Rob Kaas

2.9k citations
35 papers · 1.8k · h-index 19

Impact in

Papers in

Rob Kaas

35 papers receiving 1.7k citations

Peers

Rob Kaas
Comparison fields: 5 of 73
  • Management Science and Operations Research 1.3k
  • Finance 797
  • Demography 633
  • Statistics and Probability 423
  • General Decision Sciences 81
Replace Hans Bühlmann with:
Hans Bühlmann Switzerland
R. Kaas Netherlands
Harry H. Panjer Canada
Ruodu Wang Canada
Larry Y. Tzeng Taiwan
Ričardas Zitikis Canada
Virginia R. Young United States
Patrick Cheridito Switzerland
Steven Vanduffel Belgium
Dirk Tasche Germany
Rob Kaas relative to Hans Bühlmann Switzerland Hans Bühlmann's profile →
Citations per field
00.5×1.5×
Hans Bühlmann · 1×
Citations per year

Countries citing papers authored by Rob Kaas

Since Specialization
Citations

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

Fields of papers citing papers by Rob Kaas

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 19 scholars most cited alongside Rob Kaas, 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 Rob Kaas Line = papers co-authored together Rob Kaas links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 35 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Actuarial Theory for Dependent Risks: Measures, Orders and Models
2005351
2 2008348
3 2002174
4 2000146
5 1987129
6 2003100
7 200579
8 200652
9 200446
10 201039
11 200935
12 200333
13 199730
14 200528
15 200324
16
Solvency capital, risk measures and comonotonicity: a review
200424
17 200221
18 201119
19
Capital requirements, risk measures and comonotonicity
200418
20 201018

About Rob Kaas

Rob Kaas is a scholar working on Management Science and Operations Research, Finance, Demography, Economics and Econometrics and Artificial Intelligence, having authored 35 papers that have together received 1.8k indexed citations. Recurring topics across this work include Risk and Portfolio Optimization (19 papers), Probability and Risk Models (18 papers), Insurance, Mortality, Demography, Risk Management (15 papers), Insurance and Financial Risk Management (10 papers), Stochastic processes and financial applications (10 papers), Financial Risk and Volatility Modeling (6 papers), Decision-Making and Behavioral Economics (3 papers) and Stochastic processes and statistical mechanics (3 papers). The work is most often cited by research in Management Science and Operations Research (1.3k citations), Finance (797 citations), Demography (633 citations), Statistics and Probability (423 citations) and General Decision Sciences (81 citations). Rob Kaas has collaborated with scholars based in Netherlands, Belgium and United States. Frequent co-authors include Marc Goovaerts, Jan Dhaene, Michel Denuit, Qihe Tang, Roger J. A. Laeven, Hans U. Gerber, David Vyncke, Raluca Vernic, Roger B. Nelsen and Steven Vanduffel. Their work appears in journals such as Insurance Mathematics and Economics, Astin Bulletin, North American Actuarial Journal, Scandinavian Actuarial Journal and Operations Research.

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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