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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM63847
Volume:
10 |
5 |
May 2026
Pages:
1-3
Publication Frequency:
Monthly (12 issues per year)
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.

Master of computer application
Bapuji institute of engineering and technology Davanagere
Master of computer application
Bapuji institute of engineering and technology Davanagere
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
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
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
Publication Date
5/23/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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