Explainable Text-Driven Neural Network for Stock Prediction
|Title:||Explainable Text-Driven Neural Network for Stock Prediction||Authors:||Yang, Linyi; Zhang, Zheng; Xiong, Su; Wei, Lirui; Ng, James; Xu, Lina; Dong, Ruihai||Permanent link:||http://hdl.handle.net/10197/10784||Date:||15-Apr-2019||Online since:||2019-06-11T07:03:28Z||Abstract:||It has been shown that financial news leads to the fluctuation of stock prices. However, previous work on news-driven financial market prediction focused only on predicting stock price movement without providing an explanation. In this paper, we propose a dual-layer attention-based neural network to address this issue. In the initial stage, we introduce a knowledge-based method to adaptively extract relevant financial news. Then, we use an input attention to pay more attention to the more influential news and concatenate the day embeddings with the output of the news representation. Finally, we use an output attention mechanism to allocate different weights to different days in terms of their contribution to stock price movement. Thorough empirical studies based upon historical prices of several individual stocks demonstrate the superiority of our proposed method in stock price prediction compared to state-of-the-art methods.||Funding Details:||Science Foundation Ireland||Type of material:||Conference Publication||Publisher:||IEEE||Start page:||441||End page:||445||Copyright (published version):||2018 IEEE||Keywords:||Stock prediction; Attention mechanism; Explainable model||DOI:||10.1109/CCIS.2018.8691233||Other versions:||http://ccis2018.csp.escience.cn/dct/page/1||Language:||en||Status of Item:||Peer reviewed||Is part of:||2018 5th IEEE International Conference on Cloud Computing and Intelligence Systems (CCIS)||Conference Details:||IEEE CCIS 2018: 5th IEEE International Conference on Cloud Computing and Intelligence Systems (CCIS), Nanjing, China, 23-25 November 2018||ISBN:||978-1-5386-6005-8|
|Appears in Collections:||Insight Research Collection|
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