International Research Journal of Innovations in Engineering and Technology - IRJIET International Open Access, Monthly, Peer Reviewed, Reputed Journal ISSN (online): 2581-3048

Impact Factor (2025): 6.9

DOI Prefix: 10.47001/IRJIET

Predictive Analysis of NEPSE Using LSTM and Technical Indicators

Abstract

The stock market in Nepal has gained a lot of attention in recent times and limited numbers of research are available to predict the stock market based on technical indicators. Predicting a stock market is not easy because of its non-linearity and volatility nature. It is very difficult to make a model that will accurately predict the time series data of the stock market but it can be predicted with some acceptable discrepancies.

Technical analysis is used to predict the stock market but there are some researches that support its effectiveness while other rejects this claim. There is a conflict with technical indicators work in the Nepal Stock Exchange Limited. This comparative analysis checks the effectiveness of the technical indicators to predict the stock market. Among all the other neural networks, long short-term memory is used in this research to predict the stock market.

The results of this research support the statement that technical indicators have some sort of relation between them and closing value which also shows in the correlation matrix. Fundamental and sentimental data along with technical indicators produced more effective results than those of fundamental and sentimental data.

Country : Nepal

1 Bikash Kunwar2 Paras Khati

  1. Department of Electronics and Computer Engineering, Paschimanchal Campus, Gandaki Province, Nepal
  2. Department of Electronics and Computer Engineering, Paschimanchal Campus, Gandaki Province, Nepal

IRJIET, Volume 7, Issue 10, October 2023 pp. 1-9

doi.org/10.47001/IRJIET/2023.710001

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