A. V. Nagaev
- Management Science and Operations Research top 2%
- Mathematical Physics top 5%
- Finance top 5%
- Statistics and Probability top 2%
- Artificial Intelligence
- Co-authors
- Thomas MikoschA. N. StartsevYu. I. DavydovS.M. Shkol'nikГ. Ш. ЦициашвилиRobert M. KunstAdam JakubowskiAbram Kagan
- Topics
- Probability and Risk Models (15 papers)Stochastic processes and financial applications (15 papers)Stochastic processes and statistical mechanics (9 papers)
- Journals
- Journal of Applied ProbabilityJournal of Multivariate AnalysisAdvances in Applied Probability
- Partner nations
- PolandUzbekistanAustria
In The Last Decade
A. V. Nagaev
46 papers receiving 426 citations
Peers
Comparison fields: 5 of 41
- Management Science and Operations Research 262
- Mathematical Physics 231
- Finance 190
- Statistics and Probability 144
- Artificial Intelligence 90
Countries citing papers authored by A. V. Nagaev
This map shows the geographic impact of A. V. Nagaev'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 A. V. Nagaev with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites A. V. Nagaev more than expected).
Fields of papers citing papers by A. V. Nagaev
This network shows the impact of papers produced by A. V. Nagaev. 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 A. V. Nagaev. The network helps show where A. V. Nagaev may publish in the future.
Co-authorship network of co-authors of A. V. Nagaev
This figure shows the co-authorship network connecting the top 25 collaborators of A. V. Nagaev. A scholar is included among the top collaborators of A. V. Nagaev 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 A. V. Nagaev. A. V. Nagaev 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 | A Diffusion Approximation for the Riskless Profit Under Selling of Discrete Time Call Options. Non-identically Distributed Jumps | 3 |
| 4 | A Diffusion Approximation to the Markov Chains Model of the Financial Market and the Expected Riskless Profit Under Selling of Call and Put Options | 4 |
| 5 | Local large deviation theorem for sums of i.i.d. random vectors when the Cramér condition holds in the whole space | 1 |
| 6 | 1 | |
| 7 | 2 | |
| 8 | 1 | |
| 9 | 11 | |
| 10 | 1 | |
| 11 | 2 | |
| 12 | 1 | |
| 13 | 10 | |
| 14 | 2 | |
| 15 | 5 | |
| 16 | 2 | |
| 17 | 9 | |
| 18 | 0 | |
| 19 | 2 | |
| 20 | 1 |
About A. V. Nagaev
A. V. Nagaev is a scholar working on Finance, Mathematical Physics and Management Science and Operations Research, having authored 53 papers that have together received 486 indexed citations. Recurring topics across this work include Probability and Risk Models (15 papers), Stochastic processes and financial applications (15 papers) and Stochastic processes and statistical mechanics (9 papers). The work is most often cited by research in Mathematical Physics (231 citations), Management Science and Operations Research (262 citations) and Finance (190 citations). A. V. Nagaev has collaborated with scholars based in Poland, Uzbekistan and Austria. Frequent co-authors include Thomas Mikosch, A. N. Startsev, Yu. I. Davydov, S.M. Shkol'nik, Г. Ш. Цициашвили, Robert M. Kunst, Adam Jakubowski, Abram Kagan and Anne Philippe. Their work appears in journals such as Journal of Applied Probability, Journal of Multivariate Analysis and Advances in Applied Probability.
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.