Applied Nonlinear Time Series Analysis
Nonlinear time series models, which have recently begun to take up a significant portion of the econometrics literature, have been developed as an alternative to linear time series models. Due to their structure, these models can reveal the asymmetric structure between both economic and financial variables and capture variations in different periods and regimes. Nonlinear time series models are divided into two categories: nonlinear models in the mean and nonlinear models in variance. In the book, both of these model structures are discussed, their theoretical frameworks are mentioned and their applications are given. First, the tests for nonlinearity are explained. Then, nonlinear unit root tests, nonlinear cointegration tests and nonlinear causality tests are mentioned and volatility models are included and causality tests in variance are mentioned.
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