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Robert Ślepaczuk
(Robert Slepaczuk)

Personal Details

First Name:Robert
Middle Name:
Last Name:Slepaczuk
Suffix:
RePEc Short-ID:ple519
[This author has chosen not to make the email address public]

Affiliation

Wydział Nauk Ekonomicznych
Uniwersytet Warszawski

Warszawa, Poland
http://www.wne.uw.edu.pl/
RePEc:edi:fesuwpl (more details at EDIRC)

Research output

as
Jump to: Working papers Articles

Working papers

  1. Bartosz Bieganowski & Robert Ślepaczuk, 2024. "Supervised Autoencoder MLP for Financial Time Series Forecasting," Working Papers 2024-03, Faculty of Economic Sciences, University of Warsaw.
  2. Bartosz Bieganowski & Robert Slepaczuk, 2024. "Supervised Autoencoder MLP for Financial Time Series Forecasting," Papers 2404.01866, arXiv.org.
  3. Sahil Teymurzade & Robert Ślepaczuk, 2023. "Predicting DJIA, NASDAQ and NYSE index prices using ARIMA and VAR models," Working Papers 2023-27, Faculty of Economic Sciences, University of Warsaw.
  4. Pawe{l} Sakowski & Rafa{l} Sieradzki & Robert 'Slepaczuk, 2023. "Systemic risk indicator based on implied and realized volatility," Papers 2307.05719, arXiv.org.
  5. Jakub Micha'nk'ow & Pawe{l} Sakowski & Robert 'Slepaczuk, 2023. "Mean Absolute Directional Loss as a New Loss Function for Machine Learning Problems in Algorithmic Investment Strategies," Papers 2309.10546, arXiv.org.
  6. Maudud Hassan Uzzal & Robert Ślepaczuk, 2023. "The performance of time series forecasting based on classical and machine learning methods for S&P 500 index," Working Papers 2023-05, Faculty of Economic Sciences, University of Warsaw.
  7. Paweł Sakowski & Rafał Sieradzki & Robert Ślepaczuk, 2023. "The systemic risk approach based on implied and realized volatility," Working Papers 2023-07, Faculty of Economic Sciences, University of Warsaw.
  8. Karol Chojnacki & Robert Ślepaczuk, 2023. "This study compares well-known tools of technical analysis (Moving Average Crossover MAC) with Machine Learning based strategies (LSTM and XGBoost) and Ensembled Machine Learning Strategies (LSTM ense," Working Papers 2023-15, Faculty of Economic Sciences, University of Warsaw.
  9. Damian Ślusarczyk & Robert Ślepaczuk, 2023. "Optimal Markowitz Portfolio Using Returns Forecasted with Time Series and Machine Learning Models," Working Papers 2023-17, Faculty of Economic Sciences, University of Warsaw.
  10. Jakub Micha'nk'ow & Pawe{l} Sakowski & Robert 'Slepaczuk, 2023. "Hedging Properties of Algorithmic Investment Strategies using Long Short-Term Memory and Time Series models for Equity Indices," Papers 2309.15640, arXiv.org.
  11. Paweł Jakubowski & Robert Ślepaczuk & Franciszek Windorbski, 2023. "REnsembling ARIMAX Model in Algorithmic Investment Strategies on Commodities Market," Working Papers 2023-20, Faculty of Economic Sciences, University of Warsaw.
  12. Illia Baranochnikov & Robert Ślepaczuk, 2022. "A comparison of LSTM and GRU architectures with novel walk-forward approach to algorithmic investment strategy," Working Papers 2022-21, Faculty of Economic Sciences, University of Warsaw.
  13. Thi Huyen Tran & Robert Ślepaczuk, 2022. "Quantile regression analysis to predict GDP distribution using data from the US and UK," Working Papers 2022-30, Faculty of Economic Sciences, University of Warsaw.
  14. Baiquan Ma & Robert Ślepaczuk, 2022. "The profitability of pairs trading strategies on Hong-Kong stock market: distance, cointegration, and correlation methods," Working Papers 2022-02, Faculty of Economic Sciences, University of Warsaw.
  15. Katarzyna Kryńska & Robert Ślepaczuk, 2022. "Daily and intraday application of various architectures of the LSTM model in algorithmic investment strategies on Bitcoin and the S&P 500 Index," Working Papers 2022-25, Faculty of Economic Sciences, University of Warsaw.
  16. Thi Thu Giang Nguyen & Robert Ślepaczuk, 2022. "The efficiency of various types of input layers of LSTM model in investment strategies on S&P500 index," Working Papers 2022-29, Faculty of Economic Sciences, University of Warsaw.
  17. Kamil Korzeń & Robert Ślepaczuk, 2021. "Enhanced Index Replication Based on Smart Beta and Tail-Risk Asset Allocation," Working Papers 2021-18, Faculty of Economic Sciences, University of Warsaw.
  18. Sergio Castellano Gómez & Robert Ślepaczuk, 2021. "Robust optimisation in algorithmic investment strategies," Working Papers 2021-27, Faculty of Economic Sciences, University of Warsaw.
  19. Jan Grudniewicz & Robert Ślepaczuk, 2021. "Application of machine learning in quantitative investment strategies on global stock markets," Working Papers 2021-23, Faculty of Economic Sciences, University of Warsaw.
  20. Nguyen Vo & Robert Ślepaczuk, 2021. "Applying Hybrid ARIMA-SGARCH in Algorithmic Investment Strategies on S&P500 Index," Working Papers 2021-25, Faculty of Economic Sciences, University of Warsaw.
  21. Mateusz Kijewski & Robert Ślepaczuk, 2020. "Predicting prices of S&P500 index using classical methods and recurrent neural networks," Working Papers 2020-27, Faculty of Economic Sciences, University of Warsaw.
  22. Oleh Bilyk & Paweł Sakowski & Robert Ślepaczuk, 2020. "Investing in VIX futures based on rolling GARCH models forecasts," Working Papers 2020-10, Faculty of Economic Sciences, University of Warsaw.
  23. Quynh Bui & Robert Ślepaczuk, 2020. "Applying Hurst Exponent in Pair Trading Strategies," Working Papers 2020-39, Faculty of Economic Sciences, University of Warsaw.
  24. Robert Ślepaczuk & Igor Wabik, 2020. "The impact of the results of football matches on the stock prices of soccer clubs," Working Papers 2020-35, Faculty of Economic Sciences, University of Warsaw.
