CV
Lee, Kyungsub (이경섭)
Email: ksublee@yu.ac.kr or kyungsub@gmail.com
Employment
Associate Professor, Department of Statistics, Yeungnam University, Gyeongsan, Korea, 2021.9.-
Assistant Professor, Department of Statistics, Yeungnam University, Gyeongsan, Korea, 2015.9.-2021.8.
UNIST Research Scientist, School of Business Administration, UNIST, Ulsan, Korea, 2013.8.-2015.8.
Postdoctoral Researcher, Department of Mathematical Sciences, KAIST, Daejeon, Korea, 2012.3.-2013.2.
Education
Ph.D. Mathematical Sciences, KAIST, 2012.
Dissertation: GARCH Intensity Model and New Methods of Option Pricing
M.S. Mathematical Sciences, KAIST, 2008.
B.S. Mathematics and Computer Sciences (dual degree), KAIST, 2006.
Publication (Google scholar, ORCID, Scopus, arXiv)
Recurrent neural network based parameter estimation of Hawkes model on high-frequency financial data, Finance Research Letters, 2023.
Multi-kernel property in high-frequency price dynamics under Hawkes model, To appear, Studies in Nonlinear Dynamics & Econometrics, 2023.
Modeling bid and ask price dynamics with an extended Hawkes process and its empirical applications for high-frequency stock market data, (with B.K. Seo), To appear, Journal of Financial Econometrics, 2023.
Analytic formula for option margin with liquidity costs under dynamic delta hedging, (with B.K. Seo), 53, pp.3391-3407, Applied Economics, 2021.
Optimal market-Making strategies under synchronised order arrivals with deep neural networks (with S.E. Choi, H.J. Jang and H. Zheng), 125, pp.124098, Journal of Economic Dynamics and Control, 2021.
Computational method for probability distribution on recursive relationships in financial application (with J.J. Park), 34, pp.258-278, Probability in the Engineering and Informational Sciences, 2020.
Systemic risk in market microstructure of crude oil and gasoline futures prices: A Hawkes flocking model approach (with H.J. Jang and K. Lee), 40, pp.247-275, Journal of Futures Markets, 2020.
Filtered historical simulation for initial margin of interest rate swap under Korean market (with B.K. Seo) , 54, pp. 2516-2532, Emerging Markets Finance and Trade, 2018
Modeling microstructure price dynamics with symmetric Hawkes and diffusion model using ultra-high-frequency stock data (with B.K. Seo), 79, pp.154-183, Journal of Economic Dynamics and Control, 2017.
Marked Hawkes process modeling of price dynamics and volatility estimation (with B.K. Seo), 40, pp.174-220, Journal of Empirical Finance, 2017.
Probability distribution of tail hedged portfolio with third moment swap (with B.K. Seo), 50, pp.447-471, Computational Economics, 2017.
Distribution of discrete time delta-hedging error via a recursive relation (with G.H. Choe and M. Park), 6, pp.314-336, East Asian Journal on Applied Mathematics, 2016.
Probabilistic and statistical properties of moment variations and their use in inference and estimation based on high frequency return data, Studies in Nonlinear Dynamics and Econometrics, 20, pp.19-36, 2016.
Recursive formula for arithmetic Asian option prices, Journal of Futures Markets, 34, pp.220-234, 2014.
Conditional correlation in asset return and GARCH intensity model (with G.H. Choe), AStA Advances in Statistical Analysis, 98, pp.197-224, 2014.
High moment variations and their application (with G.H. Choe), Journal of Futures Markets, 34, pp.1040-1061, 2014.
R package
Teaching
2023 Spring : Programming for statistics, Introduction to financial statistics, Machine learning project in education
2022 Fall : Statistical database, Statistical machine learning, Statistical data analysis, Machine learning and its application
2022 Spring : Programming for statistics, Introduction to financial statistics, Advanced big data analytics
2021 Fall : Design and analysis of experiments, Statistical database, Big data analytics, Financial statistics
2021 Spring : Programming for statistics, Stochastic simulations, Introduction to financial statistics, Advanced big data analytics
2020 Fall : Design and analysis of experiments, Statistical database, Big data analytics, Statistical data analysis
2020 Summer : Statistics I
2020 Spring : Applied statistics, Programming for statistics, Stochastic simulations, Financial stochastic modeling
2019 Fall : Design and analysis of experiments, Statistical database, Big data analytics, Applied statistics
2019 Spring : Applied statistics, Programming for statistics, Stochastic simulations, Stochastic processes
2018 Fall : Design and analysis of experiments, Statistical database, Big data analytics, Advanced big data analytics
2018 Spring : Applied statistics, Programming for statistics, Stochastic simulations, Statistical package design
2017 Winter : Statistics I
2017 Fall : Design and analysis of experiments, Statistical database, Big data analytics
2017 Spring : Applied statistics, Programming for statistics, Stochastic simulations
2016 Fall : Applied statistics, Design and analysis of experiments, Statistical database
2016 Spring : Applied statistics, Programming for statistics, Stochastic simulations
2015 Fall : Applied statistics, Statistical database