Stationary Threshold Vector Autoregressive Models
AbstractThis paper examines the steady state properties of the Threshold Vector Autoregressive model. Assuming that the trigger variable is exogenous and the regime process follows a Bernoulli distribution, necessary and sufficient conditions for the existence of stationary distribution are derived. A situation related to so-called “locally explosive models”, where the stationary distribution exists though the model is explosive in one regime, is analysed. Simulations show that locally explosive models can generate some of the key properties of financial and economic data. They also show that assessing the stationarity of threshold models based on simulations might well lead to wrong conclusions. View Full-Text
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Grynkiv, G.; Stentoft, L. Stationary Threshold Vector Autoregressive Models. J. Risk Financial Manag. 2018, 11, 45.
Grynkiv G, Stentoft L. Stationary Threshold Vector Autoregressive Models. Journal of Risk and Financial Management. 2018; 11(3):45.Chicago/Turabian Style
Grynkiv, Galyna; Stentoft, Lars. 2018. "Stationary Threshold Vector Autoregressive Models." J. Risk Financial Manag. 11, no. 3: 45.
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