Shiraishi, Hiroshi

写真a

Affiliation

Faculty of Science and Technology, Department of Mathematics ( Yagami )

Position

Professor

E-mail Address

E-mail address

Related Websites

External Links
Scopus Paper Info  
Paper Count: 16 Citation Count: 39 h-index: 3

Click to view the Scopus page. The data was downloaded from Scopus API in May 17, 2026, via http://api.elsevier.com and http://www.scopus.com .

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Career 【 Display / hide 】

  • 1998.04
    -
    2000.01

    GE Capital Edison Life Insurance Company

  • 2000.02
    -
    2005.03

    Prudential Life Insurance Co,. Ltd.

  • 2005.04
    -
    2007.03

    Hannover Re Services Japan

  • 2007.04
    -
    2008.03

    Waseda University, Department of Applied Mathematics School of Fundamental Science and Engineering, Research associate

  • 2008.04
    -
    2009.03

    Waseda University, Department of Applied Mathematics School of Fundamental Science and Engineering, Assistant Professor

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Academic Background 【 Display / hide 】

  • 1994.04
    -
    1998.03

    Waseda University, School of Sciences, Department of Mathematics

    University, Graduated

  • 2002.04
    -
    2004.03

    Waseda University, School of Sciences, Department of Mathematics

    Graduate School, Completed, Master's course

  • 2004.04
    -
    2007.03

    Waseda University, School of Sciences, Department of Mathematics

    Graduate School, Withdrawal after completion of doctoral course requirements, Doctoral course

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Academic Degrees 【 Display / hide 】

  • 博士（理学）, Waseda University, 2007.10

    Statistical Estimation of Optimal Portfolios for Dependent Returns of Assets

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Licenses and Qualifications 【 Display / hide 】

  • Fellow of Institute of Actuaries Japan (FIAJ), 2007.02

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Research Areas 【 Display / hide 】

  • Informatics / Statistical science

  • Humanities & Social Sciences / Money and finance

  • Humanities & Social Sciences / Economic statistics

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Research Keywords 【 Display / hide 】

  • Statistical Estimation

  • Asymptotic Theory

  • Point Process

  • actuarial science

  • portfolio

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Research Themes 【 Display / hide 】

  • Modeling of Time Series Data using Random Forests, 

    2021.04
    -
    Present

  • Statistical Estimation for discrete observed discritized locally stationary Hawkes process, 

    2018.02
    -
    Present

  • Statistical Estimation of Optimal Dividend Barrier in Insurance Mathematics, 

    2014.04
    -
    Present

  • Asymptotic Property of Statistics for Time Series Data, 

    2005
    -
    Present

  • Optimal Portfolio Selection Problem, 

    2005
    -
    Present

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Books 【 Display / hide 】

  • Semiparametric Estimation of Optimal Dividend Barrier for Spectrally Negative Lévy Process

    Shimizu Y., Shiraishi H., Research Papers in Statistical Inference for Time Series and Related Models: Essays in Honor of Masanobu Taniguchi, 2023.01

    　View Summary

    We discuss a statistical estimation problem of an optimal dividend barrier when the surplus process follows a Lévy insurance risk process. The optimal dividend barrier is defined as the level of the barrier that maximizes the expectation of the present value of all dividend payments until ruin. In this paper, an estimator of the expected present value of all dividend payments is defined based on “quasi-process” in which sample paths are generated by shuffling increments of a sample path of the Lévy insurance risk process. The consistency of the optimal dividend barrier estimator is shown. Moreover, our approach is examined numerically in the case of the compound Poisson risk model perturbed by diffusion.

  • 時系列データ解析

    Hiroshi Shiraishi, 森北出版, 2022.02,  Page： 248

  • Statistical Portfolio Estimation

    Taniguchi M, Shiraishi H, Hirukawa J, Solvang K H, Yamashita T, Chapman and Hall/CRC, 2017.08,  Page： 377

    Scope: 3章、4章、8章の一部

    　View Summary

    The composition of portfolios is one of the most fundamental and important methods in financial engineering, used to control the risk of investments. This book provides a comprehensive overview of statistical inference for portfolios and their various applications. A variety of asset processes are introduced, including non-Gaussian stationary processes, nonlinear processes, non-stationary processes, and the book provides a framework for statistical inference using local asymptotic normality (LAN). The approach is generalized for portfolio estimation, so that many important problems can be covered.

    This book can primarily be used as a reference by researchers from statistics, mathematics, finance, econometrics, and genomics. It can also be used as a textbook by senior undergraduate and graduate students in these fields.

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Papers 【 Display / hide 】

  • Sparse estimators for multivariate integer-valued autoregressive models with applications to inference for Hawkes processes

    Fujimori K., Shiraishi H., Hirukawa J., Fokianos K.

