ScholarGate
Assistent

Jämför metoder

Granska de valda metoderna sida vid sida; rader som skiljer sig är markerade.

Modeller med långt minne (ARFIMA, FIGARCH)×ARIMA (Autoregressive Integrated Moving Average) Modell×Högfrekvensdata och analys av marknadsmikrostruktur×
ÄmnesområdeFinansiell ekonomiEkonometriFinansiell ekonomi
FamiljRegression modelRegression modelRegression model
Ursprungsår198020152007
UpphovspersonGranger & Joyeux (ARFIMA); Baillie, Bollerslev & Mikkelsen (FIGARCH)Box & Jenkins (Box-Jenkins methodology)Hasbrouck (2007); Aït-Sahalia & Jacod (2014)
TypFractionally integrated time series modelUnivariate time-series modelMarket microstructure / high-frequency econometrics
UrsprungskällaGranger, 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 ↗Box, G. E. P., Jenkins, G. M., Reinsel, G. C. & Ljung, G. M. (2015). Time Series Analysis: Forecasting and Control (5th ed.). Wiley. ISBN: 978-1118675021Hasbrouck, 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 integrationBox-Jenkins model, ARIMA(p,d,q), ARIMA Modelimarket microstructure, high-frequency financial econometrics, tick data analysis, Yüksek Frekanslı Veri ve Piyasa Mikro Yapısı
Närliggande455
SammanfattningLong-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.ARIMA 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).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).
ScholarGateDatamängd
  1. v1
  2. 2 Källor
  3. PUBLISHED
  1. v1
  2. 1 Källor
  3. PUBLISHED
  1. v1
  2. 2 Källor
  3. PUBLISHED

Gå till sökningen Ladda ner bildspel

ScholarGateJämför metoder: Long-Memory Models · ARIMA · Market Microstructure Analysis. Hämtad 2026-06-18 från https://scholargate.app/sv/compare