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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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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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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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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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Predictive modeling of foreign exchange trading signals using machine learning techniques
Enkhbayar, Sugarbayar; Ślepaczuk, Robert - 2024
Persistent link: https://www.econbiz.de/10014634708
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Improving realized LGD approximation : a novel framework with XGBoost for handling missing cash-flow data
Kostecka, Zuzanna; Ślepaczuk, Robert - 2024
Persistent link: https://www.econbiz.de/10014634855
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The hybrid forecast of S&P 500 volatility ensembled from VIX, GARCH and LSTM models
Roszyk, Natalia; Ślepaczuk, Robert - 2024
Persistent link: https://www.econbiz.de/10014634883
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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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Quantile regression analysis to predict GDP distribution using data from the US and UK
Thi Huyen Tran; Ślepaczuk, Robert - 2022
Persistent link: https://www.econbiz.de/10013474017
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Application of machine learning in algorithmic investment strategies on global stock markets
Grudniewicz, Jan; Ślepaczuk, Robert - In: Research in international business and finance 66 (2023), pp. 1-24
Persistent link: https://www.econbiz.de/10014463386