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ARCHモデル(Autoregressive Conditional Heteroskedasticity)×GARCHモデル(ボラティリティ予測)×分位点回帰×
分野計量経済学計量経済学計量経済学
系統Regression modelRegression modelRegression model
提唱年198219861978
提唱者Robert F. EngleTim BollerslevKoenker & Bassett
種類Conditional volatility modelConditional volatility modelConditional quantile regression
原典Engle, R. F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica, 50(4), 987–1007. DOI ↗Bollerslev, T. (1986). Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 31(3), 307–327. DOI ↗Koenker, R. & Bassett, G., Jr. (1978). Regression Quantiles. Econometrica, 46(1), 33-50. DOI ↗
別名ARCH, autoregressive conditional heteroskedasticity, Engle ARCH, conditional variance modelGARCH, GARCH(1,1), conditional volatility model, GARCH Modeli (Oynaklık Tahmini)conditional quantile regression, regression quantiles, Kantil Regresyon
関連655
概要The 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 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.Quantile regression models conditional quantiles of an outcome - the median, the 25th or 75th percentile, and so on - rather than the conditional mean that OLS targets. Introduced by Koenker and Bassett in 1978, it reveals how predictors act across the whole distribution, including its tails.
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ScholarGate手法を比較: ARCH model · GARCH Model · Quantile Regression. 2026-06-18に以下より取得 https://scholargate.app/ja/compare