Hyung Joo Kim

I am an Assistant Professor of Finance at Copenhagen Business School.

My research interests include asset pricing, derivatives, financial econometrics, and macro-finance.

Curriculum Vitae
Email: hyk.fi@cbs.dk

Publication

Options on Interbank Rates and Implied Disaster Risk (with Hitesh Doshi and Sang Byung Seo): Journal of Financial and Quantitative Analysis (Internet Appendix); SSRN | FEDS WP; Best Paper Award Semifinalist, FMA (2019); Previously circulated under the title "What Interbank Rates Tell Us About Time-Varying Disaster Risk"
Volatility Risk and the Specification of the Pricing Kernel (with Steven Heston and Kris Jacobs): Review of Asset Pricing Studies, Forthcoming; SSRN | FEDS WP; Previously circulated under the title "The Pricing Kernel in Options"

A New Closed-Form Discrete-Time Option Pricing Model with Stochastic Volatility (with Steven Heston and Kris Jacobs): SSRN; Presentations: AFA (2025), Paris December Finance Meeting (2024), CBOE Conference on Derivatives and Volatility (2024), SoFiE (2024), NYU Mathematical Modeling in Finance Workshop (2024), University Paris 1 (2024), Federal Reserve Board (2024), Seoul National University (2024), Cancun Derivatives and Asset Pricing Conference (2024)
Characterizing the Conditional Pricing Kernel: A New Approach: SSRN | FEDS WP; Presentations: IAAE (2023), EEA-ESEM (2022), Virtual Derivatives Workshop (2021), NZFM (2021), WFBS (2021), Concordia University, Cornerstone Research, Federal Reserve Board of Governors, Korea Development Institute, Korea Insurance Research Institute, Saint Mary's University, University of Houston, Wilfrid Laurier University
Improved Forecasts from Option Pricing Models Through State-Dependent Estimation (with Dong Hwan Oh): SSRN | FEDS WP; Presentations: SNDE (2026), MFA (2026), Yonsei University (2026), Copenhagen Business School (2026), Erasmus School of Economics (2025), Amsterdam Business School (2025); Previously circulated under the title "Local Estimation for Option Pricing: Improving Forecasts with Market State Information"
Capturing Heterogeneity: Machine Learning Approaches to Implied Volatility Forecasting (with Dong Hwan Oh): SSRN | FEDS WP; Presentations: FinEML (2026)$^\dagger$, Federal Reserve Board (2026)

Volatility and Risk Premia in Term Structure Models (with Kasra Baniasadi, Hitesh Doshi, and Kris Jacobs)

Corporate Finance (FINA 4330) at the University of Houston: Mean Evaluation: 4.9/5.0