Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Модель нелинейной ARCH (NARCH)× | Модель ARCH (авторегрессионная условная гетероскедастичность)× | |
|---|---|---|
| Область | Эконометрика | Эконометрика |
| Семейство | Regression model | Regression model |
| Год появления≠ | 1992 | 1982 |
| Автор метода≠ | Higgins & Bera | Robert F. Engle |
| Тип≠ | Volatility model | Conditional volatility model |
| Основополагающий источник≠ | Higgins, M. L., & Bera, A. K. (1992). A class of nonlinear ARCH models. International Economic Review, 33(1), 137-158. DOI ↗ | Engle, R. F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica, 50(4), 987–1007. DOI ↗ |
| Другие названия | NARCH, Nonlinear ARCH, nonlinear conditional heteroscedasticity model, NARCH model | ARCH, autoregressive conditional heteroskedasticity, Engle ARCH, conditional variance model |
| Связанные≠ | 4 | 6 |
| Сводка≠ | The Nonlinear ARCH (NARCH) model, introduced by Higgins and Bera (1992), extends Engle's original ARCH framework by allowing the power transformation of volatility to be estimated from the data rather than fixed at two. This flexibility captures a broader class of volatility dynamics observed in financial and macroeconomic time series. | 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. |
| ScholarGateНабор данных ↗ |
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