Abstract and Applied Analysis
Volume 2013 (2013), Article ID 143194, 13 pages
http://dx.doi.org/10.1155/2013/143194
Research Article

Measuring and Forecasting Volatility in Chinese Stock Market Using HAR-CJ-M Model

Chuangxia Huang,1 Xu Gong,2,3 Xiaohong Chen,3 and Fenghua Wen3

1College of Mathematics and Computing Science, Changsha University of Science and Technology, Changsha, Hunan 410114, China
2School of Economics and Management, Changsha University of Science and Technology, Hunan 410114, China
3School of Business, Central South University, Changsha, Hunan Province 410083, China

Received 7 January 2013; Accepted 22 February 2013

Academic Editor: Zhichun Yang

Copyright © 2013 Chuangxia Huang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Basing on the Heterogeneous Autoregressive with Continuous volatility and Jumps model (HAR-CJ), converting the realized Volatility (RV) into the adjusted realized volatility (ARV), and making use of the influence of momentum effect on the volatility, a new model called HAR-CJ-M is developed in this paper. At the same time, we also address, in great detail, another two models (HAR-ARV, HAR-CJ). The applications of these models to Chinese stock market show that each of the continuous sample path variation, momentum effect, and ARV has a good forecasting performance on the future ARV, while the discontinuous jump variation has a poor forecasting performance. Moreover, the HAR-CJ-M model shows obviously better forecasting performance than the other two models in forecasting the future volatility in Chinese stock market.