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Model Ingatan Jangka Panjang (ARFIMA, FIGARCH)×Analisis Mikrostruktur Pasaran dan Data Frekuensi Tinggi×
BidangKewanganKewangan
KeluargaRegression modelRegression model
Tahun asal19802007
PengasasGranger & Joyeux (ARFIMA); Baillie, Bollerslev & Mikkelsen (FIGARCH)Hasbrouck (2007); Aït-Sahalia & Jacod (2014)
JenisFractionally integrated time series modelMarket microstructure / high-frequency econometrics
Sumber perintisGranger, C. W. J. & Joyeux, R. (1980). An Introduction to Long-Memory Time Series Models and Fractional Differencing. Journal of Time Series Analysis, 1(1), 15-29. DOI ↗Hasbrouck, J. (2007). Empirical Market Microstructure: The Institutions, Economics, and Econometrics of Securities Trading. Oxford University Press. ISBN: 978-0195301649
AliasARFIMA, FIGARCH, fractionally integrated models, fractional integrationmarket microstructure, high-frequency financial econometrics, tick data analysis, Yüksek Frekanslı Veri ve Piyasa Mikro Yapısı
Berkaitan45
RingkasanLong-memory models are fractional-integration methods that capture genuine long memory through a hyperbolically decaying autocorrelation structure. ARFIMA, introduced by Granger and Joyeux (1980), models long memory in return series, while FIGARCH, introduced by Baillie, Bollerslev and Mikkelsen (1996), captures long memory in volatility series; the parameter d measures the degree of fractional integration.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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ScholarGateBandingkan kaedah: Long-Memory Models · Market Microstructure Analysis. Dicapai 2026-06-15 daripada https://scholargate.app/ms/compare