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GARCH-model (volatilitetsprognoser)×Højfrekvensdata og markedsmikrostrukturanalyse×
FagområdeØkonometriFinansiering
FamilieRegression modelRegression model
Oprindelsesår19862007
OphavspersonTim BollerslevHasbrouck (2007); Aït-Sahalia & Jacod (2014)
TypeConditional volatility modelMarket microstructure / high-frequency econometrics
Oprindelig kildeBollerslev, 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
AliasserGARCH, 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
Relaterede55
ResuméThe 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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ScholarGateSammenlign metoder: GARCH Model · Market Microstructure Analysis. Hentet 2026-06-18 fra https://scholargate.app/da/compare