Comparative Assessment of SARIMA and SSES Models for Forecasting Cucumber Prices in Nepal

Anisha Giri; Vijay Raj Giri

doi:doi:10.11648/j.aas.20230803.17

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Comparative Assessment of SARIMA and SSES Models for Forecasting Cucumber Prices in Nepal

Anisha Giri, Vijay Raj Giri

Published in Advances in Applied Sciences (Volume 8, Issue 3)

Received: 24 August 2023 Accepted: 11 September 2023 Published: 20 September 2023

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Abstract

Cucumber, originally indigenous to Southern Asia, thrives in diverse areas of Nepal. However, despite its promising prospects, cucumber cultivation in Nepal encounters obstacles resulting in reduced profits for farmers. These challenges encompass price volatility, marketing issues, the involvement of intermediaries in pricing, susceptibility to spoilage, and the substantial importation of cucumbers from neighboring India. Moreover, the agricultural market dynamics have led to traders shifting the burden of price risks onto farmers, culminating in lower returns for their produce. In that regard, this study focuses on the forecasting of cucumber prices in Nepal using time series analysis and compare the performance of two popular forecasting models: Seasonal Autoregressive Integrated Moving Average (SARIMA) and Simple Seasonal Exponential Smoothing (SSES). The objective is to provide accurate and reliable price predictions to assist stakeholders in making informed decisions in the cucumber market. The study utilizes historical cucumber price data spanning the past decade to understand the seasonal variations and trends in cucumber prices. The SARIMA model, known for its ability to capture seasonal effects, and the SSES model, a benchmark for seasonal time-series analysis, are both employed in the comparative assessment. The results reveal that the SSES model outperforms the SARIMA model in terms of forecasting accuracy, with lower Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), and Mean Absolute Percentage Error (MAPE) values. The study's findings have significant implications for policymakers, researchers, and farmers involved in the cucumber market, offering valuable insights to optimize production and pricing strategies.

Published in	Advances in Applied Sciences (Volume 8, Issue 3)
DOI	10.11648/j.aas.20230803.17
Page(s)	106-121
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Econometric Analysis, Time Series, Seasonality Index, Box-Jenkins, Holt-Winters

References

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Anisha Giri, Vijay Raj Giri. (2023). Comparative Assessment of SARIMA and SSES Models for Forecasting Cucumber Prices in Nepal. Advances in Applied Sciences, 8(3), 106-121. https://doi.org/10.11648/j.aas.20230803.17

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Anisha Giri; Vijay Raj Giri. Comparative Assessment of SARIMA and SSES Models for Forecasting Cucumber Prices in Nepal. Adv. Appl. Sci. 2023, 8(3), 106-121. doi: 10.11648/j.aas.20230803.17

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AMA Style

Anisha Giri, Vijay Raj Giri. Comparative Assessment of SARIMA and SSES Models for Forecasting Cucumber Prices in Nepal. Adv Appl Sci. 2023;8(3):106-121. doi: 10.11648/j.aas.20230803.17

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@article{10.11648/j.aas.20230803.17,
  author = {Anisha Giri and Vijay Raj Giri},
  title = {Comparative Assessment of SARIMA and SSES Models for Forecasting Cucumber Prices in Nepal},
  journal = {Advances in Applied Sciences},
  volume = {8},
  number = {3},
  pages = {106-121},
  doi = {10.11648/j.aas.20230803.17},
  url = {https://doi.org/10.11648/j.aas.20230803.17},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.aas.20230803.17},
  abstract = {Cucumber, originally indigenous to Southern Asia, thrives in diverse areas of Nepal. However, despite its promising prospects, cucumber cultivation in Nepal encounters obstacles resulting in reduced profits for farmers. These challenges encompass price volatility, marketing issues, the involvement of intermediaries in pricing, susceptibility to spoilage, and the substantial importation of cucumbers from neighboring India. Moreover, the agricultural market dynamics have led to traders shifting the burden of price risks onto farmers, culminating in lower returns for their produce. In that regard, this study focuses on the forecasting of cucumber prices in Nepal using time series analysis and compare the performance of two popular forecasting models: Seasonal Autoregressive Integrated Moving Average (SARIMA) and Simple Seasonal Exponential Smoothing (SSES). The objective is to provide accurate and reliable price predictions to assist stakeholders in making informed decisions in the cucumber market. The study utilizes historical cucumber price data spanning the past decade to understand the seasonal variations and trends in cucumber prices. The SARIMA model, known for its ability to capture seasonal effects, and the SSES model, a benchmark for seasonal time-series analysis, are both employed in the comparative assessment. The results reveal that the SSES model outperforms the SARIMA model in terms of forecasting accuracy, with lower Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), and Mean Absolute Percentage Error (MAPE) values. The study's findings have significant implications for policymakers, researchers, and farmers involved in the cucumber market, offering valuable insights to optimize production and pricing strategies.},
 year = {2023}
}

