A LSTM based model for stock price analysis and prediction

Title

A LSTM based model for stock price analysis and prediction

Creator

Basha M.S.A.; Sucharitha M.M.; Krishnan V.S.; Lakshmi M.B.

Description

The share market in India is exceedingly unpredictable and volatile, with an infinite range of factors regulating the share market's orientations and tendencies; hence, forecasting the upswing and downturn is a difficult procedure. Because of several essential aspects, the principles of share market have always been unclear for shareholders. This study aims to significantly reduce the likelihood of analysis and forecasting with Long Short-term Memory (LSTM) model approach that is both resilient yet easy is still suggested. LSTM is a complete Learning Model that is a Predictive Method. Conversely, advancements in technology have opened the way for more efficient and precise share market forecasting in current times. Using the provided historical data sets, the results showed that the LSTM model has considerable potential for forecasting. 2023 Author(s).

Source

AIP Conference Proceedings, Vol-2888, No. 1

Date

2023-01-01

Publisher

American Institute of Physics Inc.

Subject

LSTM; Machine Learning; Stock Price prediction

Coverage

Basha M.S.A., GITAM School of Business, Gandhi Institute of Technology and Management, GITAM University, Karnataka, Bengaluru, India; Sucharitha M.M., School of Commerce, Finance and Accountancy, CHRIST University, Karnataka, Bengaluru, India; Krishnan V.S., School of Commerce, Finance and Accountancy, CHRIST University, Karnataka, Bengaluru, India; Lakshmi M.B., School of Commerce, Finance and Accountancy, CHRIST University, Karnataka, Bengaluru, India

Rights

Restricted Access

Relation

ISSN: 0094243X

Format

Online

Language

English

Type

Conference paper

Identifier

https://doi.org/10.1063/5.0164524

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85176772176&doi=10.1063%2f5.0164524&partnerID=40&md5=264f5ba90dd52ae413e34b076aa14af3