Research interests 

• Statistical inference in big data,  Machine Learning, Explainable AI  

• Credit risk model, credit derivatives 

• Bayesian inference (especially for credit risk model, stochastic  volatility model) 

• Multiple (Bayesian) imputation 

Education 

• Ph.D. in Statistics (cognate area: Finance)

Harvard University, Cambridge, MA, U.S.A.

September 2005 - June 2012

Thesis: Three Essays on Credit Risk Models and Their Bayesian Estimation.

• M.A. of Statistics

Korea University, Seoul, Korea .

September  2002 - August 2004

Thesis: Goodness of fit test for categorical data with intra-cluster correlation and spatial correlation.

• B.A. of Economics in Department of Statistics 

Minor Field : Economics

Korea University, Seoul, Korea.

March 1999 - August 2002 (Early Graduation : 7 semesters)

Teaching 

• Fall 2017~ (Department of International Finance, Hankuk University of Foreign Studies)

  • Advanced Finance Analytics (Undergraduate), 고급 파이낸스 어낼리틱스 실습 (학부) 

  • Finance Analytics (Undergraduate), 파이낸스어낼리틱스 (학부) 

  • Financial Programing (Undergraduate), 금융프로그래밍(학부)

  • Business Statistics / Statistics (Undergraduate), 경영통계학/통계학(학부) 

  • Seminar for Freshmen (Undergraduate), 신입생세미나(학부) 

  • Finance Data Analytics (Graduate), 금융데이터 어낼리틱스(대학원) 

• Fall 2017~ (Previously Taught Courses, Department of International Finance, Hankuk University of Foreign Studies)

  • Mathematics (Undergraduate), 경영수학(학부)

  • Financial Econometrics (Undergraduate), 금융계량분석(학부)

  • Seminar for Developing Career Path 1 (Undergraduate) 

  • Seminar for Developing Career Path 2 (Undergraduate) 

  • Quantitative Finance I  (Graduate), 계량금융1 (대학원)

  • Quantitative Finance II  (Graduate), 계량금융2(대학원)

  • Seminar in Financial Market  (Graduate), 금융시장세미나(대학원)

  • Research Methods on Financial Market  (Graduate),금융시장 조사방법론(대학원) 

• Fall 2014 ~ Fall 2016 (Department of Statistics and Financial Engineering, Korea University)

  • Elementary Computational Statistics (Undergraduate, Fall 2015, Spring 2016 & Fall 2016)

  • Exploratory Data Analysis (Graduate school of policy study, Fall 2016)

  • Elementary Statistics (Undergraduate, Spring 2015)

  • Social Statistics (Graduate school of policy study, Spring 2015)

  • Statistical Method in Social Science (Undergraduate, Fall 2014)

  • Introduction to Financial Engineering (Graduate, Financial Engineering, Fall 2014)

• Fall 2006~ Fall 2009 (Department of Statistics, Harvard University) - as teaching fellow

  • Statistical Sleuthing through Linear Models (Graduate, Fall 2009)

  • Fundamentals of Biostatistics (Undergraduate, Fall 2008)

  • Intermediate Biostatistical Methods (Undergraduate, Spring 2007)

  • Introduction to Quantitative Methods for the Social Sciences and Humanities (Undergraduate, Fall 2007 & Spring 2008)

  •  Introduction to Quantitative Methods

Publications

• Kwon, T. Y.* (2026+). Generative Deep Learning for Class Imbalance in Credit Risk Modeling: Comparative Evaluation of Synthetic Oversampling Methods and an Elastic Oversampling Extension,  Financial Innovation, (accepted).  [SSCI]

• Jeon, S., & Kwon, T. Y.* (2026). Sequential projection of headship based household composition ratios. Journal of Forecasting, 1–18. [SSCI] https://doi.org/10.1002/for.70112

•  Kwon, T. Y.*, & Jeon, S. (2025). Analysis on corporate credit scoring models and key financial variables using machine learning. Asian Review of Financial Research, 38(3), 1–36. [Scopus/KCI] https://doi.org/10.37197/ARFR.2025.38.3.1

•  Kwon, T. Y.* (2025). The Korea News Financial Sentiment Index (KNFSI) and its relationship with the KOSPI 200. Journal of The Korean Data Analysis Society, 27(2), 521–534. [KCI] https://doi.org/10.37727/jkdas.2025.27.2.521

•  Kwon, T. Y.* (2025). Feature importance in linear models with ensemble machine learning: A study of the Fama and French five-factor model. Finance Research Letters, 71, 106406. [SSCI] https://doi.org/10.1016/j.frl.2024.106406

•  Park, Y., & Kwon, T. Y.* (2024). Ensemble with divisive bagging for feature selection in big data. Computational Economics, 66(2), 1321–1354. [SSCI/SCIE] https://doi.org/10.1007/s10614-024-10741-y

•  Kwon, T. Y.* (2024). Tracking the size of the estimation window in time-series data. Data Technologies and Applications, 58(5), 768–786. [SCIE] https://doi.org/10.1108/DTA-11-2023-0797

•  Jeon, S., & Kwon, T. Y.* (2024). N-point modified exponential model for household projections in Korea using multi-point register-based census data. Communications for Statistical Applications and Methods, 31(4), 377–391. [ESCI/Scopus]