  25. Karol Kielak & Robert Ślepaczuk, 2020. "Value-at-risk — the comparison of state-of-the-art models on various assets," Working Papers 2020-28, Faculty of Economic Sciences, University of Warsaw.
  26. Bartłomiej Bollin & Robert Ślepaczuk, 2020. "Variance Gamma Model in Hedging Vanilla and Exotic Options," Working Papers 2020-31, Faculty of Economic Sciences, University of Warsaw.
  27. Maciej Wysocki & Robert Ślepaczuk, 2020. "Artificial Neural Networks Performance in WIG20 Index Options Pricing," Working Papers 2020-19, Faculty of Economic Sciences, University of Warsaw.
  28. Michał Latoszek & Robert Ślepaczuk, 2019. "Does the inclusion of exposure to volatility into diversified portfolio improve the investment results? Portfolio construction from the perspective of a Polish investor," Working Papers 2019-14, Faculty of Economic Sciences, University of Warsaw.
  29. Kamil Korzeń & Robert Ślepaczuk, 2019. "Hybrid Investment Strategy Based on Momentum and Macroeconomic Approach," Working Papers 2019-17, Faculty of Economic Sciences, University of Warsaw.
  30. Maryna Zenkova & Robert Ślepaczuk, 2019. "Robustness of Support Vector Machines in Algorithmic Trading on Cryptocurrency Market," Working Papers 2019-02, Faculty of Economic Sciences, University of Warsaw.
  31. Małgorzata Jabłczyńska & Krzysztof Kosc & Przemysław Ryś & Robert Ślepaczuk & Paweł Sakowski & Grzegorz Zakrzewski, 2018. "Why you should not invest in mining endeavour? The efficiency of BTC mining under current market conditions," Working Papers 2018-18, Faculty of Economic Sciences, University of Warsaw.
  32. Krzysztof Kość & Paweł Sakowski & Robert Ślepaczuk, 2018. "Momentum and contrarian effects on the cryptocurrency market," Working Papers 2018-09, Faculty of Economic Sciences, University of Warsaw.
  33. Przemysław Ryś & Robert Ślepaczuk, 2018. "Machine learning in algorithmic trading strategy optimization - implementation and efficiency," Working Papers 2018-25, Faculty of Economic Sciences, University of Warsaw.
  34. Paweł Sakowski & Robert Ślepaczuk & Mateusz Wywiał, 2016. "Applying Exogenous Variables and Regime Switching To Multifactor Models on Equity Indices," Working Papers 2016-10, Faculty of Economic Sciences, University of Warsaw.
  35. Paweł Sakowski & Robert Ślepaczuk & Mateusz Wywiał, 2016. "Do Multi-Factor Models Produce Robust Results? Econometric And Diagnostic Issues In Equity Risk Premia Study," Working Papers 2016-08, Faculty of Economic Sciences, University of Warsaw.
  36. Paweł Sakowski & Robert Ślepaczuk & Mateusz Wywiał, 2016. "Can We Invest Based on Equity Risk Premia and Risk Factors from Multi-Factor Models?," Working Papers 2016-09, Faculty of Economic Sciences, University of Warsaw.
  37. Paweł Sakowski & Robert Ślepaczuk & Mateusz Wywiał, 2015. "Cross-Sectional Returns With Volatility Regimes From Diverse Portfolio of Emerging and Developed Equity Indices," Working Papers 2015-39, Faculty of Economic Sciences, University of Warsaw.
  38. Juliusz Jabłecki & Ryszard Kokoszczyński & Paweł Sakowski & Robert Ślepaczuk & Piotr Wójcik, 2014. "Volatility as a new class of assets? The advantages of using volatility index futures in investment strategies," Working Papers 2014-26, Faculty of Economic Sciences, University of Warsaw.
  39. Juliusz Jabłecki & Ryszard Kokoszczyński & Paweł Sakowski & Robert Ślepaczuk & Piotr Wójcik, 2014. "Does historical volatility term structure contain valuable in-formation for predicting volatility index futures?," Working Papers 2014-18, Faculty of Economic Sciences, University of Warsaw.
  40. Juliusz Jabłecki & Ryszard Kokoszczyński & Paweł Sakowski & Robert Ślepaczuk & Piotr Wójcik, 2014. "Simple heuristics for pricing VIX options," Working Papers 2014-25, Faculty of Economic Sciences, University of Warsaw.
  41. Juliusz Jabłecki & Ryszard Kokoszczyński & Paweł Sakowski & Robert Ślepaczuk & Piotr Wójcik, 2014. "Options delta hedging with no options at all," Working Papers 2014-27, Faculty of Economic Sciences, University of Warsaw.
  42. Robert Ślepaczuk & Grzegorz Zakrzewski & Paweł Sakowski, 2012. "Investment strategies beating the market. What can we squeeze from the market?," Working Papers 2012-04, Faculty of Economic Sciences, University of Warsaw.
  43. Ryszard Kokoszczyński & Paweł Sakowski & Robert Ślepaczuk, 2010. "Midquotes or Transactional Data? The Comparison of Black Model on HF Data," Working Papers 2010-15, Faculty of Economic Sciences, University of Warsaw.
  44. Ryszard Kokoszczyński & Paweł Sakowski & Robert Ślepaczuk, 2010. "Which Option Pricing Model is the Best? High Frequency Data for Nikkei225 Index Options," Working Papers 2010-16, Faculty of Economic Sciences, University of Warsaw.
  45. Ryszard Kokoszczyński & Natalia Nehrebecka & Paweł Sakowski & Paweł Strawiński & Robert Ślepaczuk, 2010. "Option Pricing Models with HF Data – a Comparative Study. The Properties of Black Model with Different Volatility Measures," Working Papers 2010-03, Faculty of Economic Sciences, University of Warsaw.
  46. Robert Ślepaczuk & Grzegorz Zakrzewski, 2009. "High-Frequency and Model-Free Volatility Estimators," Working Papers 2009-13, Faculty of Economic Sciences, University of Warsaw.
  47. Robert Ślepaczuk & Grzegorz Zakrzewski, 2009. "Emerging versus developed volatility indices. The comparison of VIW20 and VIX indices," Working Papers 2009-11, Faculty of Economic Sciences, University of Warsaw.
  48. Strawinski, Pawel & Slepaczuk, Robert, 2008. "Analysis of HF data on the WSE in the context of EMH," MPRA Paper 9532, University Library of Munich, Germany.

