Using Data Mining with Time Series Data in Short-Term Stocks Prediction: A Literature Review

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International Journal of Intelligence Science

ISSN Print: 2163-0283
ISSN Online: 2163-0356
www.scirp.org/journal/ijis
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"Using Data Mining with Time Series Data in Short-Term Stocks Prediction: A Literature Review"
written by José Manuel Azevedo, Rui Almeida, Pedro Almeida,
published by International Journal of Intelligence Science, Vol.2 No.4A, 2012

has been cited by the following article(s):

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[2]	The Predictability of Stock Price: Empirical Study onTick Data in Chinese Stock Market
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[3]	Application and performance of data mining techniques in stock market: A review
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[4]	Green supply chain practices and sustainable performance of mining firms: Evidence from a developing country
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[5]	A Comparative Study on Mathematical Approaches to Determine the Time Lag and Synchrony Between Two Time-Series Data in Different Engineering Applications
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[6]	Assessment of Interannual Variability of Moistening of Siberian Territory According to Observational Data
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[7]	Data-Driven Roadmapping (DDRM): Approach and Case Demonstration
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[8]	Stock Movement Modeling Based on the Analysis of Negative Correlation
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[9]	Selección del Modelo Completo en Bases de Datos Temporales a través de Metaheurısticas
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[10]	Forecasting, valuation and portfolio returns of stock market evolution: problems, paradoxes and efficient information. Worldwide implications and Romanian evidence
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[11]	Deep Stock Ranker: A LSTM Neural Network Model for Stock Selection
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[12]	Data-driven Roadmapping Turning Challenges into Opportunities
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[13]	Data mining and big data
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[14]	A Comprehensive Survey of Data Mining Techniques on Time Series Data for Rainfall Prediction.
	2017

[15]	Experimental Modelling
	Digital Signal Processing with Matlab Examples, Volume 2, 2017

[16]	A Comprehensive Survey of Data Mining Techniques on Time Series Data for Rainfall Prediction
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[17]	An Improved Approach to Forecast Equity Market Using Time Series Method
	2015

[18]	An Experimental Study on Predictive Models Using Hierarchical Time Series
	Progress in Artificial Intelligence, 2015

[19]	Time Series Data Mining: A Retail Application
	International journal of business analytics (IJBAN), 2014

[20]	Matching Observed with Empirical Reality–What you see is what you get?
	Fundamenta Informaticae, 2014, 2014

[21]	Cleaner Logistics and Supply Chain


[22]	PORTFOLIO MANAGEMENT USING TIME SERIES ANALYSIS

[1]	The Predictability of Stock Price: Empirical Study on Tick Data in Chinese Stock Market Big Data Research, 2024 DOI:10.1016/j.bdr.2023.100414

[2]	Future‐Oriented Technology Assessment 2024 DOI:10.1002/9781119909880.ch13

[3]	Data-Driven Roadmapping (DDRM): Approach and Case Demonstration IEEE Transactions on Engineering Management, 2022 DOI:10.1109/TEM.2020.3005341

[4]	Green supply chain practices and sustainable performance of mining firms: Evidence from a developing country Cleaner Logistics and Supply Chain, 2022 DOI:10.1016/j.clscn.2022.100046

[5]	Application and performance of data mining techniques in stock market: A review Intelligent Systems in Accounting, Finance and Management, 2022 DOI:10.1002/isaf.1518

[6]	Data-Driven Roadmapping (DDRM): Approach and Case Demonstration IEEE Transactions on Engineering Management, 2022 DOI:10.1109/TEM.2020.3005341

[7]	Application and performance of data mining techniques in stock market: A review Intelligent Systems in Accounting, Finance and Management, 2022 DOI:10.1002/isaf.1518

[8]	Recent Trends in Design, Materials and Manufacturing Lecture Notes in Mechanical Engineering, 2022 DOI:10.1007/978-981-16-4083-4_22

[9]	Assessment of Interannual Variability of Moistening of Siberian Territory According to Observational Data Water, 2021 DOI:10.3390/w13162200

[10]	Stock Movement Modeling Based on the Analysis of Negative Correlation International Journal of e-Education, e-Business, e-Management and e-Learning, 2020 DOI:10.17706/ijeeee.2020.10.2.125-134

[11]	FORECASTING, VALUATION AND PORTFOLIO RETURNS OF STOCK MARKET EVOLUTION: PROBLEMS, PARADOXES AND EFFICIENT INFORMATION. WORLDWIDE IMPLICATIONS AND ROMANIAN EVIDENCE Journal of Business Economics and Management, 2019 DOI:10.3846/jbem.2019.11355

[12]	Data-driven Roadmapping Turning Challenges into Opportunities 2018 Portland International Conference on Management of Engineering and Technology (PICMET), 2018 DOI:10.23919/PICMET.2018.8481975

[13]	Digital Signal Processing with Matlab Examples, Volume 2 Signals and Communication Technology, 2017 DOI:10.1007/978-981-10-2537-2_6

[14]	Progress in Artificial Intelligence Lecture Notes in Computer Science, 2015 DOI:10.1007/978-3-319-23485-4_50

[15]	Progress in Artificial Intelligence Lecture Notes in Computer Science, 2015 DOI:10.1007/978-3-319-23485-4_50

[16]	Time Series Data Mining International Journal of Business Analytics, 2014 DOI:10.4018/ijban.2014100104

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