DAViS: a unified solution for data collection, analyzation, and visualization in real-time stock market prediction
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DOI: 10.1186/s40854-021-00269-7
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References listed on IDEAS
- Huina Mao & Scott Counts & Johan Bollen, 2011. "Predicting Financial Markets: Comparing Survey, News, Twitter and Search Engine Data," Papers 1112.1051, arXiv.org.
- Dharmaraja Selvamuthu & Vineet Kumar & Abhishek Mishra, 2019. "Indian stock market prediction using artificial neural networks on tick data," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 5(1), pages 1-12, December.
- R. Gopinathan & S. Raja Sethu Durai, 2019. "Stock market and macroeconomic variables: new evidence from India," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 5(1), pages 1-17, December.
- Daning Hu & Gerhard Schwabe & Xiao Li, 2015. "Systemic risk management and investment analysis with financial network analytics: research opportunities and challenges," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 1(1), pages 1-9, December.
- Rajagopal, 2015. "Market Trend Analysis," Palgrave Macmillan Books, in: The Butterfly Effect in Competitive Markets, chapter 4, pages 95-118, Palgrave Macmillan.
- Wenbo Wu & Jiaqi Chen & Liang Xu & Qingyun He & Michael L. Tindall, 2019. "A statistical learning approach for stock selection in the Chinese stock market," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 5(1), pages 1-18, December.
- Catalin Stoean & Wiesław Paja & Ruxandra Stoean & Adrian Sandita, 2019. "Deep architectures for long-term stock price prediction with a heuristic-based strategy for trading simulations," PLOS ONE, Public Library of Science, vol. 14(10), pages 1-19, October.
- Wen, Fenghua & Xu, Longhao & Ouyang, Guangda & Kou, Gang, 2019. "Retail investor attention and stock price crash risk: Evidence from China," International Review of Financial Analysis, Elsevier, vol. 65(C).
- Gang Kou & Özlem Olgu Akdeniz & Hasan Dinçer & Serhat Yüksel, 2021. "Fintech investments in European banks: a hybrid IT2 fuzzy multidimensional decision-making approach," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-28, December.
- Bomfim, Antulio N., 2003. "Pre-announcement effects, news effects, and volatility: Monetary policy and the stock market," Journal of Banking & Finance, Elsevier, vol. 27(1), pages 133-151, January.
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- Suppawong Tuarob & Thanapon Noraset & Tanisa Tawichsri, 2022. "Using Large-Scale Social Media Data for Population-Level Mental Health Monitoring and Public Sentiment Assessment: A Case Study of Thailand," PIER Discussion Papers 169, Puey Ungphakorn Institute for Economic Research.
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Keywords
Investment support system; Stock data visualization; Time series analysis; Ensemble machine learning; Text mining;All these keywords.
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