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Exploiting social media with higher-order factorization machines: statistical arbitrage on high-frequency data of the S&P 500
Knoll, Julian; Stübinger, Johannes; Grottke, Michael - In: Essays on quantitative finance in the context of …, (pp. 203-236). 2018
Persistent link: https://www.econbiz.de/10011901819
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Exploiting social media with higher-order Factorization Machines : statistical arbitrage on high-frequency data of the S&P 500
Knoll, Julian; Stübinger, Johannes; Grottke, Michael - 2017
Over the past 15 years,there have been a number of studies using text mining for predicting stock market data. Two recent publications employed support vector machines and second-order Factorization Machines, respectively, to this end. However, these approaches either completely neglect...
Persistent link: https://www.econbiz.de/10011656152
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Exploiting social media with higher-order factorization machines: statistical arbitrage on high-frequency data of the S&P 500
Knoll, Julian; Stübinger, Johannes; Grottke, Michael - In: Higher-order factorization machines : implementation, …, (pp. 69-104). 2017
Persistent link: https://www.econbiz.de/10011901662
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Forecasting Bitcoin prices using artificial intelligence : combination of ML, SARIMA, and Facebook Prophet models
Cheng, Jiyang; Tiwari, Sunil; Khaled, Djebbouri; … - In: Technological forecasting and social change : an … 198 (2024), pp. 1-15
Persistent link: https://www.econbiz.de/10015075791
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A modified Bayesian boosting algorithm with weight-guided optimal feature selection for sentiment analysis
Nayak, Smitha; Savita; Sharma, Yogesh Kumar - In: Decision analytics journal 8 (2023), pp. 1-13
more focused learning for accurate sentiment prediction. The proposed algorithm is evaluated on a benchmark sentiment …
Persistent link: https://www.econbiz.de/10014517151
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Asset return prediction via machine learning
Zhang, Liangliang - In: Journal of mathematical finance 9 (2019) 4, pp. 691-697
Persistent link: https://www.econbiz.de/10012433454
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Predicting retirement and social security claiming decisions using machine learning
Kwon, Alexander; Maliar, Lilia - 2024
Persistent link: https://www.econbiz.de/10014564329
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Stock market index prediction using artificial neural network
Moghaddam, Amin Hedayati; Moghaddam, Moein Hedayati; … - In: Journal of economics, finance & administrative science 21 (2016) 41, pp. 89-93
to March 7) are selected as training dataset and the last 29 days are used for testing the model prediction ability …. Networks for NASDAQ index prediction for two type of input dataset (four prior days and nine prior days) were developed and …
Persistent link: https://www.econbiz.de/10011875195
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Prediction machines, insurance, and protection : an alternative perspective on AI's role in production
Agrawal, Ajay; Gans, Joshua; Goldfarb, Avi - In: Journal of the Japanese and international economies : … 72 (2024), pp. 1-10
Persistent link: https://www.econbiz.de/10014545476
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Integrated explainable deep learning prediction of harmful algal blooms
Lee, Donghyun; Kim, Mingyun; Lee, Beomhui; Chae, Sangwon; … - In: Technological forecasting & social change : an … 185 (2022), pp. 1-11
Persistent link: https://www.econbiz.de/10014233744