László Gillemot

999 total citations
9 papers, 544 citations indexed

About

László Gillemot is a scholar working on Economics and Econometrics, Finance and Management Science and Operations Research. According to data from OpenAlex, László Gillemot has authored 9 papers receiving a total of 544 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Economics and Econometrics, 7 papers in Finance and 1 paper in Management Science and Operations Research. Recurrent topics in László Gillemot's 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). László Gillemot is often cited by papers focused on Complex Systems and Time Series Analysis (8 papers), Financial Risk and Volatility Modeling (5 papers) and Financial Markets and Investment Strategies (3 papers). László Gillemot collaborates with scholars based in United States, Hungary and Italy. László Gillemot's 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 and has published in prestigious journals such as Physical Review Letters, Physica A Statistical Mechanics and its Applications and Quantitative Finance.

In The Last Decade

László Gillemot

9 papers receiving 512 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
László Gillemot United States	7	485	387	104	66	52	9	544
Stacy Williams United Kingdom	8	301 0.6×	186 0.5×	123 1.2×	99 1.5×	23 0.4×	10	413
Mark McDonald United Kingdom	7	282 0.6×	171 0.4×	101 1.0×	99 1.5×	23 0.4×	9	378
Ioane Muni Toke France	6	340 0.7×	194 0.5×	79 0.8×	100 1.5×	23 0.4×	14	432
Szabolcs Mike Hungary	5	303 0.6×	252 0.7×	49 0.5×	33 0.5×	29 0.6×	6	327
Bence Tóth France	10	253 0.5×	202 0.5×	47 0.5×	38 0.6×	37 0.7×	19	320
Michael C. Münnix Germany	8	219 0.5×	142 0.4×	40 0.4×	61 0.9×	25 0.5×	8	264
Claire G. Gilmore United States	15	755 1.6×	558 1.4×	81 0.8×	168 2.5×	29 0.6×	22	882
Austin Gerig United States	8	223 0.5×	211 0.5×	58 0.6×	31 0.5×	16 0.3×	14	285
Kaushik Matia United States	11	585 1.2×	217 0.6×	67 0.6×	278 4.2×	79 1.5×	14	647
Ilija I. Zovko Netherlands	4	272 0.6×	207 0.5×	84 0.8×	40 0.6×	15 0.3×	6	323

Countries citing papers authored by László Gillemot

Since Specialization

Citations

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

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

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9 of 9 papers shown

Lillo, Fabrizio, László Gillemot, & J. Doyne Farmer. (2011). There's more to volatility than volume. Social Science Open Access Repository (GESIS – Leibniz Institute for the Social Sciences). 29 indexed citations

Iori, Giulia, J. Doyne Farmer, Eric Smith, & László Gillemot. (2005). Quantitative Model of Price Diffusion and Market Friction Based on Trading as a Mechanistic Random Process. SSRN Electronic Journal. 2 indexed citations

Gillemot, László, J. Doyne Farmer, & Fabrizio Lillo. (2005). There's More to Volatility than Volume. SSRN Electronic Journal. 13 indexed citations

Farmer, J. Doyne, László Gillemot, Fabrizio Lillo, Szabolcs Mike, & Anindya Sen. (2004). What really causes large price changes?. Quantitative Finance. 4(4). 383–397. 178 indexed citations

Daniels, Marcus, J. Doyne Farmer, László Gillemot, Giulia Iori, & Eric Smith. (2003). Quantitative Model of Price Diffusion and Market Friction Based on Trading as a Mechanistic Random Process. Physical Review Letters. 90(10). 108102–108102. 104 indexed citations

Smith, Eric, J. Doyne Farmer, László Gillemot, & Supriya Krishnamurthy. (2003). Statistical theory of the continuous double auction. Quantitative Finance. 3(6). 481–514. 188 indexed citations

Iori, Giulia, Marcus Daniels, J. Doyne Farmer, et al.. (2003). An analysis of price impact function in order-driven markets. Physica A Statistical Mechanics and its Applications. 324(1-2). 146–151. 18 indexed citations

Gillemot, László, Juuso Töyli, János Kertész, & Kimmo Kaski. (2000). Time-independent models of asset returns revisited. Physica A Statistical Mechanics and its Applications. 282(1-2). 304–324. 11 indexed citations

Gillemot, László. (1966). Die Ermittlung des Zusammenhanges zwischen der wahren Spannung und der Einschnürung an Zugproben. Archiv für das Eisenhüttenwesen. 37(7). 591–598. 1 indexed citations

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.

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