László Gillemot
- Economics and Econometrics top 2%
- Finance top 2%
- Management Science and Operations Research top 5%
- Statistical and Nonlinear Physics top 10%
- Condensed Matter Physics
- Co-authors
- J. Doyne FarmerEric SmithSupriya KrishnamurthyFabrizio LilloAnindya SenSzabolcs MikeGiulia IoriMarcus Daniels
- Topics
- Complex Systems and Time Series Analysis (8 papers)Financial Risk and Volatility Modeling (5 papers)Financial Markets and Investment Strategies (3 papers)
- Journals
- Physical Review LettersPhysica A Statistical Mechanics and its ApplicationsQuantitative Finance
- Partner nations
- United StatesHungaryItaly
In The Last Decade
László Gillemot
9 papers receiving 512 citations
Peers
Comparison fields: 5 of 38
- Economics and Econometrics 485
- Finance 387
- Management Science and Operations Research 104
- Statistical and Nonlinear Physics 66
- Condensed Matter Physics 52
Countries citing papers authored by László Gillemot
This map shows the geographic impact of László Gillemot'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 László Gillemot with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites László Gillemot more than expected).
Fields of papers citing papers by László Gillemot
This network shows the impact of papers produced by László Gillemot. 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 László Gillemot. The network helps show where László Gillemot may publish in the future.
Co-authorship network of co-authors of László Gillemot
This figure shows the co-authorship network connecting the top 25 collaborators of László Gillemot. A scholar is included among the top collaborators of László Gillemot 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 László Gillemot. László Gillemot is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 29 | |
| 2 | Quantitative Model of Price Diffusion and Market Friction Based on Trading as a Mechanistic Random Process | 2 |
| 3 | 13 | |
| 4 | 178 | |
| 5 | 104 | |
| 6 | 188 | |
| 7 | 18 | |
| 8 | 11 | |
| 9 | 1 |
About László Gillemot
László Gillemot is a scholar working on Finance, Economics and Econometrics and Management Science and Operations Research, having authored 9 papers that have together received 544 indexed citations. Recurring topics across this work include Complex Systems and Time Series Analysis (8 papers), Financial Risk and Volatility Modeling (5 papers) and Financial Markets and Investment Strategies (3 papers). The work is most often cited by research in Finance (387 citations), Economics and Econometrics (485 citations) and Management Science and Operations Research (104 citations). László Gillemot has collaborated with scholars based in United States, Hungary and Italy. Frequent co-authors include J. Doyne Farmer, Eric Smith, Supriya Krishnamurthy, Fabrizio Lillo, Anindya Sen, Szabolcs Mike, Giulia Iori, Marcus Daniels, János Kertész and Kimmo Kaski. Their work appears in journals such as Physical Review Letters, Physica A Statistical Mechanics and its Applications and Quantitative Finance.
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.