论文信息 - AUTOREGRESSIVE MODELS WITH PIECEWISE CONSTANT VOLATILITY AND REGRESSION PARAMETERS

AUTOREGRESSIVE MODELS WITH PIECEWISE CONSTANT VOLATILITY AND REGRESSION PARAMETERS

We introduce herein a new class of autoregressive models in which the regression parameters and error variances may undergo changes at unknown time points while staying constant between adjacent change-points. Assuming conjugate priors, we derive closed-form recursive Bayes estimates of the regression parame- ters and error variances. Approximations to the Bayes estimates are developed that have much lower computational complexity and yet are comparable to the Bayes estimates in statistical eciency . We also address the problem of unknown hyper- parameters and propose two practical methods for simultaneous estimation of the hyperparameters, regression parameters and error variances.

T. Lai | Haipeng Xing | Haiyan Liu

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