Stock Market Price Prediction Using Machine Learning

Stock Market Price Prediction Using Machine Learning

Registration ID: IJNRD_216647

Published ID: IJNRD2403534

DOI: Click Here to Get

Arpitha Mantrodi , Amruthhamshu M G , Shwetha M C , Ankith M S

Decision Tree, Random forest,Linear Decriminant Analysis and Logistics Regression

! Nowadays,stock trading is an essential component of the finance industry. Because the market is always changing, using machine learning to forecast stock values could be challenging. Conversely, however we can more efficiently analyse and visualise stock price projections by utilising machine learning techniques. Many models that machine learning provides aid in improving the precision and dependability of these forecasts. People who are eager to learn more about purchasing or selling stocks may find this to be very helpful as it offers insightful information. It's incredible how technology enables us to forecast stock price movements for businesses worldwide. You might start by looking through books and online courses on machine learning for finance. They can offer insightful advice and help you navigate the process of building models that forecast stock price prediction.

Published Paper   E-Certificate

"Stock Market Price Prediction Using Machine Learning ", IJNRD - INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (www.IJNRD.org), ISSN:2456-4184, Vol.9, Issue 3, page no.f313-f317, March-2024, Available :https://ijnrd.org/papers/IJNRD2403534.pdf

Volume 9 Issue 3, March-2024

Pages : f313-f317

Paper Reg. ID: IJNRD_216647

Published Paper Id: IJNRD2403534

Downloads: 000121195

Research Area: Computer Science & Technology 

Country: Shimoga , Karnataka, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2403534.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2403534

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

This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition

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