Yu. M. Kabanov
- Finance top 1%
- Economics and Econometrics top 5%
- Management Science and Operations Research top 5%
- Demography top 5%
- Mathematical Physics top 10%
- Co-authors
- Dmitry KramkovAlbert N. ShiryaevGiovanni B. Di MasiWolfgang J. RunggaldierC. StrickerR. LiptserAlexander MelnikovMarek Rutkowski
- Topics
- Stochastic processes and financial applications (16 papers)Economic theories and models (5 papers)advanced mathematical theories (3 papers)
- Journals
- Probability Theory and Related FieldsRussian Mathematical SurveysJournal of Mathematical Economics
- Partner nations
- RussiaFranceUnited States
In The Last Decade
Yu. M. Kabanov
27 papers receiving 687 citations
Peers
Comparison fields: 5 of 56
- Finance 583
- Economics and Econometrics 293
- Management Science and Operations Research 149
- Demography 109
- Mathematical Physics 79
Countries citing papers authored by Yu. M. Kabanov
This map shows the geographic impact of Yu. M. Kabanov'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 Yu. M. Kabanov with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yu. M. Kabanov more than expected).
Fields of papers citing papers by Yu. M. Kabanov
This network shows the impact of papers produced by Yu. M. Kabanov. 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 Yu. M. Kabanov. The network helps show where Yu. M. Kabanov may publish in the future.
Co-authorship network of co-authors of Yu. M. Kabanov
This figure shows the co-authorship network connecting the top 25 collaborators of Yu. M. Kabanov. A scholar is included among the top collaborators of Yu. M. Kabanov 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 Yu. M. Kabanov. Yu. M. Kabanov is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 3 | |
| 2 | 4 | |
| 3 | 15 | |
| 4 | 7 | |
| 5 | 19 | |
| 6 | 145 | |
| 7 | 47 | |
| 8 | 131 | |
| 9 | 32 | |
| 10 | 10 | |
| 11 | 4 | |
| 12 | 7 | |
| 13 | 25 | |
| 14 | 1 | |
| 15 | 22 | |
| 16 | 1 | |
| 17 | 12 | |
| 18 | 30 | |
| 19 | 100 | |
| 20 | 21 |
About Yu. M. Kabanov
Yu. M. Kabanov is a scholar working on Finance, Applied Mathematics and Statistics and Probability, having authored 28 papers that have together received 823 indexed citations. Recurring topics across this work include Stochastic processes and financial applications (16 papers), Economic theories and models (5 papers) and advanced mathematical theories (3 papers). The work is most often cited by research in Finance (583 citations), Management Science and Operations Research (149 citations) and Economics and Econometrics (293 citations). Yu. M. Kabanov has collaborated with scholars based in Russia, France and United States. Frequent co-authors include Dmitry Kramkov, Albert N. Shiryaev, Giovanni B. Di Masi, Wolfgang J. Runggaldier, C. Stricker, R. Liptser, Alexander Melnikov, Marek Rutkowski, Alan Brace and Martin Schweizer. Their work appears in journals such as Probability Theory and Related Fields, Russian Mathematical Surveys and Journal of Mathematical Economics.
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.