An empirical analysis of the volatility of the Japanese stock price index: a non-parametric approach

作者：Takahashi Katsuyuki; Shoji Isao^*

来源：Journal of Applied Statistics, 2011, 38(7): 1381-1394.

DOI：10.1080/02664763.2010.505947

• high-frequency data
• local polynomial model
• non-parametric estimation
• stock index
• volatility function

This paper presents an empirical analysis of stochastic features of volatility in the Japanese stock price index, or TOPIX, using high-frequency data sampled every 5min. The process of TOPIX is modeled by a stochastic differential equation with the time-homogeneous drift and diffusion coefficients. To avoid the risk of misspecification for the volatility function, which is defined by the squared diffusion coefficient, the local polynomial model is applied to the data, and then produced the estimates of the volatility function together with their confidence intervals. The result of the estimation suggests that the volatility function shows similar patterns for one period, but drastically changes for another.

• 出版日期2011