Functional coefficient autoregressive conditional root model

This paper proposes an extended model based on ACR model: Functional coefficient autoregressive conditional root model (FCACR). Under some assumptions, the authors show that the process is geometrically ergodic, stationary and all moments of the process exist. The authors use the polynomial spline function to approximate the functional coefficient, and show that the estimate is consistent with the rate of convergence O _p (h ^??+1 + n ^?1/3). By simulation study, the authors discover the proposed method can approximate well the real model. Furthermore, the authors apply the model to real exchange rate data analysis.