A Study on Predictive Models for the Stock Market

Authors

  • Bhavisshya Amit Goyal 21K School (British), Indiranagar, Bangalore- 560038, Karnataka, India.

Keywords:

stock merket, shares, stocks

Abstract

Prediction of futuristic price of stocks (shares) of listed companies at exchange has always been a fascinating area of interest for all kind of market participants. Whether short term traders. long term investors, or risk managers, everyone interest lies in forecasting the market accurately and in time. This work of mine “Stock Prediction using LSTM (Long Short-Term Memory”) method is a sincere effort in same direction, and I hope it will immensely help all
market participants and serve them with more accuracy in forecasting share prices in near future period.

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References

Hochreiter, S., & Schmidhuber, J. (1997). Long short-term memory. Neural Computation, 9(8),

–1780. https://doi.org/10.1162/neco.1997.9.8.1735

Chen, K., Zhou, Y., & Dai, F. (2015). A LSTM-based method for stock price prediction. Expert Systems with

Applications, 42(8), 3903–3910. https://doi.org/10.1016/j.eswa.2014.11.047

Li Qi, et al. (2024). Integrating Symbolic Genetic Programming With Lstm for Forecasting Cross-Sectional

Price Returns: A Comparative Analysis of Chinese And Japanese Stock Market. Advances in Artificial Intelligence and Machine Learning, 4(4), 2981-3005.

YahooFinance. (n.d.). Historical market data. Retrieved from https://www.yfinance.com

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Published

2025-05-27

How to Cite

Goyal, B. A. (2025). A Study on Predictive Models for the Stock Market. Graduate Journal of Interdisciplinary Research, Reports and Reviews , 3(01), 62–67. Retrieved from https://jpr.vyomhansjournals.com/index.php/gjir/article/view/54

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