We propose an early warning model for predicting the likelihood of a financial stress event for a given future time, and examine whether credit plays an important role in the model as a non-linear propagator of shocks.
We measure systemic risk in the network of financial market infrastructures (FMIs) as the probability that two or more FMIs have a large credit risk exposure to the same FMI participant.
Testing for the Diffusion Matrix in a Continuous-Time Markov Process Model with Applications to the Term Structure of Interest RatesThe author proposes a test for the parametric specification of each component in the diffusion matrix of a d-dimensional diffusion process. Overall, d (d-1)/2 test statistics are constructed for the off-diagonal components, while d test statistics are constructed for the main diagonal components.
The objective of this paper is to propose an early warning system that can predict the likelihood of the occurrence of financial stress events within a given period of time. To achieve this goal, the signal extraction approach proposed by Kaminsky, Lizondo and Reinhart (1998) is used to monitor the evolution of a number of economic indicators that tend to exhibit an unusual behaviour in the periods preceding a financial stress event.
The authors use the Financial Stress Index created by the International Monetary Fund to predict the likelihood of financial stress events for five developed countries: Canada, France, Germany, the United Kingdom and the United States.