Earticle

초록

영어

This study has investigated sudden changes of volatility and examined the volatility asymmetry and persistence for the Shanghai and Shenzhen indices. In an effort to assess the impact of sudden changes in volatility asymmetry and persistence, we identify the time points at which sudden changes in volatility occur, and then incorporate this information into the GARCH and GJR-GARCH models. Using the ICSS algorithm, we found that the identification of sudden changes is largely associated with domestic and global events. When these sudden changes are incorporated into GARCH and GJR-GARCH models, the evidences of asymmetry and persistence has been vanished in the volatility of both markets. In addition, out-ofsample analysis confirms that volatility models with incorporating sudden changes provide more accurate one-step-ahead volatility forecasts than their counterparts without sudden changes.

목차

Abstract
 1. Introduction
 2. Methodology
  2.1. Detecting points of sudden change in variance
  2.2. GARCH(1,1) and GJR-GARCH models
  2.3. Multiple sudden changes with GARCH and GJR-GARCH models
 3. Data and descriptive statistics
 4. Empirical results
  4.1. Sudden changes in variance
  4.2. GARCH and GJR-GARCH estimation with and without sudden changes
  4.3. Out-of-sample forecasts
 5. Conclusions
 References

키워드

저자

• Sang Hoon Kang [ Assistant Professor, Division of Business Administration, Pusan National University ]
• Seong-Min Yoon [ Professor, Department of Economics, Pusan National University ] Author for Correspondence

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  한국재무학회 학술대회

• 간기

  부정기

• 수록기간

  2006~2024

• 십진분류

  KDC 325 DDC 330