Paper Title

A Novel Web Application for Stock Market Analysis and Prediction Using Machine Learning Methods.

Article Identifiers

Registration ID: IJNRD_188534

Published ID: IJNRD2303118

DOI: Click Here to Get

Authors

Pradeep B M , Prasanna G

Keywords

SMAP, News portal and general stock-related chatbot, Deep Neural Network (DNN)

Abstract

Stock Market Analysis and Prediction (SMAP) is a web-based application able to predict the stock prices of companies based on their market values and news sentiments surrounding the company. It is a portal where general stock market enthusiasts can keep track of their invested companies and are also able to instantly contact their brokers for purchases or sales of the stocks. The main application of this system however would be to predict the market values. Along with that, it has the features of a news portal and a general stock-related chatbot. Deep Neural Network (DNN), is used for stock market analysis and prediction. The algorithm’s main goal is to learn market trends by training with past data and predicting future value. The calculated values of the computational analysis i.e., prediction is used to display nearly accurate result.

How To Cite

"A Novel Web Application for Stock Market Analysis and Prediction Using Machine Learning Methods.", IJNRD - INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (www.IJNRD.org), ISSN:2456-4184, Vol.8, Issue 3, page no.b111-b117, March-2023, Available :https://ijnrd.org/papers/IJNRD2303118.pdf

Issue

Volume 8 Issue 3, March-2023

Pages : b111-b117

Other Publication Details

Paper Reg. ID: IJNRD_188534

Published Paper Id: IJNRD2303118

Downloads: 000121163

Research Area: Computer Science & Technology 

Country: MYSORE, KARNATAKA, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2303118.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2303118

About Publisher

Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Publisher: IJNRD (IJ Publication) Janvi Wave

Publication Timeline

Peer Review
Through Scholar9.com Platform

Article Preview: View Full Paper

Call For Paper

Call For Paper - Volume 10 | Issue 8 | August 2025

IJNRD is Scholarly open access journals, Peer-reviewed, and Refereed Journals, High Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool), Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI) with Open-Access Publications.

INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (IJNRD) aims to explore advances in research pertaining to applied, theoretical and experimental Technological studies. The goal is to promote scientific information interchange between researchers, developers, engineers, students, and practitioners working in and around the world. IJNRD will provide an opportunity for practitioners and educators of engineering field to exchange research evidence, models of best practice and innovative ideas.

Indexing In Google Scholar, SSRN, ResearcherID-Publons, Semantic Scholar | AI-Powered Research Tool, Microsoft Academic, Academia.edu, arXiv.org, Research Gate, CiteSeerX, ResearcherID Thomson Reuters, Mendeley : reference manager, DocStoc, ISSUU, Scribd, and many more

How to submit the paper?

Important Dates for Current issue

Paper Submission Open For: August 2025

Current Issue: Volume 10 | Issue 8

Last Date for Paper Submission: Till 31-Aug-2025

Notification of Review Result: Within 1-2 Days after Submitting paper.

Publication of Paper: Within 01-02 Days after Submititng documents.

Frequency: Monthly (12 issue Annually).

Journal Type: International Peer-reviewed, Refereed, and Open Access Journal.

Subject Category: Research Area