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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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Application of machine learning in algorithmic investment strategies on global stock markets
Grudniewicz, Jan; Ślepaczuk, Robert - In: Research in international business and finance 66 (2023), pp. 1-24
Persistent link: https://www.econbiz.de/10014463386
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Artificial Neural Networks Performance in WIG20 Index Options Pricing
Wysockia, Maciej; Ślepaczuk, Robert - 2020
Persistent link: https://www.econbiz.de/10012322176
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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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Mean absolute directional loss as a new loss function for machine learning problems in algorithmic investment strategies
Michańków, Jakub; Sakowski, Paweł; Ślepaczuk, Robert - 2023
Persistent link: https://www.econbiz.de/10014448222
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The performance of time series forecasting based on classical and machine learning methods for S&P 500 index
Uzzal, Maudud Hassan; Ślepaczuk, Robert - 2023
Persistent link: https://www.econbiz.de/10014305886
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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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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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LSTM-ARIMA as a hybrid approach in algorithmic investment strategies
Kashif, Kamil; Ślepaczuk, Robert - 2024
Persistent link: https://www.econbiz.de/10014634690
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The hybrid forecast of S&P 500 volatility ensembled from VIX, GARCH and LSTM models
Roszyk, Natalia; Ślepaczuk, Robert - 2024
Persistent link: https://www.econbiz.de/10014634883