Jun‐ya Gotoh

1.1k total citations
35 papers, 669 citations indexed

About

Jun‐ya Gotoh is a scholar working on Management Science and Operations Research, Finance and Statistics and Probability. According to data from OpenAlex, Jun‐ya Gotoh has authored 35 papers receiving a total of 669 indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Management Science and Operations Research, 12 papers in Finance and 8 papers in Statistics and Probability. Recurrent topics in Jun‐ya Gotoh's work include Risk and Portfolio Optimization (21 papers), Stochastic processes and financial applications (12 papers) and Advanced Optimization Algorithms Research (6 papers). Jun‐ya Gotoh is often cited by papers focused on Risk and Portfolio Optimization (21 papers), Stochastic processes and financial applications (12 papers) and Advanced Optimization Algorithms Research (6 papers). Jun‐ya Gotoh collaborates with scholars based in Japan, Canada and United States. Jun‐ya Gotoh's co-authors include Yuichi Takano, Akiko Takeda, Hiroshi Konno, Michael Jong Kim, Andrew E. B. Lim, Stan Uryasev, Ushio Sumita, Hui Jin, Yoshitsugu Yamamoto and Takeaki Uno and has published in prestigious journals such as Management Science, European Journal of Operational Research and Expert Systems with Applications.

In The Last Decade

Jun‐ya Gotoh

32 papers receiving 635 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Jun‐ya Gotoh Japan	13	323	171	165	89	87	35	669
Wai-Ki Ching Hong Kong	15	156 0.5×	198 1.2×	205 1.2×	155 1.7×	24 0.3×	80	838
Alexei A. Gaivoronski Norway	14	535 1.7×	292 1.7×	94 0.6×	38 0.4×	34 0.4×	59	895
C. Lucas United Kingdom	15	485 1.5×	200 1.2×	169 1.0×	105 1.2×	40 0.5×	35	880
Luis F. Zuluaga United States	15	159 0.5×	78 0.5×	53 0.3×	29 0.3×	133 1.5×	47	703
José H. Dulá United States	17	528 1.6×	52 0.3×	42 0.3×	36 0.4×	17 0.2×	40	797
Maziar Salahi Iran	12	302 0.9×	50 0.3×	43 0.3×	23 0.3×	190 2.2×	106	605
Wanmo Kang South Korea	10	133 0.4×	191 1.1×	86 0.5×	27 0.3×	29 0.3×	35	449
Jianjun Gao China	15	380 1.2×	307 1.8×	26 0.2×	11 0.1×	61 0.7×	66	692
A. P. Korostelev United States	13	162 0.5×	98 0.6×	26 0.2×	23 0.3×	28 0.3×	38	698

Countries citing papers authored by Jun‐ya Gotoh

Since Specialization

Citations

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

Fields of papers citing papers by Jun‐ya Gotoh

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jun‐ya Gotoh. 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 Jun‐ya Gotoh. The network helps show where Jun‐ya Gotoh may publish in the future.

Co-authorship network of co-authors of Jun‐ya Gotoh

This figure shows the co-authorship network connecting the top 25 collaborators of Jun‐ya Gotoh. A scholar is included among the top collaborators of Jun‐ya Gotoh 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 Jun‐ya Gotoh. Jun‐ya Gotoh 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

Gotoh, Jun‐ya, et al.. (2023). Exact penalty method for knot selection of B-spline regression. Japan Journal of Industrial and Applied Mathematics. 41(2). 1033–1059.

