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A comparison of LSTM and GRU architectures with novel walk-forward approach to algorithmic investment strategy
Baranochnikov, Illia; Ślepaczuk, Robert - 2022
Persistent link: https://www.econbiz.de/10013473692
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Applying hybrid ARIMA-SGARCH in algorithmic investment strategies on S&P 500 Index
Nguyen Vo; Ślepaczuk, Robert - 2021
Persistent link: https://www.econbiz.de/10012816706
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Q-learning-based financial trading systems with applications
Corazza, Marco; Bertoluzzo, Francesco - 2014 - First draft
Persistent link: https://www.econbiz.de/10011632153
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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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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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Machine learning in algorithmic trading strategy optimization - implementation and efficiency
Ryś, Przemysław; Ślepaczuk, Robert - Uniwersytet Warszawski / Wydział Nauk Ekonomicznych - 2018
Persistent link: https://www.econbiz.de/10011981706
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Bayesian approaches to shrinkage and sparse estimation
Korobilis, Dimitris; Shimizu, Kenichi - 2022
Persistent link: https://www.econbiz.de/10012814611
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Robust optimisation in algorithmic investment strategies
Castellano Gómez, Sergio; Ślepaczuk, Robert - 2021
Persistent link: https://www.econbiz.de/10012816708
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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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Trade patterns and pollution
Saint-Paul, Gilles - 1994
Persistent link: https://www.econbiz.de/10000898467