A Bayesian-adaboost model for stock trading rule discovery

2017 10th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI) ◽

10.1109/cisp-bmei.2017.8302138 ◽

2017 ◽

Author(s):

Zhoufan Kong ◽

Jie Yang ◽

Qinghua Huang ◽

Xuelong Li

Keyword(s):

Rule Discovery ◽

Trading Rule ◽

Stock Trading

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Stock trading rule discovery with an evolutionary trend following model

Expert Systems with Applications ◽

10.1016/j.eswa.2014.07.059 ◽

2015 ◽

Vol 42 (1) ◽

pp. 212-222 ◽

Cited By ~ 38

Author(s):

Yong Hu ◽

Bin Feng ◽

Xiangzhou Zhang ◽

E.W.T. Ngai ◽

Mei Liu

Keyword(s):

Evolutionary Trend ◽

Rule Discovery ◽

Trading Rule ◽

Stock Trading

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Stock trading rule discovery with double deep Q-network

Applied Soft Computing ◽

10.1016/j.asoc.2021.107320 ◽

2021 ◽

pp. 107320

Author(s):

Yong Shi ◽

Wei Li ◽

Luyao Zhu ◽

Kun Guo ◽

Erik Cambria

Keyword(s):

Rule Discovery ◽

Trading Rule ◽

Stock Trading

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Stock Trading Rule Discovery based on temporal data mining

International Conference on Electrical & Computer Engineering (ICECE 2010) ◽

10.1109/icelce.2010.5700755 ◽

2010 ◽

Cited By ~ 3

Author(s):

Asadullah Al Galib ◽

Mahbub Alam ◽

Nowshad Hossain ◽

Rashedur M Rahman

Keyword(s):

Data Mining ◽

Rule Discovery ◽

Temporal Data Mining ◽

Temporal Data ◽

Trading Rule ◽

Stock Trading

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An evolutionary trend reversion model for stock trading rule discovery

Knowledge-Based Systems ◽

10.1016/j.knosys.2014.08.010 ◽

2015 ◽

Vol 79 ◽

pp. 27-35 ◽

Cited By ~ 13

Author(s):

Xiangzhou Zhang ◽

Yong Hu ◽

Kang Xie ◽

Weiguo Zhang ◽

Lijun Su ◽

...

Keyword(s):

Evolutionary Trend ◽

Rule Discovery ◽

Trading Rule ◽

Stock Trading

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Study on Financial Data Hybrid Clustering Based on Stock Trading Rule

Proceedings of the 2012 International Conference on Cybernetics and Informatics - Lecture Notes in Electrical Engineering ◽

10.1007/978-1-4614-3872-4_300 ◽

2013 ◽

pp. 2351-2357 ◽

Cited By ~ 2

Author(s):

Jian Huang

Keyword(s):

Financial Data ◽

Trading Rule ◽

Stock Trading ◽

Hybrid Clustering

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Trading rule discovery on Warsaw Stock Exchange using revolutionary algorithms

2009 International Multiconference on Computer Science and Information Technology ◽

10.1109/imcsit.2009.5352748 ◽

2009 ◽

Cited By ~ 3

Author(s):

Pawel B. Myszkowski ◽

Lukasz Rachwalski

Keyword(s):

Stock Exchange ◽

Rule Discovery ◽

Trading Rule ◽

Warsaw Stock Exchange

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Stock market trading rule discovery using pattern recognition and technical analysis

Expert Systems with Applications ◽

10.1016/j.eswa.2006.05.002 ◽

2007 ◽

Vol 33 (2) ◽

pp. 304-315 ◽

Cited By ~ 46

Author(s):

Jar-Long Wang ◽

Shu-Hui Chan

Keyword(s):

Pattern Recognition ◽

Stock Market ◽

Technical Analysis ◽

Rule Discovery ◽

Trading Rule ◽

Stock Market Trading

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Empirical study of trading rule discovery in China stock market

Expert Systems with Applications ◽

10.1016/j.eswa.2004.12.014 ◽

2005 ◽

Vol 28 (3) ◽

pp. 531-535 ◽

Cited By ~ 10

Author(s):

Luo Bo ◽

Sun Linyan ◽

Richard Mweene

Keyword(s):

Stock Market ◽

Empirical Study ◽

Rule Discovery ◽

Trading Rule ◽

China Stock Market

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Does Moving Average Technical Trading Rule Provide Value for Intraday Stock Trading?: Evidence from the Indonesia Stock Exchange

Indonesian Capital Market Review ◽

10.21002/icmr.v4i2.3619 ◽

2014 ◽

Vol 4 (2) ◽

Author(s):

Ario Harsanto ◽

Irwan Adi Ekaputra

Keyword(s):

Stock Exchange ◽

Moving Average ◽

Trading Rule ◽

Technical Trading ◽

Stock Trading

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Evidence on a New Stock Trading Rule that Produces Higher Returns with Lower Risk

International Journal of Economics and Finance ◽

10.5539/ijef.v3n1p92 ◽

2011 ◽

Vol 3 (1) ◽

Author(s):

Eric Latimer Prentis

Keyword(s):

Lower Risk ◽

Trading Rule ◽

Stock Trading

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