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Tail Risk Measures×Modeli wa GARCH (Utabiri wa Msukosuko)×
NyanjaFedhaEkonometriki
FamiliaRegression modelRegression model
Mwaka wa asili19991986
MwanzilishiArtzner, Delbaen, Eber & Heath (coherent risk axioms); Acerbi & Tasche (Expected Shortfall)Tim Bollerslev
AinaCoherent tail risk measureConditional volatility model
Chanzo asiliaArtzner, P., Delbaen, F., Eber, J.-M. & Heath, D. (1999). Coherent Measures of Risk. Mathematical Finance, 9(3), 203–228. DOI ↗Bollerslev, T. (1986). Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 31(3), 307–327. DOI ↗
Majina mbadalaexpected shortfall, conditional value at risk, CVaR, spectral risk measureGARCH, GARCH(1,1), conditional volatility model, GARCH Modeli (Oynaklık Tahmini)
Zinazohusiana55
MuhtasariTail risk measures quantify the loss distribution beyond Value-at-Risk (VaR). Expected Shortfall — the expected loss given that VaR is exceeded — is the leading coherent risk measure, formalised by Artzner, Delbaen, Eber and Heath (1999) and shown to be coherent by Acerbi and Tasche (2002). Spectral and expectile-based measures generalise it.The Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model, introduced by Tim Bollerslev in 1986, models the time-varying conditional variance of a financial time series. It captures volatility clustering and the ARCH effect, and is the standard tool for estimating risk and volatility in return series.
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  3. PUBLISHED

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ScholarGateLinganisha mbinu: Tail Risk Measures · GARCH Model. Imepatikana 2026-06-18 kutoka https://scholargate.app/sw/compare