20 citations · 25 across the 5 of their papers we have counts for
5 papers
Matrix GARCH Model: Inference and Application
Cheng Yu, Dong Li, Feiyu Jiang +1
Matrix-variate time series data are largely available in applications. However, no attempt has been made to study their conditional heteroskedasticity that is often observed in eco…
Testing error distribution by kernelized Stein discrepancy in multivariate time series models
Donghang Luo, Ke Zhu, Huan Gong +1
Knowing the error distribution is important in many multivariate time series applications. To alleviate the risk of error distribution mis-specification, testing methodologies are…
Adaptive inference for a semiparametric generalized autoregressive conditional heteroskedasticity model
Feiyu Jiang, Dong Li, Ke Zhu
This paper considers a semiparametric generalized autoregressive conditional heteroskedasticity (S-GARCH) model. For this model, we first estimate the time-varying long run compone…
A Double AR Model Without Intercept: an Alternative to Modeling Nonstationarity and Heteroscedasticity
Dong Li, Shaojun Guo, Ke Zhu
This paper presents a double AR model without intercept (DARWIN model) and provides us a new way to study the non-stationary heteroskedastic time series. It is shown that the DARWI…
On moving-average models with feedback
Dong Li, Shiqing Ling, Howell Tong
Moving average models, linear or nonlinear, are characterized by their short memory. This paper shows that, in the presence of feedback in the dynamics, the above characteristic ca…