Jan Palczewski

893 citations
46 papers · 435 · h-index 11

Impact in

Papers in

    • Stochastic processes and financial applications 26
    • Financial Markets and Investment Strategies 13
    • Financial Risk and Volatility Modeling 5
    • Capital Investment and Risk Analysis 3
    • Economic theories and models 19
    • Complex Systems and Time Series Analysis 10

Jan Palczewski

39 papers receiving 409 citations

Peers

Jan Palczewski
Comparison fields: 5 of 117
  • Finance 125
  • Energy Engineering and Power Technology 16
  • Management Science and Operations Research 58
  • Computational Theory and Mathematics 59
  • Economics and Econometrics 93
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Citations per field
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Citations per year

Countries citing papers authored by Jan Palczewski

Since Specialization
Citations

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

Fields of papers citing papers by Jan Palczewski

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Jan Palczewski, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Jan Palczewski Line = papers co-authored together Jan Palczewski links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 46 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2017113
2 201346
3 202042
4 201932
5 201318
6 201018
7 201516
8 200713
9 201812
10 201610
11 201510
12 201710
13 20218
14 20178
15 20196
16 20156
17 20195
18 20225
19 20135
20 20204

About Jan Palczewski

Jan Palczewski is a scholar working on Finance, Economics and Econometrics, Electrical and Electronic Engineering, Control and Systems Engineering and Computational Theory and Mathematics, having authored 46 papers that have together received 435 indexed citations. Recurring topics across this work include Stochastic processes and financial applications (26 papers), Economic theories and models (19 papers), Financial Markets and Investment Strategies (13 papers), Complex Systems and Time Series Analysis (10 papers), Financial Risk and Volatility Modeling (5 papers), Advanced Queuing Theory Analysis (3 papers), Insurance, Mortality, Demography, Risk Management (3 papers) and Capital Investment and Risk Analysis (3 papers). The work is most often cited by research in Finance (125 citations), Energy Engineering and Power Technology (16 citations), Management Science and Operations Research (58 citations), Computational Theory and Mathematics (59 citations) and Economics and Econometrics (93 citations). Jan Palczewski has collaborated with scholars based in United Kingdom, Poland and Norway. Frequent co-authors include Anna Palczewska, Richard Marchese Robinson, Łukasz Stettner, Andrzej Palczewski, Tim Cockerill, Andrew Pimm, Klaus Reiner Schenk–Hoppé, Edward Barbour, Daniel Neagu and John Moriarty. Their work appears in journals such as European Journal of Operational Research, SIAM Journal on Control and Optimization, Stochastic Processes and their Applications, Journal of Economic Dynamics and Control and Applied Mathematics & Optimization.

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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