| Momentum and contrarian effects on the cryptocurrency market K Kosc, P Sakowski, R Ślepaczuk Physica A: Statistical Mechanics and its Applications 523, 691-701, 2019 | 49 | 2019 |
| Applying Hurst Exponent in pair trading strategies on Nasdaq 100 index Q Bui, R Ślepaczuk Physica A: Statistical Mechanics and its Applications 592, 126784, 2022 | 34 | 2022 |
| „Analysis of high frequency data on the Warsaw Stock Exchange in the context of efficient market hypothesis” P Strawiński, R Ślepaczuk Journal of Applied Economic Sciences 3 (3), 306-319, 2008 | 29 | 2008 |
| Applying hybrid ARIMA-SGARCH in algorithmic investment strategies on S&P500 index N Vo, R Ślepaczuk Entropy 24 (2), 158, 2022 | 26 | 2022 |
| LSTM in algorithmic investment strategies on BTC and S&P500 index J Michańków, P Sakowski, R Ślepaczuk Sensors 22 (3), 917, 2022 | 24 | 2022 |
| Anomalie rynku kapitałowego w świetle hipotezy efektywności rynku R Ślepaczuk eFinanse 1, 1-12, 2006 | 24 | 2006 |
| High-frequency and model-free volatility estimators R Ślepaczuk, G Zakrzewski Available at SSRN 2508648, 2009 | 23* | 2009 |
| Robustness of support vector machines in algorithmic trading on cryptocurrency market R Ślepaczuk, M Zenkova Central European Economic Journal 5 (52), 186-205, 2018 | 21 | 2018 |
| Predicting prices of S&P500 index using classical methods and recurrent neural networks M Kijewski, R Ślepaczuk Work. Pap. Fac. Econ. Sci. Univ. Wars, 2020 | 17 | 2020 |
| Application of machine learning in algorithmic investment strategies on global stock markets J Grudniewicz, R Ślepaczuk Research in International Business and Finance 66, 102052, 2023 | 12* | 2023 |
| Volatility as an Asset Class, Obvious Benefits and Hidden Risks. P Jabłecki, J., Kokoszczynski, R., Sakowski P., Ślepaczuk, R., Wójcik Frankfurt: PeterLang 1, 1-231, 2015 | 10* | 2015 |
| Midquotes or transactional prices? Evaluation of Black model on high-frequency data R Kokoszczyński, P Sakowski, R Ślepaczuk Studia Ekonomiczne 366, 43-58, 2018 | 9* | 2018 |
| High-frequency and model-free volatility estimators, University of Warsaw, Faculty of Economic Sciences R Ślepaczuk, G Zakrzewski Working Papers 13/2009 (23), 2009 | 9 | 2009 |
| Artificial Neural Networks Performance in WIG20 Index Options Pricing M Wysocki, R Ślepaczuk Entropy 24 (1), 35, 2021 | 8 | 2021 |
| Does the inclusion of exposure to volatility into diversified portfolio improve the investment results? Portfolio construction from the perspective of a Polish investor M Latoszek, R Ślepaczuk Economics and Business Review 6 (1), 46-81, 2020 | 8 | 2020 |
| Option pricing models with HF data: An application of the Black model to the WIG20 index R Kokoszczynski, P Sakowski, R Slepaczuk JOURNAL OF CENTRUM CATHEDRA 5, 70-90, 2012 | 8* | 2012 |
| Anomalie rynku kapitałowego w świetle hipotezy efektywności rynku,“e‑Finanse”, no. 1 R Ślepaczuk Wyższa Szkoła Informatyki i Zarządzania, Rzeszów, 3-12, 2006 | 8 | 2006 |
| Machine Learning Methods in Algorithmic Trading Strategy Optimization–Design and Time Efficiency P Ryś, R Ślepaczuk Central European Economic Journal 5 (52), 206-229, 2018 | 7* | 2018 |
| A comparison of LSTM and GRU architectures with novel walk-forward approach to algorithmic investment strategy I Baranochnikov, R Ślepaczuk Working Papers of Faculty of Economic Sciences, University of Warsaw, WP 21 …, 2022 | 5 | 2022 |
| Investment Strategies that Beat the Market. What Can We Squeeze from the Market? R Ślepaczuk, P Sakowski, G Zakrzewski Financial Internet Quarterly 14 (4), 36-55, 2018 | 5* | 2018 |
Paweł SakowskiUniversity of Warsaw, Faculty of Economic SciencesVerified email at wne.uw.edu.pl
