1997/10/01 by Adrian R. Fleissig, James L. Swofford
Economics, Econometrics and Finance · #Economic theories and models #Financial Risk and Volatility Modeling #Monetary Policy and Economic Impact
paper · doi:10.1080/07350015.1997.10524726
openalex publication_date 1997/10/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/29
We extend Barnett and Jonas's asymptotically ideal model (AIM) to model for the possibility that the data were generated by a dynamic process. Prediction errors for dynamic and static AIM models are compared for various simulated datasets. Monetary data are also used to evaluate the AIM specifications. There is substantial evidence that an AR(1) correction considerably improves the quality of low-order finite approximations of AIM with the cost of estimating only one additional parameter. Furthermore, restricting a dynamic AIM to approximate only linear homogenous functions often results in severe misspecification.