•  Chun, Y. J., & Kwon, T. Y.* (2023). Causal inference between social activities and sales of venture start-up: Using causal forest. Journal of The Korean Data Analysis Society, 25(6), 2217–2228. [KCI] https://doi.org/10.37727/jkdas.2023.25.6.2217

•  Kwon, T. Y.* (2023). Causality change in life insurance demand: Focusing on financial market and insurance provider factors. Journal of The Korean Data Analysis Society, 25(1), 173–184. [KCI] https://doi.org/10.37727/jkdas.2022.25.1.173

• Park, Y., Oh, S. M., & Kwon, T. Y.* (2021). Non-identifiability and testability of missing mechanisms in incomplete two-way contingency tables. Communications for Statistical Applications and Methods, 28(3), 307–314. [ESCI/Scopus]

•  Kwon, T. Y.* (2021). Applications of regression-based multiple imputation methods considering logical boundary information of missing values in financial and health survey data. Journal of The Korean Data Analysis Society, 23(2), 939–951. [KCI] https://doi.org/10.37727/jkdas.2021.23.2.939

•  Park, Y., & Kwon, T. Y.* (2020). A new double hot-deck imputation method for missing values under boundary conditions. Survey Methodology, 46(1), 121–139. [SSCI/SCIE]

•  Park, Y., Oh, D. Y., & Kwon, T. Y.* (2019). Robust multiple imputation method for missings with boundary and outliers. The Korean Journal of Applied Statistics, 32(6), 889–898. [KCI] https://doi.org/10.5351/KJAS.2019.32.6.889

•  Jeon, S., Kwon, T. Y., & Park, Y. (2019). Variable-based missing mechanism for an incomplete contingency table with unit missingness. Statistics and Probability Letters, 146, 90–96. [SCIE]

•  Park, Y., Kim, N. H., Kwon, T. Y., & Kim, S. G. (2018). A novel adiposity index as an integrated predictor of cardiometabolic disease morbidity and mortality. Scientific Reports, 8, 16753. [SCIE] https://doi.org/10.1038/s41598-018-35073-4

•  Kwon, T. Y.* (2018). Particle filtering of volatility dynamics for KOSPI200 and its sequential prediction. Journal of Forecasting, 37(7), 720–728. [SSCI]

•  Kwon, T. Y.*, & Lee, Y. (2018). Industry-specific defaults. Journal of Empirical Finance, 45, 45–58. [SSCI]

•  Kwon, T. Y.* (2018). Causality change between Korea and other major equity markets. Communications for Statistical Applications and Methods, 25(4), 397–409. [ESCI/Scopus]

•  Park, Y., Jeon, S., & Kwon, T. Y.* (2018). A sample size calibration approach for the p-value problem in huge samples. Communications for Statistical Applications and Methods, 25(5), 545–557. [ESCI/Scopus]

•  Kim, K. J., Kwon, T. Y., Yu, S., Seo, J. A., Kim, N. H., Choi, K. M., Baik, S. H., Choi, D. S., Kim, S. G., Park, Y., & Kim, N. H. (2018). 10-year mortality trends for adults with and without diabetes mellitus in South Korea, 2003–2013. Diabetes and Metabolism Journal, 42(5), 394–401. [SCIE]

•  Kim, N. H., Kwon, T. Y., Yu, S., Kim, N. H., Choi, K. M., Baik, S. H., Park, Y., & Kim, S. G. (2017). Increased vascular disease mortality risk in prediabetic Korean adults is mainly attributable to ischemic stroke. Stroke, 48(4), 840–845. [SCIE]

•  Kwon, T. Y.*, Lim, J. Y., & Park, Y. (2017). Health life expectancy in Korea based on Sample Cohort Database of National Health Insurance Services. The Korean Journal of Applied Statistics, 30(3), 1–14. [KCI]

•  Kwon, T. Y.* (2016). Correlated structural credit risk model with random coefficients and its Bayesian estimation using stock and credit market information. Journal of Risk Model Validation, 10(3), 21–48. [SSCI]

•  Kwon, T. Y.* (2016). Bayesian estimation of Black-Cox structural credit risk model with consideration of stock market trading noise. Journal of The Korean Data Analysis Society, 18(5B), 2523–2533. [KCI]

•  Kwon, T. Y.*, & Lee, Y. (2016). Estimating structural credit risk models when market prices are contaminated with noise. Applied Stochastic Models in Business and Industry, 32(1), 18–32. [SCIE]

•  Kwon, T. Y.*, & Park, Y. (2016). Reliability of self-reported data for prevalence and health life expectancy studies: Comparison with Sample Cohort DB of National Health Insurance Services. The Korean Journal of Applied Statistics, 29(7), 1329–1346. [KCI]

•  Kwon, T. Y.*, & Jeon, S. (2016). A study on the violent crime and control factors in Korea. Journal of the Korean Data and Information Science Society, 27(6), 1511–1523. [KCI] https://doi.org/10.7465/jkdi.2016.27.6.1511

•  Park, Y., Park, H. M., & Kwon, T. Y.* (2015). Financial projection for National Health Insurance using NHIS Sample Cohort Data Base. The Korean Journal of Applied Statistics, 28(4), 663–683. [KCI]

•  Kwon, T. Y.*, & Park, Y. (2015). A new multiple imputation method for bounded missing values. Statistics and Probability Letters, 107, 204–209. [SCIE]

* First or corresponding author 

Working Papers

• Large-Scale wage modeling with Ensemble Divisive Bagging using ACS PUMS (2026+)