Articles

  1. Grudniewicz, Jan & Ślepaczuk, Robert, 2023. "Application of machine learning in algorithmic investment strategies on global stock markets," Research in International Business and Finance, Elsevier, vol. 66(C).
  2. Sheraliev Iskandar & Ślepaczuk Robert, 2023. "Cross-Country Differences in Return and Volatility Metrics of World Equity Indices," Central European Economic Journal, Sciendo, vol. 10(57), pages 91-115, January.
  3. Bui, Quynh & Ślepaczuk, Robert, 2022. "Applying Hurst Exponent in pair trading strategies on Nasdaq 100 index," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 592(C).
  4. Latoszek Michał & Ślepaczuk Robert, 2020. "Does the inclusion of exposure to volatility into diversified portfolio improve the investment results? Portfolio construction from the perspective of a Polish investor," Economics and Business Review, Sciendo, vol. 6(1), pages 46-81, March.
  5. Kosc, Krzysztof & Sakowski, Paweł & Ślepaczuk, Robert, 2019. "Momentum and contrarian effects on the cryptocurrency market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 691-701.
  6. Ryś Przemysław & Ślepaczuk Robert, 2018. "Machine Learning Methods in Algorithmic Trading Strategy Optimization – Design and Time Efficiency," Central European Economic Journal, Sciendo, vol. 5(52), pages 206-229, January.
  7. Ślepaczuk Robert & Zenkova Maryna, 2018. "Robustness of Support Vector Machines in Algorithmic Trading on Cryptocurrency Market," Central European Economic Journal, Sciendo, vol. 5(52), pages 186-205, January.
  8. Ślepaczuk Robert & Sakowski Paweł & Zakrzewski Grzegorz, 2018. "Investment Strategies that Beat the Market. What Can We Squeeze from the Market?," Financial Internet Quarterly (formerly e-Finanse), Sciendo, vol. 14(4), pages 36-55, December.
  9. Ryszard Kokoszczyński & Paweł Sakowski & Robert Ślepaczuk, 2017. "Which Option Pricing Model Is the Best? HF Data for Nikkei 225 Index Options," Central European Economic Journal, Sciendo, vol. 4(51), pages 18-39, December.
  10. Pawe³ Sakowski & Robert Œlepaczuk & Mateusz Wywia³, 2016. "Cross-Sectional Returns With Volatility Regimes From A Diverse Portfolio Of Emerging And Developed Equity Indices," "e-Finanse", University of Information Technology and Management, Institute of Financial Research and Analysis, vol. 12(2), pages 23-35, October.
  11. Paweł Sakowski & Robert Ślepaczuk & Mateusz Wywiał, 2016. "Applying exogenous variables and regime switching to multi-factor models on equity indices," Ekonomia journal, Faculty of Economic Sciences, University of Warsaw, vol. 47.
  12. Juliusz Jablecki & Robert Slepaczuk & Ryszard Kokoszczynski & Pawel Sakowski & Piotr Wojcik, 2014. "Does historical VIX term structure contain valuable information for predicting VIX futures?," Dynamic Econometric Models, Uniwersytet Mikolaja Kopernika, vol. 14, pages 5-28.
  13. Juliusz Jabłecki & Ryszard Kokoszczyński & Paweł Sakowski & Robert Ślepaczuk & Piotr Wójcik, 2014. "Wycena opcji na VIX – podejscie heurystyczne," Ekonomia journal, Faculty of Economic Sciences, University of Warsaw, vol. 38.
  14. Juliusz Jabłecki & Ryszard Kokoszczyński & Paweł Sakowski & Robert Ślepaczuk & Piotr Wójcik, 2012. "Volatility Measurement, Modeling and Forecasting—An Overview of the Literature," Ekonomia journal, Faculty of Economic Sciences, University of Warsaw, vol. 31.
  15. Pawel STRAWINSKI & Robert SLEPACZUK, 2008. "Analysis Of High Frequency Data On The Warsaw Stock Exchange In The Context Of Efficient Market Hypothesis," Journal of Applied Economic Sciences, Spiru Haret University, Faculty of Financial Management and Accounting Craiova, vol. 3(3(5)_Fall), pages 306-319.
  16. Robert Ślepaczuk, 2004. "Efficiency of the Market of Derivative Instruments Listed on the Warsaw Stock Exchange," Ekonomia journal, Faculty of Economic Sciences, University of Warsaw, vol. 12.

