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Marcin Chlebus

Personal Details

First Name:Marcin
Middle Name:
Last Name:Chlebus
Suffix:
RePEc Short-ID:pch1469

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 Chapters

Working papers

  1. Szymon Lis & Marcin Chlebus, 2021. "Comparison of the accuracy in VaR forecasting for commodities using different methods of combining forecasts," Working Papers 2021-11, Faculty of Economic Sciences, University of Warsaw.
  2. Michał Woźniak & Marcin Chlebus, 2021. "HCR & HCR-GARCH – novel statistical learning models for Value at Risk estimation," Working Papers 2021-10, Faculty of Economic Sciences, University of Warsaw.
  3. Aleksander Schiffers & Marcin Chlebus, 2021. "The effectiveness of Value-at-Risk models in various volatility regimes," Working Papers 2021-28, Faculty of Economic Sciences, University of Warsaw.
  4. Piotr Borowski & Marcin Chlebus, 2021. "Machine learning in the prediction of flat horse racing results in Poland," Working Papers 2021-13, Faculty of Economic Sciences, University of Warsaw.
  5. Przemys{l}aw Biecek & Marcin Chlebus & Janusz Gajda & Alicja Gosiewska & Anna Kozak & Dominik Ogonowski & Jakub Sztachelski & Piotr Wojewnik, 2021. "Enabling Machine Learning Algorithms for Credit Scoring -- Explainable Artificial Intelligence (XAI) methods for clear understanding complex predictive models," Papers 2104.06735, arXiv.org.
  6. Mateusz Buczyński & Marcin Chlebus, 2021. "GARCHNet - Value-at-Risk forecasting with novel approach to GARCH models based on neural networks," Working Papers 2021-08, Faculty of Economic Sciences, University of Warsaw.
  7. Michał Lewandowski & Marcin Chlebus, 2021. "Predicting football outcomes from Spanish league using machine learning models," Working Papers 2021-22, Faculty of Economic Sciences, University of Warsaw.
  8. Marek Stelmach & Marcin Chlebus, 2020. "Novel multilayer stacking framework with weighted ensemble approach for multiclass credit scoring problem application," Working Papers 2020-08, Faculty of Economic Sciences, University of Warsaw.
  9. Marta Kłosok & Marcin Chlebus, 2020. "Towards better understanding of complex machine learning models using Explainable Artificial Intelligence (XAI) - case of Credit Scoring modelling," Working Papers 2020-18, Faculty of Economic Sciences, University of Warsaw.
  10. Mateusz Heba & Marcin Chlebus, 2020. "Impact of using industry benchmark financial ratios on performance of bankruptcy prediction logistic regression model," Working Papers 2020-30, Faculty of Economic Sciences, University of Warsaw.
  11. Marcin Chlebus & Maciej Stefan Świtała, 2020. "So close and so far. Finding similar tendencies in econometrics and machine learning papers. Topic models comparison," Working Papers 2020-16, Faculty of Economic Sciences, University of Warsaw.
  12. Marcin Chlebus & Michał Dyczko & Michał Woźniak, 2020. "Nvidia’s stock returns prediction using machine learning techniques for time series forecasting problem," Working Papers 2020-22, Faculty of Economic Sciences, University of Warsaw.
  13. Marcin Chlebus & Zuzanna Osika, 2020. "Comparison of tree-based models performance in prediction of marketing campaign results using Explainable Artificial Intelligence tools," Working Papers 2020-15, Faculty of Economic Sciences, University of Warsaw.
  14. Illya Barziy & Marcin Chlebus, 2020. "HRP performance comparison in portfolio optimization under various codependence and distance metrics," Working Papers 2020-21, Faculty of Economic Sciences, University of Warsaw.
  15. Mateusz Buczyński & Marcin Chlebus, 2020. "Size does matter. A study on the required window size for optimal quality market risk models," Working Papers 2020-09, Faculty of Economic Sciences, University of Warsaw.
  16. Mateusz Buczyński & Marcin Chlebus, 2019. "Old-fashioned parametric models are still the best. A comparison of Value-at-Risk approaches in several volatility states," Working Papers 2019-12, Faculty of Economic Sciences, University of Warsaw.
  17. Mateusz Buczyński & Marcin Chlebus, 2017. "Is CAViaR model really so good in Value at Risk forecasting? Evidence from evaluation of a quality of Value-at-Risk forecasts obtained based on the: GARCH(1,1), GARCH-t(1,1), GARCH-st(1,1), QML-GARCH(," Working Papers 2017-29, Faculty of Economic Sciences, University of Warsaw.
  18. Marcin Chlebus, 2016. "EWS-GARCH: New Regime Switching Approach to Forecast Value-at-Risk," Working Papers 2016-06, Faculty of Economic Sciences, University of Warsaw.
  19. Marcin Chlebus, 2016. "One-Day Prediction of State of Turbulence for Portfolio. Models for Binary Dependent Variable," Working Papers 2016-01, Faculty of Economic Sciences, University of Warsaw.