    Stochastic Processes and their Applications 198 2026.08

    ISSN  03044149

    　View Summary

    We investigate sparse and low-rank estimation methods for the intensity functions of multivariate Hawkes processes. While univariate Hawkes processes are approximated by integer-valued autoregressive models in the weak topology, we extend this approximation result to the multivariate setting. Building on this foundation, we develop new sparse and higher-order reduced-rank estimation procedures for multivariate Hawkes processes by leveraging methodology for multivariate integer-valued time series. In addition, we study a sparse weighted least squares estimator and establish error bounds for all proposed estimators. All theoretical results are derived by verifying novel moment and mixing conditions that ensure the applicability of concentration inequalities to weakly dependent data. Finally, we conduct an empirical study to assess the finite-sample performance of all estimation methods.

  • モデル依存・非依存型の変数重要度の理論と応用

    中村知繁，白石博

    日本保険・年金リスク学会誌 14 ( 1 )  2025.05

    Research paper (bulletin of university, research institution), Joint Work

  • Time Series Quantile Regression Using Random Forests

    Shiraishi H., Nakamura T., Shibuki R.

    Journal of Time Series Analysis 45 ( 4 ) 639 - 659 2024.07

    ISSN  01439782

    　View Summary

    We discuss an application of Generalized Random Forests (GRF) proposed to quantile regression for time series data. We extended the theoretical results of the GRF consistency for i.i.d. data to time series data. In particular, in the main theorem, based only on the general assumptions for time series data and trees, we show that the tsQRF (time series Quantile Regression Forest) estimator is consistent. Compare with existing article, different ideas are used throughout the theoretical proof. In addition, a simulation and real data analysis were conducted. In the simulation, the accuracy of the conditional quantile estimation was evaluated under time series models. In the real data using the Nikkei Stock Average, our estimator is demonstrated to capture volatility more efficiently, thus preventing underestimation of uncertainty.

  • Estimating the effective reproduction number of COVID-19 via the chain ladder method

    Lin X., Matsunaka Y., Shiraishi H.

    Japanese Journal of Statistics and Data Science 7 ( 2 ) 861 - 893 2024

    　View Summary

    This paper addressed a critical issue of reporting delays in estimating the effective reproduction number, focusing on the context of the COVID-19 pandemic. The reporting delay problem is a pervasive challenge, impacting the accuracy of the estimation and consequently influencing public health decision-making. Through the exploration of the application of the Chain Ladder method, a well-established technique from actuarial science, a novel approach to mitigate the effects of reporting delays in infectious disease epidemiology was proposed. By applying the Chain Ladder method to infectious disease data, we illustrated its potential to provide more accurate and timely estimation, accounting for reporting delays inherent in epidemiological surveillance systems.

  • Association between prehospital transfer distance and surgical mortality in emergency thoracic aortic surgery

    Yu Izumisawa, Hideki Endo, Nao Ichihara, Arata Takahashi, Kan Nawata, Hiroshi Shiraishi, Hiroaki Miyata, Noboru Motomura

    The Journal of Thoracic and Cardiovascular Surgery 163 ( 1 ) 28 - 35 2022.01

    Research paper (scientific journal), Joint Work, Accepted,  ISSN  00225223

    　View Summary

    © 2020 The American Association for Thoracic Surgery Objective: To examine whether there is an association between prehospital transfer distance and surgical mortality in emergency thoracic aortic surgery. Methods: A retrospective cohort study using a national clinical database in Japan was conducted. Patients who underwent emergency thoracic aortic surgery from January 1, 2014, to December 31, 2016, were included. Patients with type B dissection were excluded. A multilevel logistic regression analysis was performed to examine the association between prehospital transfer distance and surgical mortality. In addition, an instrumental variable analysis was performed to address unmeasured confounding. Results: A total of 12,004 patients underwent emergency thoracic aortic surgeries at 495 hospitals. Surgical mortality was 13.8%. The risk-adjusted mortality odds ratio for standardized distance (mean 12.8 km, standard deviation 15.2 km) was 0.94 (95% confidence interval, 0.87-1.01; P = .09). Instrumental variable analysis did not reveal a significant association between transfer distance and surgical mortality as well. Conclusions: No significant association was found between surgical mortality and prehospital transfer distance in emergency thoracic aortic surgery cases. Suspected cases of acute thoracic aortic syndrome may be transferred safely to distant high-volume hospitals.

