ScholarGate
Avustaja

Vertaile menetelmiä

Tarkastele valitsemiasi menetelmiä rinnakkain; eroavat rivit korostetaan.

EGARCH-malli (Exponential GARCH)×Autoregressiivisen ehdollisen heteroskedastisuuden (ARCH) malli×
TieteenalaEkonometriaEkonometria
MenetelmäperheRegression modelRegression model
Syntyvuosi19911982
KehittäjäDaniel B. NelsonRobert F. Engle
TyyppiVolatility / conditional variance modelConditional volatility model
AlkuperäislähdeNelson, D. B. (1991). Conditional heteroskedasticity in asset returns: A new approach. Econometrica, 59(2), 347–370. DOI ↗Engle, R. F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica, 50(4), 987–1007. DOI ↗
RinnakkaisnimetExponential GARCH, EGARCH, Nelson EGARCH, log-GARCHARCH, autoregressive conditional heteroskedasticity, Engle ARCH, conditional variance model
Liittyvät66
TiivistelmäThe Exponential GARCH (EGARCH) model, introduced by Nelson (1991), extends the standard GARCH framework by modelling the logarithm of conditional variance. This ensures variance is always positive without parameter constraints and, crucially, allows negative and positive shocks to have asymmetric effects on volatility — capturing the well-known leverage effect in financial markets.The ARCH model, introduced by Robert Engle in 1982, captures time-varying volatility in financial and macroeconomic time series. It models the conditional variance of today's error as a function of past squared errors, explaining why volatile periods cluster together — a phenomenon known as volatility clustering.
ScholarGateAineisto
  1. v1
  2. 2 Lähteet
  3. PUBLISHED
  1. v1
  2. 2 Lähteet
  3. PUBLISHED

Siirry hakuun Lataa diat

ScholarGateVertaile menetelmiä: EGARCH model · ARCH model. Haettu 2026-06-17 osoitteesta https://scholargate.app/fi/compare