Journal of Ubiquitous Computing and Communication Technologies
IRO Journals
Volume 5 — Issue 2 — June 2023

Indian Machinery and Transport Equipment Exports - Forecasting with External Factors Using Chain of Hybrid Sarimax-Garch Model

https://doi.org/10.36548/jucct.2023.2.005
Ramneet Singh Chadha
Associate Director, C-DAC, Noida, Uttar Pradesh, India
Shahzadi Parveen
Project Engineer,C-DAC, Noida, Uttar Pradesh, India
Jugesh
Project Intern,C-DAC, Noida, Uttar Pradesh, India
Jasmehar Singh
Shiv Nadar University, Noida, Uttar Pradesh, India
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How to Cite

Chadha, Ramneet Singh, Shahzadi Parveen, Jugesh, and Jasmehar Singh. 2023. “Indian Machinery and Transport Equipment Exports - Forecasting With External Factors Using Chain of Hybrid Sarimax-Garch Model”. Journal of Ubiquitous Computing and Communication Technologies 5 (2): 175-92. https://doi.org/10.36548/jucct.2023.2.005.
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Keywords

— Time Series Forecasting
— SARIMAX
— External Factors
— Export Prediction
— GARCH
— ARCH
— Hybrid Forecasting model
— Exogenous variable
— Export Forecasting
— India Machinery and Transport export
Published: 28-06-2023

Abstract

To choose the best forecasting model, it is essential to comprehend time series data since external influences like social, economic, and political events may affect the way the data behave. This study considers outside variables that could have an impact on the target variable used in improving the predictions. India Machinery and Transport Equipment Dataset is gathered from various sources, are cleaned, pre-processed, the missing values are removed, data types are converted, and dependent variables are identified before being used. By incorporating the SARIMAX model with the GARCH model and experimenting with various parameters and conditions, the current study seeks to enhance it. The SARIMAX-GARCH Model is a time series forecasting method used to predict market swings and export values. A helper model is developed to forecast the exogenous value to forecast the export value, which is then used as input for the final model. The ideal parameters for boosting the hybrid model's performance were identified through hyperparameter tuning. The results of this study provide estimates for future export values and contribute to a better understanding of India's Machinery and Transport Equipment export market. This research work focuses on export value forecasting with the use of future exogenous variables. Exogenous factors are essential for predicting market changes and, as a result, support the forecasting of precise export values.

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