Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Modelling Extremal Events
19972.8k citationsPaul Embrechts, Thomas Mikosch et al.profile →
Modelling of extremal events in insurance and finance
Countries citing papers authored by Paul Embrechts
Since
Specialization
Citations
This map shows the geographic impact of Paul Embrechts'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 Paul Embrechts with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Paul Embrechts more than expected).
This network shows the impact of papers produced by Paul Embrechts. 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 Paul Embrechts. The network helps show where Paul Embrechts may publish in the future.
Co-authorship network of co-authors of Paul Embrechts
This figure shows the co-authorship network connecting the top 25 collaborators of Paul Embrechts.
A scholar is included among the top collaborators of Paul Embrechts 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 Paul Embrechts. Paul Embrechts 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.
McNeil, Alexander J., Rüdiger Frey, & Paul Embrechts. (2015). Quantitative Risk Management: Concepts, Techniques and Tools : Concepts, Techniques and Tools. Princeton University Press eBooks.26 indexed citations
Degen, Matthias & Paul Embrechts. (2011). Scaling of High-Quantile Estimators. Journal of Applied Probability. 48(4). 968–983.7 indexed citations
7.
Dias, Alexandra & Paul Embrechts. (2010). Modeling Exchange Rate Dependence Dynamics at Different Time Horizons. SSRN Electronic Journal.1 indexed citations
Dias, Alexandra & Paul Embrechts. (2008). Testing for Structural Changes in Exchange Rates Dependence Beyond Linear Correlation. SSRN Electronic Journal.5 indexed citations
Embrechts, Paul. (2005). Skew-Elliptical Distributions and Their Applications: A Journey Beyond Normality. 100(471). 1099–1100.11 indexed citations
14.
Cairns, Andrew J. G. & Paul Embrechts. (2004). Guidelines to Authors. Astin Bulletin. 34(2). 467–468.1 indexed citations
15.
Dias, Alexandra & Paul Embrechts. (2004). Change-point analysis for dependence structures in finance and insurance. Leicester Research Archive (University of Leicester).34 indexed citations
Bühlmann, Hans, Freddy Delbaen, Paul Embrechts, & Albert N. Shiryaev. (1996). No-arbitrage, change of measure and conditional Esscher transforms. Centrum Wiskunde & Informatica (CWI), the national research institute for mathematics and computer science in the Netherlands. 9(4). 291–317.141 indexed citations
Embrechts, Paul. (1982). Estimates for the probability of ruin with special emphasis on the possibility of large claims. Insurance. 1. 55–72.8 indexed citations
20.
Embrechts, Paul. (1978). On a theorem of E. Lukacs. Proceedings of the American Mathematical Society. 68(3). 292–294.4 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.