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GARCHモデル(ボラティリティ予測)×高頻データと市場マイクロストラクチャ分析×
分野計量経済学ファイナンス
系統Regression modelRegression model
提唱年19862007
提唱者Tim BollerslevHasbrouck (2007); Aït-Sahalia & Jacod (2014)
種類Conditional volatility modelMarket microstructure / high-frequency econometrics
原典Bollerslev, 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
別名GARCH, 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
関連55
概要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.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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ScholarGate手法を比較: GARCH Model · Market Microstructure Analysis. 2026-06-18に以下より取得 https://scholargate.app/ja/compare