In this paper a flexible GARCH-type model is developed with the aim of describing sign and size asymmetries in financial volatility as well as intermittent dynamics and excess of kurtosis. A sufficient condition for strict stationarity and ergodicity of the model is established and the existence of the second- and fourth-order moments is discussed. It is shown that the model may have explosive regimes and still be strictly stationary and ergodic. Furthermore, estimation of the parameters is carefully addressed and the asymptotic properties of the quasi-maximum likelihood estimator is derived. A modeling cycle based on a sequence of simple and easily implemented Lagrange multiplier tests is discussed in order to avoid the estimation of unidentified models. A Monte-Carlo experiment is designed to evaluate the methodology. Empirical examples are used to illustrate the use of the model in practical situations.
Volatility GARCH models multiple regimes nonlinear time series smooth transition finance asymmetry leverage effect excess of kurtosis.