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Original Article

Enhanced BSE SENSEX Forecasting Through Technical Indicator Integration and PSO-Based Feature Selection

Open Access Peer Reviewed Crossref DOI

Authors

  • Aman Sahu1
  • Vineet kumar Awasthi2

1 Student, Department of Computer Science and Information Technology, Guru Ghasidas Vishwavidyalaya, Bilaspur, India 2 Professor, Department of Computer Science and Information Technology, Guru Ghasidas Vishwavidyalaya, Bilaspur, India

Article Information

Published Online
September-December 2026
Pages
741-751
Article Type
Original Article
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References

[1] G. E. P. Box, G. M. Jenkins, G. C. Reinsel, and G. M. Ljung, Time Series Analysis: Forecasting and Control, 5th ed. Hoboken, NJ, USA: Wiley, 2015.
[2] J. Patel, S. Shah, P. Thakkar, and K. Kotecha, “Predicting stock and stock price index movement using trend deterministic data preparation and machine learning techniques,” Expert Syst. Appl., vol. 42, no. 1, pp. 259–268, 2015.
[3] L. Breiman, “Random forests,” Mach. Learn., vol. 45, no. 1, pp. 5–32, 2001.
[4] E. F. Fama, “Efficient capital markets: A review of theory and empirical work,” J. Finance, vol. 25, no. 2, pp. 383–417, 1970.
[5] C. Bergmeir and J. M. Benítez, “On the use of cross-validation for time series predictor evaluation,” Inf. Sci., vol. 191, pp. 192–213, 2012.
[6] L. Breiman, “Bagging predictors,” Mach. Learn., vol. 24, no. 2, pp. 123–140, 1996.
[7] T. Hastie, R. Tibshirani, and J. Friedman, The Elements of Statistical Learning, 2nd ed. New York, NY, USA: Springer, 2009.
[8] R. J. Hyndman and A. B. Koehler, “Another look at measures of forecast accuracy,” Int. J. Forecast., vol. 22, no. 4, pp. 679–688, 2006.
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