Supervised Machine Learning for Financial Marketing Forecasting

Abstract:- One of the most intricate and sophisticated forms of trade is the stock market, also referred to as the stock exchange. Small businesses, brokerage firms, and the banking industry all rely on this one entity to generate income and distribute risks; it's a very intricate arrangement. This article discusses utilising machine learning algorithms to anticipate the future stock price on the exchange using open-source libraries and already-existing algorithms in order to make this unstable business model a little more predictable. We'll see if this straightforward implementation yields respectable outcomes. The result is entirely dependent on math and makes numerous axiomatic assumptions that may or may not be true at the time of prediction. Keywords— Supervised Machine Learning, Stock Market, Linear Regression, Fundamental, Data Analysis, Basics.

Authors

Publication Details

Journal
International Scientific Journal of Engineering and Management
Published
2025-08-04
DOI
https://doi.org/10.55041/isjem04943
Primary Topic
Stock Market Forecasting Methods
Type
article
Field-Weighted Citation Impact
0.00
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article

Supervised Machine Learning for Financial Marketing Forecasting

Meeta Tarani, NALI RAVITEJA
International Scientific Journal of Engineering and Management
Stock Market Forecasting Methods
article

Supervised Machine Learning for Financial Marketing Forecasting

Meeta Tarani, NALI RAVITEJA
article en

Abstract

Abstract:- One of the most intricate and sophisticated forms of trade is the stock market, also referred to as the stock exchange. Small businesses, brokerage firms, and the banking industry all rely on this one entity to generate income and distribute risks; it's a very intricate arrangement. This article discusses utilising machine learning algorithms to anticipate the future stock price on the exchange using open-source libraries and already-existing algorithms in order to make this unstable business model a little more predictable. We'll see if this straightforward implementation yields respectable outcomes. The result is entirely dependent on math and makes numerous axiomatic assumptions that may or may not be true at the time of prediction. Keywords— Supervised Machine Learning, Stock Market, Linear Regression, Fundamental, Data Analysis, Basics.

International Scientific Journal of Engineering and ManagementVol. 04(08)
Openalex Percentile: Top 77%
Stock Market Forecasting Methods
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