Assessing the Price Relationship and Weather Impact on Selected Pairs of Closely Related Commodities Assessing the Price Relationship and Weather Impact on Selected Pairs of Closely Related Commodities

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opiribo_olaniyo
opiribo_olaniyo
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Opiribo Olaniyo
Opiribo Olaniyo
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Adebanjo Adeniyi
Adebanjo Adeniyi
4
Franklyn Ogbeide Okogun
Franklyn Ogbeide Okogun
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Assessing the Price Relationship and Weather Impact on Selected Pairs of Closely Related Commodities Assessing the Price Relationship and Weather Impact on Selected Pairs of Closely Related Commodities Banner
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As indicated by various works of literature, climate change has a significant impact on agricultural commodities resulting in variation between demand and supply. The research study adopted quantitative analysis for comparative analysis of price relationships for three pairs of agricultural commodities against closely related products and how weather impacts them. As an interesting comparison, we also selected a pair of non-agricultural commodities for analysis. Downloaded data for the analysis were daily historical price data for the commodities, and daily summary of weather data for precipitation and temperature for the regions were the selected commodities are most produced. Using programming languages like Python and R, we carried out exploratory data analysis using the following statistics, such as graphs, scatter plots of returns, QQ plots for normality, time series diagnostics (AC, PAC) ARIMA, correlation. An exciting part of our work is our model selection, where we used SARIMAX for regressing endogenous data, i.e., commodity prices and exogenous data weather data.

Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

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No ethics committee approval was required for this article type.

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Not applicable for this article.

opiribo_olaniyo. 2021. \u201cAssessing the Price Relationship and Weather Impact on Selected Pairs of Closely Related Commodities Assessing the Price Relationship and Weather Impact on Selected Pairs of Closely Related Commodities\u201d. Global Journal of Computer Science and Technology - C: Software & Data Engineering GJCST-C Volume 21 (GJCST Volume 21 Issue C1): .

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Improving accuracy on commodity price and weather effects analysis.
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GJCST Volume 21 Issue C1
Pg. 21- 59
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Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

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August 18, 2021

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English

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As indicated by various works of literature, climate change has a significant impact on agricultural commodities resulting in variation between demand and supply. The research study adopted quantitative analysis for comparative analysis of price relationships for three pairs of agricultural commodities against closely related products and how weather impacts them. As an interesting comparison, we also selected a pair of non-agricultural commodities for analysis. Downloaded data for the analysis were daily historical price data for the commodities, and daily summary of weather data for precipitation and temperature for the regions were the selected commodities are most produced. Using programming languages like Python and R, we carried out exploratory data analysis using the following statistics, such as graphs, scatter plots of returns, QQ plots for normality, time series diagnostics (AC, PAC) ARIMA, correlation. An exciting part of our work is our model selection, where we used SARIMAX for regressing endogenous data, i.e., commodity prices and exogenous data weather data.

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Assessing the Price Relationship and Weather Impact on Selected Pairs of Closely Related Commodities Assessing the Price Relationship and Weather Impact on Selected Pairs of Closely Related Commodities

Opiribo Olaniyo
Opiribo Olaniyo
Adebanjo Adeniyi
Adebanjo Adeniyi
Franklyn Ogbeide Okogun
Franklyn Ogbeide Okogun

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