3 papers
stat.ME2026
Private Federated Learning for High-dimensional Time Series
Kejun Chen, Qianqian Zhu
In the era of big data, leveraging information from multiple clients while preserving data privacy has emerged as a critical challenge in modern statistical modeling and forecastin…
math.ST2026
A robust and scalable estimation for high-dimensional volatility models
Kejun Chen, Yuchang Lin, Qianqian Zhu
This paper introduces a robust and computationally efficient estimation framework for high-dimensional volatility models in the BEKK-ARCH class. The proposed approach employs data…
stat.ME2025
Improving time series estimation and prediction via transfer learning
Yuchang Lin, Qianqian Zhu, Guodong Li
There are many time series in the literature with high dimension yet limited sample sizes, such as macroeconomic variables, and it is almost impossible to obtain efficient estimati…