English Abstract
Abstract :
Stock market price prediction is considered a critically important issue for designing future investments and
consumption plans. Besides, given the fact that the COVID-19 pandemic has adversely impacted stock markets
worldwide, especially over the past two years, investment decisions have become more challenging for risky.
Hence, we propose a two-phase framework for forecasting prices of oil, coal, and natural gas in India, both for
pre-and post-COVID-19 scenarios. Notably, the Autoregressive Integrated Moving Average, Simple Exponential
Smoothing, and K- Nearest Neighbor approaches are utilized for analyses using data from January 2020 to May
2022. Besides, the various outcomes from the analytical exercises are matched with root mean squared error and
mean absolute and percentage errors. Overall, the empirical outcomes show that the Autoregressive Integrated
Moving Average method is appropriate for predicting India’s oil, coal, and natural gas prices. Moreover, the
predictive precision of oil, coal, and natural gas in the pre-COVID-19 period seems to be better than in that the
post-COVID-19 stage. Additionally, prices of these energy resources are forecasted to increase through the year
2025. Finally, in line with the findings, significant policy recommendations are made.