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Working papers

  1. Illia Baranochnikov & Robert Ślepaczuk, 2022. "A comparison of LSTM and GRU architectures with novel walk-forward approach to algorithmic investment strategy," Working Papers 2022-21, Faculty of Economic Sciences, University of Warsaw.

    Cited by:

    1. Jin Shang & Shigeyuki Hamori, 2023. "Do Large Datasets or Hybrid Integrated Models Outperform Simple Ones in Predicting Commodity Prices and Foreign Exchange Rates?," JRFM, MDPI, vol. 16(6), pages 1-25, June.
    2. Katarzyna Kryńska & Robert Ślepaczuk, 2022. "Daily and intraday application of various architectures of the LSTM model in algorithmic investment strategies on Bitcoin and the S&P 500 Index," Working Papers 2022-25, Faculty of Economic Sciences, University of Warsaw.

  2. Katarzyna Kryńska & Robert Ślepaczuk, 2022. "Daily and intraday application of various architectures of the LSTM model in algorithmic investment strategies on Bitcoin and the S&P 500 Index," Working Papers 2022-25, Faculty of Economic Sciences, University of Warsaw.

    Cited by:

    1. Karol Chojnacki & Robert Ślepaczuk, 2023. "This study compares well-known tools of technical analysis (Moving Average Crossover MAC) with Machine Learning based strategies (LSTM and XGBoost) and Ensembled Machine Learning Strategies (LSTM ense," Working Papers 2023-15, Faculty of Economic Sciences, University of Warsaw.

  3. Thi Thu Giang Nguyen & Robert Ślepaczuk, 2022. "The efficiency of various types of input layers of LSTM model in investment strategies on S&P500 index," Working Papers 2022-29, Faculty of Economic Sciences, University of Warsaw.

    Cited by:

    1. Rayadurgam, Vikram Chandramouli & Mangalagiri, Jayasree, 2023. "Does inclusion of GARCH variance in deep learning models improve financial contagion prediction?," Finance Research Letters, Elsevier, vol. 54(C).

  4. Sergio Castellano Gómez & Robert Ślepaczuk, 2021. "Robust optimisation in algorithmic investment strategies," Working Papers 2021-27, Faculty of Economic Sciences, University of Warsaw.

    Cited by:

    1. Karol Chojnacki & Robert Ślepaczuk, 2023. "This study compares well-known tools of technical analysis (Moving Average Crossover MAC) with Machine Learning based strategies (LSTM and XGBoost) and Ensembled Machine Learning Strategies (LSTM ense," Working Papers 2023-15, Faculty of Economic Sciences, University of Warsaw.

  5. Jan Grudniewicz & Robert Ślepaczuk, 2021. "Application of machine learning in quantitative investment strategies on global stock markets," Working Papers 2021-23, Faculty of Economic Sciences, University of Warsaw.

    Cited by:

    1. Katarzyna Kryńska & Robert Ślepaczuk, 2022. "Daily and intraday application of various architectures of the LSTM model in algorithmic investment strategies on Bitcoin and the S&P 500 Index," Working Papers 2022-25, Faculty of Economic Sciences, University of Warsaw.

  6. Mateusz Kijewski & Robert Ślepaczuk, 2020. "Predicting prices of S&P500 index using classical methods and recurrent neural networks," Working Papers 2020-27, Faculty of Economic Sciences, University of Warsaw.

    Cited by:

    1. Bui, Quynh & Ślepaczuk, Robert, 2022. "Applying Hurst Exponent in pair trading strategies on Nasdaq 100 index," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 592(C).
    2. Bartosz Bieganowski & Robert Ślepaczuk, 2024. "Supervised Autoencoder MLP for Financial Time Series Forecasting," Working Papers 2024-03, Faculty of Economic Sciences, University of Warsaw.

  7. Bartłomiej Bollin & Robert Ślepaczuk, 2020. "Variance Gamma Model in Hedging Vanilla and Exotic Options," Working Papers 2020-31, Faculty of Economic Sciences, University of Warsaw.

    Cited by:

    1. Marwa Belhaj Salem & Mitra Fouladirad & Estelle Deloux, 2021. "Prognostic and Classification of Dynamic Degradation in a Mechanical System Using Variance Gamma Process," Mathematics, MDPI, vol. 9(3), pages 1-25, January.

  8. Michał Latoszek & Robert Ślepaczuk, 2019. "Does the inclusion of exposure to volatility into diversified portfolio improve the investment results? Portfolio construction from the perspective of a Polish investor," Working Papers 2019-14, Faculty of Economic Sciences, University of Warsaw.

