EcoSta 2018: Registration
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Title: Statistic inference for a single-index ARCH-M model Authors:  Qiang Xiong - Guangzhou University (China) [presenting]
Abstract: For a single-index autoregressive conditional heteroscedastic in mean (SI-ARCH-M) model, estimators of the parametric and nonparametric components are proposed by the profile likelihood method. The research results had shown that all the estimators have consistency and asymptotic normality. Based on the asymptotic properties, we propose Wald statistic and generalized likelihood ratio statistic to investigate the testing problems for ARCH effect and goodness of fit, respectively. A simulation study is conducted to evaluate the finite-sample performance of the proposed estimation methodology and testing procedure.