John P. Nolan

3.3k total citations
61 papers, 1.8k citations indexed

About

John P. Nolan is a scholar working on Finance, Economics and Econometrics and Statistics and Probability. According to data from OpenAlex, John P. Nolan has authored 61 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Finance, 17 papers in Economics and Econometrics and 14 papers in Statistics and Probability. Recurrent topics in John P. Nolan's work include Financial Risk and Volatility Modeling (22 papers), Complex Systems and Time Series Analysis (14 papers) and Stochastic processes and financial applications (6 papers). John P. Nolan is often cited by papers focused on Financial Risk and Volatility Modeling (22 papers), Complex Systems and Time Series Analysis (14 papers) and Stochastic processes and financial applications (6 papers). John P. Nolan collaborates with scholars based in United States, Greece and United Kingdom. John P. Nolan's co-authors include Anna K. Panorska, Balram S. Rajput, Hippolyte Fofack, J. Huston McCulloch, William D. Shannon, Daniel E. Weeks, T. Byczkowski, Joseph D. Terwilliger, G. Mark Lathrop and Gary A. Chase and has published in prestigious journals such as SHILAP Revista de lepidopterología, Gastroenterology and The Journal of Physical Chemistry B.

In The Last Decade

John P. Nolan

58 papers receiving 1.7k citations

Peers

John P. Nolan
Comparison fields: 5 of 154
  • Finance 574
  • Economics and Econometrics 377
  • Statistics and Probability 348
  • Artificial Intelligence 213
  • Electrical and Electronic Engineering 170
Replace Krzysztof Podgórski with:
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John E. Angus United States
Georges Oppenheim France
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В. М. Золотарев Russia
Michael Sørensen Denmark
H. L. Gray United States
Guy P. Nason United Kingdom
Gerhard Winkler Austria
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Citations per field, relative to John P. Nolan
John P. Nolan · 1×
Citations per year, relative to John P. Nolan
John P. Nolan · 1×

Countries citing papers authored by John P. Nolan

Since Specialization
Citations

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

Fields of papers citing papers by John P. Nolan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by John P. Nolan. 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 John P. Nolan. The network helps show where John P. Nolan may publish in the future.

Co-authorship network of co-authors of John P. Nolan

This figure shows the co-authorship network connecting the top 25 collaborators of John P. Nolan. A scholar is included among the top collaborators of John P. Nolan 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 John P. Nolan. John P. Nolan 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
# Work Indexed citations
1 2
2 0
3 1
4 5
5 3
6 2
7 9
8 2
9 21
10 3
11 5
12 13
13 1
14
Stable Distributions in Mathematica
17
15 55
16 21
17 41
18
Univariate stable distributions: parameterizations and software
8
19
Multivariate stable distributions: approximation, estimation, simulation and identification
25
20 111

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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