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Shane Henderson researches discrete event simulation and Monte Carlo simulation. His research on variance reduction techniques is being applied to option pricing problems. In addition, his work on random vector generation can be applied in credit risk settings to model dependence structures.
Robert Jarrow (Johnson Graduate School of Management) has done extensive research in the areas of derivatives, investments, and risk management. Most recently, he has studied term structure, credit risk, and liquidity risk modeling.
Philip Protter has broad research interests in mathematical finance, including liquidity risk, credit risk, incomplete markets, energy market derivatives, extensions of Value at Risk to risk measures, credit contagion, and numerical methods for pricing and hedging.
Sidney Resnick includes among his research interests: Extreme value problems in finance and insurance including Value at Risk; stochastic models for dependent heavy-tailed data such as ARCH and GARCH; and multidimensional heavy tailed problems pertaining to exchange rate returns.
David Ruppert does a variety of statistical research, including regression, splines, MCMC, modeling of term structure, measurement error models, and semiparametric modeling.
Gennady Samorodnitsky focuses on models with heavy tails and/or long memory, which are models where traditional Black-Scholes approaches fail due to lack of moments, incompleteness of the market, and potential arbitrage opportunities. He is interested in measures of risk, including both coherent and incoherent ones, and ones coherent only in a certain range. Samorodnitsky is also interested in high-dimensional models, shot models, and in issues related to portfolio optimization and related tail analysis.
Alexander Schied is interested in the applications of probability, stochastic analysis, and control theory to problems in financial engineering and mathematical economics. In recent years, his focus has been on risk measures, liquidity risk, robust portfolio optimization, incomplete markets, and model risk.
Stefan Weber’s research focuses on mathematical finance. His interests include credit, liquidity and operational risk, risk measures, optimal portfolio choice, and Monte Carlo methods.