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Laika mainīgo parametru TGARCH modelis×GARCH modelis (volatilitātes prognozēšana)×
NozareEkonometrijaEkonometrija
SaimeRegression modelRegression model
Izcelsmes gads1990s–2000s1986
AutorsExtension combining Zakoïan (1994) TGARCH and time-varying parameter methodsTim Bollerslev
TipsVolatility model with asymmetry and parameter evolutionConditional volatility model
PirmavotsZakoïan, J.-M. (1994). Threshold heteroskedastic models. Journal of Economic Dynamics and Control, 18(5), 931–955. DOI ↗Bollerslev, T. (1986). Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 31(3), 307–327. DOI ↗
Citi nosaukumiTVP-TGARCH, time-varying TGARCH, threshold GARCH with time-varying parameters, TVP Threshold GARCHGARCH, GARCH(1,1), conditional volatility model, GARCH Modeli (Oynaklık Tahmini)
Saistītās45
KopsavilkumsThe TVP-TGARCH model extends Threshold GARCH by allowing its volatility parameters to evolve over time via a state-space representation. It captures both the leverage effect — that negative return shocks increase volatility more than positive ones — and structural change in that asymmetry, making it well-suited for long financial time series subject to regime shifts.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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ScholarGateSalīdzināt metodes: Time-varying parameter TGARCH model · GARCH Model. Izgūts 2026-06-18 no https://scholargate.app/lv/compare