Michał Jerzy Woźniak
(Michal Jerzy Wozniak)
Personal Details
First Name: | Michal |
Middle Name: | Jerzy |
Last Name: | Wozniak |
Suffix: | |
RePEc Short-ID: | pwo298 |
| |
Affiliation
Wydział Nauk Ekonomicznych
Uniwersytet Warszawski
Warszawa, Polandhttp://www.wne.uw.edu.pl/
RePEc:edi:fesuwpl (more details at EDIRC)
Research output
Jump to: Working papers ArticlesWorking papers
- 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.
- Jacek Lewkowicz & Michał Woźniak & Michał Wrzesiński, 2021. "Institutional Framework of Central Bank Independence: Revisited," Working Papers 2021-06, Faculty of Economic Sciences, University of Warsaw.
- Mateusz Kijewski & Szymon Lis & Michał Woźniak & Maciej Wysocki, 2021. "Don’t Worry, Be Happy – But Only Seasonally," Working Papers 2021-12, Faculty of Economic Sciences, University of Warsaw.
- 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.
- 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.
Articles
- Lewkowicz, Jacek & Woźniak, Michał & Wrzesiński, Michał, 2022. "COVID-19 and erosion of democracy," Economic Modelling, Elsevier, vol. 106(C).
- 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.
- 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.
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
- 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.
- 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.
Cited by:
- 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.
- 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.
Articles
- Lewkowicz, Jacek & Woźniak, Michał & Wrzesiński, Michał, 2022.
"COVID-19 and erosion of democracy,"
Economic Modelling, Elsevier, vol. 106(C).
Cited by:
- Gossé, Jean-Baptiste & Jehle, Camille, 2024. "Benefits of diversification in EU capital markets: Evidence from stock portfolios," Economic Modelling, Elsevier, vol. 135(C).
- Thierry Blayac & Dimitri Dubois & Sébastien Duchêne & Phu Nguyen-Van & Bruno Ventelou & Marc Willinger, 2022.
"What drives the acceptability of restrictive health policies: An experimental assessment of individual preferences for anti-COVID 19 strategies,"
Post-Print
hal-03866196, HAL.
- Blayac, Thierry & Dubois, Dimitri & Duchêne, Sébastien & Nguyen-Van, Phu & Ventelou, Bruno & Willinger, Marc, 2022. "What drives the acceptability of restrictive health policies: An experimental assessment of individual preferences for anti-COVID 19 strategies," Economic Modelling, Elsevier, vol. 116(C).
- Croissant, Aurel & Kühn, David & Macias-Weller, Ariam & Pion-Berlin, David, 2023. "Militarisation of COVID-19 responses and autocratisation: A comparative study of eight countries in Asia-Pacific and Latin America," GIGA Working Papers 334, GIGA German Institute of Global and Area Studies.
- Bandyopadhyay, Simanti & Kabiraj, Sujana & Majumder, Subrata, 2023. "Subnational governments and COVID management," Economic Modelling, Elsevier, vol. 124(C).
- Alba Taboada-Villamarín & Cristóbal Torres-Albero, 2024. "Digital Communication Studies during the Pandemic: A Sociological Review Using Topic Modeling Strategy," Social Sciences, MDPI, vol. 13(2), pages 1-18, January.
- Nguenda Anya, Saturnin Bertrand & Nzepang, Fabrice, 2022. "The role of the separation of democratic powers on structural transformation in Sub-Saharan Africa," Economic Systems, Elsevier, vol. 46(4).
- Stankov, Petar, 2024. "Will voters polarize over pandemic restrictions? Theory and evidence from COVID-19," Economic Modelling, Elsevier, vol. 136(C).
- Fabrice Nzepang & Saturnin Bertrand Nguenda Anya, 2024. "What Is the Interaction Between Separation of Democratic Powers and Structural Transformation in Sub-Saharan Africa?," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 15(2), pages 7702-7722, June.
- 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.
- 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.
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 4 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.- NEP-BIG: Big Data (2) 2020-08-24 2021-07-12. Author is listed
- NEP-ORE: Operations Research (2) 2020-08-24 2021-06-14. Author is listed
- NEP-CBA: Central Banking (1) 2021-05-24. Author is listed
- NEP-CMP: Computational Economics (1) 2020-08-24. Author is listed
- NEP-ETS: Econometric Time Series (1) 2021-06-14. Author is listed
- NEP-FMK: Financial Markets (1) 2020-08-24. Author is listed
- NEP-FOR: Forecasting (1) 2020-08-24. Author is listed
- NEP-HAP: Economics of Happiness (1) 2021-07-12. Author is listed
- NEP-MAC: Macroeconomics (1) 2021-05-24. Author is listed
- NEP-RMG: Risk Management (1) 2021-06-14. Author is listed
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