340 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
2542-4750 https://www.djfm-journal.com/article/predictive-modeling-of-nigerias-currency-in-circulation-using-x-12-autoregressive-integrated-moving-13340 |
dc.rights.driver.fl_str_mv |
http://creativecommons.org/licenses/by/4.0/ info:eu-repo/semantics/openAccess |
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http://creativecommons.org/licenses/by/4.0/ |
eu_rights_str_mv |
openAccess |
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IADITI Editions |
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IADITI Editions |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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