We define a dynamic and self-adjusting mixture of Gaussian Graphical Models to cluster financial returns, and provide a new method for extraction of nonparametric estimates of dynamic alphas (excess return) and betas (to a choice set of explanatory factors) in a multivariate setting. This...

Investors and analysts classify firms to conduct valuations or to evaluate performance. The industry groupings usually rely on SIC, NAIC, GICS, or Fama-French classifications. Our purpose is to form groups of companies based on the structure of their financial statements. Using cluster analysis,...

This paper proposes a cluster HAR-type model that adopts the hierarchical clustering technique to form the cascade of heterogeneous volatility components. In contrast to the conventional HAR-type models, the proposed cluster models are based on the relevant lagged volatilities selected by the...

Information Geometry provides a correspondence between differential geometry and statistics through the Fisher Information matrix. In particular, given two models from the same parametric family of distributions, one can define the distance between these models as the length of the shortest...

This paper introduces a new jump diffusion process where the occurrence and the size of past jumps have an impact on both the instantaneous and the long term propensities of observing a jump instantaneously. Here, the intensity of jump arrival is a multifactor self-excited process whereas the...