Ochi(1983) proposed an estimator for the autoregressive coefficient of the first-order autoregressive model (AR(1)) by using two constants for the end points of the process. Classical estimators for AR(1) , such as the least squares estimator, Burg's estimator, and Yule- Walker estimator are obtained as special cases by choice of the constants in Ochi's estimator. By writing the first-order autoregressive conditional heteroskedastic model, ARCH(1), in a form similar to that of AR(1), we extend Ochi ' s estimator to ARCH(1) models. This allows introducing analogues of the least squares estimator, Burg's estimator and Yule- Walker estimator, and we compare the relations of these with Ochi's estimator for ARCH(1) models. We then provide a simulation for AR(1) models and examine the performance of Ochi ' s estimator. Also, we simulate Ochi's estimator for ARCH(1) with different parameter values and sample sizes.
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