A novel class of dimension reduction methods is combined with a stochastic multi-factor panel regression-based state-space model in order to model the dynamics of yield curves whilst incorporating regression factors. This is achieved via Probabilistic Principal Component Analysis (PPCA) in which...

A novel class of dimension reduction methods is combined with a stochastic multi-factor panel regression-based state-space model in order to model the dynamics of yield curves whilst incorporating regression factors. This is achieved via Probabilistic Principal Component Analysis (PPCA) in which...

This paper proposes a systemic risk index based on Functional Data Analysis (FDA), overcoming salient shortcomings of standard methodologies related to data usage, data sparseness, and high dimensionality issues. Using Mexican data, a set of systemic risk indexes are constructed and we show that...

This paper proposes a systemic risk index based on Functional Data Analysis (FDA), overcoming salient shortcomings of standard methodologies related to data usage, data sparseness, and high dimensionality issues. Using Mexican data, a set of systemic risk indexes are constructed and we show that...