Gotoh, Jun‐ya, et al.. (2020). On the superiority of PGMs to PDCAs in nonsmooth nonconvex sparse regression. arXiv (Cornell University). 5 indexed citations

Gotoh, Jun‐ya, et al.. (2018). Peer-To-Peer Lending: Classification in the Loan Application Process. Risks. 6(4). 129–129. 4 indexed citations

Gotoh, Jun‐ya, Michael Jong Kim, & Andrew E. B. Lim. (2018). Robust empirical optimization is almost the same as mean–variance optimization. Operations Research Letters. 46(4). 448–452. 42 indexed citations

Gotoh, Jun‐ya & Stan Uryasev. (2015). Two pairs of families of polyhedral norms versus $$\ell _p$$ ℓ p -norms: proximity and applications in optimization. Mathematical Programming. 156(1-2). 391–431. 14 indexed citations

Takano, Yuichi & Jun‐ya Gotoh. (2013). Multi-period portfolio selection using kernel-based control policy with dimensionality reduction. Expert Systems with Applications. 41(8). 3901–3914. 16 indexed citations

Gotoh, Jun‐ya, et al.. (2013). Robust portfolio techniques for mitigating the fragility of CVaR minimization and generalization to coherent risk measures. Quantitative Finance. 13(10). 1621–1635. 29 indexed citations

Takano, Yuichi & Jun‐ya Gotoh. (2011). A NONLINEAR CONTROL POLICY USING KERNEL METHOD FOR DYNAMIC ASSET ALLOCATION(<Special Issue>SCOPE (Seminar on Computation and OPtimization for new Extensions)). Journal of the Operations Research Society of Japan. 54(4). 201–218. 3 indexed citations

Gotoh, Jun‐ya & Akiko Takeda. (2011). On the role of norm constraints in portfolio selection. Computational Management Science. 8(4). 323–353. 41 indexed citations

10.

Takano, Yuichi & Jun‐ya Gotoh. (2011). A NONLINEAR CONTROL POLICY USING KERNEL METHOD FOR DYNAMIC ASSET ALLOCATION. 4 indexed citations

11.

Takano, Yuichi & Jun‐ya Gotoh. (2010). Constant Rebalanced Portfolio Optimization Under Nonlinear Transaction Costs. Asia-Pacific Financial Markets. 18(2). 191–211. 9 indexed citations

12.

Gotoh, Jun‐ya & Akiko Takeda. (2009). On the Role of the Norm Constraint in Portfolio Selection. 1 indexed citations

13.

Gotoh, Jun‐ya & Akiko Takeda. (2006). Conditional Minimum Volume Ellipsoid with Applications to Subset Selection for MVE Estimator and Multiclass Discrimination. Terrestrial Environment Research Center (University of Tsukuba). 1 indexed citations

14.

Gotoh, Jun‐ya & Hiroshi Konno. (2005). Minimal Ellipsoid Circumscribing a Polytope Defined by a System of Linear Inequalities. Journal of Global Optimization. 34(1). 1–14. 2 indexed citations

15.

Gotoh, Jun‐ya & Akiko Takeda. (2004). A linear classification model based on conditional geometric score. Terrestrial Environment Research Center (University of Tsukuba). 17 indexed citations

16.

Sumita, Ushio, Jun‐ya Gotoh, & Hui Jin. (2003). Numerical exploration of dynamic behavior of the ornstein-uhlenbeck process via ehrenfest process approximation. Terrestrial Environment Research Center (University of Tsukuba). 2004. 194–195. 6 indexed citations

17.

Konno, Hiroshi, et al.. (2002). A cutting plane algorithm for semi-definite programming problems with applications to failure discriminant analysis. Journal of Computational and Applied Mathematics. 146(1). 141–154. 8 indexed citations

18.

Gotoh, Jun‐ya & Hiroshi Konno. (2002). Bounding Option Prices by Semidefinite Programming: A Cutting Plane Algorithm. Management Science. 48(5). 665–678. 18 indexed citations

19.

Gotoh, Jun‐ya & Hiroshi Konno. (2001). Maximization of the Ratio of Two Convex Quadratic Functions over a Polytope. Computational Optimization and Applications. 20(1). 43–60. 42 indexed citations

20.

Gotoh, Jun‐ya & Hiroshi Konno. (2000). Third Degree Stochastic Dominance and Mean-Risk Analysis. Management Science. 46(2). 289–301. 48 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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