    Cited by:

    1. Souto Hugo Gobato & Moradi Amir, 2023. "Forecasting realized volatility through financial turbulence and neural networks," Economics and Business Review, Sciendo, vol. 9(2), pages 133-159, April.
    2. Bui, Quynh & Ślepaczuk, Robert, 2022. "Applying Hurst Exponent in pair trading strategies on Nasdaq 100 index," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 592(C).
    3. Paweł Jakubowski & Robert Ślepaczuk & Franciszek Windorbski, 2023. "REnsembling ARIMAX Model in Algorithmic Investment Strategies on Commodities Market," Working Papers 2023-20, Faculty of Economic Sciences, University of Warsaw.

  9. Maryna Zenkova & Robert Ślepaczuk, 2019. "Robustness of Support Vector Machines in Algorithmic Trading on Cryptocurrency Market," Working Papers 2019-02, Faculty of Economic Sciences, University of Warsaw.

    Cited by:

    1. Maudud Hassan Uzzal & Robert Ślepaczuk, 2023. "The performance of time series forecasting based on classical and machine learning methods for S&P 500 index," Working Papers 2023-05, Faculty of Economic Sciences, University of Warsaw.
    2. Yanzhao Zou & Dorien Herremans, 2022. "PreBit -- A multimodal model with Twitter FinBERT embeddings for extreme price movement prediction of Bitcoin," Papers 2206.00648, arXiv.org, revised Oct 2023.
    3. Bartosz Bieganowski & Robert Ślepaczuk, 2024. "Supervised Autoencoder MLP for Financial Time Series Forecasting," Working Papers 2024-03, Faculty of Economic Sciences, University of Warsaw.

  10. Krzysztof Kość & Paweł Sakowski & Robert Ślepaczuk, 2018. "Momentum and contrarian effects on the cryptocurrency market," Working Papers 2018-09, Faculty of Economic Sciences, University of Warsaw.

    Cited by:

    1. Maryna Zenkova & Robert Ślepaczuk, 2019. "Robustness of Support Vector Machines in Algorithmic Trading on Cryptocurrency Market," Working Papers 2019-02, Faculty of Economic Sciences, University of Warsaw.
    2. Zaremba, Adam & Bilgin, Mehmet Huseyin & Long, Huaigang & Mercik, Aleksander & Szczygielski, Jan J., 2021. "Up or down? Short-term reversal, momentum, and liquidity effects in cryptocurrency markets," International Review of Financial Analysis, Elsevier, vol. 78(C).
    3. Day, Min-Yuh & Ni, Yensen, 2023. "Do clean energy indices outperform using contrarian strategies based on contrarian trading rules?," Energy, Elsevier, vol. 272(C).
    4. Bui, Quynh & Ślepaczuk, Robert, 2022. "Applying Hurst Exponent in pair trading strategies on Nasdaq 100 index," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 592(C).
    5. Kumar, Ashish & Iqbal, Najaf & Mitra, Subrata Kumar & Kristoufek, Ladislav & Bouri, Elie, 2022. "Connectedness among major cryptocurrencies in standard times and during the COVID-19 outbreak," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 77(C).
    6. Mehdi Zolfaghari & Bahram Sahabi, 2021. "The impact of oil price and exchange rate on momentum strategy profits in stock market: evidence from oil-rich developing countries," Review of Managerial Science, Springer, vol. 15(7), pages 1981-2023, October.
    7. Guglielmo Maria Caporale & Alex Plastun, 2020. "Momentum effects in the cryptocurrency market after one-day abnormal returns," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 34(3), pages 251-266, September.
    8. Petkova, Ralitsa, 2023. "Extrapolative beliefs about Bitcoin returns," Finance Research Letters, Elsevier, vol. 56(C).
    9. Paweł Sakowski & Anna Turovtseva, 2020. "Verification of Investment Opportunities on the Cryptocurrency Market within the Markowitz Framework," Working Papers 2020-41, Faculty of Economic Sciences, University of Warsaw.
    10. Ladislav Kristoufek, 2022. "On the role of stablecoins in cryptoasset pricing dynamics," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-26, December.
    11. Min-Yuh Day & Yensen Ni & Chinning Hsu & Paoyu Huang, 2022. "Do Investment Strategies Matter for Trading Global Clean Energy and Global Energy ETFs?," Energies, MDPI, vol. 15(9), pages 1-15, May.
    12. Borgards, Oliver, 2021. "Dynamic time series momentum of cryptocurrencies," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).

  11. Przemysław Ryś & Robert Ślepaczuk, 2018. "Machine learning in algorithmic trading strategy optimization - implementation and efficiency," Working Papers 2018-25, Faculty of Economic Sciences, University of Warsaw.

    Cited by:

    1. Kamil Korzeń & Robert Ślepaczuk, 2019. "Hybrid Investment Strategy Based on Momentum and Macroeconomic Approach," Working Papers 2019-17, Faculty of Economic Sciences, University of Warsaw.

  12. Paweł Sakowski & Robert Ślepaczuk & Mateusz Wywiał, 2016. "Applying Exogenous Variables and Regime Switching To Multifactor Models on Equity Indices," Working Papers 2016-10, Faculty of Economic Sciences, University of Warsaw.

    Cited by:

    1. Paweł Sakowski & Robert Ślepaczuk & Mateusz Wywiał, 2016. "Can We Invest Based on Equity Risk Premia and Risk Factors from Multi-Factor Models?," Working Papers 2016-09, Faculty of Economic Sciences, University of Warsaw.

