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Linganisha mbinu

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Component GARCH×Mtihani wa usababishaji katika kiwango cha tofauti×
NyanjaEkonometrikiEkonometriki
FamiliaRegression modelRegression model
Mwaka wa asili19991996
MwanzilishiEngle and LeeYin-Wong Cheung and Lilian Ng
AinaDecomposed variance modelConditional variance test
Chanzo asiliaEngle, R. F., & Lee, G. (1999). A permanent and transitory component model of stock return volatility. Journal of Political Economy, 107(6), 1363-1384. link ↗Cheung, Y. W., & Ng, L. K. (1996). A causality-in-variance test and its application to financial market prices. Journal of Econometrics, 72(1-2), 33-61. DOI ↗
Majina mbadalaVolatility components modelVolatility spillover test
Zinazohusiana33
MuhtasariComponent GARCH decomposes conditional variance into transitory (short-term) and permanent (long-term) components with different dynamics, allowing flexibility in capturing volatility behavior at multiple frequencies. Introduced by Engle and Lee (1999), it elegantly models the empirical finding that volatility exhibits both rapid mean-reversion (daily shocks) and slow mean-reversion (level shifts). This framework is crucial for understanding volatility persistence and improving long-horizon volatility forecasting.The causality-in-variance test detects whether shocks to one variable cause changes in the conditional variance (volatility) of another variable, distinct from mean-level causality. Introduced by Cheung and Ng (1996), it identifies volatility spillovers and contagion effects—crucial for risk management and understanding financial market interdependencies. This approach has become standard in studying shock transmission across asset classes and geographies.
ScholarGateSeti ya data
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  1. v1
  2. 2 Vyanzo
  3. PUBLISHED

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ScholarGateLinganisha mbinu: Component GARCH · Causality in Variance Test. Imepatikana 2026-06-17 kutoka https://scholargate.app/sw/compare