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My research to date has focused on Bayesian econometrics and time series analysis, with applications in developing innovative approaches to stochastic volatility and high-dimensional time series models analysis with policy implications. I have papers on high dimensional time series analysis with novel methodologies in obtaining analytical expressions for the likelihood of inverse gamma stochastic volatility models in nonlinear, non-Gaussian state space models.
My current work and future research interests explores alternative machine learning and stochastic volatility hybrid approaches for volatility forecasting, with applications in climate risk and development economics.
I am always open to collaboration, particularly on interdisciplinary projects beyond mathematics and finance, and look forward to connecting with those interested in advancing the field of econometrics together.
Currently, I hold the following positions in Tokyo, Japan:
1) Adjunct Lecturer, Sophia University
I teach undergraduate courses in Time Series Analysis, focusing on econometric modeling, forecasting methods, and applied data analysis.
2) Consultant in Research Methods, National Graduate Institute for Policy Studies (GRIPS)
I teach and provide research consultation in data science and quantitative methods, supporting graduate students in econometrics and programming using R, C++, Python, MATLAB, EViews, and Stata.
3) Project Research Assistant, Keio University
I serve as the technical lead in an interdisciplinary research project developing dynamic models of heterogeneous multi-server systems, with a focus on real-time service rate estimation and statistical modeling.
4) Researcher, Credit Risk Database Association (CRD), Tokyo
I contribute to the development and refinement of quantitative credit risk models, integrating econometric and machine learning techniques for applied risk assessment.
Please find my full CV here and a link to the current version of my Job Market Paper here.
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