  13. Paweł Sakowski & Robert Ślepaczuk & Mateusz Wywiał, 2016. "Can We Invest Based on Equity Risk Premia and Risk Factors from Multi-Factor Models?," Working Papers 2016-09, Faculty of Economic Sciences, University of Warsaw.

    Cited by:

    1. Paweł Sakowski & Daria Turovtseva, 2020. "Does Bitcoin Improve Investment Portfolio Efficiency?," Working Papers 2020-42, Faculty of Economic Sciences, University of Warsaw.
    2. Paweł Sakowski & Anna Turovtseva, 2020. "Verification of Investment Opportunities on the Cryptocurrency Market within the Markowitz Framework," Working Papers 2020-41, Faculty of Economic Sciences, University of Warsaw.

  14. Paweł Sakowski & Robert Ślepaczuk & Mateusz Wywiał, 2015. "Cross-Sectional Returns With Volatility Regimes From Diverse Portfolio of Emerging and Developed Equity Indices," Working Papers 2015-39, Faculty of Economic Sciences, University of Warsaw.

    Cited by:

    1. Paweł Sakowski & Robert Ślepaczuk & Mateusz Wywiał, 2016. "Do Multi-Factor Models Produce Robust Results? Econometric And Diagnostic Issues In Equity Risk Premia Study," Working Papers 2016-08, Faculty of Economic Sciences, University of Warsaw.

  15. Juliusz Jabłecki & Ryszard Kokoszczyński & Paweł Sakowski & Robert Ślepaczuk & Piotr Wójcik, 2014. "Does historical volatility term structure contain valuable in-formation for predicting volatility index futures?," Working Papers 2014-18, Faculty of Economic Sciences, University of Warsaw.

    Cited by:

    1. Ballestra, Luca Vincenzo & Guizzardi, Andrea & Palladini, Fabio, 2019. "Forecasting and trading on the VIX futures market: A neural network approach based on open to close returns and coincident indicators," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1250-1262.

  16. Robert Ślepaczuk & Grzegorz Zakrzewski & Paweł Sakowski, 2012. "Investment strategies beating the market. What can we squeeze from the market?," Working Papers 2012-04, Faculty of Economic Sciences, University of Warsaw.

    Cited by:

    1. Maryna Zenkova & Robert Ślepaczuk, 2019. "Robustness of Support Vector Machines in Algorithmic Trading on Cryptocurrency Market," Working Papers 2019-02, Faculty of Economic Sciences, University of Warsaw.
    2. Agata Gemzik-Salwach, 2012. "The Use Of A Value At Risk Measure For The Analysis Of Bank Interest Margins," "e-Finanse", University of Information Technology and Management, Institute of Financial Research and Analysis, vol. 8(4), pages 15-29, February.
    3. Kamil Korzeń & Robert Ślepaczuk, 2019. "Hybrid Investment Strategy Based on Momentum and Macroeconomic Approach," Working Papers 2019-17, Faculty of Economic Sciences, University of Warsaw.

  17. Ryszard Kokoszczyński & Paweł Sakowski & Robert Ślepaczuk, 2010. "Midquotes or Transactional Data? The Comparison of Black Model on HF Data," Working Papers 2010-15, Faculty of Economic Sciences, University of Warsaw.

    Cited by:

    1. Maciej Wysocki & Robert Ślepaczuk, 2020. "Artificial Neural Networks Performance in WIG20 Index Options Pricing," Working Papers 2020-19, Faculty of Economic Sciences, University of Warsaw.
    2. Katarzyna Toporek, 2012. "Simple is better. Empirical comparison of American option valuation methods," Ekonomia journal, Faculty of Economic Sciences, University of Warsaw, vol. 29.

  18. Ryszard Kokoszczyński & Natalia Nehrebecka & Paweł Sakowski & Paweł Strawiński & Robert Ślepaczuk, 2010. "Option Pricing Models with HF Data – a Comparative Study. The Properties of Black Model with Different Volatility Measures," Working Papers 2010-03, Faculty of Economic Sciences, University of Warsaw.

    Cited by:

    1. Maciej Wysocki & Robert Ślepaczuk, 2020. "Artificial Neural Networks Performance in WIG20 Index Options Pricing," Working Papers 2020-19, Faculty of Economic Sciences, University of Warsaw.

  19. Robert Ślepaczuk & Grzegorz Zakrzewski, 2009. "High-Frequency and Model-Free Volatility Estimators," Working Papers 2009-13, Faculty of Economic Sciences, University of Warsaw.

    Cited by:

    1. Chuong Luong & Nikolai Dokuchaev, 2016. "Modeling Dependency Of Volatility On Sampling Frequency Via Delay Equations," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 11(02), pages 1-21, June.
    2. Svetlana Lapinova & Alexander Saichev & Maria Tarakanova, 2012. "Volatility estimation based on extremes of the bridge (in Russian)," Quantile, Quantile, issue 10, pages 73-90, December.
    3. Ahmad Sarlak & Zahra Talei, 2016. "Impact of High-Frequency Trading on the Stock Returns of Large and Small Companies in the Tehran Stock Exchange," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 8(4), pages 216-228, April.
    4. Ślepaczuk Robert & Sakowski Paweł & Zakrzewski Grzegorz, 2018. "Investment Strategies that Beat the Market. What Can We Squeeze from the Market?," Financial Internet Quarterly (formerly e-Finanse), Sciendo, vol. 14(4), pages 36-55, December.
    5. Ryszard Kokoszczyński & Natalia Nehrebecka & Paweł Sakowski & Paweł Strawiński & Robert Ślepaczuk, 2010. "Option Pricing Models with HF Data – a Comparative Study. The Properties of Black Model with Different Volatility Measures," Working Papers 2010-03, Faculty of Economic Sciences, University of Warsaw.
    6. Robert Ślepaczuk & Grzegorz Zakrzewski & Paweł Sakowski, 2012. "Investment strategies beating the market. What can we squeeze from the market?," Working Papers 2012-04, Faculty of Economic Sciences, University of Warsaw.

