Kaushik Matia
- Economics and Econometrics top 2%
- Statistical and Nonlinear Physics top 2%
- Finance top 5%
- Condensed Matter Physics top 10%
- Management Science and Operations Research top 10%
- Co-authors
- H. Eugene StanleyYosef AshkenazyMassimo RiccaboniSergey V. BuldyrevFabio PammolliKazuko YamasakiDongfeng FuLuı́s A. Nunes Amaral
- Topics
- Complex Systems and Time Series Analysis (12 papers)Financial Risk and Volatility Modeling (5 papers)Firm Innovation and Growth (5 papers)
- Journals
- Proceedings of the National Academy of SciencesPhysica A Statistical Mechanics and its ApplicationsEurophysics Letters (EPL)
- Partner nations
- United StatesItalyJapan
In The Last Decade
Kaushik Matia
14 papers receiving 613 citations
Peers
Comparison fields: 5 of 57
- Economics and Econometrics 585
- Statistical and Nonlinear Physics 278
- Finance 217
- Condensed Matter Physics 79
- Management Science and Operations Research 67
Countries citing papers authored by Kaushik Matia
This map shows the geographic impact of Kaushik Matia'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 Kaushik Matia with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kaushik Matia more than expected).
Fields of papers citing papers by Kaushik Matia
This network shows the impact of papers produced by Kaushik Matia. 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 Kaushik Matia. The network helps show where Kaushik Matia may publish in the future.
Co-authorship network of co-authors of Kaushik Matia
This figure shows the co-authorship network connecting the top 25 collaborators of Kaushik Matia. A scholar is included among the top collaborators of Kaushik Matia 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 Kaushik Matia. Kaushik Matia is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 14 | |
| 2 | 17 | |
| 3 | 4 | |
| 4 | 9 | |
| 5 | 27 | |
| 6 | 130 | |
| 7 | Statistical Properties of Business Firms Structure and Growth | 37 |
| 8 | 17 | |
| 9 | 12 | |
| 10 | 296 | |
| 11 | 5 | |
| 12 | 43 | |
| 13 | 12 | |
| 14 | 24 |
About Kaushik Matia
Kaushik Matia is a scholar working on Economics and Econometrics, Finance and Statistical and Nonlinear Physics, having authored 14 papers that have together received 647 indexed citations. Recurring topics across this work include Complex Systems and Time Series Analysis (12 papers), Financial Risk and Volatility Modeling (5 papers) and Firm Innovation and Growth (5 papers). The work is most often cited by research in Statistical and Nonlinear Physics (278 citations), Finance (217 citations) and Economics and Econometrics (585 citations). Kaushik Matia has collaborated with scholars based in United States, Italy and Japan. Frequent co-authors include H. Eugene Stanley, Yosef Ashkenazy, Massimo Riccaboni, Sergey V. Buldyrev, Fabio Pammolli, Kazuko Yamasaki, Dongfeng Fu, Luı́s A. Nunes Amaral, Plamen Ch. Ivanov and Boris Podobnik. Their work appears in journals such as Proceedings of the National Academy of Sciences, Physica A Statistical Mechanics and its Applications and Europhysics Letters (EPL).
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.