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The conventional linear models are unable to cope with the tremendous variability that is posed by this crisis, which has engulfed the world. In this context, in this study, the power of Long Short-Term Memory has been employed to understand the effect of the disruptive footprint of this pandemic on the Healthcare, IT, and Real Estate sectors in India. Contrary to the traditional approach of treating the pandemic as an outlier, the present study integrates the daily infection curves directly into the deep learning mechanism, in effect, compelling the model to learn the pandemic’s momentum in real-time. In this regard, our assessment based on Root Mean Square Error (RMSE) metric verifies the high predictive consistency of all sectors. Unlike traditional econometric tools that fail to filter through the noise of the markets, the architecture of the LSTM model was able to decode the erratic patterns of the Indian equity markets with uniform accuracy. This shows that the layers of deep learning have the ability to tap into the non-linear patterns that exist within financial markets, even when the economy is in a state of free fall. The study thus contributes to understanding sectoral behavior under crisis conditions and provides significant implications for both investors and financial analysts.
Keywords:
LSTM, COVID-19, stock market prediction, Indian stock market, sectoral analysis, time series forecasting
Cite Article:
"STOCK MARKET PREDICTION DURING COVID-19 USING LSTM", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2456-3315, Vol.11, Issue 4, page no.a210-a215, April-2026, Available :http://www.ijrti.org/papers/IJRTI2604031.pdf
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2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator