The least-squares criteria of the random coefficient dynamic regression model

Abstract

The random coefficient dynamic regression (RCDR) model develops from random coefficient autoregressive (RCA) model and autoregressive (AR) model. The RCDR model is considered by adding exogenous variables. In this article, the concept of the least-squares (LS) criterion is used to estimate the parameter on the RCDR model. Simulation results have shown that the proposed coefficient of the AR model provided asymptotically unbiased estimates nearly for most of the six data-generating models. The RCDR model is then applied to a series of daily observations of the exchange rate of Baht/GBP and Baht/EUR to illustrate the methodology. The predictions of LS criteria are used with those obtained on 20 hold-out future values of withheld observations. Copyright © Grace Scientific Publishing, LLC.