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초록
With a wide recognition that financial time series typically exhibits asymmetry patterns in volatility so called leverage effects, various asymmetric GARCH(1, 1) processes have been introduced to investigate asymmetric volatilities. A lot of researches have also been directed to non-stationary volatilities to deal with frequent high ups and downs in financial time series. This article is concerned with both asymmetric and non-stationary GARCH-type models. As a subsequent paper of Choi et al. (2020), we review various asymmetric and non-stationary GARCH(1, 1) processes, and in turn propose how to compare competing models using a parametric bootstrap methodology. As an illustration, Dow Jones Industrial Average (DJIA) is analyzed.
키워드
asymmetric volatility; non-stationary volatility; parametric bootstrap; 비대칭 변동성; 비정상 변동성; 모수적 붓스트랩
- 제목
- 비대칭-비정상 변동성 모형 평가를 위한 모수적-붓스트랩
- 제목 (타언어)
- Asymmetric and non-stationary GARCH($1,1$) models: parametric bootstrap to evaluate forecasting performance
- 저자
- 황선영; 최선우; 윤재은; 이성덕
- 발행일
- 2021-08
- 유형
- Article
- 저널명
- 응용통계연구
- 권
- 34
- 호
- 4
- 페이지
- 611 ~ 622