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Predicting prices of S&P500 index using classical methods and recurrent neural networks
Kijewskia, Mateusz
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Ślepaczuk, Robert
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2020
Persistent link: https://www.econbiz.de/10012322224
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Applying hurst exponent in pair trading strategies
Quynh Bui
;
Ślepaczuk, Robert
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2020
Persistent link: https://www.econbiz.de/10012322277
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3
Optimal markowitz portfolio using returns forecasted with time series and machine learning models
Ślusarczyk, Damian
;
Ślepaczuk, Robert
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2023
Persistent link: https://www.econbiz.de/10014446491
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Ensembling ARIMAX model in algorithmic investment strategies on commodities market
Jakubowski, Paweł
;
Ślepaczuk, Robert
;
Windorbski, …
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2023
Persistent link: https://www.econbiz.de/10014448210
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5
Hedging properties of algorithmic investment strategies using long short-term memory and time series models for equity indices
Michańków, Jakub
;
Sakowsk, Paweł
;
Ślepaczuk, Robert
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2023
Persistent link: https://www.econbiz.de/10014448237
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6
Predicting DJIA, NASDAQ and NYSE index prices using ARIMA and VAR models
Teymurzade, Sahil
;
Ślepaczuk, Robert
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2023
Persistent link: https://www.econbiz.de/10014448266
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7
Supervised autoencoder MLP for financial time series forecasting
Bieganowski, Bartosz
;
Ślepaczuk, Robert
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2024
Persistent link: https://www.econbiz.de/10014507808
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The hybrid forecast of S&P 500 volatility ensembled from VIX, GARCH and LSTM models
Roszyk, Natalia
;
Ślepaczuk, Robert
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2024
Persistent link: https://www.econbiz.de/10014634883
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9
The performance of time series forecasting based on classical and machine learning methods for S&P 500 index
Uzzal, Maudud Hassan
;
Ślepaczuk, Robert
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2023
Persistent link: https://www.econbiz.de/10014305886
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