High frequency finance and market microstructure.
The research is devoted to the mathematical modeling and empirical characterization of financial time series at high (transaction by transaction) and ultra-high (offers to buy and sell, limit order book) frequency. The areas of interest are liquidity modeling, price formation mechanisms, and optimal order execution. Finally the group investigates possible metrics of financial market instability at high frequency and the role of market structure on the high frequency properties of prices.
Dependency between financial variables, correlation structures, and networks.
By using techniques from multivariate statistics, data mining, and the theory of complex networks, we investigate and model the dependencies between financial variables, such as stock returns, Credit Default Swap returns, and trading activity of investors or brokerage firms. The objectives are to identify and model risk factors of an asset portfolio, to build more efficient estimators of covariance matrix for optimal portfolio allocation, and to build taxonomies of investors in order to study their mutual interaction.
The group is involved in researches on the mechanisms that might lead financial markets (or the whole economy) to an excessive risk of systemic events. This is done by using mathematical and computational models and empirical analyses. The considered entities are banks or investment firms, which invest in assets and are connected through credit networks. The mechanisms investigated as possible responsible of systemic risk are excessive leverage, positive feedback loops that amplifies small perturbations, and an excessive homogeneity among portfolios.
Methods for network (re)construction: codes available