59 citations · 202 across the 12 of their papers we have counts for
6 papers · 1 filter
On Convergence Rates of Spiked Eigenvalue Estimates: A General Study of Global and Local Laws in Sample Covariance Matrices
Bing-Yi Jing, Weiming Li, Jiahui Xie +2
This paper investigates global and local laws for sample covariance matrices with general growth rates of dimensions. The sample size and population dimension can have the…
Convergence of Gaussian process regression: Optimality, robustness, and relationship with kernel ridge regression
Wenjia Wang, Bing-Yi Jing
In this work, we investigate Gaussian process regression used to recover a function based on noisy observations. We derive upper and lower error bounds for Gaussian process regress…
Testing for pure-jump processes for high-frequency data
Xin-Bing Kong, Zhi Liu, Bing-Yi Jing
Pure-jump processes have been increasingly popular in modeling high-frequency financial data, partially due to their versatility and flexibility. In the meantime, several statistic…
Nonparametric estimate of spectral density functions of sample covariance matrices: A first step
Bing-Yi Jing, Guangming Pan, Qi-Man Shao +1
The density function of the limiting spectral distribution of general sample covariance matrices is usually unknown. We propose to use kernel estimators which are proved to be cons…
Modeling high-frequency financial data by pure jump processes
Bing-Yi Jing, Xin-Bing Kong, Zhi Liu
It is generally accepted that the asset price processes contain jumps. In fact, pure jump models have been widely used to model asset prices and/or stochastic volatilities. The que…
Saddlepoint approximation for Student's t-statistic with no moment conditions
Bing-Yi Jing, Qi-Man Shao, Wang Zhou
A saddlepoint approximation of the Student's t-statistic was derived by Daniels and Young [Biometrika 78 (1991) 169-179] under the very stringent exponential moment condition that…