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Model GARCH (predikcia volatility)×Analýza vysokofrekvenčných dát a trhovej mikroštruktúry×
OdborEkonometriaFinancie
RodinaRegression modelRegression model
Rok vzniku19862007
TvorcaTim BollerslevHasbrouck (2007); Aït-Sahalia & Jacod (2014)
TypConditional volatility modelMarket microstructure / high-frequency econometrics
Pôvodný zdrojBollerslev, T. (1986). Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 31(3), 307–327. DOI ↗Hasbrouck, J. (2007). Empirical Market Microstructure: The Institutions, Economics, and Econometrics of Securities Trading. Oxford University Press. ISBN: 978-0195301649
Ďalšie názvyGARCH, GARCH(1,1), conditional volatility model, GARCH Modeli (Oynaklık Tahmini)market microstructure, high-frequency financial econometrics, tick data analysis, Yüksek Frekanslı Veri ve Piyasa Mikro Yapısı
Príbuzné55
ZhrnutieThe 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.Market microstructure analysis studies how prices form from tick-level trade and quote data, examining order-book dynamics, the bid-ask spread, and price discovery. The modern econometric framework was set out by Hasbrouck (2007) and extended for high-frequency data by Aït-Sahalia and Jacod (2014).
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ScholarGatePorovnať metódy: GARCH Model · Market Microstructure Analysis. Získané 2026-06-18 z https://scholargate.app/sk/compare