Paper Title
Stock Price Prediction using Machine Learning
Article Identifiers
Authors
Surbhi Doliya , Priti Sharma
Keywords
Abstract
In the realm of market prediction, investors have historically relied on the analysis of stock prices, indicators, and related news to anticipate market movements, underscoring the significance of news in influencing stock prices. Previous studies in this field have largely focused on categorizing market news as positive, negative, or neutral and examining their impact on stock prices, or on analyzing historical price data to forecast future movements. In our research, we present an automated trading system that amalgamates mathematical functions, machine learning techniques, and external factors such as sentiment analysis of news to enhance stock prediction accuracy and facilitate profitable trades. Specifically, our objective is to forecast the price or trend of a given stock by the end of the trading day based on its performance during the initial trading hours. To accomplish this objective, we have trained conventional machine learning algorithms and developed multiple deep learning models, taking into account the significance of relevant news.
Downloads
How To Cite
"Stock Price Prediction using Machine Learning", IJNRD - INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (www.IJNRD.org), ISSN:2456-4184, Vol.9, Issue 4, page no.e930-e936, April-2024, Available :https://ijnrd.org/papers/IJNRD2404497.pdf
Issue
Volume 9 Issue 4, April-2024
Pages : e930-e936
Other Publication Details
Paper Reg. ID: IJNRD_218485
Published Paper Id: IJNRD2404497
Downloads: 000121181
Research Area: Computer Science & TechnologyÂ
Country: Noida, Uttar Pradesh, India
Published Paper PDF: https://ijnrd.org/papers/IJNRD2404497.pdf
Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2404497
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
Licence
This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition


Publication Timeline
Article Preview: View Full Paper
Call For Paper
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?
By Our website
Click Here to Submit Paper Online
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