Testing for Nonlinearities in Economic and Financial Time Series
Cyclical asymmetry has been recognised as a nonlinear phenomenon in numerous recent studies examining various economic and financial time series. If the nonlinear phenomena can be modelled by a nonlinear stochastic structure like the bilinear (BL), exponential autoregressive (EAR), smooth transition autoregressive (STAR), or self-exciting threshold autoregressive (SETAR) types, then we need tests to enable us to identify these various nonlinear models. In this paper we suggest modifications to the Tsay (1991) general test for identifying nonlinearities of the BL, EAR, and SETAR types as they occur in time series. Our testing procedure is simulated to determine its empirical properties.
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