Makoto Maejima

2.3k citations
86 papers · 1.3k indexed · h-index 21
Topics
Stochastic processes and financial applications (47 papers)Probability and Risk Models (33 papers)Financial Risk and Volatility Modeling (17 papers)

In The Last Decade

Makoto Maejima

82 papers receiving 1.2k citations

Peers

Makoto Maejima
Comparison fields: 5 of 60
  • Finance 790
  • Mathematical Physics 446
  • Economics and Econometrics 335
  • Management Science and Operations Research 288
  • Statistics and Probability 263
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Citations per year

Countries citing papers authored by Makoto Maejima

Since Specialization
Citations

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

Fields of papers citing papers by Makoto Maejima

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Makoto Maejima

This figure shows the co-authorship network connecting the top 25 collaborators of Makoto Maejima. A scholar is included among the top collaborators of Makoto Maejima 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 Makoto Maejima. Makoto Maejima 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
#WorkIndexed citations
1 1
2
SEVERAL FORMS OF STOCHASTIC INTEGRAL REPRESENTATIONS OF GAMMA RANDOM VARIABLES AND RELATED TOPICS
2
3 5
4 16
5 13
6 3
7
Some classes of multivariate infinitely divisible distributions admitting stochastic integral representations
57
8
The Lamperti transformation for self-similar processes : Dedicated to the memory of Stamatis Cambanis)
7
9 40
10 10
11 24
12 17
13 1
14 16
15
SOJOURNS OF MULTIDIMENSIONAL GAUSSIAN PROCESSES WITH DEPENDENT COMPONENTS
2
16
A GENERALIZED BLACKWELL RENEWAL THEOREM
5
17
A NOTE ON THE NONUNIFORM RATE OF CONVERGENCE TO NORMALITY
1
18
A NON-UNIFORM RATE OF CONVERGENCE IN A LOCAL LIMIT THEOREM CONCERNING VARIABLES IN THE DOMAIN OF NORMAL ATTRACTION OF A STABLE LAW
1
19
NON-UNIFORM ESTIMATES IN THE CENTRAL LIMIT THEOREM
6
20
A NON-UNIFORM ESTIMATE IN THE LOCAL LIMIT THEOREM FOR DENSITIES, I
2

About Makoto Maejima

Makoto Maejima is a scholar working on Finance, Mathematical Physics and Statistics and Probability, having authored 86 papers that have together received 1.3k indexed citations. Recurring topics across this work include Stochastic processes and financial applications (47 papers), Probability and Risk Models (33 papers) and Financial Risk and Volatility Modeling (17 papers). The work is most often cited by research in Finance (790 citations), Mathematical Physics (446 citations) and Statistics and Probability (263 citations). Makoto Maejima has collaborated with scholars based in Japan, United States and United Kingdom. Frequent co-authors include Hideyuki Kawaguchi, Patrick Cheridito, Ken‐iti Sato, Paul Embrechts, Ciprian A. Tudor, Yuji Kasahara, Ole E. Barndorff–Nielsen, J. David Mason, J. Rosiński and Stamatis Cambanis. Their work appears in journals such as Lecture notes in mathematics, Pacific Journal of Mathematics and The Annals of Probability.

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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