Stock Price Prediction using Machine Learning

Registration ID: IJNRD_218485

Published ID: IJNRD2404497

DOI: Click Here to Get

Surbhi Doliya , Priti Sharma

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.

Published Paper   E-Certificate

Surbhi Doliya & Priti Sharma (April-2024). Stock Price Prediction using Machine Learning. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 9(4), e930-e936. https://ijnrd.org/papers/IJNRD2404497.pdf

Volume 9 Issue 4, April-2024

Pages : e930-e936

Paper Reg. ID: IJNRD_218485

Published Paper Id: IJNRD2404497

Downloads: 000121992

Research Area: Computer Science & Technology 

Country: Noida, Uttar Pradesh, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2404497.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2404497

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

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

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