교수 상세

닫기
김현균
김현균
  • 박사
  • 금융공학전공(과)
 교직원
정보
학력
  • 2023.02 연세대학교대학원 박사
  • 2017.02 연세대학교 학사
논문 및 연구활동 연구활동(주요논문)
  1. [논문] 김현균, 조소윤, 김정훈, A martingale method for option pricing under a CEV-based fast-varying fractional stochastic volatility model , COMPUTATIONAL & APPLIED MATHEMATICS , Vol.42 , No.6 , pp.296 -296 (Aug, 2023)
  2. [논문] 김현균, 김정훈, A stochastic-local volatility model with Levy jumps for pricing derivatives , APPLIED MATHEMATICS AND COMPUTATION , Vol.451 , pp.128034 -128034 (Aug, 2023)
  3. [논문] 김태경, 김현균, 허정규, Large-scale online learning of implied volatilities , EXPERT SYSTEMS WITH APPLICATIONS , Vol.203 , pp.117365 -117365 (Oct, 2022)
  4. [논문] 김현균, 권세진, 김정훈, 허정규, Pricing path-dependent exotic options with flow-based generative networks , APPLIED SOFT COMPUTING , Vol.124 , pp.109049 -109049 (Jul, 2022)
  5. [논문] 김현균, 권세진, 김정훈, Fractional stochastic volatility correction to CEV implied volatility , QUANTITATIVE FINANCE , Vol.21 , No.4 , pp.565 -574 (Apr, 2021)
국제학술논문지
  1. [논문] 고효준, 권순우, 김진영, 이윤성, 최성택, 김현균, ScoreCL: augmentation‑adaptive contrastive learningvia score‑matching function , MACHINE LEARNING , Vol.114 , pp.1 -22 (Jan, 2025)
  2. [논문] 김현균, 허정규, Deep learning of optimal exercise boundaries for American options , INTERNATIONAL JOURNAL OF COMPUTER MATHEMATICS , pp.1 -28 (Dec, 2024)
  3. [논문] 김현균, 김형미, 허정규, Considering appropriate input features of neural network to calibrate option pricing models , Computational Economics , pp.1 -28 (Aug, 2024)
  4. [논문] 김현균, 김시우, 김정훈, Variance and volatility swaps and options under the exponential fractional Ornstein–Uhlenbeck model , North American Journal of Economics and Finance , Vol.72 , pp.102155 -102155 (May, 2024)
  5. [논문] 김현균, 조소윤, 김정훈, A martingale method for option pricing under a CEV-based fast-varying fractional stochastic volatility model , COMPUTATIONAL & APPLIED MATHEMATICS , Vol.42 , No.6 , pp.296 -296 (Aug, 2023)
  6. [논문] 김현균, 김정훈, A stochastic-local volatility model with Levy jumps for pricing derivatives , APPLIED MATHEMATICS AND COMPUTATION , Vol.451 , pp.128034 -128034 (Aug, 2023)
  7. [논문] 김현균, Jiling Cao, Wenjun Zhang, 김정훈, A Mellin transform approach to pricing barrier options under stochastic elasticity of variance , APPLIED STOCHASTIC MODELS IN BUSINESS AND INDUSTRY , Vol.39 , No.2 , pp.160 -176 (Mar, 2023)
  8. [논문] 김현균, 김정훈, Forecasting the elasticity of variance with LSTM recurrent neural networks , INTERNATIONAL JOURNAL OF COMPUTER MATHEMATICS , Vol.100 , No.1 , pp.209 -218 (Jan, 2023)
  9. [논문] 이건, 김현균, 김태경, 허정규, Newton–Raphson emulation network for highly efficient computation of numerous implied volatilities , JOURNAL OF RISK AND FINANCIAL MANAGEMENT , Vol.15 , No.12 , pp.616 -623 (Dec, 2022)
  10. [논문] 김태경, 김현균, 허정규, Large-scale online learning of implied volatilities , EXPERT SYSTEMS WITH APPLICATIONS , Vol.203 , pp.117365 -117365 (Oct, 2022)
  11. [논문] 김현균, 권세진, 김정훈, 허정규, Pricing path-dependent exotic options with flow-based generative networks , APPLIED SOFT COMPUTING , Vol.124 , pp.109049 -109049 (Jul, 2022)
  12. [논문] 김현균, 권세진, 김정훈, Fractional stochastic volatility correction to CEV implied volatility , QUANTITATIVE FINANCE , Vol.21 , No.4 , pp.565 -574 (Apr, 2021)
  13. [논문] 김성태, 김현균, 김정훈, ELS pricing and hedging in a fractional Brownian motion environment , CHAOS SOLITONS & FRACTALS , Vol.142 , pp.110453 -110453 (Jan, 2021)
국제학술발표
  1. [학술회의] 고효준, 권순우, 김진영, 김현균, Denoising task difficulty-based curriculum for training diffusion models , International Conference on Learning Representations (Apr, 2025)
특허 및 기타
갤러리