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广义自回归条件相关模型AI 解读

This paper develops a generalized autoregressive conditional correlation (GARCC) model when the standardized residuals follow a random coefficient vector autoregressive process. As a multivariate generalization of the Tsay (1987, Journal of the American Statistical Association 82, 590–604) random coefficient autoregressive (RCA) model, the GARCC model provides a motivation for the conditional correlations to be time varying. GARCC is also more general than the Engle (2002,…

Log-ACD 模型准极大似然估计的有限样本性质：澳大利亚股票应用AI 解读

This paper concerns the properties of the Quasi Maximum Likelihood Estimator (QMLE) of the Logarithmic Autoregressive Conditional Duration (Log-ACD) model. Proofs of consistency and asymptotic normality of QMLE for the Log-ACD model with log-normal density are presented. This is an important issue as the Log-ACD is used widely for testing various market microstructure models and effects. Knowledge of the distribution of the QMLE is crucial for purposes of valid inference and…

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STAR 与 STAR-GARCH 模型的极大似然估计：理论与蒙特卡洛证据AI 解读

Abstract Theoretical and practical interest in non‐linear time series models, particularly regime switching models, have increased substantially in recent years. Given the abundant research activity in analysing time‐varying volatility through Generalized Autoregressive Conditional Heteroscedasticity (GARCH) processes (see Engle, 1982 ; Bollerslev, 1986 ), it is important to analyse regime switching models with GARCH errors. A popular specification in this class is the…