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This paper provides a general framework for the quantitative analysis of stochastic dynamic models. We review the convergence properties of some numerical algorithms and available methods to bound approximation errors. We then address the convergence and accuracy properties of the simulated...
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We develop a score-driven time-varying parameter model where no particular parametric error distribution needs to be specified. The proposed method relies on a versatile spline-based density, which produces a score function that follows a natural cubic spline. This flexible approach nests the...
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We study the strong consistency and asymptotic normality of the maximum likelihood estimator for a class of time series … processes. We formulate primitive conditions for global identification, invertibility, strong consistency, and asymptotic …
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In this article consistency and asymptotic normality of the quasi-maximum likelihood esti- mator (QMLE) in the class of … introduced by (Duan, 1997) which contains many commonly employed GARCH models as special cases. The conditions for consistency … normality ; consistency ; polynomial augmented GARCH models ; quasi-maximum likelihood estimation …
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