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TY  - JOUR
T1  - Comparative Assessment of SARIMA and SSES Models for Forecasting Cucumber Prices in Nepal
AU  - Anisha Giri
AU  - Vijay Raj Giri
Y1  - 2023/09/20
PY  - 2023
N1  - https://doi.org/10.11648/j.aas.20230803.17
DO  - 10.11648/j.aas.20230803.17
T2  - Advances in Applied Sciences
JF  - Advances in Applied Sciences
JO  - Advances in Applied Sciences
SP  - 106
EP  - 121
PB  - Science Publishing Group
SN  - 2575-1514
UR  - https://doi.org/10.11648/j.aas.20230803.17
AB  - Cucumber, originally indigenous to Southern Asia, thrives in diverse areas of Nepal. However, despite its promising prospects, cucumber cultivation in Nepal encounters obstacles resulting in reduced profits for farmers. These challenges encompass price volatility, marketing issues, the involvement of intermediaries in pricing, susceptibility to spoilage, and the substantial importation of cucumbers from neighboring India. Moreover, the agricultural market dynamics have led to traders shifting the burden of price risks onto farmers, culminating in lower returns for their produce. In that regard, this study focuses on the forecasting of cucumber prices in Nepal using time series analysis and compare the performance of two popular forecasting models: Seasonal Autoregressive Integrated Moving Average (SARIMA) and Simple Seasonal Exponential Smoothing (SSES). The objective is to provide accurate and reliable price predictions to assist stakeholders in making informed decisions in the cucumber market. The study utilizes historical cucumber price data spanning the past decade to understand the seasonal variations and trends in cucumber prices. The SARIMA model, known for its ability to capture seasonal effects, and the SSES model, a benchmark for seasonal time-series analysis, are both employed in the comparative assessment. The results reveal that the SSES model outperforms the SARIMA model in terms of forecasting accuracy, with lower Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), and Mean Absolute Percentage Error (MAPE) values. The study's findings have significant implications for policymakers, researchers, and farmers involved in the cucumber market, offering valuable insights to optimize production and pricing strategies.
VL  - 8
IS  - 3
ER  -

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Author Information

Anisha Giri

National Center for Potato, Vegetable and Spice Crops Development, Department of Agriculture, Ministry of Agriculture and Livestock Development, Government of Nepal, Kathmandu, Nepal
Vijay Raj Giri

Department of Mechanical Engineering, University of Michigan-Dearborn, Michigan, USA

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APA Style

Anisha Giri, Vijay Raj Giri. (2023). Comparative Assessment of SARIMA and SSES Models for Forecasting Cucumber Prices in Nepal. Advances in Applied Sciences, 8(3), 106-121. https://doi.org/10.11648/j.aas.20230803.17

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ACS Style

Anisha Giri; Vijay Raj Giri. Comparative Assessment of SARIMA and SSES Models for Forecasting Cucumber Prices in Nepal. Adv. Appl. Sci. 2023, 8(3), 106-121. doi: 10.11648/j.aas.20230803.17

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AMA Style

Anisha Giri, Vijay Raj Giri. Comparative Assessment of SARIMA and SSES Models for Forecasting Cucumber Prices in Nepal. Adv Appl Sci. 2023;8(3):106-121. doi: 10.11648/j.aas.20230803.17

