Analysis of Machine Learning Methods for Predictions of Stock Exchange Share Prices

Aug 2, 2026

Upload by Liam

Stock market price trend prediction remains a major research topic across finance and technology, with machine-learning algorithms increasingly used to analyze price patterns and forecast stock prices and index movements. The research focuses on improving future price prediction accuracy in volatile, non-linear markets by applying support vector machines, linear regression, decision stumps, and nearest-neighbor classification. The study also defines useful parameters for recognizing predictive stock behaviors and discusses combining boosting with other learning methods to enhance forecasting performance.

LanguageEnglish

CategoryResearch & Report

FormatPDF

Pages7

Reading Time18 min

AccessFree to download

Introduction

Problem formulation

Stock market forecasting and risk reduction

Role of intelligent trading and AI

Fundamental vs. technical analysis

Hybrid approaches and prior research

94 Scientific Journal of Astana IT University ISSN (P): 2707-9031 ISSN (E): 2707-904X DOI: 10.37943/AITU.2021.47.22.009 V. Serbin Associate professor of Department of Information Systems [v_serbin@mail.ru](v_serbin@mail.ru), [orcid.org/0000-0002-5807-3873](orcid.org/0000-0002-5807-3873)[ ](orcid.org/0000-0002-5807-3873)International Information Technology University, Kazakhstan U. Zhenisserov Master of Science in “Management of IT-projects” [zheniserov@gmail.com](zheniserov@gmail.com), [orcid.org/0000-0003-2948-1189](orcid.org/0000-0003-2948-1189)[ ](orcid.org/0000-0003-2948-1189)International Information Technology University, Kazakhstan ANALYSIS OF MACHINE LEARNING METHODS FOR PREDICTIONS OF STOCK EXCHANGE SHARE PRICES Abstract: Since the stock market is one of the most important areas for investors, stock market price trend prediction is still a hot subject for researchers in both financial and technical fields. Lately, a lot of work has been analyzed and done in the field of machine learning algorithms for analyzing price patterns and predicting stock prices and index changes. Currently, machine-learning methods are receiving a lot of attention for predicting prices in financial markets. The main goal of current research is to improve and develop a system for predicting future prices in financial markets with higher accuracy using machine-learning methods. Precise predicting stock market returns is a very difficult task due to the volatile and non-linear nature of financial stock markets. With the advent of artificial intelligence and machine learning, forecasting methods have become more effective at predicting stock prices. In this article, we looked at the machine learning techniques that have been used to trade stocks to predict price changes before an actual rise or fall in the stock price occurs. In particular, the article discusses in detail the use of support vector machines, linear regression, and prediction using decision stumps, classification using the nearest neighbor algorithm, and the advantages and disadvantages of each method. The paper introduces parameters and variables that can be used to recognize stock price patterns that might be useful in future stock forecasting, and how the boost can be combined with other learning algorithms to improve the accuracy of such forecasting systems. Keywords: Neural networks, stock market, price prediction, machine learning. Introduction Formulation of the problem. Everyone wants to be rich in their life without making a lot of effort and having great advantages. Likewise, we want to look into our future with the innermost desire, since we do not want to take risks or want to reduce the risk factor. The stock market is a place where buying and selling can secure future life goals. [12] Now the question is, how can we benefit from the stock market? Alternatively, what are the steps that can give us predictions in the stock markets before you get into the risk zone [13]. How can artificial intelligence with machine learning algorithms help predict future market trends. By predicting the trend of the stock market, we can avoid wasting money. Stock market forecasting is the process of predicting the future based on past data. Forecasting reduces the level of risk for investors and increases the level of confidence for investments. If they predicted goals before they reached them, they could avoid losing money. All of these considerations DOI: 10. 37943/AITU.2021.47.22.009 © V. Serbin, U. Zhenisserov 95 work like forecasting the stock market. Based on trends in historical data, we propose a future trend called the stock market forecast. According to an international Microsoft survey, 94% of CEOs believe that artificial intelligence technologies are important for the strategic goals of their organizations. At the sametime, 27% of respondents have already implemented the relevant technologies in key business processes; another 46% are condu

FAQs

Why is stock price prediction difficult?

Stock markets are highly dynamic, with rapid changes driven by both known parameters and external unknown factors. Their volatile and non-linear behavior makes accurate forecasting challenging.

What goal does the research focus on?

The goal is to improve and develop a system for predicting future financial market prices with higher accuracy using machine-learning methods.

Which machine-learning techniques are discussed in the study?

The article details support vector machines, linear regression, decision stumps, and nearest-neighbor classification. It also explains how parameters can recognize stock price patterns and how boosting can be combined with other algorithms.

Aug 2, 2026

Upload by Liam