  20. Robert Ślepaczuk & Grzegorz Zakrzewski, 2009. "Emerging versus developed volatility indices. The comparison of VIW20 and VIX indices," Working Papers 2009-11, Faculty of Economic Sciences, University of Warsaw.

    Cited by:

    1. Fassas, Athanasios P. & Siriopoulos, Costas, 2021. "Implied volatility indices – A review," The Quarterly Review of Economics and Finance, Elsevier, vol. 79(C), pages 303-329.

Articles

  1. Bui, Quynh & Ślepaczuk, Robert, 2022. "Applying Hurst Exponent in pair trading strategies on Nasdaq 100 index," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 592(C).

    Cited by:

    1. Baiquan Ma & Robert Ślepaczuk, 2022. "The profitability of pairs trading strategies on Hong-Kong stock market: distance, cointegration, and correlation methods," Working Papers 2022-02, Faculty of Economic Sciences, University of Warsaw.
    2. Rayadurgam, Vikram Chandramouli & Mangalagiri, Jayasree, 2023. "Does inclusion of GARCH variance in deep learning models improve financial contagion prediction?," Finance Research Letters, Elsevier, vol. 54(C).
    3. Paweł Jakubowski & Robert Ślepaczuk & Franciszek Windorbski, 2023. "REnsembling ARIMAX Model in Algorithmic Investment Strategies on Commodities Market," Working Papers 2023-20, Faculty of Economic Sciences, University of Warsaw.

  2. Latoszek Michał & Ślepaczuk Robert, 2020. "Does the inclusion of exposure to volatility into diversified portfolio improve the investment results? Portfolio construction from the perspective of a Polish investor," Economics and Business Review, Sciendo, vol. 6(1), pages 46-81, March.
    See citations under working paper version above.
  3. Kosc, Krzysztof & Sakowski, Paweł & Ślepaczuk, Robert, 2019. "Momentum and contrarian effects on the cryptocurrency market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 691-701.
    See citations under working paper version above.
  4. Ryś Przemysław & Ślepaczuk Robert, 2018. "Machine Learning Methods in Algorithmic Trading Strategy Optimization – Design and Time Efficiency," Central European Economic Journal, Sciendo, vol. 5(52), pages 206-229, January.

    Cited by:

    1. Illia Baranochnikov & Robert Ślepaczuk, 2022. "A comparison of LSTM and GRU architectures with novel walk-forward approach to algorithmic investment strategy," Working Papers 2022-21, Faculty of Economic Sciences, University of Warsaw.

  5. Ślepaczuk Robert & Zenkova Maryna, 2018. "Robustness of Support Vector Machines in Algorithmic Trading on Cryptocurrency Market," Central European Economic Journal, Sciendo, vol. 5(52), pages 186-205, January.
    See citations under working paper version above.
  6. Ślepaczuk Robert & Sakowski Paweł & Zakrzewski Grzegorz, 2018. "Investment Strategies that Beat the Market. What Can We Squeeze from the Market?," Financial Internet Quarterly (formerly e-Finanse), Sciendo, vol. 14(4), pages 36-55, December.

    Cited by:

    1. Jakub Micha'nk'ow & Pawe{l} Sakowski & Robert 'Slepaczuk, 2023. "Hedging Properties of Algorithmic Investment Strategies using Long Short-Term Memory and Time Series models for Equity Indices," Papers 2309.15640, arXiv.org.

  7. Ryszard Kokoszczyński & Paweł Sakowski & Robert Ślepaczuk, 2017. "Which Option Pricing Model Is the Best? HF Data for Nikkei 225 Index Options," Central European Economic Journal, Sciendo, vol. 4(51), pages 18-39, December.

    Cited by:

    1. Maciej Wysocki & Robert Ślepaczuk, 2020. "Artificial Neural Networks Performance in WIG20 Index Options Pricing," Working Papers 2020-19, Faculty of Economic Sciences, University of Warsaw.

  8. Pawe³ Sakowski & Robert Œlepaczuk & Mateusz Wywia³, 2016. "Cross-Sectional Returns With Volatility Regimes From A Diverse Portfolio Of Emerging And Developed Equity Indices," "e-Finanse", University of Information Technology and Management, Institute of Financial Research and Analysis, vol. 12(2), pages 23-35, October.
    See citations under working paper version above.
  9. Paweł Sakowski & Robert Ślepaczuk & Mateusz Wywiał, 2016. "Applying exogenous variables and regime switching to multi-factor models on equity indices," Ekonomia journal, Faculty of Economic Sciences, University of Warsaw, vol. 47.
    See citations under working paper version above.
  10. Juliusz Jablecki & Robert Slepaczuk & Ryszard Kokoszczynski & Pawel Sakowski & Piotr Wojcik, 2014. "Does historical VIX term structure contain valuable information for predicting VIX futures?," Dynamic Econometric Models, Uniwersytet Mikolaja Kopernika, vol. 14, pages 5-28.

