I completed the Ph.D degree in Actuarial Science at the Department of Statistics and Actuarial Science, University of Waterloo under the supervision of professors Prof. Marius Hofert. My CV is available here.

Education

  • PhD in Actuarial Science, University of Waterloo, 2017 - 2020
    • Supervisor: Marius Hofert
    • Risk Analysis: Measures of concordance, their compatibility and capital allocation
    MSc in Mathematics, Keio University, 2015 - 2017
    • Supervisor: Mihoko Minami
    • Thesis: Computation of Risk Contributions with MCMC 
  • BSc in Mathematics, Keio University, 2011 - 2015
    • Supervisor: Mihoko Minami
    • Thesis: VaR Bounds and the Case Study Using Rearrangement Algorith





Membership of Professional Societies

  • Japan Statistical Society
  • Institute of Actuaries of Japan (Associate)


Research Interest

  • Quantitative Risk Management
  • Risk Aggregation and Risk Allocation
  • Model Uncertainty in Risk Aggregation
  • Copula and Modelling of Dependence
  • Extreme Value Theory and Its Applications
  • Computation with Monte Carlo in Finance
  • Markov Chain Monte Carlo
  • Measures of Dependence and Association
  • Neural Network
  • Rare Event Simulation


Publications

  • Koike, T., and Hofert, M. (2020). Markov Chain Monte Carlo Methods for Estimating Systemic Risk Allocations, Risks 2020, 8(1), 6; https://doi.org/10.3390/risks8010006. URL
  • Hofert, M., and Koike, T. (2019). Compatibiity and Attainability of Matrices of Correlation-Based Measures of Concordance. ASTIN Bulletin: The Journal of the IAA  49(3): 885-918.
 URL
  • Koike, T., and Minami, M. (2019). Estimation of Risk Contributions with MCMC. Quantitative Finance, 1-19. URL
  • Koike, T., Minami, M. and Shiraishi, H. (2016). “Calculation of Value-at-Risk Bounds using Rearrangement Algorithm”. (in Japanese), 日本統計学会誌 (Japanese Journal of the Japan Statistical Society), 45(2), 353-375. URL


Manuscripts

  • Koike, T., and Hofert, M. (2020+). Modality for Scenario Analysis and Maximum Likelihood Allocation, Available at arXiv and Talk.
  • Koike, T., and Hofert, M. (2020+). Estimation and Comparison of Correlation-based Measures of Concordance, Available at arXiv and Talk.
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Talks

  • “Compatibility of matrices for correlation-based measures of concordance” CFE-CMStatistics at University of London in December, 2019. pdf
  • "Compatibility and attainability of matrices for correlation-based measures of concordance” Japanese Joint Statistical Meeting at Shiga University in September, 2019. pdf
  • “Compatibility of matrices for correlation-based measures of concordance” Wednesday seminar at Keio University in May, 2019.
  • “Compatibility of matrices for correlation-based measures of concordance” 3rd SAS/WatRISQ Research Presentation Day at University of Waterloo in February, 2019. pdf
  • “Efficient computation of risk contributions by using MCMC” Keio Symposium on Risk Assessment, at Keio Univ in September, 2016.
  • “Computation of risk contributions with MCMC on VaR-fiber”, Japanese Joint Statistical Meeting, at Kanazawa University in September, 2016.
  • “Efficient computation of risk contributions by using MCMC” Boston University/Keio University workshop, at Boston University in August, 2016. pdf
  • “Rearrangement Algorithm in Financial Risk Assessment and its problems” (in Japanese),  Japan Statistical Meeting in Spring, at Tohoku University in March, 2016.