Copy | Download

@article{10.11648/j.aas.20230803.17,
  author = {Anisha Giri and Vijay Raj Giri},
  title = {Comparative Assessment of SARIMA and SSES Models for Forecasting Cucumber Prices in Nepal},
  journal = {Advances in Applied Sciences},
  volume = {8},
  number = {3},
  pages = {106-121},
  doi = {10.11648/j.aas.20230803.17},
  url = {https://doi.org/10.11648/j.aas.20230803.17},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.aas.20230803.17},
  abstract = {Cucumber, originally indigenous to Southern Asia, thrives in diverse areas of Nepal. However, despite its promising prospects, cucumber cultivation in Nepal encounters obstacles resulting in reduced profits for farmers. These challenges encompass price volatility, marketing issues, the involvement of intermediaries in pricing, susceptibility to spoilage, and the substantial importation of cucumbers from neighboring India. Moreover, the agricultural market dynamics have led to traders shifting the burden of price risks onto farmers, culminating in lower returns for their produce. In that regard, this study focuses on the forecasting of cucumber prices in Nepal using time series analysis and compare the performance of two popular forecasting models: Seasonal Autoregressive Integrated Moving Average (SARIMA) and Simple Seasonal Exponential Smoothing (SSES). The objective is to provide accurate and reliable price predictions to assist stakeholders in making informed decisions in the cucumber market. The study utilizes historical cucumber price data spanning the past decade to understand the seasonal variations and trends in cucumber prices. The SARIMA model, known for its ability to capture seasonal effects, and the SSES model, a benchmark for seasonal time-series analysis, are both employed in the comparative assessment. The results reveal that the SSES model outperforms the SARIMA model in terms of forecasting accuracy, with lower Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), and Mean Absolute Percentage Error (MAPE) values. The study's findings have significant implications for policymakers, researchers, and farmers involved in the cucumber market, offering valuable insights to optimize production and pricing strategies.},
 year = {2023}
}

Copy | Download

TY  - JOUR
T1  - Comparative Assessment of SARIMA and SSES Models for Forecasting Cucumber Prices in Nepal
AU  - Anisha Giri
AU  - Vijay Raj Giri
Y1  - 2023/09/20
PY  - 2023
N1  - https://doi.org/10.11648/j.aas.20230803.17
DO  - 10.11648/j.aas.20230803.17
T2  - Advances in Applied Sciences
JF  - Advances in Applied Sciences
JO  - Advances in Applied Sciences
SP  - 106
EP  - 121
PB  - Science Publishing Group
SN  - 2575-1514
UR  - https://doi.org/10.11648/j.aas.20230803.17
AB  - Cucumber, originally indigenous to Southern Asia, thrives in diverse areas of Nepal. However, despite its promising prospects, cucumber cultivation in Nepal encounters obstacles resulting in reduced profits for farmers. These challenges encompass price volatility, marketing issues, the involvement of intermediaries in pricing, susceptibility to spoilage, and the substantial importation of cucumbers from neighboring India. Moreover, the agricultural market dynamics have led to traders shifting the burden of price risks onto farmers, culminating in lower returns for their produce. In that regard, this study focuses on the forecasting of cucumber prices in Nepal using time series analysis and compare the performance of two popular forecasting models: Seasonal Autoregressive Integrated Moving Average (SARIMA) and Simple Seasonal Exponential Smoothing (SSES). The objective is to provide accurate and reliable price predictions to assist stakeholders in making informed decisions in the cucumber market. The study utilizes historical cucumber price data spanning the past decade to understand the seasonal variations and trends in cucumber prices. The SARIMA model, known for its ability to capture seasonal effects, and the SSES model, a benchmark for seasonal time-series analysis, are both employed in the comparative assessment. The results reveal that the SSES model outperforms the SARIMA model in terms of forecasting accuracy, with lower Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), and Mean Absolute Percentage Error (MAPE) values. The study's findings have significant implications for policymakers, researchers, and farmers involved in the cucumber market, offering valuable insights to optimize production and pricing strategies.
VL  - 8
IS  - 3
ER  -

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