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Can the leading US energy stock prices be predicted using the Ichimoku cloud?
Gurrib, Ikhlaas; Kamalov, Firuz; Elshareif, Elgilani Eltahir - In: International Journal of Energy Economics and Policy : IJEEP 11 (2021) 1, pp. 41-51
Persistent link: https://www.econbiz.de/10012586842
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Pensionskasse als Wettbewerbsfaktor für gesuchte Arbeitskräfte
Schmid, Hans - 1998
Persistent link: https://www.econbiz.de/10001363197
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Trading the stock market using Google search volumes : a long short-term memory approach
Pierre, Joseph St.; Klimkiewicz, Mateusz; Resom, Adonay; … - In: International journal of financial engineering and risk … 3 (2019) 1, pp. 3-18
Persistent link: https://www.econbiz.de/10012253455
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Essays in empirical macroeconomics
Shin, Joong Suk - 2000
Persistent link: https://www.econbiz.de/10001608968
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The U-Mart system as an artificial intelligent stock market project
2008
Persistent link: https://www.econbiz.de/10003539948
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Why are some Chinese firms failing in the US capital markets? : a machine learning approach
Colak, Gonul; Fu, Mengchuan; Hasan, Iftekhar - In: Pacific-Basin finance journal 61 (2020), pp. 1-22
Persistent link: https://www.econbiz.de/10012494429
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Predicting the returns of the US real estate investment trust market : evidence from the group method of data handling neural network
Zhang, Wendi; Li, Bin; Liew, Alan Wee-Chung; Roca, Eduardo - In: Financial innovation : FIN 9 (2023) 1, pp. 1-33
Purpose: The Group Method of Data Handling (GMDH) neural network has demonstrated good performance in data mining, prediction, and optimization. Scholars have used it to forecast stock and real estate investment trust (REIT) returns in some countries and region, but not in the United States (US)...
Persistent link: https://www.econbiz.de/10014363989
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The role of big data research methodologies in describing investor risk attitudes and predicting stock market performance : deep learning and risk tolerance
Heo, Wookjae; Kwak, Eun Jin; Grable, John E. - In: Handbook of research on new challenges and global …, (pp. 293-315). 2022
Persistent link: https://www.econbiz.de/10013171821
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Machine learning for US cross-industry return predictability under information uncertainty
Awijen, Haithem; Zaied, Younes Ben; Ben Lahouel, Bechir; … - In: Research in international business and finance 64 (2023), pp. 1-13
Persistent link: https://www.econbiz.de/10014279809
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Investor confidence and forecastability of US stock market realized volatility : evidence from machine learning
Gupta, Rangan; Nel, Jacobus; Pierdzioch, Christian - In: The journal of behavioral finance : a publication of … 24 (2023) 1, pp. 111-122
Persistent link: https://www.econbiz.de/10013547864