Flexible binomial AR(1) processes using copulas.

In order to accurately and flexibly capture the correlation structure between two random coefficients in the binomial AR(1) process, we propose a new class of models with copula. We derive some basic properties of the process. Then we discuss the conditional least squares (CLS) and conditional maximum likelihood (CML) estimators, as well as their asymptotic properties. We also investigate the finite-sample performance of the proposed method in simulation studies. Finally, a real data example is provided to illustrate the model. • A flexible binomial AR(1) (FBAR(1)) model based on copulas. • Basic probabilistic and statistical properties. • The CLS and CML estimators and the related asymptotic properties. • Real data applications in the fields of meteorology and finance. [ABSTRACT FROM AUTHOR]