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Papers, etc., Registered in KOARA 【 Display / hide 】

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Presentations 【 Display / hide 】

  • Generalized random forests for dependent data

    Hiroshi Shiraishi, Tomoshige Nakamura

    [International presentation]  5th International Conference on Econometrics and Statistics (EcoSta2022)) (Ryukoku University(Web)) , 

    2022.06
    , 

    Oral presentation (general), EcoSta

  • Time Series Quantile Regressions by using Random Forests

    Hiroshi Shiraishi, Ryotaro Shibuki, Tomoshige Nakamura

    [International presentation]  Waseda International Symposium : Topological Data Science, Causality, Analysis of Variance and Time Series (Waseda University) , 

    2022.03
    , 

    Oral presentation (general), Yan Liu, Yuichi Goto

  • ランダムフォレストを用いた時系列分位点回帰

    Hiroshi Shiraishi, Ryotaro Shibuki, Tomoshige Nakamura

    [International presentation]  Innovative development of theory and methodology on statistical science in various fields (Niigata University, Station South Campus Tokimate, Lecture Room A, B) , 

    2021.09
    , 

    Symposium, workshop panel (public), Junichi Hirukawa (Niigata Universiry)，Makoto Aoshima (University of Tsukuba)

  • Semiparametric estimation of optimal dividend barrier for Levy processes

    Hiroshi Shiraishi, Yasutaka Shimizu

    [International presentation]  4th International Conference on Econometrics and Statistics (EcoSta2021) (Hong Kong University of Science and Technology(Web)) , 

    2021.06
    , 

    Oral presentation (general), EcoSta

  • Local Asymptotic Normality and Efficient Estimation for Multivariate INAR(p) Models

    Hiroshi Shiraishi

    [International presentation]  Kinosaki Seminar Data Science&Causality (Blue Ridge Hotel) , 

    2019.03
    , 

    Symposium, workshop panel (public), Masanobu Taniguchi (Waseda University)

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Research Projects of Competitive Funds, etc. 【 Display / hide 】

  • 決定木を利用した機械学習モデルに対する統計的漸近理論の構築とその拡張

    2026
    -
    2030

    文部科学省・日本学術振興会, 科学研究費助成事業, 基盤研究(C), Research grant, Principal investigator

  • ネイマン直交性を用いた機械学習と統計的推論を併用した推定理論の時系列解析への応用

    2021.04
    -
    2026.03

    MEXT,JSPS, Grant-in-Aid for Scientific Research, Grant-in-Aid for Scientific Research (C), Principal investigator

  • Statistical Estimation for Optimal Dividend Barrier with Insurance Portfolio

    2016.10
    -
    2022.03

    Keio University, Grant-in-Aid for Scientific Research, Shiraishi Hiroshi, Research grant, Principal investigator

  • Portfolio Optimization Problem for High Dimensional Data

    2012.04
    -
    2017.03

    Jikei Medical University, Keio University, Grant-in-Aid for Scientific Research, Shiraishi Hiroshi, Research grant, Principal investigator

  • Statistical Estimation of Optimal Portfolios for Dependent Returns of Assets

    2008.04
    -
    2011.03

    Waseda University, Jikei Medical University, Grant-in-Aid for Scientific Research, Shiraishi Hiroshi, Research grant, Principal investigator

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Courses Taught 【 Display / hide 】

  • GRADUATE RESEARCH ON FUNDAMENTAL SCIENCE AND TECHNOLOGY 2

    2026

  • TOPICS IN STATISTICAL SCIENCES A

    2026

  • BACHELOR'S THESIS

    2026

  • MATHEMATICAL SCIENCES PRACTICAL RESEARCH ACTIVITY D

    2026

  • MATHEMATICAL SCIENCES PRACTICAL RESEARCH ACTIVITY A

    2026

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Courses Previously Taught 【 Display / hide 】

  • 数理統計学第１同演習

    Keio University

    2015.04
    -
    2016.03
    , 

    Spring Semester, Seminar, Within own ｆaculty, 2h

  • 時系列モデル

    Keio University

    2015.04
    -
    2016.03
    , 

    Spring Semester, Lecture, Within own ｆaculty, 1h

  • 生命保険概論

    Keio University

    2015.04
    -
    2016.03
    , 

    Spring Semester, Lecture, 1h

  • 数学1B

    Keio University

    2015.04
    -
    2016.03
    , 

    Autumn Semester, Lecture, Within own ｆaculty, 1h

  • 統計科学輪講

    Keio University

    2015.04
    -
    2016.03
    , 

    Autumn Semester, Seminar, Within own ｆaculty, 1h

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Memberships in Academic Societies 【 Display / hide 】

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Committee Experiences 【 Display / hide 】

  • 2026.04
    -
    Present

    副会長, 日本保険・年金リスク学会

  • 2024.06
    -
    Present

    庶務委員会会計担当, 日本統計学会

  • 2023.04
    -
    Present

    学術委員会　委員長, 日本アクチュアリー会

  • 2022.04
    -
    2026.03

    大会担当理事, 日本保険・年金リスク学会

  • 2022.04
    -
    2026.03

    会計担当理事, 日本保険・年金リスク学会

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