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)

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. Pawe{l} Sakowski & Rafa{l} Sieradzki & Robert 'Slepaczuk, 2023. "Systemic risk indicator based on implied and realized volatility," Papers 2307.05719, arXiv.org.

   Cited by:

   1. Kim, Jinhwan & Cho, Hoon & Seok, Sangik, 2023. "Liquidity risk, return performance, and tracking error: Synthetic vs. Physical ETFs," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 89(C).

2. 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. Kamil Kashif & Robert Ślepaczuk, 2024. "LSTM-ARIMA as a Hybrid Approach in Algorithmic Investment Strategies," Working Papers 2024-07, Faculty of Economic Sciences, University of Warsaw.
      • Kamil Kashif & Robert 'Slepaczuk, 2024. "LSTM-ARIMA as a Hybrid Approach in Algorithmic Investment Strategies," Papers 2406.18206, arXiv.org.
   3. 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.

3. 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. Kamil Kashif & Robert Ślepaczuk, 2024. "LSTM-ARIMA as a Hybrid Approach in Algorithmic Investment Strategies," Working Papers 2024-07, Faculty of Economic Sciences, University of Warsaw.
      • Kamil Kashif & Robert 'Slepaczuk, 2024. "LSTM-ARIMA as a Hybrid Approach in Algorithmic Investment Strategies," Papers 2406.18206, arXiv.org.
   2. 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.

4. 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).

5. 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.

   Cited by:

   1. Kim, Jinhwan & Cho, Hoon & Seok, Sangik, 2023. "Liquidity risk, return performance, and tracking error: Synthetic vs. Physical ETFs," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 89(C).

6. 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. Kamil Kashif & Robert Ślepaczuk, 2024. "LSTM-ARIMA as a Hybrid Approach in Algorithmic Investment Strategies," Working Papers 2024-07, Faculty of Economic Sciences, University of Warsaw.
      • Kamil Kashif & Robert 'Slepaczuk, 2024. "LSTM-ARIMA as a Hybrid Approach in Algorithmic Investment Strategies," Papers 2406.18206, arXiv.org.
   2. 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.

7. 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.

8. 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. Kamil Kashif & Robert Ślepaczuk, 2024. "LSTM-ARIMA as a Hybrid Approach in Algorithmic Investment Strategies," Working Papers 2024-07, Faculty of Economic Sciences, University of Warsaw.
      • Kamil Kashif & Robert 'Slepaczuk, 2024. "LSTM-ARIMA as a Hybrid Approach in Algorithmic Investment Strategies," Papers 2406.18206, arXiv.org.
   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.
      • Bartosz Bieganowski & Robert Slepaczuk, 2024. "Supervised Autoencoder MLP for Financial Time Series Forecasting," Papers 2404.01866, arXiv.org, revised Jun 2024.
   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).

9. 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.

10. 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.
    • 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.

    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. 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.
    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. Helena Gaspars-Wieloch & Dominik Gawroński, 2024. "How can one improve SAW and max-min multi-criteria rankings based on uncertain decision rules?," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 34(1), pages 131-148.

11. 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.
    • 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.

    Cited by:

    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.
       • Bartosz Bieganowski & Robert Slepaczuk, 2024. "Supervised Autoencoder MLP for Financial Time Series Forecasting," Papers 2404.01866, arXiv.org, revised Jun 2024.
    2. 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.
    3. 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.

12. 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.
    • 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.

    Cited by:

    1. 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.
    2. 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.
       • 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.
    3. 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).
    4. 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).
    5. 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.
    6. Petkova, Ralitsa, 2023. "Extrapolative beliefs about Bitcoin returns," Finance Research Letters, Elsevier, vol. 56(C).
    7. Christian Fieberg & Gerrit Liedtke & Daniel Metko & Adam Zaremba, 2023. "Cryptocurrency factor momentum," Quantitative Finance, Taylor & Francis Journals, vol. 23(12), pages 1853-1869, November.
    8. 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.
    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. Borgards, Oliver, 2021. "Dynamic time series momentum of cryptocurrencies," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).
    11. 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.
        • Guglielmo Maria Caporale & Alex Plastun, 2019. "Momentum Effects in the Cryptocurrency Market After One-Day Abnormal Returns," CESifo Working Paper Series 7917, CESifo.
    12. Day, Min-Yuh & Ni, Yensen, 2023. "Do clean energy indices outperform using contrarian strategies based on contrarian trading rules?," Energy, Elsevier, vol. 272(C).
    13. Zhang, Zhehao & Xing, Ruina & Liu, Jiajun & Shao, Yifei, 2023. "Correlation-based investment strategies: A comparison between Chinese and US stock markets," Pacific-Basin Finance Journal, Elsevier, vol. 82(C).
    14. 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).

