Damiano is part of the Mathematical Finance and Stochastic Analysis research groups.
Damiano's current interests include the areas of quantitative finance, probability and statistics, stochastic analysis, nonlinear filtering and information geometry.
In quantitative finance the main areas of interest are valuation and pricing, risk measurement and liquidity risk, term structure modeling and interest rates, multivariate volatility smile modeling, credit and default modeling, counterparty risk, collateral and funding costs, nonlinear PDEs and Backward SDEs for funding costs and nonlinear valuation more generally, stochastic dynamical models for commodities and inflation, algorithmic trading and optimal execution. Interaction between optimal execution and term structures, and ineffectiveness of risk measures under S-shaped utility (limited liability of excessive tail-risk-seeking traders) are further themes of interest. Impact of AI and RPA in insurance and more general the issue of interpretability when machine learning is applied to finance are more recent interests.
In Probability and Statistics the interest is on the interaction between the exponential statistical manifold and the dynamic features of stochastic processes laws, nonlinear stochastic filtering, and stochastic processes consistent with mixtures of distributions. Many of these interests are related to the differential geometric approach to statistics, occasionally called "information geometry". This led to research identifying an Ito stochastic differential equation on a manifold as a 2-jet and to optimal ways to approximate a given SDE on a submanifold, with applications to optimal projection filtering. Damiano is also interested in dependence structure across arrival times that can be iterated. This led to a new characterization of the Marshall Olkin law.
Damiano's research papers and preprints are available at his
A comprehensive list of references is available on his google scholar page.