A survey on machine learning for stock price prediction: algorithms and techniques
A survey on machine learning for stock price prediction: algorithms and techniques
Stock market trading is an activity in which investors need fast and accurate information to make effective decisions. Since many stocks are traded on a stock exchange, numerous factors influence the decision-making process. Moreover, the behaviour of stock prices is uncertain and hard to predict. For these reasons, stock price prediction is an important process and a challenging one. This leads to the research of finding the most effective prediction model that generates the most accurate prediction with the lowest error percentage. This paper reviews studies on machine learning techniques and algorithm employed to improve the accuracy of stock price prediction.
Deep Learning, Finance, Machine Learning, Stock Price Prediction, Time Series Analysis
63-71
Obthong, Mehtabhorn
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Tantisantiwong, Nongnuch
73b57288-a4dc-4456-8d1b-12b8d07dc3b4
Jeamwatthanachai, Watthanasak
08576ac1-124d-4bfa-8ca2-49e6663161c3
Wills, Gary
3a594558-6921-4e82-8098-38cd8d4e8aa0
6 May 2020
Obthong, Mehtabhorn
d7aae1b9-9dfc-4d29-b314-a9a00c138ab8
Tantisantiwong, Nongnuch
73b57288-a4dc-4456-8d1b-12b8d07dc3b4
Jeamwatthanachai, Watthanasak
08576ac1-124d-4bfa-8ca2-49e6663161c3
Wills, Gary
3a594558-6921-4e82-8098-38cd8d4e8aa0
Obthong, Mehtabhorn, Tantisantiwong, Nongnuch, Jeamwatthanachai, Watthanasak and Wills, Gary
(2020)
A survey on machine learning for stock price prediction: algorithms and techniques.
2nd International Conference on Finance, Economics, Management and IT Business, Vienna House Diplomat Prague, Prague, Czech Republic.
05 - 06 May 2020.
.
(doi:10.5220/0009340700630071).
Record type:
Conference or Workshop Item
(Paper)
Abstract
Stock market trading is an activity in which investors need fast and accurate information to make effective decisions. Since many stocks are traded on a stock exchange, numerous factors influence the decision-making process. Moreover, the behaviour of stock prices is uncertain and hard to predict. For these reasons, stock price prediction is an important process and a challenging one. This leads to the research of finding the most effective prediction model that generates the most accurate prediction with the lowest error percentage. This paper reviews studies on machine learning techniques and algorithm employed to improve the accuracy of stock price prediction.
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mo1n18_FEMIB_2020
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Submitted date: 12 December 2019
Accepted/In Press date: 17 February 2020
Published date: 6 May 2020
Additional Information:
Publisher Copyright:
Copyright © 2020 by SCITEPRESS - Science and Technology Publications, Lda. All rights reserved.
Venue - Dates:
2nd International Conference on Finance, Economics, Management and IT Business, Vienna House Diplomat Prague, Prague, Czech Republic, 2020-05-05 - 2020-05-06
Keywords:
Deep Learning, Finance, Machine Learning, Stock Price Prediction, Time Series Analysis
Identifiers
Local EPrints ID: 437785
URI: http://eprints.soton.ac.uk/id/eprint/437785
PURE UUID: 02b3a893-5a10-4496-a569-7d367f0930bb
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Date deposited: 17 Feb 2020 17:30
Last modified: 17 Mar 2024 02:43
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Contributors
Author:
Mehtabhorn Obthong
Author:
Nongnuch Tantisantiwong
Author:
Watthanasak Jeamwatthanachai
Author:
Gary Wills
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