ScholarGate
Asisten

Bandingkan metode

Tinjau metode pilihan Anda berdampingan; baris yang berbeda akan disorot.

Model ARCH (Autoregressive Conditional Heteroskedasticity)×Model ARMA (Autoregressive Moving Average)×
BidangEkonometrikaEkonometrika
KeluargaRegression modelRegression model
Tahun asal19821970
PencetusRobert F. EngleGeorge E. P. Box and Gwilym M. Jenkins
TipeConditional volatility modelTime series model
Sumber perintisEngle, R. F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica, 50(4), 987–1007. DOI ↗Box, G. E. P., & Jenkins, G. M. (1970). Time Series Analysis: Forecasting and Control. Holden-Day. link ↗
AliasARCH, autoregressive conditional heteroskedasticity, Engle ARCH, conditional variance modelARMA, Box-Jenkins model, autoregressive moving average, AR(p)MA(q)
Terkait65
RingkasanThe ARCH model, introduced by Robert Engle in 1982, captures time-varying volatility in financial and macroeconomic time series. It models the conditional variance of today's error as a function of past squared errors, explaining why volatile periods cluster together — a phenomenon known as volatility clustering.The ARMA(p,q) model describes a stationary time series as a combination of two components: an autoregressive part that regresses the current value on its own past p values, and a moving average part that accounts for past q error terms. It is the foundational framework of the Box-Jenkins methodology for univariate time series modelling and short-run forecasting.
ScholarGateSet data
  1. v1
  2. 2 Sumber
  3. PUBLISHED
  1. v1
  2. 2 Sumber
  3. PUBLISHED

Ke halaman pencarian Unduh salindia

ScholarGateBandingkan metode: ARCH model · ARMA model. Diakses 2026-06-17 dari https://scholargate.app/id/compare