13. 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.

14. 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.
    • 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.

    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.

15. 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 & 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.
    2. Paweł Sakowski & Daria Turovtseva, 2020. "Does Bitcoin Improve Investment Portfolio Efficiency?," Working Papers 2020-42, Faculty of Economic Sciences, University of Warsaw.

16. 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.
    • 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.
    • Sakowski Paweł & Ślepaczuk Robert & Wywiał Mateusz, 2016. "Cross-Sectional Returns with Volatility Regimes from a Diverse Portfolio of Emerging and Developed Equity Indices," Financial Internet Quarterly (formerly e-Finanse), Sciendo, vol. 12(2), pages 23-35.

    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.

17. 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.

18. 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.
       • 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.
    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.

19. 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.

20. 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.

21. 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. 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.
    2. 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.
    3. 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.
       • 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.

22. 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. 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).
   2. 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.
   3. Day, Min-Yuh & Ni, Yensen, 2023. "Be greedy when others are fearful: Evidence from a two-decade assessment of the NDX 100 and S&P 500 indexes," International Review of Financial Analysis, Elsevier, vol. 90(C).
   4. Mar Grande & Florentino Borondo & Juan Carlos Losada & Javier Borondo, 2024. "Anti-Persistent Values of the Hurst Exponent Anticipate Mean Reversion in Pairs Trading: The Cryptocurrencies Market as a Case Study," Mathematics, MDPI, vol. 12(18), pages 1-14, September.
   5. 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.
   • 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.
   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.
   • 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.
   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.
   • 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.
   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.
      • Jakub Michańków & Paweł Sakowski & Robert Ślepaczuk, 2023. "Hedging Properties of Algorithmic Investment Strategies using Long Short-Term Memory and Time Series models for Equity Indices," Working Papers 2023-25, Faculty of Economic Sciences, University of Warsaw.

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.
   • 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.
   • Sakowski Paweł & Ślepaczuk Robert & Wywiał Mateusz, 2016. "Cross-Sectional Returns with Volatility Regimes from a Diverse Portfolio of Emerging and Developed Equity Indices," Financial Internet Quarterly (formerly e-Finanse), Sciendo, vol. 12(2), pages 23-35.
   • 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.
   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.
   • 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.
   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. 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.
    2. 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.

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 Gil-Alana & Alex Plastun & Inna Makarenko, 2014. "Intraday Anomalies and Market Efficiency: A Trading Robot Analysis," Discussion Papers of DIW Berlin 1377, DIW Berlin, German Institute for Economic Research.
       • Guglielmo Caporale & Luis Gil-Alana & Alex Plastun & Inna Makarenko, 2016. "Intraday Anomalies and Market Efficiency: A Trading Robot Analysis," Computational Economics, Springer;Society for Computational Economics, vol. 47(2), pages 275-295, February.
       • 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. 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.
    3. Stavarek, Daniel & Heryan, Tomas, 2012. "Day of the week effect in central European stock markets," MPRA Paper 38431, University Library of Munich, Germany.
    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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NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 41 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 (23) 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 2024-05-06 2024-07-15 2024-07-15 2024-07-22 2024-07-29 2024-07-29 2024-08-12 2024-08-26. Author is listed
2. NEP-BIG: Big Data (22) 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 2024-05-06 2024-07-15 2024-07-15 2024-07-22 2024-07-22 2024-07-29 2024-07-29 2024-08-12. Author is listed
3. NEP-FMK: Financial Markets (18) 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 2024-07-22 2024-08-19 2024-08-26 2024-09-02. Author is listed
4. NEP-FOR: Forecasting (7) 2014-07-13 2020-05-25 2023-01-09 2023-03-27 2023-11-20 2024-07-22 2024-08-26. 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-BAN: Banking (3) 2023-03-27 2023-08-21 2024-07-22
7. NEP-ECM: Econometrics (2) 2009-12-19 2020-09-14
8. NEP-INV: Investment (2) 2023-10-23 2023-11-06
9. NEP-CFN: Corporate Finance (1) 2019-10-07
10. NEP-CUL: Cultural Economics (1) 2020-11-02
11. NEP-FDG: Financial Development and Growth (1) 2023-08-21

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