1. Variance reduction approach for the volatility over a finite-time horizon.
- Author
-
Song, Yuping, Sun, Zheng, Zhao, Qicheng, and Chen, Youyou
- Subjects
- *
MONTE Carlo method , *ASYMPTOTIC normality , *FINANCIAL risk , *RETURN on assets - Abstract
The volatility is a measure for the uncertainty of an asset's return and is used to reflect the risk level of a financial asset. In this article, we consider the double kernel nonparametric estimator for the volatility function in a diffusion model over a finite-time span based on high frequency sampling data. Under the minimum conditions, the asymptotic mixed normality for the underlying estimator is derived. Moreover, the better finite-sample performance as variance reduction and even mean squared error reduction of the proposed estimator is verified through a Monte Carlo simulation study and an empirical analysis on overnight Shibor in China. [ABSTRACT FROM AUTHOR]
- Published
- 2022
- Full Text
- View/download PDF