Daniel Ševčovič

983 total citations
58 papers, 527 citations indexed

About

Daniel Ševčovič is a scholar working on Finance, Computational Theory and Mathematics and Applied Mathematics. According to data from OpenAlex, Daniel Ševčovič has authored 58 papers receiving a total of 527 indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Finance, 13 papers in Computational Theory and Mathematics and 13 papers in Applied Mathematics. Recurrent topics in Daniel Ševčovič's work include Stochastic processes and financial applications (25 papers), Advanced Mathematical Modeling in Engineering (9 papers) and Advanced Numerical Analysis Techniques (9 papers). Daniel Ševčovič is often cited by papers focused on Stochastic processes and financial applications (25 papers), Advanced Mathematical Modeling in Engineering (9 papers) and Advanced Numerical Analysis Techniques (9 papers). Daniel Ševčovič collaborates with scholars based in Slovakia, Russia and Czechia. Daniel Ševčovič's co-authors include Karol Mikula, Carlos Vázquez, Peter Sarkoci, Michal Beneš, Miroslav Kolář, Naoyuki Ishimura, Subhasis Chaudhuri, Sumantra Dutta Roy, P. Brunovský and Michael Günther and has published in prestigious journals such as SHILAP Revista de lepidopterología, Physica D Nonlinear Phenomena and SIAM Journal on Scientific Computing.

In The Last Decade

Daniel Ševčovič

48 papers receiving 454 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Daniel Ševčovič Slovakia 13 199 161 104 100 85 58 527
Roberto Ferretti Italy 13 348 1.7× 69 0.4× 110 1.1× 202 2.0× 107 1.3× 61 724
Antoine Lejay France 16 67 0.3× 383 2.4× 90 0.9× 64 0.6× 201 2.4× 70 705
Iosif Pinelis United States 16 81 0.4× 87 0.5× 344 3.3× 98 1.0× 51 0.6× 66 796
Søren Jensen United States 14 144 0.7× 276 1.7× 45 0.4× 27 0.3× 74 0.9× 38 707
Sylvain Maire France 10 36 0.2× 56 0.3× 27 0.3× 67 0.7× 74 0.9× 28 251
Raphael Kruse Germany 11 148 0.7× 307 1.9× 60 0.6× 84 0.8× 110 1.3× 18 434
Lina von Sydow Sweden 11 84 0.4× 210 1.3× 19 0.2× 143 1.4× 47 0.6× 26 386
Z. Ciesielski Poland 14 96 0.5× 188 1.2× 399 3.8× 107 1.1× 96 1.1× 37 793
Stefania Corsaro Italy 8 129 0.6× 59 0.4× 9 0.1× 38 0.4× 39 0.5× 21 273
Peter Schwartz United States 12 220 1.1× 9 0.1× 45 0.4× 21 0.2× 37 0.4× 19 553

Countries citing papers authored by Daniel Ševčovič

Since Specialization
Citations

This map shows the geographic impact of Daniel Ševčovič'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 Daniel Ševčovič with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Ševčovič more than expected).

Fields of papers citing papers by Daniel Ševčovič

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel Ševčovič. 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 Daniel Ševčovič. The network helps show where Daniel Ševčovič may publish in the future.

Co-authorship network of co-authors of Daniel Ševčovič

This figure shows the co-authorship network connecting the top 25 collaborators of Daniel Ševčovič. A scholar is included among the top collaborators of Daniel Ševčovič 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 Daniel Ševčovič. Daniel Ševčovič is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Ševčovič, Daniel, et al.. (2023). On the Moore-Penrose pseudo-inversion of block symmetric matrices and its application in the graph theory. Linear Algebra and its Applications. 673. 280–303. 1 indexed citations
2.
3.
Grossinho, Maria do Rosário, et al.. (2020). Pricing American call options using the Black–Scholes equation with a nonlinear volatility function. The Journal of Computational Finance. 1 indexed citations
4.
Ševčovič, Daniel, et al.. (2019). PDE models for American options with counterparty risk and two stochastic factors: Mathematical analysis and numerical solution. Computers & Mathematics with Applications. 79(5). 1525–1542. 10 indexed citations
5.
Ševčovič, Daniel, et al.. (2019). Mathematical analysis of a nonlinear PDE model for European options with counterparty risk. Comptes Rendus Mathématique. 357(3). 252–257. 3 indexed citations
6.
Ševčovič, Daniel, et al.. (2018). Total value adjustment for European options with two stochastic factors. Mathematical model, analysis and numerical simulation. Computers & Mathematics with Applications. 76(4). 725–740. 15 indexed citations
7.
Ševčovič, Daniel, et al.. (2018). On construction of upper and lower bounds for the HOMO-LUMO spectral gap. Numerical Algebra Control and Optimization. 9(1). 53–69. 2 indexed citations
8.
Ševčovič, Daniel, et al.. (2017). On a construction of integrally invertible graphs and their spectral properties. Linear Algebra and its Applications. 532. 512–533. 2 indexed citations
9.
Kolář, Miroslav, Michal Beneš, & Daniel Ševčovič. (2016). Computational analysis of the conserved curvature driven flow for open curves in the plane. Mathematics and Computers in Simulation. 126. 1–13. 4 indexed citations
10.
Ševčovič, Daniel, et al.. (2014). Solution to the inverse Wulff problem by means of the enhanced semidefinite relaxation method. Journal of Inverse and Ill-Posed Problems. 23(3). 263–285. 1 indexed citations
11.
Ishimura, Naoyuki & Daniel Ševčovič. (2012). On traveling wave solutions to a Hamilton–Jacobi–Bellman equation with inequality constraints. Japan Journal of Industrial and Applied Mathematics. 30(1). 51–67. 4 indexed citations
12.
Ševčovič, Daniel, et al.. (2010). Dynamic stochastic accumulation model with application to pension savings management. SHILAP Revista de lepidopterología. 1 indexed citations
13.
Ševčovič, Daniel, et al.. (2009). SENSITIVITY ANALYSIS FOR A DYNAMIC STOCHASTIC ACCUMULATION MODEL FOR OPTIMAL PENSION SAVINGS MANAGEMENT. SSRN Electronic Journal. 57(8). 1 indexed citations
14.
Ševčovič, Daniel, et al.. (2009). On the singular limit of solutions to the Cox-Ingersoll-Ross interest rate model with stochastic volatility. Kybernetika. 45(4). 670–680. 3 indexed citations
15.
16.
Ševčovič, Daniel, et al.. (2008). On the Singular Limit of Solutions to the Cox-Intersoll-Ross Interest Rate Model with Stochastic Volatility. SSRN Electronic Journal. 1 indexed citations
17.
Ševčovič, Daniel, et al.. (2006). Dynamic and Static Strategies for the Funded Pillar of the Slovak Pension System. SSRN Electronic Journal.
18.
Mikula, Karol & Daniel Ševčovič. (2005). Evolution of curves on a surface driven by the geodesic curvature and external force. Applicable Analysis. 85(4). 345–362. 27 indexed citations
19.
Ševčovič, Daniel. (1994). Limiting behaviour of invariant manifolds for a system of singularly perturbed evolution equations. Mathematical Methods in the Applied Sciences. 17(8). 643–666. 1 indexed citations
20.
Ševčovič, Daniel. (1990). Existence and limiting behaviour for damped nonlinear evolution equations with nonlocal terms. Commentationes Mathematicae Universitatis Carolinae. 31(2). 283–293. 7 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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