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Comparative Analysis of Time Series Forecasting Models for Predicting Hydrogen Fuel-Related Stock in the Indian Market

The study compares the capabilities of various time series and machine learning models including ARIMA, LSTM, CatBoost, XGBoost, and LightGBM, by predicting the equity movement for major Indian infrastructure and energy companies with hydrogen related exposure, namely Larsen & Toubro, NTPC Limited,...

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Principais autores: Angel Mary Jais, Nandhini Haribabu Muthuvel, Sunanda Saha, Abhishek Das, Venkatesh Subramanian
Format: Artigo
Sprog:Inglês
Udgivet: Ram Arti Publishers 2026-06-01
Serier:International Journal of Mathematical, Engineering and Management Sciences
Fag:
time series
lstm
gradient boosting
stock market forecasting
hydrogen fuel-related stock
Online adgang:https://www.ijmems.in/cms/storage/app/public/uploads/volumes/58-IJMEMS-25-0950-11-3-1424-1443-2026.pdf
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