Crossref DOIMemberCiteFactoropen accessissn
SJIF Impact Factor 8.659 | ISSN: 2582-3930
IJSREM Logo

International Journal of Scientific Research in Engineering and Management

(Gateway to Global Scholars - An International, Scholarly, Multi-Disciplinary, Open Access Journal)

Peer-Reviewed Journal Designed to Meet UGC's Quality Parameters

HomeCurrent IssuePast IssuesPay OnlineConferencesEditorial BoardAbout UsContact Us
IJSREM

Loading article...

Follow Us

  • Google Scholar
  • ResearchGate
  • Academia.edu
  • Mendeley
  • LinkedIn
  • Facebook
  • Instagram

Journal Policies

  • Peer Review Policy
  • Publication Ethics
  • Copyright Infringement
  • Refund & Cancellation Policy
  • Terms and Conditions
  • Privacy Policy

Journal Identifiers & Licenses

  • ISSN Verified: 2582-3930ISSN Verified: 2582-3930
  • Crossref DOI: 10.55041Crossref DOI: 10.55041
  • SJIF Ranking: 08.659SJIF Ranking: 08.659
  • Licensed under CC BY 4.0Licensed under CC BY 4.0
  • ISO Certification: 9001:2015ISO Certification: 9001:2015
  • Indexed & Cited In: Google ScholarIndexed & Cited In: Google Scholar

Contact Us

International Journal of Scientific Research in Engineering and Management (IJSREM)

#62/1, New No 7, 1st Cross, 2nd Main, Ganganagar, R T Nagar, Bangalore North, Bangalore, Karnataka, India – 560032
[email protected]+91 93911 67991
logos
logos
Working Hours

Mon – Sat: 9:00 AM – 6:00 PM

Sunday: 10:00 AM – 4:00 PM

+91 93911 67991

© 2026 IJSREM – International Journal of Scientific Research in Engineering and Management. This is an open-access journal. Articles are published under the Creative Commons Attribution (CC BY 4.0) License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

DisclaimerPrivacy PolicyTerms and Conditions
ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREM63847

Ai for market trend analysis

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM63847

Volume:

10 |

5 |

May 2026

Pages:

1-3

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/IJSREM63847

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

Share this article:

Authors

BHAVANA S B

BHAVANA S B

Master of computer application

Bapuji institute of engineering and technology Davanagere

Download Author Certificate

Mentors

DGM

Dr. Geetha M

Master of computer application

Bapuji institute of engineering and technology Davanagere

Download Mentor Certificate

Author Services & Downloads

Full ArticlesAcceptance Certificate

Abstract

Artificial Intelligence (AI) has emerged as a transformative technology in financial and business analytics, enabling accurate prediction and interpretation of market trends. This paper presents an AI-based market trend analysis system that leverages machine learning and data analytics techniques to forecast future market movements. The proposed system utilizes historical market data, news sentiment, and social media signals to identify patterns and generate predictive insights. Advanced algorithms such as Linear Regression, Random Forest, and Long Short-Term Memory (LSTM) networks are employed to analyze time-series data and detect hidden correlations. Natural Language Processing (NLP) techniques are integrated to perform sentiment analysis on financial news and online content, enhancing prediction accuracy. The system is designed to assist investors, analysts, and businesses in making data-driven decisions by providing real-time trend visualization and risk assessment. Experimental results demonstrate improved forecasting accuracy compared to traditional statistical methods. The proposed AI-driven approach enhances decision-making efficiency, reduces uncertainty, and contributes to more strategic investment planning in dynamic market environments.

KEYWORDS

KEYWORDS: Artificial Intelligence (AI)Market Trend Analysis Machine Learning Deep Learning Predictive Analytics Time Series Forecasting Data Mining Big Data Analytics Financial Market Prediction Stock Market Analysis Natural Language Processing (NLP) Sentiment Analysis Feature Engineering Algorithmic Trading.

Cite This Article

BHAVANA S B, Dr. Geetha M, "Ai for market trend analysis," International Journal of Scientific Research in Engineering and Management, vol. 10, no. 5, pp. 1-3, May 2026. https://doi.org/10.55041/IJSREM63847

Full Article/Conclusion

  The project “AI for Market Trend Analysis” successfully demonstrates visualization tools the system effectively analyzes data to uncover meaningful insights. This project involved assisting the organization in implementing data-driven decision-making with the analysis of market trends and opportunities in the future.This particular project can be taken to be a significant contribution in the increasing field of business intelligence with the aid of AI as this particular project has come up with a feasible model that can detect trends automatically. More efficient in handling live data input and accurate with predictions that match actual performances in the markets.AI for Market Trend Analysis has developed an efficient system applied in making decisions for businesses. The findings of the research confirm that artificial intelligence is applicable in modern analysis processes thereby offering a new dawn in carrying out fast and accurate market analysis Artificial Intelligence in understanding, predicting, and responding to dynamic market conditions. By integrating machine learning algorithms, data mining techniques, and real-time analytics, the proposed system effectively analyzes historical and live market data to identify hidden patterns, forecast future trends, and support strategic decision-making. The study highlights how advanced models such as Long Short-Term Memory networks and Random Forest improve prediction accuracy compared to traditional statistical approaches. Furthermore, the incorporation of big data processing tools and visualization dashboards enhances interpretability and usability for businesses and investors. Experimental results confirm that AI-driven models provide higher accuracy

References

1.    Brownlee J. (2020). ML Mastery with Python: Understand Your Data Create Accurate Models and Work Projects End-to-End. Machine Learning Mastery. 2.    Han J. Kamber M. & Pei J. (2021). Concepts and Techniques. Elsevier. 3.    Bishop C. M. (2019). Pattn Recog and Machine Learning. Springer. 4.    Russell S. & Norvig P. (2021). Artificial Intelligence: A Modern Approach (4th Edition). Pearson. 5.    IBM Cloud Education. (2023). What is Market Analysis with AI? Retrieved from https://www.ibm.com/topics/ai-market-analysis 6.    Kaggle Datasets. (2024). Global Market Trends Dataset for Machine Learning. Retrieved from https://www.kaggle.com 7.    Google Cloud AI Blog. (2023). AI in Predictive Analytics and Business Forecasting. Retrieved from https://cloud.google.com/blog

Editorial & Review Transparency

Publication Date

5/23/2026

Peer Review Type

Double-Blind Peer Review

Review Rounds: 2

Documents

Review Report (Confidential)
Copyright Form (Office)

Article Metrics & Impact

Article Views

0

Total views since publication

PDF Downloads

2

Total downloads since publication

Geographic Reach

5

Indexing, Archiving & Preservation

Google Scholar
Academia
ResearchGate
Crossref
SSRN
Semantic Scholar
Thomson Reuters
WorldCat
Mendeley
OpenAlex
EBSCO
Zenodo

Digital Preservation: This article is permanently archived on Zenodo and complies with all data preservation standards across major indexing platforms.

Ethics, Compliance & Transparency

Plagiarism Screening

This manuscript has been checked for plagiarism using TurnitinPlagiarismChecker software.

Conflict of Interest

The authors declare no conflict of interest related to this research work.

Funding Information

No funding information available for this research.

Similar & Recommended Articles

Similar Articles by Topic

Related research in the same subject area

Loading similar articles...