Articles

  1. Chlebus Marcin & Dyczko Michał & Woźniak Michał, 2021. "Nvidia's Stock Returns Prediction Using Machine Learning Techniques for Time Series Forecasting Problem," Central European Economic Journal, Sciendo, vol. 8(55), pages 44-62, January.
  2. Cylwik Stefan & Gabryelczyk Renata & Chlebus Marcin, 2020. "Ridesharing in the Polish Experience: A Study using Unified Theory of Acceptance and Use of Technology," Central European Economic Journal, Sciendo, vol. 7(54), pages 279-299, January.
  3. Szubzda Filip & Chlebus Marcin, 2019. "Comparison of Block Maxima and Peaks Over Threshold Value-at-Risk models for market risk in various economic conditions," Central European Economic Journal, Sciendo, vol. 6(53), pages 70-85, January.
  4. Buczyński Mateusz & Chlebus Marcin, 2018. "Comparison of Semi-Parametric and Benchmark Value-At-Risk Models in Several Time Periods with Different Volatility Levels," Financial Internet Quarterly (formerly e-Finanse), Sciendo, vol. 14(2), pages 67-82, June.
  5. Marcin Chlebus, 2018. "One-day-ahead forecast of state of turbulence based on today's economic situation," Equilibrium. Quarterly Journal of Economics and Economic Policy, Institute of Economic Research, vol. 13(3), pages 357-389, September.
  6. Chlebus Marcin, 2017. "EWS-GARCH: New Regime Switching Approach to Forecast Value-at-Risk," Central European Economic Journal, Sciendo, vol. 3(50), pages 01-25, December.
  7. Marcin Chlebus, 2014. "One-day prediction of state of turbulence for financial instrument based on models for binary dependent variable," Ekonomia journal, Faculty of Economic Sciences, University of Warsaw, vol. 37.

Chapters


    RePEc:ann:findec:book:y:2016:n:63:ch:04:ps is not listed on IDEAS

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. Aleksander Schiffers & Marcin Chlebus, 2021. "The effectiveness of Value-at-Risk models in various volatility regimes," Working Papers 2021-28, Faculty of Economic Sciences, University of Warsaw.

    Cited by:

    1. Pourkhanali, Armin & Tafakori, Laleh & Bee, Marco, 2023. "Forecasting Value-at-Risk using functional volatility incorporating an exogenous effect," International Review of Financial Analysis, Elsevier, vol. 89(C).

  2. Przemys{l}aw Biecek & Marcin Chlebus & Janusz Gajda & Alicja Gosiewska & Anna Kozak & Dominik Ogonowski & Jakub Sztachelski & Piotr Wojewnik, 2021. "Enabling Machine Learning Algorithms for Credit Scoring -- Explainable Artificial Intelligence (XAI) methods for clear understanding complex predictive models," Papers 2104.06735, arXiv.org.

    Cited by:

    1. Yu Zhao & Huaming Du & Qing Li & Fuzhen Zhuang & Ji Liu & Gang Kou, 2022. "A Comprehensive Survey on Enterprise Financial Risk Analysis from Big Data Perspective," Papers 2211.14997, arXiv.org, revised May 2023.
    2. Ahmed, Abdulaziz & Topuz, Kazim & Moqbel, Murad & Abdulrashid, Ismail, 2024. "What makes accidents severe! explainable analytics framework with parameter optimization," European Journal of Operational Research, Elsevier, vol. 317(2), pages 425-436.
    3. Emer Owens & Barry Sheehan & Martin Mullins & Martin Cunneen & Juliane Ressel & German Castignani, 2022. "Explainable Artificial Intelligence (XAI) in Insurance," Risks, MDPI, vol. 10(12), pages 1-50, December.

  3. Marcin Chlebus & Michał Dyczko & Michał Woźniak, 2020. "Nvidia’s stock returns prediction using machine learning techniques for time series forecasting problem," Working Papers 2020-22, 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. 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. Mateusz Buczyński & Marcin Chlebus, 2019. "Old-fashioned parametric models are still the best. A comparison of Value-at-Risk approaches in several volatility states," Working Papers 2019-12, Faculty of Economic Sciences, University of Warsaw.

    Cited by:

    1. Aleksander Schiffers & Marcin Chlebus, 2021. "The effectiveness of Value-at-Risk models in various volatility regimes," Working Papers 2021-28, Faculty of Economic Sciences, University of Warsaw.
    2. Szymon Lis & Marcin Chlebus, 2021. "Comparison of the accuracy in VaR forecasting for commodities using different methods of combining forecasts," Working Papers 2021-11, Faculty of Economic Sciences, University of Warsaw.
    3. Murphy, David & Vause, Nicholas, 2021. "A CBA of APC: analysing approaches to procyclicality reduction in CCP initial margin models," Bank of England working papers 950, Bank of England.

