Threshold Approaches to Asymmetric Models for Heteroscedastic Time Series
  • 황선영
  • 김태윤
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초록

Asymmetric volatility or the so called leverage effect has recently attracted considerable attention owing to empirical evidences from various time series. This review paper discusses two threshold approaches to account for asymmetries in the Generalized AutoRegressive Conditional Heteroskedasticity (GARCH) context. The first one involves directly modeling the volatility via threshold functions such as in threshold GARCH models (see, Hwang and Kim [1]). The second approach is indirect for which errors are asymmetric, for instance, skewed t-distributed. A threshold concept is introduced for errors (Hwang [2]) as an indirect asymmetry in volatility. Quasi-likelihood and Godambe optimum scores are discussed to estimate parameters. As an illustration for cell lineage studies, a random coefficient model in bifurcating process is discussed.

키워드

Asymmetric volatilityQuasi-likelihoodThreshold GARCHThreshold error
제목
Threshold Approaches to Asymmetric Models for Heteroscedastic Time Series
저자
황선영김태윤
DOI
10.22283/qbs.2016.35.2.37
발행일
2016-11
저널명
Quantitative Bio-Science
35
2
페이지
37 ~ 40