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Updated: Sep 1, 2025

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
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Impact of Healthcare on Stock Market Volatility and Its Predictive Solution Using Improved Neural Network.

Nusrat Rouf1, Majid Bashir Malik1, Sparsh Sharma2

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Summary

This study introduces a novel machine learning model for predicting stock market prices during the COVID-19 pandemic. The proposed model, utilizing technical indicators and COVID-19 data, demonstrates superior performance in stock analysis.

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Area of Science:

  • Financial Markets
  • Data Science
  • Epidemiology

Background:

  • The COVID-19 pandemic caused significant global economic disruption and stock market volatility.
  • Predicting stock market behavior during such crises is crucial for economic stability.
  • Traditional stock prediction methods face challenges due to the nonlinear and dynamic nature of financial data.

Purpose of the Study:

  • To develop and evaluate a novel machine learning model for stock index price prediction during the COVID-19 pandemic.
  • To explore the impact of hyperparameter optimization on model accuracy.
  • To investigate the importance of feature selection and preprocessing using technical and COVID-19 data.

Main Methods:

  • A customized neural network model was developed.
  • A novel dataset was created incorporating nine technical indicators and COVID-19 data.
  • Feature selection techniques and extensive hyperparameter optimization were employed.

Main Results:

  • The proposed model demonstrated superior performance compared to other evaluated models.
  • The study highlights the effectiveness of hyperparameter optimization in enhancing prediction accuracy.
  • Optimal feature selection and preprocessing were found to be critical for robust stock index prediction.

Conclusions:

  • The developed machine learning model offers a significant contribution to stock analysis research during pandemics.
  • This approach provides a robust framework for predicting stock market trends amidst global health crises.
  • The findings underscore the value of advanced machine learning techniques in financial forecasting.