Kyoung-Kuk Kim (Adjunct Professor)
Ph.D. in Business,
Columbia University, 2008
- Seoul National University 1999.02 Mathematics B.S
- Stanford University 2004.06 Mathematics M.S
- Columbia University 2006.05 Business M.S
- Columbia University 2008.10 Business Ph.D
- 2013.09 ~ present : Associate Professor, Industrial & Systems Engineering, (an affiliate professor in the department of Mathematical sciences) KAIST
- 2009.07 ∼ 2013.08 : Assistant Professor, Industrial & Systems Engineering, (an affiliate professor in the department of Mathematical sciences) KAIST
- 2010.01 ∼ 2010.06 : Jerrold E. Marsden Postdoctoral Fellow, Fields Institute, Canada
- 2008.09 ∼ 2009.05 : Credit Quantitative Analytics, Associate, Barclays Capital, New York
- 2008.07 ∼ 2008.09 : Quantitative Credit Research, Senior Associate, Lehman Brothers, New York
- 2007.07 ∼ 2007.09 : Quantitative Credit Research, Summer Associate, Lehman Brothers, New York
- Analysis and management of financial and non-financial risks based on mathematical tools such as probability, statistics, stochastic analysis, optimization, and simulation.
- Stochastic Simulation
Simulation is an essential tool in many engineering disciplines. In particular, new and efficient techniques are much required for today’s large and complex systems. We put our efforts to develop state-of-the-art simulation methods for stochastic models that arise in diverse applications.
Sample paper: “Simulation of Tempered Stable Lévy Bridges and its Applications” [Link]
Financial derivatives continue to play an important role in domestic and international markets. Ideas from probability, stochastic modeling, optimization and others are used for pricing and hedging of financial contracts.
Sample paper: “A Mathematical Model for Multi-name Credit based on Community Flocking” [Link]
Proper understanding of risk factors, suitable and efficient measurement, and effective risk management strategies are very important in the modern industry. We aim to gain new insights and applications, leading to better risk management practices.
Sample paper: “Stochastic Kriging for Conditional Value-at-Risk and its Sensitivities” [Link]
We are interested in other OR problems under risk and uncertainties. Examples include supply chains under FX risk, dynamic pricing with multivariate dependence structure, energy policy under demand uncertainty.
Sample paper: “Transferring and Sharing Exchange-Rate-Risk in a Risk-averse Supply Chain of a Multinational Firm” [Link]
- Stochastic kriging with biased sample estimates, Kyoung-Kuk Kim and Xi Chen, ACM Transactions on Modeling and Computer Simulation, accepted
- A mathematical model for multi-name credit based on community flocking, Seung-Yeal Ha, Kyoung-Kuk Kim, and Kiseop Lee, Quantitative Finance, accepted
- Fairing the gamma: An engineering approach to sensitivity estimation, Wanmo Kang, Kyoung-Kuk Kim, and Hayong Shin, IIE Transactions, accepted
- Long-term and blow-up behaviors of exponential moments in multi-dimensional affine diffusions, Rudra P. Jena, Kyoung-Kuk Kim, and Hao Xing, Stochastic Processes and their Applications, 2012
- Gamma expansion of the Heston stochastic volatility model, Paul Glasserman and Kyoung-Kuk Kim, Finance and Stochastics, 2011
- IE231/FEP321 Analysis and Probability for Finance
- IE241 Engineering Statistics I, KAIST
- IE341 Engineering Statistics II, KAIST
- IE575/FEP411 Structuring and Pricing of Financial Products
- IE576 Risk Management - IE671 Stochastic Modelling II
- IE801/MAS583 Advanced Stochastic Models