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Optimal markowitz portfolio using returns forecasted with time series and machine learning models
Ślusarczyk, Damian
;
Ślepaczuk, Robert
-
2023
Persistent link: https://www.econbiz.de/10014446491
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2
Ensembling ARIMAX model in algorithmic investment strategies on commodities market
Jakubowski, Paweł
;
Ślepaczuk, Robert
;
Windorbski, …
-
2023
Persistent link: https://www.econbiz.de/10014448210
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3
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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4
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
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5
Predicting DJIA, NASDAQ and NYSE index prices using ARIMA and VAR models
Teymurzade, Sahil
;
Ślepaczuk, Robert
-
2023
Persistent link: https://www.econbiz.de/10014448266
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6
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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7
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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8
The profitability of pairs trading strategies on Hong-Kong stock market : distance, cointegration, and correlation methods
Ma, Baiquan
;
Ślepaczuk, Robert
-
2022
Persistent link: https://www.econbiz.de/10012816711
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9
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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10
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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