Mátyás Barczy
- Finance top 5%
- Mathematical Physics top 10%
- Statistics and Probability top 5%
- Artificial Intelligence
- Management Science and Operations Research top 10%
- Co-authors
- Gyula PapZenghu LiMárton IspányLeif DöringManuel G. ScottoMaria Eduarda SilvaLajos MolnárJean Bertoin
- Topics
- Stochastic processes and statistical mechanics (24 papers)Stochastic processes and financial applications (21 papers)Financial Risk and Volatility Modeling (14 papers)
- Journals
- SHILAP Revista de lepidopterologíaJournal of Mathematical Analysis and ApplicationsJournal of Functional Analysis
In The Last Decade
Mátyás Barczy
46 papers receiving 260 citations
Peers
Comparison fields: 5 of 38
- Finance 167
- Mathematical Physics 118
- Statistics and Probability 109
- Artificial Intelligence 42
- Management Science and Operations Research 40
Countries citing papers authored by Mátyás Barczy
This map shows the geographic impact of Mátyás Barczy's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Mátyás Barczy with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mátyás Barczy more than expected).
Fields of papers citing papers by Mátyás Barczy
This network shows the impact of papers produced by Mátyás Barczy. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Mátyás Barczy. The network helps show where Mátyás Barczy may publish in the future.
Co-authorship network of co-authors of Mátyás Barczy
This figure shows the co-authorship network connecting the top 25 collaborators of Mátyás Barczy. A scholar is included among the top collaborators of Mátyás Barczy based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Mátyás Barczy. Mátyás Barczy is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 1 | |
| 3 | 1 | |
| 4 | 1 | |
| 5 | 2 | |
| 6 | 5 | |
| 7 | 0 | |
| 8 | 2 | |
| 9 | 2 | |
| 10 | 3 | |
| 11 | 2 | |
| 12 | 1 | |
| 13 | 2 | |
| 14 | 4 | |
| 15 | 2 | |
| 16 | 23 | |
| 17 | 4 | |
| 18 | Ergodicity for an affine two factor model | 1 |
| 19 | 14 | |
| 20 | 26 |
About Mátyás Barczy
Mátyás Barczy is a scholar working on Mathematical Physics, Finance and Statistics and Probability, having authored 51 papers that have together received 265 indexed citations. Recurring topics across this work include Stochastic processes and statistical mechanics (24 papers), Stochastic processes and financial applications (21 papers) and Financial Risk and Volatility Modeling (14 papers). The work is most often cited by research in Finance (167 citations), Statistics and Probability (109 citations) and Mathematical Physics (118 citations). Mátyás Barczy has collaborated with scholars based in Hungary, France and China. Frequent co-authors include Gyula Pap, Zenghu Li, Márton Ispány, Leif Döring, Manuel G. Scotto, Maria Eduarda Silva, Lajos Molnár, Jean Bertoin, Zsolt Páles and Bojan Basrak. Their work appears in journals such as SHILAP Revista de lepidopterología, Journal of Mathematical Analysis and Applications and Journal of Functional Analysis.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.