Modelling the Nigeria Crude Oil Prices Using ARIMA, Pre-intervention and Post-intervention Model

Leneenadogo, Wiri; Tuaneh, Godwin Lebari

doi:10.9734/ajpas/2019/v3i130083

Cited by 9 publications

(4 citation statements)

References 5 publications

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“…Wiri, Leneenadogo and Tuaneh, Godwin Lebari [9] found that the pre-intervention models was found to be more superior to the conventional ARIMA and post intervention models, etc.…”

Section: Crude Oil Export: a Comparative Analysis Using Artificial Neural Network And Arimamentioning

confidence: 99%

Crude Oil Export: A Comparative Analysis using Artificial Neural Network and ARIMA

Alam¹

2019

IJATCSE

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The key purpose of this study is to examine the forecasting of total annual crude oil export of the Kingdom of Saudi Arabia. The present paper is based on Secondary data taken from annual reports of Saudi Arabian Monetary Authority (SAMA).The ANN and ARIMA models for forecasting are the important tools and techniques in order to illustrate the superior growth in the economy of the country. In this study, "ANN" and "Autoregressive Integrated Moving Average models" (ARIMA) have been used for predicting the total annual crude oil export of the Kingdom of Saudi Arabia.With the help of statistical software, this study tries to predict a time series data by illustrating the ANN and ARIMA models on total annual crude oil export.The total annual crude oil export of the Kingdom is gradually increasing after the year 2003. This research shall benefit the Government Administration to study about crude oil export.The outcomes of the study present that ANN model is better to predict the total annual crude oil export of the Kingdom.This study provides an insight into the position of forecasting the total annual crude oil export. The Government organization can be applied this study in making the strategic plans.

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“…Wiri, Leneenadogo and Tuaneh, Godwin Lebari [9] found that the pre-intervention models was found to be more superior to the conventional ARIMA and post intervention models, etc.…”

Section: Crude Oil Export: a Comparative Analysis Using Artificial Neural Network And Arimamentioning

confidence: 99%

Crude Oil Export: A Comparative Analysis using Artificial Neural Network and ARIMA

Alam¹

2019

IJATCSE

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“…A research done by Wiri and Tuaneh (2019) analyzed Intervention models of crude oil prices in Nigeria. The time plot of the series revealed an abrupt increase in the series and this called for intervention models.…”

Section: Literature Reviewmentioning

confidence: 99%

Modeling and Forecasting of Nigeria Crude Oil Production

Kelechi,

Amalahu, Christain Chinenye,

Emmanuel

2023

jmss

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This paper assessed comprehensively and systematically the predictive capabilities of the Nigerian Monthly Crude Oil Production forecasting models. To obtain the generality of the empirical results, ARIMA model was used. Some of the frequently used measures of forecast adequacy such as Mean Error (ME), Mean Absolute Error (MAE), Mean Squared Error (MSE) and Root Mean Squared Error (RMSE) were used to evaluate the forecast performance of the chosen models. This study reveals the fact that ARIMA (1, 1, 1) model is the best or optimal model for the period forecasted. The study fitted an appropriate time series models of crude oil production in Nigeria (2005-2022) which provided a useful forecast for quantity of crude oil production and export for the purpose of making reliable budget for the sustenance of the economy. This study reveals the fact that ARIMA (1, 1, 1) model is the best or optimal model for the period forecasted.

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“…Shittu and Inyang (2019) [12] modelled Nigerian monthly crude oil prices using the ARIMA-Intervention model with a view to comparing the result with that of the intervention model using lag operator. Wiri and Tuaneh (2019) [14] modelled the Nigerian Crude Oil Prices Using ARIMA, Pre-intervention and Post-intervention Model. Mrinmoy et al (2014) [10] used time series Intervention Modelling for Modelling and Forecasting Cotton Yield in India.…”

Section: Introductionmentioning

confidence: 99%

Modelling intervention of Columbian peso to Nigerian naira exchange rates due to 2016 & 2020 Nigerian economic recessions

Peace,

Harrison

2023

Int. J. Stat. Appl. Math.

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The modelling and forecasting of exchange rates yield valuable outcomes that contribute to informed financial decision-making. This study aims to analyze the impact of the intervention of the Columbian PESO on the exchange rates of the Nigerian Naira during the economic recessions of 2016 and 2020. By examining the fluctuations in the exchange rate, this research seeks to gain a deeper understanding of the bilateral commercial relationship between the two nations. The data pertaining to the daily exchange rates between the Nigerian Naira and the Columbian Peso for the periods spanning from 1 January to 31 August 2016 and from 1 September to 31 December 2020, were obtained from the official websites of the Central Bank of Nigeria. Based on the acquired results, it was noted that the exchange rates of COP/NGN together with their pre-intervention series, exhibited a linear trend, indicating their nonstationary nature. The exchange rates attained stationarity through the process of differencing of order one, and the fitted intervention model was deemed appropriate.

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Modelling the Nigeria Crude Oil Prices Using ARIMA, Pre-intervention and Post-intervention Model

Cited by 9 publications

References 5 publications

Crude Oil Export: A Comparative Analysis using Artificial Neural Network and ARIMA

Crude Oil Export: A Comparative Analysis using Artificial Neural Network and ARIMA

Modeling and Forecasting of Nigeria Crude Oil Production

Modelling intervention of Columbian peso to Nigerian naira exchange rates due to 2016 & 2020 Nigerian economic recessions

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