    Cited by:

    1. Ballestra, Luca Vincenzo & Guizzardi, Andrea & Palladini, Fabio, 2019. "Forecasting and trading on the VIX futures market: A neural network approach based on open to close returns and coincident indicators," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1250-1262.
    2. Julián Andrada-Félix & Adrian Fernandez-Perez & Fernando Fernández-Rodríguez & Simón Sosvilla-Rivero, 2022. "Time connectedness of fear," Empirical Economics, Springer, vol. 62(3), pages 905-931, March.
      • Julián Andrada-Félixa & Adrian Fernandez-Perez & Fernando Fernández-Rodríguez & Simón Sosvilla-Rivero, 2018. "“Time connectedness of fear”," IREA Working Papers 201818, University of Barcelona, Research Institute of Applied Economics, revised Sep 2018.

  11. Pawel STRAWINSKI & Robert SLEPACZUK, 2008. "Analysis Of High Frequency Data On The Warsaw Stock Exchange In The Context Of Efficient Market Hypothesis," Journal of Applied Economic Sciences, Spiru Haret University, Faculty of Financial Management and Accounting Craiova, vol. 3(3(5)_Fall), pages 306-319.

    Cited by:

    1. Guglielmo Maria Caporale & Luis A. Gil-Alana & Alex Plastun & Inna Makarenko, 2014. "Intraday Anomalies and Market Efficiency: A Trading Robot Analysis," CESifo Working Paper Series 4752, CESifo.
    2. Stavarek, Daniel & Heryan, Tomas, 2012. "Day of the week effect in central European stock markets," MPRA Paper 38431, University Library of Munich, Germany.
    3. Oleg Deev & Dagmar Linnertová, 2012. "Intraday and intraweek trade anomalies on the Czech stock market," Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, Mendel University Press, vol. 60(4), pages 79-88.
    4. Montserrat Reyna Miranda & Ricardo Massa Roldán & Vicente Gómez Salcido, 2022. "Neuro-wavelet Model for price prediction in high-frequency data in the Mexican Stock market," Remef - Revista Mexicana de Economía y Finanzas Nueva Época REMEF (The Mexican Journal of Economics and Finance), Instituto Mexicano de Ejecutivos de Finanzas, IMEF, vol. 17(1), pages 1-23, Enero - M.
    5. Kemal Eyuboglu & Sinem Eyuboglu & Rahmi Yamak, 2016. "Predicting Intra-Day and Day of the Week Anomalies in Turkish Stock Market," Romanian Economic Journal, Department of International Business and Economics from the Academy of Economic Studies Bucharest, vol. 18(59), pages 73-94, March.

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Co-authorship network on CollEc

NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 38 papers announced in NEP. These are the fields, ordered by number of announcements, along with their dates. If the author is listed in the directory of specialists for this field, a link is also provided.
  1. NEP-CMP: Computational Economics (15) 2018-12-10 2019-01-28 2020-08-17 2020-08-17 2022-12-05 2022-12-05 2022-12-12 2023-01-09 2023-03-27 2023-07-24 2023-08-28 2023-10-23 2023-10-23 2023-11-06 2024-03-04. Author is listed
  2. NEP-BIG: Big Data (14) 2018-12-10 2019-01-28 2020-08-17 2020-08-17 2022-12-05 2022-12-05 2022-12-12 2023-01-09 2023-03-27 2023-08-28 2023-10-23 2023-10-23 2023-11-06 2024-03-04. Author is listed
  3. NEP-FMK: Financial Markets (14) 2015-11-21 2016-05-08 2020-05-25 2020-08-17 2020-08-17 2020-09-14 2020-09-28 2022-12-05 2023-01-09 2023-03-27 2023-07-24 2023-08-21 2023-08-28 2023-11-06. Author is listed
  4. NEP-RMG: Risk Management (12) 2009-11-21 2010-12-18 2014-07-13 2014-10-22 2014-11-07 2020-09-14 2020-09-28 2022-12-12 2023-03-27 2023-08-21 2023-10-23 2023-10-23. Author is listed
  5. NEP-ETS: Econometric Time Series (6) 2009-12-19 2020-05-25 2023-03-27 2023-09-18 2023-11-06 2023-11-20. Author is listed
  6. NEP-ORE: Operations Research (6) 2018-12-10 2020-05-25 2020-08-17 2020-08-17 2020-09-14 2020-09-28. Author is listed
  7. NEP-FOR: Forecasting (5) 2014-07-13 2020-05-25 2023-01-09 2023-03-27 2023-11-20. Author is listed
  8. NEP-MST: Market Microstructure (4) 2008-07-20 2009-12-19 2010-12-04 2010-12-18
  9. NEP-PAY: Payment Systems and Financial Technology (3) 2018-04-23 2019-01-28 2022-12-05
  10. NEP-BAN: Banking (2) 2023-03-27 2023-08-21
  11. NEP-ECM: Econometrics (2) 2009-12-19 2020-09-14
  12. NEP-INV: Investment (2) 2023-10-23 2023-11-06
  13. NEP-CFN: Corporate Finance (1) 2019-10-07
  14. NEP-CUL: Cultural Economics (1) 2020-11-02
  15. NEP-FDG: Financial Development and Growth (1) 2023-08-21
  16. NEP-PKE: Post Keynesian Economics (1) 2016-05-08
  17. NEP-SEA: South East Asia (1) 2020-09-28
  18. NEP-SPO: Sports and Economics (1) 2020-11-02
  19. NEP-UPT: Utility Models and Prospect Theory (1) 2016-05-08

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