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~subject:"Algorithmus"
~subject:"recurrent neural networks"
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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
Saved in:
2
Hedging properties of algorithmic investment strategies using long short-term memory and time series models for equity indices
Michańków, Jakub
;
Sakowsk, Paweł
;
Ślepaczuk, Robert
-
2023
Persistent link: https://www.econbiz.de/10014448237
Saved in:
3
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
Saved in:
4
Ensembled LSTM with walk forward optimization in algorithmic trading
Chojnacki, Karol
;
Ślepaczuk, Robert
-
2023
Persistent link: https://www.econbiz.de/10014308890
Saved in:
5
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:
6
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:
7
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:
8
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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