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Enhancing literature review with NLP methods algorithmic investment strategies case
Łaniewski, Stanisław
;
Ślepaczuk, Robert
-
2024
Persistent link: https://www.econbiz.de/10015080964
Saved in:
2
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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3
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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4
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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5
Fractional differentiation and its use in machine learning
Gajda, Janusz
;
Walasek, Rafał
-
2020
Persistent link: https://www.econbiz.de/10012322246
Saved in:
6
Comparison of the accuracy in VaR forecasting for commodities using different methods of combining forecasts
Lis, Szymon
;
Chlebus, Marcin
-
2021
Persistent link: https://www.econbiz.de/10012795166
Saved in:
7
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
Saved in:
8
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
Saved in:
9
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
Saved in:
10
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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