Improving Stock Market Prediction via Heterogeneous Information Fusion
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Cited by:
- Qiao Zhou & Ningning Liu, 2020. "A Stock Prediction Model Based on DCNN," Papers 2009.03239, arXiv.org.
- Junran Wu & Ke Xu & Jichang Zhao, 2019. "Online reviews can predict long-term returns of individual stocks," Papers 1905.03189, arXiv.org.
- Anna Marszal, 2022. "What news can really tell us? Evidence from a news-based sentiment index for financial markets analysis," NBP Working Papers 349, Narodowy Bank Polski.
- Ashwini Saini & Anoop Sharma, 2022. "Predicting the Unpredictable: An Application of Machine Learning Algorithms in Indian Stock Market," Annals of Data Science, Springer, vol. 9(4), pages 791-799, August.
- Fuli Feng & Huimin Chen & Xiangnan He & Ji Ding & Maosong Sun & Tat-Seng Chua, 2018. "Enhancing Stock Movement Prediction with Adversarial Training," Papers 1810.09936, arXiv.org, revised Jun 2019.
- Ahmet Murat Ozbayoglu & Mehmet Ugur Gudelek & Omer Berat Sezer, 2020. "Deep Learning for Financial Applications : A Survey," Papers 2002.05786, arXiv.org.
- Mohammad Sahabuddin & Md. Aminul Islam & Mosab I. Tabash & Suhaib Anagreh & Rozina Akter & Md. Mizanur Rahman, 2022. "Co-Movement, Portfolio Diversification, Investors’ Behavior and Psychology: Evidence from Developed and Emerging Countries’ Stock Markets," JRFM, MDPI, vol. 15(8), pages 1-15, July.
- Jinan Zou & Qingying Zhao & Yang Jiao & Haiyao Cao & Yanxi Liu & Qingsen Yan & Ehsan Abbasnejad & Lingqiao Liu & Javen Qinfeng Shi, 2022. "Stock Market Prediction via Deep Learning Techniques: A Survey," Papers 2212.12717, arXiv.org, revised Feb 2023.
- Kamaladdin Fataliyev & Aneesh Chivukula & Mukesh Prasad & Wei Liu, 2021. "Stock Market Analysis with Text Data: A Review," Papers 2106.12985, arXiv.org, revised Jul 2021.
- Cristescu Marian Pompiliu & Nerişanu Raluca Andreea & Mara Dumitru Alexandru, 2022. "Using Data Mining in the Sentiment Analysis Process on the Financial Market," Journal of Social and Economic Statistics, Sciendo, vol. 11(1-2), pages 36-58, December.
- Amit Milstein & Haoran Deng & Guy Revach & Hai Morgenstern & Nir Shlezinger, 2022. "Neural Augmented Kalman Filtering with Bollinger Bands for Pairs Trading," Papers 2210.15448, arXiv.org, revised Sep 2023.
- Zhou, Zhongbao & Gao, Meng & Xiao, Helu & Wang, Rui & Liu, Wenbin, 2021. "Big data and portfolio optimization: A novel approach integrating DEA with multiple data sources," Omega, Elsevier, vol. 104(C).
- Marian Pompiliu Cristescu & Raluca Andreea Nerisanu & Dumitru Alexandru Mara & Simona-Vasilica Oprea, 2022. "Using Market News Sentiment Analysis for Stock Market Prediction," Mathematics, MDPI, vol. 10(22), pages 1-12, November.
- Xi Zhang & Yixuan Li & Senzhang Wang & Binxing Fang & Philip S. Yu, 2018. "Enhancing Stock Market Prediction with Extended Coupled Hidden Markov Model over Multi-Sourced Data," Papers 1809.00306, arXiv.org.
- Wen, Danyan & Ma, Chaoqun & Wang, Gang-Jin & Wang, Senzhang, 2018. "Investigating the features of pairs trading strategy: A network perspective on the Chinese stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 505(C), pages 903-918.
- Zhou, Zhongbao & Gao, Meng & Liu, Qing & Xiao, Helu, 2020. "Forecasting stock price movements with multiple data sources: Evidence from stock market in China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 542(C).
- Linyi Yang & Yingpeng Ma & Yue Zhang, 2023. "Measuring Consistency in Text-based Financial Forecasting Models," Papers 2305.08524, arXiv.org, revised Jun 2023.
- Li-Chen Cheng & Wei-Ting Lu & Benjamin Yeo, 2023. "Predicting abnormal trading behavior from internet rumor propagation: a machine learning approach," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-23, December.
- Tasnim M. A. Zayet & Maizatul Akmar Ismail & Kasturi Dewi Varathan & Rafidah M. D. Noor & Hui Na Chua & Angela Lee & Yeh Ching Low & Sheena Kaur Jaswant Singh, 2021. "Investigating transportation research based on social media analysis: a systematic mapping review," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(8), pages 6383-6421, August.
- Omer Berat Sezer & Mehmet Ugur Gudelek & Ahmet Murat Ozbayoglu, 2019. "Financial Time Series Forecasting with Deep Learning : A Systematic Literature Review: 2005-2019," Papers 1911.13288, arXiv.org.
- Karolina Sowinska & Pranava Madhyastha, 2020. "A Tweet-based Dataset for Company-Level Stock Return Prediction," Papers 2006.09723, arXiv.org.
- Yu Zhao & Huaming Du & Ying Liu & Shaopeng Wei & Xingyan Chen & Fuzhen Zhuang & Qing Li & Ji Liu & Gang Kou, 2022. "Stock Movement Prediction Based on Bi-typed Hybrid-relational Market Knowledge Graph via Dual Attention Networks," Papers 2201.04965, arXiv.org, revised Jan 2022.
- Francisco de Arriba-P'erez & Silvia Garc'ia-M'endez & Jos'e A. Regueiro-Janeiro & Francisco J. Gonz'alez-Casta~no, 2024. "Detection of financial opportunities in micro-blogging data with a stacked classification system," Papers 2404.07224, arXiv.org.
- Rosdyana Mangir Irawan Kusuma & Trang-Thi Ho & Wei-Chun Kao & Yu-Yen Ou & Kai-Lung Hua, 2019. "Using Deep Learning Neural Networks and Candlestick Chart Representation to Predict Stock Market," Papers 1903.12258, arXiv.org.
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This paper has been announced in the following NEP Reports:- NEP-FMK-2018-01-15 (Financial Markets)
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