Mathematical finance: Nonparametric estimation methods and
portfolio optimization problems in continuous-time models. Emphasis on Levy
driven and jump-diffusion models.
Probability and Stochastic processes: Stochastic control,
stochastic analysis, and simulation.
Statistics: Nonparametric estimation using projection estimation,
model selection, and adaptive methods.
Information and coding theory: Concentration inequalities applied
to data compression.
Teaching:
Spring 2010:
STAT 598F.
Modeling with Jump Processes and Applications to Mathematical Finance
Maths and markets. Financial Times (03/21/2009)
writes:
"For the future we need more - and better - maths to underpin individual
banks and the enhanced regulatory regime that will oversee them. Some of
the expertise required is already out there, in universities, waiting to
be put to use."
Nonparametric estimation of time-changed L\'evy models.
Applied Mathematics Colloquia, Illinois Institute of Technology, November 2009.
Also presented at the Mathematical Finance and Probability Seminar,
Rutgers University, October 2009.