Yasuhiro Omori

10.6k total citations · 1 hit paper
43 papers, 6.6k citations indexed

About

Yasuhiro Omori is a scholar working on Finance, Economics and Econometrics and Statistics and Probability. According to data from OpenAlex, Yasuhiro Omori has authored 43 papers receiving a total of 6.6k indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Finance, 16 papers in Economics and Econometrics and 11 papers in Statistics and Probability. Recurrent topics in Yasuhiro Omori's work include Financial Risk and Volatility Modeling (24 papers), Stochastic processes and financial applications (12 papers) and Insurance, Mortality, Demography, Risk Management (9 papers). Yasuhiro Omori is often cited by papers focused on Financial Risk and Volatility Modeling (24 papers), Stochastic processes and financial applications (12 papers) and Insurance, Mortality, Demography, Risk Management (9 papers). Yasuhiro Omori collaborates with scholars based in Japan, United States and Australia. Yasuhiro Omori's co-authors include S. Kotz, Norman L. Johnson, N. Balakrishnan, Jouchi Nakajima, Neil Shephard, Siddhartha Chib, Toshiaki Watanabe, Richard A. Johnson, Akira Hibiki and Zhengjun Zhang and has published in prestigious journals such as Journal of the American Statistical Association, Biometrika and Journal of Econometrics.

In The Last Decade

Yasuhiro Omori

37 papers receiving 6.1k citations

Hit Papers

align trajectories

What are hit papers?

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.

Continuous Univariate Distributions.

1995 5.9k citations Yasuhiro Omori et al. profile →

Peers

Yasuhiro Omori

SP

SPU

FINAN

EE

AI

N. Balakrishnan Canada

S. Kotz United States

Ali S. Hadi United States

Elvezio Ronchetti Switzerland

Adelchi Azzalini Italy

Michael A. Stephens Canada

Robert Serfling United States

M. C. Jones United Kingdom

Marc G. Genton United States

Richard A. Davis United States

N. Balakrishnan Canada

Yasuhiro Omori

3.3k ×1.2

SP

1.9k ×1.4

SPU

779 ×0.7

FINAN

633 ×0.7

EE

931 ×1.0

AI

Citations per year, relative to Yasuhiro Omori Yasuhiro Omori (= 1×) peers N. Balakrishnan

Countries citing papers authored by Yasuhiro Omori

Since Specialization

Citations

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

Fields of papers citing papers by Yasuhiro Omori

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yasuhiro Omori

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

1.

Chib, Siddhartha, et al.. (2025). Stochastic volatility in mean: Efficient analysis by a generalized mixture sampler. Journal of Econometrics. 105949–105949.

2.

Takahashi, Makoto, et al.. (2023). Stochastic Volatility and Realized Stochastic Volatility Models. 3 indexed citations

3.

Omori, Yasuhiro, et al.. (2023). Dynamic factor, leverage and realized covariances in multivariate stochastic volatility. Econometric Reviews. 42(6). 513–539.

4.

Chu, Amanda M. Y., Yasuhiro Omori, Hing‐yu So, & Mike K. P. So. (2022). A Multivariate Randomized Response Model for Sensitive Binary Data. Econometrics and Statistics. 27. 16–35. 1 indexed citations

5.

Omori, Yasuhiro, Hiroshi Yoshida, Satoshi Hinokuma, et al.. (2019). Enhanced Rh-anchoring on the composite metal phosphate Y_0.33Zr₂(PO₄)₃in three-way catalysis. Catalysis Science & Technology. 9(19). 5447–5455. 8 indexed citations

6.

Omori, Yasuhiro, et al.. (2019). Multivariate Stochastic Volatility Model With Realized Volatilities and Pairwise Realized Correlations. Journal of Business and Economic Statistics. 38(4). 839–855. 7 indexed citations

7.

Nakajima, Jouchi, et al.. (2016). Bayesian modeling of dynamic extreme values: extension of generalized extreme value distributions with latent stochastic processes. Journal of Applied Statistics. 44(7). 1248–1268. 7 indexed citations

8.

Sugawara, Shinya & Yasuhiro Omori. (2016). An Econometric Analysis of Insurance Markets with Separate Identification for Moral Hazard and Selection Problems. Computational Economics. 50(3). 473–502. 2 indexed citations

9.

Omori, Yasuhiro, et al.. (2015). A discrete/continuous choice model on a nonconvex budget set. Econometric Reviews. 37(2). 89–113.

10.

Nakada, Nobuo, Toshihiro Tsuchiyama, Setsuo Takaki, et al.. (2013). Isothermal Transformation in Fe^|^ndash;N Hypereutectoid Alloy. ISIJ International. 53(1). 139–144. 13 indexed citations

11.

Sugawara, Shinya & Yasuhiro Omori. (2011). DUOPOLY IN THE JAPANESE AIRLINE MARKET: BAYESIAN ESTIMATION FOR THE ENTRY GAME*. Japanese Economic Review. 63(3). 310–332. 4 indexed citations

12.

Yamada, S., et al.. (2010). Validation of stepwise refinement with test cases generated from formal specification. 2449–2453.

13.

Omori, Yasuhiro & Toshiaki Watanabe. (2007). Block Sampler and Posterior Mode Estimation for A Nonlinear and Non-Gaussian State-Space Model with Correlated Errors. RePEc: Research Papers in Economics. 2 indexed citations

14.

Nakajima, Jouchi & Yasuhiro Omori. (2007). Leverage, heavy-tails and correlated jumps in stochastic volatility models. RePEc: Research Papers in Economics. 1 indexed citations

15.

Omori, Yasuhiro. (2007). Efficient Gibbs sampler for Bayesian analysis of a sample selection model. Statistics & Probability Letters. 77(12). 1300–1311. 6 indexed citations

16.

Omori, Yasuhiro & Richard A. Johnson. (2006). The Influence of Random Effects on Univariate and Bivariate Discrete Proportional Hazards Models. Communication in Statistics- Theory and Methods. 35(9). 1757–1764.

17.

Omori, Yasuhiro, Siddhartha Chib, Neil Shephard, & Jouchi Nakajima. (2004). Stochastic Volatility with Leverage: Fast Likelihood Inference. Oxford University Research Archive (ORA) (University of Oxford). 11 indexed citations

18.

Johnson, Richard A. & Yasuhiro Omori. (1999). Influence of random effects on bivariate and trivariate survival models. Journal of nonparametric statistics. 11(1-3). 137–159. 1 indexed citations

19.

Omori, Yasuhiro & Richard A. Johnson. (1993). The Influence of Random Effects on the Unconditional Hazard Rate and Survival Functions. Biometrika. 80(4). 910–910. 2 indexed citations

20.

Omori, Yasuhiro, et al.. (1965). Résonance Paramagnétique de l'Ion Mn²⁺ dans les Phosphores Zn (S:Se):Mn.. Journal of the Physical Society of Japan. 20(7). 1120–1131. 18 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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