ScholarGate
Assistant

Comparer des méthodes

Examinez les méthodes sélectionnées côte à côte ; les lignes qui diffèrent sont mises en évidence.

Modèle ARIMA (Autoregressive Integrated Moving Average)×Modèle GARCH (Prévision de la volatilité)×Données à haute fréquence et analyse de la microstructure de marché×
DomaineÉconométrieÉconométrieFinance
FamilleRegression modelRegression modelRegression model
Année d'origine201519862007
Auteur d'origineBox & Jenkins (Box-Jenkins methodology)Tim BollerslevHasbrouck (2007); Aït-Sahalia & Jacod (2014)
TypeUnivariate time-series modelConditional volatility modelMarket microstructure / high-frequency econometrics
Source fondatriceBox, G. E. P., Jenkins, G. M., Reinsel, G. C. & Ljung, G. M. (2015). Time Series Analysis: Forecasting and Control (5th ed.). Wiley. ISBN: 978-1118675021Bollerslev, 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
AliasBox-Jenkins model, ARIMA(p,d,q), ARIMA ModeliGARCH, 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
Apparentées555
RésuméARIMA is a univariate time-series forecasting model that combines autoregressive, integrated (differencing), and moving-average components to predict a single continuous series from its own past. It is the centrepiece of the Box-Jenkins methodology set out in Box, Jenkins, Reinsel & Ljung's Time Series Analysis (5th ed., 2015).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).
ScholarGateJeu de données
  1. v1
  2. 1 Sources
  3. PUBLISHED
  1. v1
  2. 1 Sources
  3. PUBLISHED
  1. v1
  2. 2 Sources
  3. PUBLISHED

Aller à la recherche Télécharger les diapositives

ScholarGateComparer des méthodes: ARIMA · GARCH Model · Market Microstructure Analysis. Consulté le 2026-06-18 sur https://scholargate.app/fr/compare