Abstract:The GARCH models are widely used to model various financial data with nonlinearity and heteroscedasticity structures. In this article, we propose a functional‐coefficient regression model with GARCH(r, s) errors to model these kinds of data. To deal with the effect of heteroscedasticity, we introduce a two‐step approach to estimating the unknown coefficient functions and the volatility, which results in unweighted and weighted local linear estimators. Asymptotic properties of the proposed estimators are establ… Show more
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