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Financial quantitative investment using convolutional neural network and deep learning technology.

Authors :
Chen, Chunchun
Zhang, Pu
Liu, Yuan
Liu, Jun
Source :
Neurocomputing. May2020, Vol. 390, p384-390. 7p.
Publication Year :
2020

Abstract

In order to make financial investment more stable and more profitable, convolutional neural network (CNN) and deep learning technology are used to quantify financial investment, so as to obtain more robust investment and returns. With the continuous development of in-depth learning technology, people are applying it more and more widely. Deep learning is put forward on the basis of neural network. It contains more hidden layers, shows more powerful learning ability, and can abstract data at a higher level, so as to obtain more accurate data. CNN is a multi-layer network structure which simulates the operation mechanism of biological vision system. Its special structure can obtain more useful feature descriptions from original data and is very effective in extracting data. Therefore, in this study, the two technologies are combined to quantify financial investment. The results show that the convolution neural network and deep learning algorithm can obtain relatively accurate investment strategies, thus ensuring investment returns and reducing investment risks. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
09252312
Volume :
390
Database :
Academic Search Index
Journal :
Neurocomputing
Publication Type :
Academic Journal
Accession number :
143045609
Full Text :
https://doi.org/10.1016/j.neucom.2019.09.092