This paper builds a general test of contagion in financial markets based on bivariate correlation analysis - a test that can be interpreted as an extension of the normal correlation theorem. Contagion is defined as a structural break in the data generating process of rates of return. Using a...

We propose a general method for the Bayesian estimation of nonlinear no-arbitrage term structure models. The main innovations we introduce are: 1) a computationally efficient method, based on deep learning techniques, for approximating no-arbitrage model-implied bond yields to any desired degree...

This paper deals with instability in regression coefficients. We propose a Bayesian regression model with time-varying coefficients (TVC) that allows to jointly estimate the degree of instability and the time-path of the coefficients. Thanks to the computational tractability of the model and to...

This paper proposes a Bayesian regression model with time-varying coefficients (TVC) that makes it possible to estimate jointly the degree of instability and the time-path of regression coefficients. Thanks to its computational tractability, the model proves suitable to perform the first (to our...

This paper builds a general test of contagion in financial markets based on bivariate correlation analysis - a test that can be interpreted as an extension of the normal correlation theorem. Contagion is defined as a structural break in the data generating process of rates of return. Using a...