Muneya Matsui

425 total citations
30 papers, 228 citations indexed

About

Muneya Matsui is a scholar working on Finance, Economics and Econometrics and Management Science and Operations Research. According to data from OpenAlex, Muneya Matsui has authored 30 papers receiving a total of 228 indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Finance, 11 papers in Economics and Econometrics and 10 papers in Management Science and Operations Research. Recurrent topics in Muneya Matsui's work include Financial Risk and Volatility Modeling (18 papers), Stochastic processes and financial applications (14 papers) and Probability and Risk Models (9 papers). Muneya Matsui is often cited by papers focused on Financial Risk and Volatility Modeling (18 papers), Stochastic processes and financial applications (14 papers) and Probability and Risk Models (9 papers). Muneya Matsui collaborates with scholars based in Japan, Denmark and Poland. Muneya Matsui's co-authors include Akimichi Takemura, Thomas Mikosch, Narn-Rueih Shieh, Richard A. Davis, Claudia Klüppelberg, Makoto Maejima, Gennady Samorodnitsky, Ewa Damek, Tomasz Rolski and Toshiro Watanabe and has published in prestigious journals such as Journal of Mathematical Analysis and Applications, Economic Modelling and Journal of Applied Probability.

In The Last Decade

Muneya Matsui

27 papers receiving 216 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Muneya Matsui Japan	9	129	93	72	40	36	30	228
Li‐Hsien Sun Taiwan	8	174 1.3×	51 0.5×	91 1.3×	43 1.1×	20 0.6×	19	259
Victor de la Peña United States	5	109 0.8×	51 0.5×	85 1.2×	41 1.0×	30 0.8×	17	206
Areski Cousin France	9	238 1.8×	66 0.7×	78 1.1×	105 2.6×	30 0.8×	26	333
Nestor Parolya Sweden	11	143 1.1×	80 0.9×	65 0.9×	90 2.3×	25 0.7×	23	228
Jaya P. N. Bishwal United States	8	199 1.5×	117 1.3×	33 0.5×	55 1.4×	37 1.0×	33	298
Tina Marquardt Germany	6	220 1.7×	56 0.6×	88 1.2×	44 1.1×	10 0.3×	9	258
Valentine Genon-Catalot France	7	205 1.6×	112 1.2×	44 0.6×	13 0.3×	48 1.3×	7	252
Martin Wendler Germany	9	91 0.7×	113 1.2×	59 0.8×	30 0.8×	35 1.0×	29	256
Igor Cialenco United States	10	194 1.5×	30 0.3×	59 0.8×	48 1.2×	21 0.6×	30	272
Craig A. Friedman United States	7	217 1.7×	33 0.4×	71 1.0×	60 1.5×	14 0.4×	38	277

Countries citing papers authored by Muneya Matsui

Since Specialization

Citations

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

Fields of papers citing papers by Muneya Matsui

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Muneya Matsui

This figure shows the co-authorship network connecting the top 25 collaborators of Muneya Matsui. A scholar is included among the top collaborators of Muneya Matsui 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 Muneya Matsui. Muneya Matsui is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Matsui, Muneya, Thomas Mikosch, & Olivier Wintenberger. (2025). Self-normalized partial sums of heavy-tailed time series. Stochastic Processes and their Applications. 190. 104729–104729.

Matsui, Muneya & Toshiro Watanabe. (2024). Convolution closure properties of subexponential densities. Journal of Mathematical Analysis and Applications. 545(1). 129158–129158.

Matsui, Muneya. (2023). Subexponentialiy of densities of infinitely divisible distributions. Electronic Journal of Probability. 28(none). 1 indexed citations

Matsui, Muneya, et al.. (2021). CHARACTERIZATION OF THE TAIL BEHAVIOR OF A CLASS OF BEKK PROCESSES: A STOCHASTIC RECURRENCE EQUATION APPROACH. Econometric Theory. 38(1). 1–34. 2 indexed citations

Matsui, Muneya. (2020). Asymptotics of maximum likelihood estimation for stable law with continuous parameterization. Communication in Statistics- Theory and Methods. 50(15). 3695–3712. 2 indexed citations

Matsui, Muneya, et al.. (2020). Tail indices for $$\mathbf{A}\mathbf{X}+\mathbf{B}$$ Recursion with Triangular Matrices. Journal of Theoretical Probability. 34(4). 1831–1869. 1 indexed citations

Damek, Ewa, et al.. (2019). Componentwise different tail solutions for bivariate stochastic recurrence equations with application to ${\rm GARCH}(1,1)$ processes. Colloquium Mathematicum. 155(2). 227–254. 4 indexed citations

Matsui, Muneya, Thomas Mikosch, & Gennady Samorodnitsky. (2018). Distance covariance for stochastic processes. Research at the University of Copenhagen (University of Copenhagen). 37(2). 355–372. 3 indexed citations

Davis, Richard A., et al.. (2018). Applications of distance correlation to time series. Bernoulli. 24(4A). 33 indexed citations

10.

Matsui, Muneya. (2016). Prediction of Components in Random Sums. Methodology And Computing In Applied Probability. 19(2). 573–587. 1 indexed citations

11.

Klüppelberg, Claudia & Muneya Matsui. (2015). Generalized fractional Lévy processes with fractional Brownian motion limit. Advances in Applied Probability. 47(4). 1108–1131. 6 indexed citations

12.

Matsui, Muneya, et al.. (2015). Macroeconomic dynamics in a model with heterogeneous wage contracts. Economic Modelling. 49. 72–80. 3 indexed citations

13.

Matsui, Muneya & Narn-Rueih Shieh. (2014). The Lamperti Transforms of Self-Similar Gaussian Processes and Their Exponentials. Stochastic Models. 30(1). 68–98. 1 indexed citations

14.

Matsui, Muneya. (2013). Prediction in a Poisson cluster model with multiple cluster processes. Scandinavian Actuarial Journal. 2015(1). 1–31. 8 indexed citations

15.

Matsui, Muneya. (2013). Prediction in a non-homogeneous Poisson cluster model. Insurance Mathematics and Economics. 55. 10–17. 5 indexed citations

16.

Matsui, Muneya & Thomas Mikosch. (2010). Prediction in a Poisson cluster model. Journal of Applied Probability. 47(2). 350–366. 10 indexed citations

17.

Matsui, Muneya & Thomas Mikosch. (2010). Prediction in a Poisson cluster model. Journal of Applied Probability. 47(2). 350–366. 2 indexed citations

18.

Matsui, Muneya & Akimichi Takemura. (2008). Integral representations of one-dimensional projections for multivariate stable densities. Journal of Multivariate Analysis. 100(3). 334–344. 4 indexed citations

19.

Matsui, Muneya & Akimichi Takemura. (2006). Some Improvements in Numerical Evaluation of Symmetric Stable Density and Its Derivatives. Communication in Statistics- Theory and Methods. 35(1). 149–172. 28 indexed citations

20.

Matsui, Muneya & Akimichi Takemura. (2005). Empirical characteristic function approach to goodness-of-fit tests for the Cauchy distribution with parameters estimated by MLE or EISE. Annals of the Institute of Statistical Mathematics. 57(1). 183–199. 36 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.

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