Leveraging machine learning algorithms to predict stock trends based on company data

Due to the overall continual flow of news, announcements, worldwide data points, and so on, stocks are volatile and unpredictable. This is affected by market volatility and a variety of other variables in the research, both independent and dependent, that impact the stocks’ market˘ value. These vari...

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Bibliographic Details
Main Authors: Kavitha, Mandala, Sai, M. Yaswanth, Arfeen, Md, Harrsha, K. Sri, Mamatha, S., Bajpayee, Shrinidhi Umesh
Format: Conference Proceeding
Language:English
Subjects:
Algorithms
Data points
Decision trees
Machine learning
Online Access:Get full text
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Summary:Due to the overall continual flow of news, announcements, worldwide data points, and so on, stocks are volatile and unpredictable. This is affected by market volatility and a variety of other variables in the research, both independent and dependent, that impact the stocks’ market˘ value. These variables make it difficult for a stock market expert to precisely predicts the market’s peaks and troughs. The major purpose of this essay is to anticipate market stock stability in the future. The studyafocuses˘ on the use of two approaches, gradient boosted decision trees (using XG Boost) and random forests, to forecast whether stock values will rise or fall over the following n days.
ISSN:0094-243X
1551-7616
DOI:10.1063/5.0149083