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Mfumo Imara wa GARCH×Muundo wa ARCH (Autoregressive Conditional Heteroskedasticity)×
NyanjaEkonometrikiEkonometriki
FamiliaRegression modelRegression model
Mwaka wa asili1986–20131982
MwanzilishiBoudt, Danielsson & Laurent (robust extensions); Bollerslev (standard GARCH, 1986)Robert F. Engle
AinaVolatility modelConditional volatility model
Chanzo asiliaBoudt, K., Danielsson, J., & Laurent, S. (2013). Robust forecasting of dynamic conditional correlation GARCH models. International Journal of Forecasting, 29(2), 244–257. DOI ↗Engle, R. F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica, 50(4), 987–1007. DOI ↗
Majina mbadalaRobust GARCH, outlier-robust GARCH, heavy-tail GARCH, contamination-robust volatility modelARCH, autoregressive conditional heteroskedasticity, Engle ARCH, conditional variance model
Zinazohusiana56
MuhtasariThe Robust GARCH model extends the classical GARCH framework to handle outliers and heavy-tailed innovations that commonly appear in financial return series. By down-weighting extreme observations through a robust innovation term, it produces more reliable volatility forecasts when data contain jumps, crises, or other anomalies that would otherwise distort standard GARCH estimates.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.
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ScholarGateLinganisha mbinu: Robust GARCH model · ARCH model. Imepatikana 2026-06-17 kutoka https://scholargate.app/sw/compare