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The efficiency of various types of input layers of LSTM model in investment strategies on S&P500 index
Thi Thu Giang Nguyen; Ślepaczuk, Robert - 2022
Persistent link: https://www.econbiz.de/10013474013
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Technical analysis forecasting and evaluation of stock markets : the probabilistic recovery neural network approach
Maniatopoulos, Andreas; Gazis, Alexandros; Mitianoudis, … - In: International journal of economics and business … 25 (2023) 1, pp. 64-100
Persistent link: https://www.econbiz.de/10014309021
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Predicting prices of S&P500 index using classical methods and recurrent neural networks
Kijewskia, Mateusz; Ślepaczuk, Robert - 2020
Persistent link: https://www.econbiz.de/10012322224
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Ensembled LSTM with walk forward optimization in algorithmic trading
Chojnacki, Karol; Ślepaczuk, Robert - 2023
Persistent link: https://www.econbiz.de/10014308890
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Deep learning and technical analysis in cryptocurrency market
Goutte, Stéphane; Le, Hoang-Viet; Liu, Fei; … - In: Finance research letters 54 (2023), pp. 1-11
Persistent link: https://www.econbiz.de/10014472779
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Daily and intraday application of various architectures of the LSTM model in algorithmic investment strategies on Bitcoin and the S&P 500 Index
Kryńska, Katarzyna; Ślepaczuk, Robert - 2022
Persistent link: https://www.econbiz.de/10013473995
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Application of machine learning in quantitative investment strategies on global stock markets
Grudniewicz, Jan; Ślepaczuk, Robert - 2021
Persistent link: https://www.econbiz.de/10012816704
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Quantitative Verfahren im Finanzmarktbereich
Schröder, Michael (ed.) - 1996 - 1. Aufl.
Persistent link: https://www.econbiz.de/10000592147
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Erfolgreiche Zinsprognosesysteme
Lüthje, Bernd (ed.); Deckert, Mathias (revision) - 1994 - 1. Aufl.
Persistent link: https://www.econbiz.de/10000147799