ARCH-type bilinear models with double long memory

We discuss the covariance structure and long-memory properties of stationary solutions of the bilinear equation X_t=ζ_tA_t+B_t,(), where are standard i.i.d. r.v.'s, and A_t,B_t are moving averages in X_s, s<t. Stationary solution of () is obtained as an orthogonal Volterra expansion. In the case A_t≡1, X_t is the classical AR(∞) process, while B_t≡0 gives the LARCH model studied by Giraitis et al. (Ann. Appl. Probab. 10 (2000) 1002). In the general case, X_t may exhibit long memory both in conditional mean and in conditional variance, with arbitrary fractional parameters and , respectively. We also discuss the hyperbolic decay of auto- and/or cross-covariances of X_t and X_t² and the asymptotic distribution of the corresponding partial sums’ processes.