  5. Marcin Chlebus, 2016. "EWS-GARCH: New Regime Switching Approach to Forecast Value-at-Risk," Working Papers 2016-06, Faculty of Economic Sciences, University of Warsaw.

    Cited by:

    1. Mateusz Buczynski & Marcin Chlebus, 2024. "GARCHNet: Value-at-Risk Forecasting with GARCH Models Based on Neural Networks," Computational Economics, Springer;Society for Computational Economics, vol. 63(5), pages 1949-1979, May.
    2. Mateusz Buczyński & Marcin Chlebus, 2021. "GARCHNet - Value-at-Risk forecasting with novel approach to GARCH models based on neural networks," Working Papers 2021-08, Faculty of Economic Sciences, University of Warsaw.
    3. Mateusz Buczyński & Marcin Chlebus, 2019. "Old-fashioned parametric models are still the best. A comparison of Value-at-Risk approaches in several volatility states," Working Papers 2019-12, Faculty of Economic Sciences, University of Warsaw.

  6. Marcin Chlebus, 2016. "One-Day Prediction of State of Turbulence for Portfolio. Models for Binary Dependent Variable," Working Papers 2016-01, Faculty of Economic Sciences, University of Warsaw.

    Cited by:

    1. Chlebus Marcin, 2017. "EWS-GARCH: New Regime Switching Approach to Forecast Value-at-Risk," Central European Economic Journal, Sciendo, vol. 3(50), pages 01-25, December.

Articles

  1. Chlebus Marcin & Dyczko Michał & Woźniak Michał, 2021. "Nvidia's Stock Returns Prediction Using Machine Learning Techniques for Time Series Forecasting Problem," Central European Economic Journal, Sciendo, vol. 8(55), pages 44-62, January.
    See citations under working paper version above.
  2. Buczyński Mateusz & Chlebus Marcin, 2018. "Comparison of Semi-Parametric and Benchmark Value-At-Risk Models in Several Time Periods with Different Volatility Levels," Financial Internet Quarterly (formerly e-Finanse), Sciendo, vol. 14(2), pages 67-82, June.

    Cited by:

    1. Szymon Lis & Marcin Chlebus, 2021. "Comparison of the accuracy in VaR forecasting for commodities using different methods of combining forecasts," Working Papers 2021-11, Faculty of Economic Sciences, University of Warsaw.

  3. Chlebus Marcin, 2017. "EWS-GARCH: New Regime Switching Approach to Forecast Value-at-Risk," Central European Economic Journal, Sciendo, vol. 3(50), pages 01-25, December.
    See citations under working paper version above.

Chapters

    Sorry, no citations of chapters recorded.

More information

Research fields, statistics, top rankings, if available.

Statistics

Access and download statistics for all items

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 19 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-RMG: Risk Management (12) 2016-01-18 2016-03-23 2018-01-01 2019-08-19 2020-05-25 2020-08-17 2020-08-24 2021-04-19 2021-06-14 2021-06-14 2021-07-12 2022-12-12. Author is listed
  2. NEP-BIG: Big Data (11) 2020-05-04 2020-06-15 2020-06-29 2020-08-17 2020-08-24 2020-08-24 2021-04-19 2021-06-14 2021-07-12 2021-07-12 2022-12-12. Author is listed
  3. NEP-CMP: Computational Economics (11) 2020-05-04 2020-06-15 2020-06-29 2020-08-17 2020-08-24 2020-08-24 2021-04-19 2021-06-14 2021-07-12 2021-07-12 2022-12-12. Author is listed
  4. NEP-ORE: Operations Research (8) 2019-08-19 2020-05-04 2020-05-25 2020-08-24 2020-08-24 2021-06-14 2021-06-14 2021-07-12. Author is listed
  5. NEP-FOR: Forecasting (7) 2016-01-18 2016-03-23 2018-01-01 2020-08-24 2021-06-14 2021-07-12 2022-12-12. Author is listed
  6. NEP-ETS: Econometric Time Series (6) 2016-03-23 2018-01-01 2019-08-19 2021-06-14 2021-06-14 2021-07-12. Author is listed
  7. NEP-ECM: Econometrics (5) 2019-08-19 2020-05-04 2020-05-25 2020-06-29 2021-06-14. Author is listed
  8. NEP-BAN: Banking (2) 2018-01-01 2019-08-19
  9. NEP-CWA: Central and Western Asia (2) 2021-06-14 2021-07-12
  10. NEP-SPO: Sports and Economics (2) 2021-07-12 2022-12-12
  11. NEP-CFN: Corporate Finance (1) 2020-09-28
  12. NEP-DCM: Discrete Choice Models (1) 2021-04-19
  13. NEP-FMK: Financial Markets (1) 2020-08-24
  14. NEP-PAY: Payment Systems and Financial Technology (1) 2020-08-17

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