Open AccessPredicting the tendency of stock’s price with factor-cross method based on deep learning
Author(s) -
Zhujun Zhang
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1861/1/012043
Subject(s) - estimator , computer science , artificial intelligence , econometrics , machine learning , factor (programming language) , stock price , order (exchange) , mathematical optimization , mathematics , statistics , economics , series (stratigraphy) , paleontology , finance , biology , programming language
In this paper, a solution for tendency prediction in the A-share market is presented. In data processing, the problem of non-normal factor distribution is solved by using compound processing method, and the case of non-independent distribution among factors is focused. The DNN Linear Combined Estimator model in Tensor Flow is applied to explore the first-order relationship between these factors. In order to intuitively understand the advantages of the model, an experiment is conducted between our solution and traditional machine learning methods. The result exhibits that the performance of our work is more excellent in all prediction metrics.