A novel hybrid neural network-based volatility forecasting of agricultural commodity prices: empirical evidence from India

A novel hybrid neural network-based volatility forecasting of agricultural commodity prices: empirical evidence from India

Abstract This study presents a comprehensive analysis of agricultural price volatility forecasting using a hybrid long short-term memory (LSTM)-Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model. Agricultural price volatility poses critical challenges for food security, economic...

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Bibliographic Details
Main Authors: R. L. Manogna, Vijay Dharmaji, S. Sarang
Format: Article
Language:English
Published: SpringerOpen 2025-04-01
Series:Journal of Big Data
Subjects:
Price volatility
Neural networks
Forecasting
Agricultural commodities
Hybrid model
Deep learning
Online Access:https://doi.org/10.1186/s40537-025-01131-8
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https://doi.org/10.1186/s40537-025-01131-8

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