ScholarGate
어시스턴트

방법 비교

선택한 방법을 나란히 검토하세요. 서로 다른 행은 강조 표시됩니다.

지수적 GARCH (EGARCH)×요한센 공적분 검정 및 벡터 오차 수정 모형×장기기억 모형 (ARFIMA, FIGARCH)×
분야계량경제학재무학재무학
계열Regression modelRegression modelRegression model
기원 연도199119911980
창시자NelsonSøren JohansenGranger & Joyeux (ARFIMA); Baillie, Bollerslev & Mikkelsen (FIGARCH)
유형Conditional volatility model (asymmetric GARCH variant)Multivariate cointegration / vector error correction modelFractionally integrated time series model
원전Nelson, D. B. (1991). Conditional Heteroskedasticity in Asset Returns: A New Approach. Econometrica, 59(2), 347-370. DOI ↗Johansen, S. (1991). Estimation and Hypothesis Testing of Cointegration Vectors in Gaussian Vector Autoregressive Models. Econometrica, 59(6), 1551-1580. DOI ↗Granger, C. W. J. & Joyeux, R. (1980). An Introduction to Long-Memory Time Series Models and Fractional Differencing. Journal of Time Series Analysis, 1(1), 15-29. DOI ↗
별칭exponential GARCH, Nelson's EGARCH, asymmetric GARCH, EGARCH — Üstel GARCHJohansen test, VECM, vector error correction model, multivariate cointegrationARFIMA, FIGARCH, fractionally integrated models, fractional integration
관련434
요약EGARCH is an asymmetric GARCH variant, introduced by Nelson in 1991, that models the leverage effect in which bad news raises volatility more than good news of the same size. It captures the negative-shock asymmetry of financial return series by modelling the logarithm of the conditional variance.The Johansen procedure is a multivariate cointegration framework, introduced by Søren Johansen in 1991, that tests for long-run equilibrium relationships among several I(1) time series. It determines how many cointegrating vectors link the series and then builds a Vector Error Correction Model (VECM) to describe the short-run dynamics around that equilibrium.Long-memory models are fractional-integration methods that capture genuine long memory through a hyperbolically decaying autocorrelation structure. ARFIMA, introduced by Granger and Joyeux (1980), models long memory in return series, while FIGARCH, introduced by Baillie, Bollerslev and Mikkelsen (1996), captures long memory in volatility series; the parameter d measures the degree of fractional integration.
ScholarGate데이터셋
  1. v1
  2. 2 출처
  3. PUBLISHED
  1. v1
  2. 2 출처
  3. PUBLISHED
  1. v1
  2. 2 출처
  3. PUBLISHED

검색으로 이동 슬라이드 다운로드

ScholarGate방법 비교: EGARCH · Johansen Cointegration Test · Long-Memory Models. 2026-06-19에 다음에서 검색함: https://scholargate.app/ko/compare