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This paper looks at changes in the correlations of daily returns between the four major banks in Australia. Revelations from the analysis are of importance to investors, but also to government involvement, due to the large proportion of the highly concentrated financial sector relying on the stability of the Big Four. For this purpose, a methodology for building Multivariate Time-Varying STCC-GARCH models is developed. The novel contributions in this area are the specification tests related to the correlation component, the extension of the general model to allow for additional correlation regimes, and a detailed exposition of the systematic, improved modelling cycle required for such nonlinear models. There is an R-package that includes the steps in the modelling cycle. Simulations evidence the robustness of the recommended model building approach. The empirical analysis reveals an increase in correlations of the Australia's four largest banks that coincides with the stagnation of the home loan market, technology changes, the mining boom, and Basel II alignment, increasing the exposure of the Australian financial sector to shocks.

We develop a non-dynamic panel smooth transition regression model with fixed individual effects. The model is useful for describing heterogenous panels, with regression coefficients that vary across individuals and over time. Heterogeneity is allowed for by assuming that these coefficients are continuous functions of an observable variable through a bounded function of this variable and fluctuate between a limited number (often two) of extreme regimes. The model can be viewed as a generalization of the threshold panel model of Hansen (1999). We extend the modelling strategy for univariate smooth transition regression models to the panel context. This comprises of model specification based on homogeneity tests, parameter estimation, and diagnostic checking, including tests for parameter constancy and no remaining nonlinearity. The new model is applied to describe firms' investment decisions in the presence of capital market imperfections.