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Predicting the Unpredictable: An Application of Machine Learning Algorithms in Indian Stock Market

Predicting the Unpredictable: An Application of Machine Learning Algorithms in Indian Stock Market The stock market is a popular investment option for investors because of its expected high returns. Stock market prediction is a complex task to achieve with the help of artificial intelligence. Because stock prices depend on many factors, including trends and news in the market. However, in recent years, many creative techniques and models have been proposed and applied to efficiently and accurately forecast the behaviour of the stock market. This paper presents a comparative study of fundamental and technical analysis based on different parameters. We also discuss a comparative Analysis of various prediction techniques used to predict stock price. These strategies include technical analysis like time series analysis and machine learning algorithms such as the artificial neural network (ANN). Along with them, few researchers focused on the textual analysis of stock prices by continuous analysing the public sentiments from social media and other news sources. Various approaches are compared based on methodologies, datasets, and efficiency with the help of visualisation. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Annals of Data Science Springer Journals

Predicting the Unpredictable: An Application of Machine Learning Algorithms in Indian Stock Market

Annals of Data Science , Volume 9 (4) – Aug 1, 2022

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References (22)

Publisher
Springer Journals
Copyright
Copyright © Springer-Verlag GmbH Germany, part of Springer Nature 2019
Subject
Business and Management; Business and Management, general; Statistics for Business, Management, Economics, Finance, Insurance; Artificial Intelligence
ISSN
2198-5804
eISSN
2198-5812
DOI
10.1007/s40745-019-00230-7
Publisher site
See Article on Publisher Site

Abstract

The stock market is a popular investment option for investors because of its expected high returns. Stock market prediction is a complex task to achieve with the help of artificial intelligence. Because stock prices depend on many factors, including trends and news in the market. However, in recent years, many creative techniques and models have been proposed and applied to efficiently and accurately forecast the behaviour of the stock market. This paper presents a comparative study of fundamental and technical analysis based on different parameters. We also discuss a comparative Analysis of various prediction techniques used to predict stock price. These strategies include technical analysis like time series analysis and machine learning algorithms such as the artificial neural network (ANN). Along with them, few researchers focused on the textual analysis of stock prices by continuous analysing the public sentiments from social media and other news sources. Various approaches are compared based on methodologies, datasets, and efficiency with the help of visualisation.

Journal

Annals of Data ScienceSpringer Journals

Published: Aug 1, 2022

Keywords: Stock market prediction; Machine learning algorithms; Artificial neural network; Sentiment analysis; Long short memory neural network

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