40 citations · 41 across the 2 of their papers we have counts for
5 papers
Do RNN and LSTM have Long Memory?
Jingyu Zhao, Feiqing Huang, Jia Lv +4
The LSTM network was proposed to overcome the difficulty in learning long-term dependence, and has made significant advancements in applications. With its success and drawbacks in…
Hybrid quantile estimation for asymmetric power GARCH models
Guochang Wang, Ke Zhu, Guodong Li +1
Asymmetric power GARCH models have been widely used to study the higher order moments of financial returns, while their quantile estimation has been rarely investigated. This paper…
Compact Autoregressive Network
Di Wang, Feiqing Huang, Jingyu Zhao +2
Autoregressive networks can achieve promising performance in many sequence modeling tasks with short-range dependence. However, when handling high-dimensional inputs and outputs, t…
High-dimensional vector autoregressive time series modeling via tensor decomposition
Di Wang, Yao Zheng, Heng Lian +1
The classical vector autoregressive model is a fundamental tool for multivariate time series analysis. However, it involves too many parameters when the number of time series and l…
Quantile double autoregression
Qianqian Zhu, Guodong Li
Many financial time series have varying structures at different quantile levels, and also exhibit the phenomenon of conditional heteroscedasticity at the same time. In the meanwhil…