Enhancing Stock Market Prediction with Extended Coupled Hidden Markov Model over Multi-Sourced Data
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- Paul C. Tetlock & Maytal Saar‐Tsechansky & Sofus Macskassy, 2008. "More Than Words: Quantifying Language to Measure Firms' Fundamentals," Journal of Finance, American Finance Association, vol. 63(3), pages 1437-1467, June.
- Sanjiv R. Das & Mike Y. Chen, 2007. "Yahoo! for Amazon: Sentiment Extraction from Small Talk on the Web," Management Science, INFORMS, vol. 53(9), pages 1375-1388, September.
- Paul C. Tetlock, 2007. "Giving Content to Investor Sentiment: The Role of Media in the Stock Market," Journal of Finance, American Finance Association, vol. 62(3), pages 1139-1168, June.
- Xi Zhang & Yunjia Zhang & Senzhang Wang & Yuntao Yao & Binxing Fang & Philip S. Yu, 2018. "Improving Stock Market Prediction via Heterogeneous Information Fusion," Papers 1801.00588, arXiv.org.
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Cited by:
- Ashish Kumar & Abeer Alsadoon & P. W. C. Prasad & Salma Abdullah & Tarik A. Rashid & Duong Thu Hang Pham & Tran Quoc Vinh Nguyen, 2021. "Generative Adversarial Network (GAN) and Enhanced Root Mean Square Error (ERMSE): Deep Learning for Stock Price Movement Prediction," Papers 2112.03946, arXiv.org.
- Thomas Dierckx & Jesse Davis & Wim Schoutens, 2020. "Using Machine Learning and Alternative Data to Predict Movements in Market Risk," Papers 2009.07947, arXiv.org.
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NEP fields
This paper has been announced in the following NEP Reports:- NEP-FMK-2018-10-01 (Financial Markets)
- NEP-TRA-2018-10-01 (Transition Economics)
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